Prof. Wanmin Zhao
Prof. Wei Zeng
ISSN: 2095-6304
Journal of Human Settlements in West China is formerly known as Interior Design founded in 1986, which officially changed its name in 2013. Journal of Human Settlements in West China, as the first comprehensive academic journal in China under the name of human settlements, will pay extensive attention to the major scientific problems faced by urban and rural human settlements from a global perspective based on the western regions and oriented to both domestic and international authors and readers.
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2026(1),1-7
DOI: 10.13791/j.cnki.hsfwest.20251126001
Abstract:
The transition of resource-based cities represents a crucial strategic issue in China’s regional development agenda. These cities, which have historically relied heavily on the extraction and processing of natural resources, face significant challenges in ensuring sustainable growth, environmental protection, and economic diversification. In this context, research focusing on the transformation of resource-based cities has gained increasing academic and policy relevance. This paper conducts a systematic review and bibliometric analysis of the core literature on this topic over the past two decades, with the aim of uncovering the developmental logic and evolution patterns that characterize this research field. By leveraging CiteSpace’s burst detection and knowledge mapping tools, the study investigates the field’s evolution from the perspectives of policy change, research trajectories, and academic hotspots. Transitioning from foundational inquiry to empirical synthesis, the study reveals that the evolution of research on the transformation of resource-based cities in China has been shaped by a dynamic interplay between policy guidance and academic exploration. This dual-track development has led to the emergence of a coherent yet diversified body of knowledge. According to the analysis, the evolution of this field can be broadly divided into three key stages, each marked by distinct themes and paradigmatic shifts in both policy focus and research orientation. The first stage, identified as the crisis mitigation phase, is characterized by scholarly and policy attention centered on industrial succession and ecological restoration. During this period, the primary goal was to address the economic downturn and environmental degradation that followed resource depletion. Research emphasized the importance of fostering alternative industries and initiating basic environmental remediation projects. Transitioning from survival to stability, efforts during this phase laid the groundwork for more comprehensive transformation strategies. The second stage, referred to as the differentiated governance phase, witnessed a notable broadening of the analytical lens. Scholars began to explore the life-cycle dynamics of resource-based cities, emphasizing the heterogeneity among cities at different stages of resource exhaustion and development. Research expanded to include performance evaluations of policy interventions, fiscal sustainability, employment resilience, and institutional capacity. Transitioning from uniform solutions to tailored governance models, this phase highlighted the necessity of adopting nuanced and context-specific strategies for urban transformation. The third and most recent stage is identified as the high-quality development phase. This period marks a transition towards frontier topics such as green and low-carbon transformation, innovation-driven development, and digital empowerment. The emergence of these themes reflects the broader national shift toward sustainable development and technological modernization. Scholars now focus on how resourcebased cities can leverage digital technologies, promote green industries, and foster innovation ecosystems to achieve high-quality transformation. This stage is further characterized by the convergence of multiple disciplines including urban planning, environmental science, economics, and data science—indicating a deepening of interdisciplinary integration. Transitioning from thematic evolution to methodological insights, the study also analyzes the burst keywords andtheir dynamic shifts over time. The co-evolution of research topics and national strategies is clearly evident: keyword bursts show strong alignment with major policy initiatives such as the “New Urbanization Plan”, the “National Sustainable Development Agenda”, and more recently, “carbon peaking and neutrality goals”. This coupling indicates that the research agenda is not only shaped by academic interest but also strongly driven by state-level strategic priorities. Furthermore, the findings underscore three overarching trends in the academic development of this field: increasing interdisciplinarity, methodological diversification, and theoretical localization. Interdisciplinarity is evident in the integration of environmental science, economics, sociology, and geography, forming a comprehensive lens for understanding urban transformation. Methodological diversification is reflected in the application of big data, spatial analysis, and policy simulation techniques. Theoretical localization, meanwhile, involves the adaptation and innovation of existing western urban theories within China’s unique institutional and socio-political context. Transitioning from retrospective insights to future directions, the study highlights key emerging research areas that warrant further exploration. Under the new imperatives of carbon neutrality, urban regeneration, and sustainable innovation, scholars are called to advance the discourse in several domains. First, there is a need to deepen research on green transformation mechanisms, particularly how cities can achieve systemic shifts towards sustainability in their industrial structures and energy consumption. Second, the issue of spatial-social coordinated governance must be addressed, including questions of equity, inclusivity, and public participation in urban transformation. Third, the role of digital technologies in enabling transformation, through smart governance, digital twins, and intelligent infrastructure, remains a promising but underexplored area. In conclusion, the transformation of resource-based cities in China is a complex, multi-dimensional process that demands ongoing theoretical innovation and practical experimentation. This study contributes to the academic literature by mapping the historical trajectory, thematic evolution, and methodological diversification of this field, while also identifying key areas for future scholarly inquiry. It offers valuable references for policymakers, researchers, and practitioners working to foster sustainable, resilient, and innovation-driven urban futures in resource-dependent regions.
The transition of resource-based cities represents a crucial strategic issue in China’s regional development agenda. These cities, which have historically relied heavily on the extraction and processing of natural resources, face significant challenges in ensuring sustainable growth, environmental protection, and economic diversification. In this context, research focusing on the transformation of resource-based cities has gained increasing academic and policy relevance. This paper conducts a systematic review and bibliometric analysis of the core literature on this topic over the past two decades, with the aim of uncovering the developmental logic and evolution patterns that characterize this research field. By leveraging CiteSpace’s burst detection and knowledge mapping tools, the study investigates the field’s evolution from the perspectives of policy change, research trajectories, and academic hotspots. Transitioning from foundational inquiry to empirical synthesis, the study reveals that the evolution of research on the transformation of resource-based cities in China has been shaped by a dynamic interplay between policy guidance and academic exploration. This dual-track development has led to the emergence of a coherent yet diversified body of knowledge. According to the analysis, the evolution of this field can be broadly divided into three key stages, each marked by distinct themes and paradigmatic shifts in both policy focus and research orientation. The first stage, identified as the crisis mitigation phase, is characterized by scholarly and policy attention centered on industrial succession and ecological restoration. During this period, the primary goal was to address the economic downturn and environmental degradation that followed resource depletion. Research emphasized the importance of fostering alternative industries and initiating basic environmental remediation projects. Transitioning from survival to stability, efforts during this phase laid the groundwork for more comprehensive transformation strategies. The second stage, referred to as the differentiated governance phase, witnessed a notable broadening of the analytical lens. Scholars began to explore the life-cycle dynamics of resource-based cities, emphasizing the heterogeneity among cities at different stages of resource exhaustion and development. Research expanded to include performance evaluations of policy interventions, fiscal sustainability, employment resilience, and institutional capacity. Transitioning from uniform solutions to tailored governance models, this phase highlighted the necessity of adopting nuanced and context-specific strategies for urban transformation. The third and most recent stage is identified as the high-quality development phase. This period marks a transition towards frontier topics such as green and low-carbon transformation, innovation-driven development, and digital empowerment. The emergence of these themes reflects the broader national shift toward sustainable development and technological modernization. Scholars now focus on how resourcebased cities can leverage digital technologies, promote green industries, and foster innovation ecosystems to achieve high-quality transformation. This stage is further characterized by the convergence of multiple disciplines including urban planning, environmental science, economics, and data science—indicating a deepening of interdisciplinary integration. Transitioning from thematic evolution to methodological insights, the study also analyzes the burst keywords andtheir dynamic shifts over time. The co-evolution of research topics and national strategies is clearly evident: keyword bursts show strong alignment with major policy initiatives such as the “New Urbanization Plan”, the “National Sustainable Development Agenda”, and more recently, “carbon peaking and neutrality goals”. This coupling indicates that the research agenda is not only shaped by academic interest but also strongly driven by state-level strategic priorities. Furthermore, the findings underscore three overarching trends in the academic development of this field: increasing interdisciplinarity, methodological diversification, and theoretical localization. Interdisciplinarity is evident in the integration of environmental science, economics, sociology, and geography, forming a comprehensive lens for understanding urban transformation. Methodological diversification is reflected in the application of big data, spatial analysis, and policy simulation techniques. Theoretical localization, meanwhile, involves the adaptation and innovation of existing western urban theories within China’s unique institutional and socio-political context. Transitioning from retrospective insights to future directions, the study highlights key emerging research areas that warrant further exploration. Under the new imperatives of carbon neutrality, urban regeneration, and sustainable innovation, scholars are called to advance the discourse in several domains. First, there is a need to deepen research on green transformation mechanisms, particularly how cities can achieve systemic shifts towards sustainability in their industrial structures and energy consumption. Second, the issue of spatial-social coordinated governance must be addressed, including questions of equity, inclusivity, and public participation in urban transformation. Third, the role of digital technologies in enabling transformation, through smart governance, digital twins, and intelligent infrastructure, remains a promising but underexplored area. In conclusion, the transformation of resource-based cities in China is a complex, multi-dimensional process that demands ongoing theoretical innovation and practical experimentation. This study contributes to the academic literature by mapping the historical trajectory, thematic evolution, and methodological diversification of this field, while also identifying key areas for future scholarly inquiry. It offers valuable references for policymakers, researchers, and practitioners working to foster sustainable, resilient, and innovation-driven urban futures in resource-dependent regions.
2026(1),8-14
DOI: 10.13791/j.cnki.hsfwest.20251127004
Abstract:
The transformation of resource-based areas represents a critical strategic task in China’s pursuit of high-quality regional development, particularly under the combined pressures of resource depletion, ecological constraints, and structural economic adjustment. Historically dependent on the extraction and primary processing of natural resources such as coal, minerals, and petroleum, these areas have long played a foundational role in national industrialization. However, persistent path dependence and the well-documented “resource curse” have increasingly exposed them to economic stagnation, environmental degradation, and social imbalance. In this context, a systematic understanding of how academic research on resource-based area transformation has evolved, as well as a clear identification of the key driving conditions underlying different transformation pathways, is essential for advancing theory and informing policy practice.Previous studies on resource-based area transformation can generally be grouped into three methodological streams: qualitative case-based analyses, quantitative econometric research, and bibliometric or knowledge-mapping studies. While each has generated valuable insights, their limitations are also evident. Qualitative case studies offer rich contextual understanding but often lack generalizability. Quantitative econometric approaches typically focus on selected explanatory variables and outcomes, making it difficult to capture the internal mechanisms and multidimensional interactions involved in transformation processes. Bibliometric analyses, relying on tools such as citation networks and keyword co-occurrence, are effective in identifying research hotspots and collaboration patterns, yet they remain constrained to surface-level information and are insufficient for uncovering mechanism-oriented semantic structures and their evolution over time. As a result, a methodological gap persists in conducting large-scale, fine-grained, and mechanism-focused synthesis of the transformation literature.To address this gap, this study develops a hybrid analytical framework that integrates large language models (LLMs) with multi-algorithm machine learning (ML) techniques to enable structured text mining and robust identification of key driving conditions. The analysis is based on a corpus of 1,240 Chinese-language academic articles published in authoritative journals indexed in CNKI that address resource-based area transformation. Using an LLM-based structured extraction approach supported by carefully designed prompt engineering, unstructured full-text content is transformed into a standardized dataset. This process enables field-level semantic judgment across 61 predefined indicators, encompassing seven dimensions of driving conditions—policy environment, market environment, technological environment, regional environment, industrial structure, factor structure, and urban–rural structure— as well as five representative transformation modes: green transformation, cultural tourism transformation, industrial diversification, platform-dependent transformation, and regional integration. Building on the structured dataset, the study constructs a multi-algorithm key condition identification framework to enhance the stability and reliability of variable selection. This framework integratesensemble tree models, regularized linear models, and statistical testing methods, and synthesizes their outputs through a consensus-based frequency approach. By emphasizing agreement across different algorithmic assumptions, the framework reduces the bias associated with any single model and highlights the most stable and influential driving conditions associated with each transformation mode.The results indicate that the existing literature exhibits a highly concentrated attention structure, with the policy environment and industrial structure consistently receiving the highest levels of scholarly attention. This concentration reflects the prominent role of government-led top-level design in China’s resource-based area transformation, where institutional arrangements, policy instruments, and strategic planning are widely recognized as core drivers. At the same time, a clear evolutionary trend can be observed. Early research was overwhelmingly policy-oriented, whereas more recent studies show a marked increase in attention to the technological environment, particularly in relation to digital transformation, innovation platforms, and the energy transition under carbon constraints. Although market mechanisms, regional coordination, and urbanrural integration remain relatively underrepresented, their presence in the literature has gradually expanded, indicating a slow but discernible broadening of analytical perspectives.Further analysis reveals substantial heterogeneity in the configurations of key driving conditions across different transformation modes. Green transformation, cultural tourism transformation, industrial diversification, and regional integration all position the policy environment as a central driver, yet each emphasizes different complementary mechanisms. Green transformation is characterized by the combined effects of policy enforcement and endogenous industrial restructuring; cultural tourism transformation relies on policy support alongside spatial restructuring and urban-rural integration; industrial diversification emphasizes strategic policy guidance coupled with industrial upgrading and market expansion; and regional integration highlights the joint role of regional connectivity and policy coordination. In contrast, platform-dependent transformation follows a distinct logic, in which the construction of technological platforms, such as innovation parks, research infrastructure, and collaborative innovation systems—and the activation of market vitality emerge as the primary driving forces, with policy support playing a secondary but enabling role. From a methodological perspective, the study demonstrates that integrating LLM-based deep semantic understanding with multi-algorithm ML analysis provides an effective way to overcome the limitations of traditional bibliometric approaches. This integrated framework enables large-scale, field-level, and mechanism-oriented knowledge discovery, offering a more nuanced understanding of transformation drivers. In fact, the findings contribute a differentiated and empirically grounded account of resource-based area transformation, providing a rigorous reference for future theoretical research and for the formulation of more balanced and resilient transformation policies that move beyond excessive reliance on policy intervention toward a coordinated role of markets, technology, and regional collaboration.
The transformation of resource-based areas represents a critical strategic task in China’s pursuit of high-quality regional development, particularly under the combined pressures of resource depletion, ecological constraints, and structural economic adjustment. Historically dependent on the extraction and primary processing of natural resources such as coal, minerals, and petroleum, these areas have long played a foundational role in national industrialization. However, persistent path dependence and the well-documented “resource curse” have increasingly exposed them to economic stagnation, environmental degradation, and social imbalance. In this context, a systematic understanding of how academic research on resource-based area transformation has evolved, as well as a clear identification of the key driving conditions underlying different transformation pathways, is essential for advancing theory and informing policy practice.Previous studies on resource-based area transformation can generally be grouped into three methodological streams: qualitative case-based analyses, quantitative econometric research, and bibliometric or knowledge-mapping studies. While each has generated valuable insights, their limitations are also evident. Qualitative case studies offer rich contextual understanding but often lack generalizability. Quantitative econometric approaches typically focus on selected explanatory variables and outcomes, making it difficult to capture the internal mechanisms and multidimensional interactions involved in transformation processes. Bibliometric analyses, relying on tools such as citation networks and keyword co-occurrence, are effective in identifying research hotspots and collaboration patterns, yet they remain constrained to surface-level information and are insufficient for uncovering mechanism-oriented semantic structures and their evolution over time. As a result, a methodological gap persists in conducting large-scale, fine-grained, and mechanism-focused synthesis of the transformation literature.To address this gap, this study develops a hybrid analytical framework that integrates large language models (LLMs) with multi-algorithm machine learning (ML) techniques to enable structured text mining and robust identification of key driving conditions. The analysis is based on a corpus of 1,240 Chinese-language academic articles published in authoritative journals indexed in CNKI that address resource-based area transformation. Using an LLM-based structured extraction approach supported by carefully designed prompt engineering, unstructured full-text content is transformed into a standardized dataset. This process enables field-level semantic judgment across 61 predefined indicators, encompassing seven dimensions of driving conditions—policy environment, market environment, technological environment, regional environment, industrial structure, factor structure, and urban–rural structure— as well as five representative transformation modes: green transformation, cultural tourism transformation, industrial diversification, platform-dependent transformation, and regional integration. Building on the structured dataset, the study constructs a multi-algorithm key condition identification framework to enhance the stability and reliability of variable selection. This framework integratesensemble tree models, regularized linear models, and statistical testing methods, and synthesizes their outputs through a consensus-based frequency approach. By emphasizing agreement across different algorithmic assumptions, the framework reduces the bias associated with any single model and highlights the most stable and influential driving conditions associated with each transformation mode.The results indicate that the existing literature exhibits a highly concentrated attention structure, with the policy environment and industrial structure consistently receiving the highest levels of scholarly attention. This concentration reflects the prominent role of government-led top-level design in China’s resource-based area transformation, where institutional arrangements, policy instruments, and strategic planning are widely recognized as core drivers. At the same time, a clear evolutionary trend can be observed. Early research was overwhelmingly policy-oriented, whereas more recent studies show a marked increase in attention to the technological environment, particularly in relation to digital transformation, innovation platforms, and the energy transition under carbon constraints. Although market mechanisms, regional coordination, and urbanrural integration remain relatively underrepresented, their presence in the literature has gradually expanded, indicating a slow but discernible broadening of analytical perspectives.Further analysis reveals substantial heterogeneity in the configurations of key driving conditions across different transformation modes. Green transformation, cultural tourism transformation, industrial diversification, and regional integration all position the policy environment as a central driver, yet each emphasizes different complementary mechanisms. Green transformation is characterized by the combined effects of policy enforcement and endogenous industrial restructuring; cultural tourism transformation relies on policy support alongside spatial restructuring and urban-rural integration; industrial diversification emphasizes strategic policy guidance coupled with industrial upgrading and market expansion; and regional integration highlights the joint role of regional connectivity and policy coordination. In contrast, platform-dependent transformation follows a distinct logic, in which the construction of technological platforms, such as innovation parks, research infrastructure, and collaborative innovation systems—and the activation of market vitality emerge as the primary driving forces, with policy support playing a secondary but enabling role. From a methodological perspective, the study demonstrates that integrating LLM-based deep semantic understanding with multi-algorithm ML analysis provides an effective way to overcome the limitations of traditional bibliometric approaches. This integrated framework enables large-scale, field-level, and mechanism-oriented knowledge discovery, offering a more nuanced understanding of transformation drivers. In fact, the findings contribute a differentiated and empirically grounded account of resource-based area transformation, providing a rigorous reference for future theoretical research and for the formulation of more balanced and resilient transformation policies that move beyond excessive reliance on policy intervention toward a coordinated role of markets, technology, and regional collaboration.
2026(1),15-21
DOI: 10.13791/j.cnki.hsfwest.20251028005
Abstract:
Resource-based cities have long faced prominent contradictions between economic growth and ecological protection. Faced with the urgent requirements of tightening resource and environmental constraints and transforming development modes, promoting dynamic synergy between green economic development and urban ecological resilience has become crucial for achieving sustainable development. Exploring the interactive relationship and coordinated development mechanism between green development and ecological resilience is not only an internal demand for revealing the transformation and development logic of resource-based cities, but also an important entry point for solving their “development versus conservation” reality dilemma and achieving regional sustainable development. As the core agglomeration area of resource-based cities in China, the Huanghuai region has long faced the dual pressure of economic growth and ecological protection. Taking resource-based cities in the Huanghuai region as the research object, based on panel data from 2013 to 2023, a green development efficiency and ecological resilience measurement index system was constructed using input-output model and resistance-adaptation-restoration framework. The super-efficiency SBM model and comprehensive index method were comprehensively used to measure the urban green development efficiency and ecological resilience index, and the coupling coordination degree model and Tobit model were used to reveal the evolution characteristics and influencing factors of the coupling coordination relationship. The research results indicate that during the study period, the overall green development efficiency of resource-based cities in the Huanghuai region showed a fluctuating trend, with an average lower than that of non resource-based cities, and the gap widened. Among them, regenerative cities have the highest efficiency, while declining cities have the lowest efficiency. Among provinces, Jiangsu performs the best, while Henan lags behind the most. In terms of ecological resilience index, the overall trend of the whole region is steadily increasing, and the gap between resource-based and non resource -based cities is relatively small. Regenerative cities have a leading level of resilience, while mature and declining cities still face significant ecological pressure due to the historical impact of resource development. This indicates that resource-based cities have achieved certain results in ecological restoration, but there is still significant room for improvement in green industry transformation and economic structure optimization. The coupling coordination degree between green development efficiency and ecological resilience of resource-based cities in the Huanghuai region has increased from 0.429 in 2013 to 0.547 in 2023, with an average annual growth rate of 2.46%. The overall situation has evolved from an imbalanced state to a coordinated state, but it is still in a barely coordinated stage, significantly lagging behind non resource-based cities. There are significant differences in coordination levels between different types of cities: regenerative cities have a higher degree of coordination and stablegrowth, mature cities have slow growth, and declining cities, although growing rapidly, have a low base and are still in an imbalanced range. At the inter provincial level, Jiangsu has a leading level of coordination, followed by Shandong and Anhui, while Henan has the lowest and is still on the edge of imbalance. The problem of uneven regional development is prominent. Economic development, industrial structure, and technological innovation have a significant positive promoting effect on the coupling coordination degree, indicating that intensive economic development, green industrial transformation, and technological innovation are key driving forces for promoting the synergistic improvement of efficiency and resilience. The urbanization process, population density, spatial agglomeration, and opening up to the outside world have shown significant negative impacts, reflecting that problems such as rapid urban expansion, population agglomeration, and mismatch of foreign investment structure still constrain the coordinated development. The government intervention did not pass the significance test, indicating that there is still room for optimization in policy implementation and fund allocation of current government science and technology expenditures. Overall, the coordinated development level of green development efficiency and ecological resilience in the Huanghuai region has shown a steady improvement trend, but the imbalance between regions and types is still prominent. In the future, it is necessary to further strengthen the regional coordination mechanism, focus on promoting the synergy between industrial transformation and upgrading and ecological environment protection, especially for declining cities with low coordination and resource-based cities in Henan Province, targeted support measures should be taken to increase the governance of historical legacy issues. From the coupling perspective of efficiency and resilience, this study reveals the differentiated characteristics and driving factors in the transformation of resource-based cities in the Huanghuai region, providing theoretical foundations and policy insights for the coordinated governance of green and low-carbon development and ecological resilience construction in similar regions.
Resource-based cities have long faced prominent contradictions between economic growth and ecological protection. Faced with the urgent requirements of tightening resource and environmental constraints and transforming development modes, promoting dynamic synergy between green economic development and urban ecological resilience has become crucial for achieving sustainable development. Exploring the interactive relationship and coordinated development mechanism between green development and ecological resilience is not only an internal demand for revealing the transformation and development logic of resource-based cities, but also an important entry point for solving their “development versus conservation” reality dilemma and achieving regional sustainable development. As the core agglomeration area of resource-based cities in China, the Huanghuai region has long faced the dual pressure of economic growth and ecological protection. Taking resource-based cities in the Huanghuai region as the research object, based on panel data from 2013 to 2023, a green development efficiency and ecological resilience measurement index system was constructed using input-output model and resistance-adaptation-restoration framework. The super-efficiency SBM model and comprehensive index method were comprehensively used to measure the urban green development efficiency and ecological resilience index, and the coupling coordination degree model and Tobit model were used to reveal the evolution characteristics and influencing factors of the coupling coordination relationship. The research results indicate that during the study period, the overall green development efficiency of resource-based cities in the Huanghuai region showed a fluctuating trend, with an average lower than that of non resource-based cities, and the gap widened. Among them, regenerative cities have the highest efficiency, while declining cities have the lowest efficiency. Among provinces, Jiangsu performs the best, while Henan lags behind the most. In terms of ecological resilience index, the overall trend of the whole region is steadily increasing, and the gap between resource-based and non resource -based cities is relatively small. Regenerative cities have a leading level of resilience, while mature and declining cities still face significant ecological pressure due to the historical impact of resource development. This indicates that resource-based cities have achieved certain results in ecological restoration, but there is still significant room for improvement in green industry transformation and economic structure optimization. The coupling coordination degree between green development efficiency and ecological resilience of resource-based cities in the Huanghuai region has increased from 0.429 in 2013 to 0.547 in 2023, with an average annual growth rate of 2.46%. The overall situation has evolved from an imbalanced state to a coordinated state, but it is still in a barely coordinated stage, significantly lagging behind non resource-based cities. There are significant differences in coordination levels between different types of cities: regenerative cities have a higher degree of coordination and stablegrowth, mature cities have slow growth, and declining cities, although growing rapidly, have a low base and are still in an imbalanced range. At the inter provincial level, Jiangsu has a leading level of coordination, followed by Shandong and Anhui, while Henan has the lowest and is still on the edge of imbalance. The problem of uneven regional development is prominent. Economic development, industrial structure, and technological innovation have a significant positive promoting effect on the coupling coordination degree, indicating that intensive economic development, green industrial transformation, and technological innovation are key driving forces for promoting the synergistic improvement of efficiency and resilience. The urbanization process, population density, spatial agglomeration, and opening up to the outside world have shown significant negative impacts, reflecting that problems such as rapid urban expansion, population agglomeration, and mismatch of foreign investment structure still constrain the coordinated development. The government intervention did not pass the significance test, indicating that there is still room for optimization in policy implementation and fund allocation of current government science and technology expenditures. Overall, the coordinated development level of green development efficiency and ecological resilience in the Huanghuai region has shown a steady improvement trend, but the imbalance between regions and types is still prominent. In the future, it is necessary to further strengthen the regional coordination mechanism, focus on promoting the synergy between industrial transformation and upgrading and ecological environment protection, especially for declining cities with low coordination and resource-based cities in Henan Province, targeted support measures should be taken to increase the governance of historical legacy issues. From the coupling perspective of efficiency and resilience, this study reveals the differentiated characteristics and driving factors in the transformation of resource-based cities in the Huanghuai region, providing theoretical foundations and policy insights for the coordinated governance of green and low-carbon development and ecological resilience construction in similar regions.
2026(1),22-34
DOI: 10.13791/j.cnki.hsfwest.20251207003
Abstract:
Under the mounting pressures of global climate change and energy crises, achieving carbon peak and neutrality goals has become a pivotal national strategy for China’s sustainable development. Resource-based cities, which have historically relied on the extraction and processing of local minerals and forests resources, constitute a crucial part of the country’s energy and resource security framework. However, their typically mono-industrial structure, dominated by energy-intensive and high-emission sectors, poses significant challenges to national carbon reduction goals while also offering substantial potential for emission mitigation. Consequently, exploring pathways for these cities to achieve synergistic progress in low-carbon transition and high-quality development is of urgent theoretical and practical importance under the twin goals of carbon peak and carbon neutrality. This study focused on 115 prefecture-level resource-based cities across China, utilizing carbon emissions inverted from nighttime light data. The dataset was constructed by integrating and applying continuity corrections, noise reduction, and inter-calibration to the DMSP-OLS (2000-2013) and NPPVIIRS (2012-2021) imagery, enhancing spatial comparability and temporal consistency. Additionally, this paper constructs a comprehensive, multidimensional evaluation system to measure high-quality development levels. Moving beyond generic frameworks, the system incorporated indicators specific to resource-based cities' challenges and potentials. Grounded in the “new development philosophy”, it assessed five key dimensions: innovation, coordination, openness, sustainability, and sharing. The entropy weight method, an objective weighting technique, was applied to synthesize these indicators into a composite high-quality development index for each city annually. Spatio-temporal evolution characteristics were analyzed using global spatial autocorrelation and hotspot/coldspot analysis. The decoupling relationship between carbon emission growth and high-quality development progress was examined using the decoupling model, replacing traditional GDP with the calculated high-quality development index to assess their dynamic linkage. The main findings are as follows. 1) Spatiotemporal Dynamics of Carbon Emissions. From 2000 to 2021, the total carbon emissions of these resource-based cities exhibited a persistent upward trend, increasing by approximately 297.39% from 895.31 Mt to 3 557.90 Mt, with an average annual growth rate of 6.97%. The trend showed three phases: rapid growth (2000-2012), a slight decline (2012-2016), and steady regrowth (2016-2021). Spatially, emissions displayed significant agglomeration characteristics, forming a pattern of high in the central and eastern regions, low in the western and northeastern regions. Cities in Shanxi, Hebei, and northern Shaanxi experienced the most pronounced increases. Among city types, regenerative cities had the highest absolute emissions, while growing cities exhibited the highest growth rate. Regionally, central region cities surpassed eastern cities in total emissions after 2016, and western cities overtook northeastern cities after 2017. 2) Spatio-temporal Evolution of High-QualityDevelopment. The overall high-quality development level of resource-based cities followed an inverted U-shaped trajectory, rising from an average index of 0.031 in 2000 to a peak of 0.256 in 2017, before declining to 0.151 in 2021. The overall increase across the period was 394.01%. Spatially, high-quality development levels demonstrated significant positive spatial autocorrelation and a clear descending gradient from eastern to central to western regions. Hot spots and sub-hot spots clusters were consistently concentrated in the eastern and central regions. In contrast, cold spot and sub-cold spot areas, initially widespread in the northeast in the early 2000s, contracted and later shifted back towards northeastern and northern inland regions by 2021, indicating a growing regional disparity in development quality. 3) The Decoupling Relationship between Carbon Emissions and High-quality Development. The decoupling analysis reveals that a stable decoupling state between carbon emissions and high-quality development has not been achieved for resource-based cities as a whole. The elasticity indices fluctuated significantly across the study period. Relative decoupling occurred in several years, where emission growth rate was positive but lower than HQD growth rate. However, expansive negative decoupling was observed in periods like 2001-2002 and 2016-2017, both high-quality development and emissions grow, with emission growth faster. More notably, strong negative decoupling occurred frequently, particularly after 2017. This indicates that the driving force of economic growth still overwhelmingly surpasses the reduction effect of carbon emission inhibitors like technological efficiency gains and structural adjustment in most years. The decoupling state remains unstable and fragile.
Under the mounting pressures of global climate change and energy crises, achieving carbon peak and neutrality goals has become a pivotal national strategy for China’s sustainable development. Resource-based cities, which have historically relied on the extraction and processing of local minerals and forests resources, constitute a crucial part of the country’s energy and resource security framework. However, their typically mono-industrial structure, dominated by energy-intensive and high-emission sectors, poses significant challenges to national carbon reduction goals while also offering substantial potential for emission mitigation. Consequently, exploring pathways for these cities to achieve synergistic progress in low-carbon transition and high-quality development is of urgent theoretical and practical importance under the twin goals of carbon peak and carbon neutrality. This study focused on 115 prefecture-level resource-based cities across China, utilizing carbon emissions inverted from nighttime light data. The dataset was constructed by integrating and applying continuity corrections, noise reduction, and inter-calibration to the DMSP-OLS (2000-2013) and NPPVIIRS (2012-2021) imagery, enhancing spatial comparability and temporal consistency. Additionally, this paper constructs a comprehensive, multidimensional evaluation system to measure high-quality development levels. Moving beyond generic frameworks, the system incorporated indicators specific to resource-based cities' challenges and potentials. Grounded in the “new development philosophy”, it assessed five key dimensions: innovation, coordination, openness, sustainability, and sharing. The entropy weight method, an objective weighting technique, was applied to synthesize these indicators into a composite high-quality development index for each city annually. Spatio-temporal evolution characteristics were analyzed using global spatial autocorrelation and hotspot/coldspot analysis. The decoupling relationship between carbon emission growth and high-quality development progress was examined using the decoupling model, replacing traditional GDP with the calculated high-quality development index to assess their dynamic linkage. The main findings are as follows. 1) Spatiotemporal Dynamics of Carbon Emissions. From 2000 to 2021, the total carbon emissions of these resource-based cities exhibited a persistent upward trend, increasing by approximately 297.39% from 895.31 Mt to 3 557.90 Mt, with an average annual growth rate of 6.97%. The trend showed three phases: rapid growth (2000-2012), a slight decline (2012-2016), and steady regrowth (2016-2021). Spatially, emissions displayed significant agglomeration characteristics, forming a pattern of high in the central and eastern regions, low in the western and northeastern regions. Cities in Shanxi, Hebei, and northern Shaanxi experienced the most pronounced increases. Among city types, regenerative cities had the highest absolute emissions, while growing cities exhibited the highest growth rate. Regionally, central region cities surpassed eastern cities in total emissions after 2016, and western cities overtook northeastern cities after 2017. 2) Spatio-temporal Evolution of High-QualityDevelopment. The overall high-quality development level of resource-based cities followed an inverted U-shaped trajectory, rising from an average index of 0.031 in 2000 to a peak of 0.256 in 2017, before declining to 0.151 in 2021. The overall increase across the period was 394.01%. Spatially, high-quality development levels demonstrated significant positive spatial autocorrelation and a clear descending gradient from eastern to central to western regions. Hot spots and sub-hot spots clusters were consistently concentrated in the eastern and central regions. In contrast, cold spot and sub-cold spot areas, initially widespread in the northeast in the early 2000s, contracted and later shifted back towards northeastern and northern inland regions by 2021, indicating a growing regional disparity in development quality. 3) The Decoupling Relationship between Carbon Emissions and High-quality Development. The decoupling analysis reveals that a stable decoupling state between carbon emissions and high-quality development has not been achieved for resource-based cities as a whole. The elasticity indices fluctuated significantly across the study period. Relative decoupling occurred in several years, where emission growth rate was positive but lower than HQD growth rate. However, expansive negative decoupling was observed in periods like 2001-2002 and 2016-2017, both high-quality development and emissions grow, with emission growth faster. More notably, strong negative decoupling occurred frequently, particularly after 2017. This indicates that the driving force of economic growth still overwhelmingly surpasses the reduction effect of carbon emission inhibitors like technological efficiency gains and structural adjustment in most years. The decoupling state remains unstable and fragile.
2026(1),35-45
DOI: 10.13791/j.cnki.hsfwest.20251027001
Abstract:
Industrial symbiosis achieves carbon reduction, pollution control, and sustainable growth through three dimensions: source reduction, process optimization, and end-of-pipe treatment, playing a pivotal role in ecological conservation and high-quality development. This paper begins with the conceptual framework of industrial symbiosis, employing bibliometric visualization to analyze global research trends. It systematically examines its developmental stages, influencing factors, case studies, and methodological advancements. The study reveals:1) industrial symbiosis is a mutually cooperative relationship between symbionts, and its structural form is a network. Industrial symbiosis has dynamic attributes and adaptability. In the process of industrial development, new symbionts will join the original symbiotic system, and the original symbionts may also withdraw from it. The "joining/ withdrawal" of new and old symbionts reflects their adaptability, and the dynamics and adaptability change the original symbiotic chains and networks. The symbionts in industrial symbiosis are various enterprises and coordinating institutions, and the goal of industrial symbiosis is to maximize the benefits of symbionts in the symbiosis and minimize ecological and environmental damage. 2) Research on industrial symbiosis both at home and abroad entered a period of rapid development after 2005, but there are significant differences in evolutionary trends, disciplinary layouts, and academic cooperation characteristics. Domestic research focuses on fields such as macroeconomics and sustainable development, with a low density of connections in the author network; foreign research concentrates on environmental science, green and sustainable technologies, etc., and the author cooperation network is more dense. Comparatively speaking, there are research gaps in China. 3) The development of industrial symbiosis follows a progressive law and is driven by multiple factors such as geographical proximity, social support, symbiotic awareness, information sharing and trust, information technology and infrastructure, and policies and systems. 4) Cases of industrial symbiosis at home and abroad include those at the national scale, urban scale, industrial park scale, and enterprise group scale. Among different scales, the industrial park scale is the most common, and the urban scale is less. In many cases, research methods such as enterprise interviews, field surveys, and questionnaire surveys are adopted, which are the most basic and necessary methods for industrial symbiosis research; material and energy flow analysis and life cycle assessment are traditional research methods for industrial symbiosis case studies; social network analysis is a newly emerging method in recent years, and more cases will adopt this method in the future. The research methods of industrial symbiosis have expanded from focusing on material flow and economic benefits to focusing on industrial symbiosis networks. 5) Industrial symbiosis can achieve carbon reduction and pollution reduction from the three dimensions of source reduction, process optimization, and end-of-pipe treatment, which is of great significance to ecological protection and high-quality development, especially in the Yellow River Basin where resource-based cities account for a high proportion. Currently, the sustainable development of resource-based cities in the Yellow River Basin mostly focuses on industrial transformation, but the transformation is faced with difficulties such as slow progress and slow cultivation of alternative industries. The introduction of industrial symbiosis theory can promote the establishment of symbiotic relationships between industries and enterprises in cities,achieve the maximization of economic benefits and the minimization of ecological and environmental damage, which is in line with the strategy of ecological protection and high-quality development of the Yellow River Basin and can be a useful supplement to industrial transformation. However, compared with the abundant research on industrial transformation, the research on industrial symbiosis in resource-based cities in the Yellow River Basin is still relatively weak and urgently needs systematic exploration. The depth and systematicness of existing industrial symbiosis case studies need to be strengthened, with three shortcomings: firstly, the lack of an integrated perspective, mostly focusing on single dimensions such as material and energy flow analysis and characteristics of symbiotic relationships, failing to comprehensively and systematically analyze the same case; secondly, insufficient research on driving mechanisms, even if involved, it is limited to a single factor, without considering the synergistic effect of multiple factors such as policies, markets, and technologies; thirdly, the disconnection between results and practice, as most studies do not transform conclusions into optimization paths for industrial symbiosis, making it difficult to guide practice. In the future, a multi-dimensional integrated analysis framework can be constructed to break the limitation of a single perspective and realize the systematic coupling analysis of dimensions such as material and energy flow and symbiotic characteristics. Focus on multiple factors such as policies, markets, and technologies, dig deep into their synergistic driving mechanisms, and break through the bottleneck of single-factor research. Closely link with actual scenarios, transform research conclusions into operable optimization paths, strengthen the implementation of results, build a bridge between research and practice, and provide precise guidance for the high-quality development of regional industrial symbiosis.
Industrial symbiosis achieves carbon reduction, pollution control, and sustainable growth through three dimensions: source reduction, process optimization, and end-of-pipe treatment, playing a pivotal role in ecological conservation and high-quality development. This paper begins with the conceptual framework of industrial symbiosis, employing bibliometric visualization to analyze global research trends. It systematically examines its developmental stages, influencing factors, case studies, and methodological advancements. The study reveals:1) industrial symbiosis is a mutually cooperative relationship between symbionts, and its structural form is a network. Industrial symbiosis has dynamic attributes and adaptability. In the process of industrial development, new symbionts will join the original symbiotic system, and the original symbionts may also withdraw from it. The "joining/ withdrawal" of new and old symbionts reflects their adaptability, and the dynamics and adaptability change the original symbiotic chains and networks. The symbionts in industrial symbiosis are various enterprises and coordinating institutions, and the goal of industrial symbiosis is to maximize the benefits of symbionts in the symbiosis and minimize ecological and environmental damage. 2) Research on industrial symbiosis both at home and abroad entered a period of rapid development after 2005, but there are significant differences in evolutionary trends, disciplinary layouts, and academic cooperation characteristics. Domestic research focuses on fields such as macroeconomics and sustainable development, with a low density of connections in the author network; foreign research concentrates on environmental science, green and sustainable technologies, etc., and the author cooperation network is more dense. Comparatively speaking, there are research gaps in China. 3) The development of industrial symbiosis follows a progressive law and is driven by multiple factors such as geographical proximity, social support, symbiotic awareness, information sharing and trust, information technology and infrastructure, and policies and systems. 4) Cases of industrial symbiosis at home and abroad include those at the national scale, urban scale, industrial park scale, and enterprise group scale. Among different scales, the industrial park scale is the most common, and the urban scale is less. In many cases, research methods such as enterprise interviews, field surveys, and questionnaire surveys are adopted, which are the most basic and necessary methods for industrial symbiosis research; material and energy flow analysis and life cycle assessment are traditional research methods for industrial symbiosis case studies; social network analysis is a newly emerging method in recent years, and more cases will adopt this method in the future. The research methods of industrial symbiosis have expanded from focusing on material flow and economic benefits to focusing on industrial symbiosis networks. 5) Industrial symbiosis can achieve carbon reduction and pollution reduction from the three dimensions of source reduction, process optimization, and end-of-pipe treatment, which is of great significance to ecological protection and high-quality development, especially in the Yellow River Basin where resource-based cities account for a high proportion. Currently, the sustainable development of resource-based cities in the Yellow River Basin mostly focuses on industrial transformation, but the transformation is faced with difficulties such as slow progress and slow cultivation of alternative industries. The introduction of industrial symbiosis theory can promote the establishment of symbiotic relationships between industries and enterprises in cities,achieve the maximization of economic benefits and the minimization of ecological and environmental damage, which is in line with the strategy of ecological protection and high-quality development of the Yellow River Basin and can be a useful supplement to industrial transformation. However, compared with the abundant research on industrial transformation, the research on industrial symbiosis in resource-based cities in the Yellow River Basin is still relatively weak and urgently needs systematic exploration. The depth and systematicness of existing industrial symbiosis case studies need to be strengthened, with three shortcomings: firstly, the lack of an integrated perspective, mostly focusing on single dimensions such as material and energy flow analysis and characteristics of symbiotic relationships, failing to comprehensively and systematically analyze the same case; secondly, insufficient research on driving mechanisms, even if involved, it is limited to a single factor, without considering the synergistic effect of multiple factors such as policies, markets, and technologies; thirdly, the disconnection between results and practice, as most studies do not transform conclusions into optimization paths for industrial symbiosis, making it difficult to guide practice. In the future, a multi-dimensional integrated analysis framework can be constructed to break the limitation of a single perspective and realize the systematic coupling analysis of dimensions such as material and energy flow and symbiotic characteristics. Focus on multiple factors such as policies, markets, and technologies, dig deep into their synergistic driving mechanisms, and break through the bottleneck of single-factor research. Closely link with actual scenarios, transform research conclusions into operable optimization paths, strengthen the implementation of results, build a bridge between research and practice, and provide precise guidance for the high-quality development of regional industrial symbiosis.
2026(1),46-53
DOI: 10.13791/j.cnki.hsfwest.20241112003
Abstract:
Since the mid-20th century, the rapid development of heavy industries has stimulated the emergence of many resource-based industrial cities in China. However, these cities have faced some challenges, such as resource depletion, environmental pollution, a mono-industrial economic structure, and policy constraints over the past decades. The transformation and renewal of these resource-exhausted cities have thus become a critical issue for the high-quality development of cities in China. The existing literature on the transformation of resource-exhausted cities shows that industrial substitution, industrial chain extension, and the combination of above-mentioned ways have been widely used to facilitate the renewal and transformation of resource-exhausted cities in developed economies. Meanwhile, Chinese empirical studies reveal that high-quality development, smart growth, carbon emission reduction, and territorial spatial development have been considered as the important strategies for the transformation of resource-exhausted cities. When compared the coal-resource-exhausted cities in China, such as Fuxin, Fushun, Hegang in the northeast, Zaozhuang in Shandong, Pingxiang in Jiangxi, and Shaoguan in Guangdong with those in industrialized regions in developed economies, such as Dortmund, Germany, it is found that they have faced similar challenges such as resource exhaustion, lagging economic development, population contraction, prominent livelihood and ecological protection concerns, weak capacity to attract investment, and pressure to reduce carbon emissions. Urban renewal serves as a common choice for promoting the transformation and development of resource-exhausted cities both at home and abroad. Given the successful renewal and transformation of Dortmund, a typical resource-exhausted city in Germany, this paper attempts to explore the process and mechanisms of transformation and renewal of Dortmund and aims to provide suggestions for the transformation and renewal of resource-exhausted cities in China. This paper shows that the economic development of Dortmund has undergone five stages, including pre-industrialization period, highly industrialized stage, period of economic recession triggered by the coal and steel crises, restructuring and transformation phase, and “new” Dortmund era. The launch of the “Dortmund Project” in 2000 marked a critical turning point. It successfully reversed the trends of population decrease and rising unemployment, and facilitated the transformation of the industrial structure from a dominance of primary and secondary industries towards a tertiary sector led by technology-intensive industries such as information technology, ecommerce, and microsystems technology.Drawing upon the Industrial Cluster Theory, Creative Class Theory, Resource-Based Theory, and Sustainable Development Theory, Dortmund facilitated the renewal and transformation from four dimensions, including industrial transformation, spatial transformation, ecological transformation, and institutional transformation. Furthermore, through the typical case of Phoenix Lake old industrial area, this paper shows that it applied four main regeneration strategies to facilitate renewal and transformation, including: 1) Driving urban renewal through institutional innovation, exemplified by strengthen public-private partnerships, establishing modern corporate systems, and special fundingmechanisms; 2) Promoting the development of industrial clusters through innovative development pathways, focusing on knowledge-based industries, fostering an innovation-conducive environment, providing venture capital, and cultivating talent; 3) Enhancing environmental quality through ecological spatial optimization, involving landscape remodeling, soil and river pollution remediation, and the creation of waterfront spaces; 4) Activating industrial heritage by implanting creative functions, transforming old structures into new functional spaces such as cultural venues and creative industry parks.Through the analysis of transformation and development strategies in Dortmund and its typical industrial and mining area, this paper provides suggestions for the renewal and governance of resource-exhausted cities and their brownfield sites in China, including: 1)multi-scale policy linkages between central and local governments; 2) coordinated advancement involving multiple departments and institutions; 3)multi-channel financial support; 4)formulating clear and diversified development goals; 5)providing refined and personalized services for talent and enterprises; 6)implementing sustainable long-term management of renewal projects. It is hoped that these insights will provide valuable experience and pathway references for their regeneration and revitalization.
Since the mid-20th century, the rapid development of heavy industries has stimulated the emergence of many resource-based industrial cities in China. However, these cities have faced some challenges, such as resource depletion, environmental pollution, a mono-industrial economic structure, and policy constraints over the past decades. The transformation and renewal of these resource-exhausted cities have thus become a critical issue for the high-quality development of cities in China. The existing literature on the transformation of resource-exhausted cities shows that industrial substitution, industrial chain extension, and the combination of above-mentioned ways have been widely used to facilitate the renewal and transformation of resource-exhausted cities in developed economies. Meanwhile, Chinese empirical studies reveal that high-quality development, smart growth, carbon emission reduction, and territorial spatial development have been considered as the important strategies for the transformation of resource-exhausted cities. When compared the coal-resource-exhausted cities in China, such as Fuxin, Fushun, Hegang in the northeast, Zaozhuang in Shandong, Pingxiang in Jiangxi, and Shaoguan in Guangdong with those in industrialized regions in developed economies, such as Dortmund, Germany, it is found that they have faced similar challenges such as resource exhaustion, lagging economic development, population contraction, prominent livelihood and ecological protection concerns, weak capacity to attract investment, and pressure to reduce carbon emissions. Urban renewal serves as a common choice for promoting the transformation and development of resource-exhausted cities both at home and abroad. Given the successful renewal and transformation of Dortmund, a typical resource-exhausted city in Germany, this paper attempts to explore the process and mechanisms of transformation and renewal of Dortmund and aims to provide suggestions for the transformation and renewal of resource-exhausted cities in China. This paper shows that the economic development of Dortmund has undergone five stages, including pre-industrialization period, highly industrialized stage, period of economic recession triggered by the coal and steel crises, restructuring and transformation phase, and “new” Dortmund era. The launch of the “Dortmund Project” in 2000 marked a critical turning point. It successfully reversed the trends of population decrease and rising unemployment, and facilitated the transformation of the industrial structure from a dominance of primary and secondary industries towards a tertiary sector led by technology-intensive industries such as information technology, ecommerce, and microsystems technology.Drawing upon the Industrial Cluster Theory, Creative Class Theory, Resource-Based Theory, and Sustainable Development Theory, Dortmund facilitated the renewal and transformation from four dimensions, including industrial transformation, spatial transformation, ecological transformation, and institutional transformation. Furthermore, through the typical case of Phoenix Lake old industrial area, this paper shows that it applied four main regeneration strategies to facilitate renewal and transformation, including: 1) Driving urban renewal through institutional innovation, exemplified by strengthen public-private partnerships, establishing modern corporate systems, and special fundingmechanisms; 2) Promoting the development of industrial clusters through innovative development pathways, focusing on knowledge-based industries, fostering an innovation-conducive environment, providing venture capital, and cultivating talent; 3) Enhancing environmental quality through ecological spatial optimization, involving landscape remodeling, soil and river pollution remediation, and the creation of waterfront spaces; 4) Activating industrial heritage by implanting creative functions, transforming old structures into new functional spaces such as cultural venues and creative industry parks.Through the analysis of transformation and development strategies in Dortmund and its typical industrial and mining area, this paper provides suggestions for the renewal and governance of resource-exhausted cities and their brownfield sites in China, including: 1)multi-scale policy linkages between central and local governments; 2) coordinated advancement involving multiple departments and institutions; 3)multi-channel financial support; 4)formulating clear and diversified development goals; 5)providing refined and personalized services for talent and enterprises; 6)implementing sustainable long-term management of renewal projects. It is hoped that these insights will provide valuable experience and pathway references for their regeneration and revitalization.
2026(1),54-62
DOI: 10.13791/j.cnki.hsfwest.20241030003
Abstract:
Human cognition of space is inextricably linked to the workings of the brain, yet how the human brain operates remains shrouded in numerous mysteries. Related brain science research constitutes a cutting-edge scientific question demanding urgent exploration. Concurrently, with the gradual proliferation of artificial intelligence and generative design applications, interdisciplinary research integrating brain science and architecture can both enrich fundamental studies on spatial brain cognition and contribute to architectural theory and the innovative exploration of brain-computer interaction design methods. Through a review and analysis of recent literature in related fields, this article identifies that primary research directions include parsing the brain mechanisms of spatial cognition, analyzing the impact of spatial cognition on brain health and emotions, and brain-computer interaction in design. Regarding the analysis of brain mechanisms for spatial cognition, some researchers in recent years have begun by parsing the fundamental brain mechanisms underlying spatial cognition – that is, how space influences and affects brain functional activity. The spatial elements involved range from more abstract basic spatial property elements to specific building types and even larger-scale urban open spaces. Some studies have utilized small-scale spatial constructs to assess the brain’s cognitive state concerning spatial elements, involving aspects like spatial perception and orientation in the brain. The relevant conclusions provide support for understanding the basic principles of human spatial cognition. Other scholars have approached from the perspective of architectural spatial scenes, investigating the impact of elements such as interior spaces and landmark buildings on brain activity. Unlike small and medium-scale spatial cognition research, urban spatial cognition studies focus more on large-scale spatial cognitive mechanisms, including wayfinding, path memory, and scene recognition.The aforementioned research has explored human brain activity responses in space through observational means like electroencephalography(EEG), enabling a deep analysis of the classic problem concerning the relationship between space and human cognition, which traditional architecture has long focused on. The spatial objects studied also encompass a variety of types, from abstract micro-spaces to buildings and further to urban open spaces. These studies have established a relatively mature research paradigm for architectural issues at both the object and methodological levels. By employing new technological means such as EEG monitoring, they have developed a set of methods for extracting and quantifying user perceptions and evaluations within space, providing technical and methodological support for analyzing related fundamental mechanisms. Building upon the analysis of brain mechanisms for spatial cognition, some research has further focused on the issue of how the spatial environment influences human emotions. In fields such as environmental psychology and healthy cities, the mechanisms linking space, behavior, and emotion have consistently garnered attention. Particularly, emotions and mental states induced by the environment, along with their corresponding impacts on physical and mental health, are current hot topics. Inspired by brain science theories and methods, some researchers have begun to examine the relationship between emotional health and brain activity mechanisms in environments, illustrating the impact of space on human cognitive health and emotions across multiple scales and types. This includes abilities like spatial orientation, navigation, and motor coordination within space, which subsequently affect psychological emotions and even social interactions. In recent years, some scholars have also explored brain-computer interaction and design technology methods. These studies involve interacting withcomputers and other devices through brain neural signals to explore theories and technical methods for spatial design or intervention. The integration of braincomputer intelligence and interactive design is a highly interdisciplinary field. Related research proposes a novel interdisciplinary approach. It can further explore practical applications supporting design interaction, achieving more direct human-computer design interaction or spatial use interaction, thereby enhancing the user experience in spatial design or use. These interdisciplinary studies can offer us insights. The path they embody – from basic to applied research, from internal mechanisms to health effects, and further to brain-computer interaction – is particularly worthy of our contemplation. The intrinsic thread of brain science crossover research is the integration of the trinity of “theoretical principles – demands – technology”. That is, it closely focuses on the core disciplinary issue of spatial brain cognition to analyze fundamental mechanisms. Based on this, it centers on demands such as human health and emotion, spatial quality improvement, and design participation/interaction, and combines cutting-edge technologies to explore methods and applications. This “theoretical principles-demands-technology” trinity also, to some extent, addresses the issue of scientization in architecture. It means both conducting frontier exploration through full interdisciplinary integration based on technological development, while simultaneously digging deep into theoretical depth, combining the two to interpret the intrinsic value and innovative potential of the architectural discipline.Furthermore, the main content of these crossover studies opens up a new field of research for us, namely the field of spatial brain science research concerning the “space – brain – machine” system. Inspired by advances in disciplines like brain science, it can take spatial brain science as a theme, actively exploring design theories and method systems influenced by fields like brain cognition and brain-computer interaction.
Human cognition of space is inextricably linked to the workings of the brain, yet how the human brain operates remains shrouded in numerous mysteries. Related brain science research constitutes a cutting-edge scientific question demanding urgent exploration. Concurrently, with the gradual proliferation of artificial intelligence and generative design applications, interdisciplinary research integrating brain science and architecture can both enrich fundamental studies on spatial brain cognition and contribute to architectural theory and the innovative exploration of brain-computer interaction design methods. Through a review and analysis of recent literature in related fields, this article identifies that primary research directions include parsing the brain mechanisms of spatial cognition, analyzing the impact of spatial cognition on brain health and emotions, and brain-computer interaction in design. Regarding the analysis of brain mechanisms for spatial cognition, some researchers in recent years have begun by parsing the fundamental brain mechanisms underlying spatial cognition – that is, how space influences and affects brain functional activity. The spatial elements involved range from more abstract basic spatial property elements to specific building types and even larger-scale urban open spaces. Some studies have utilized small-scale spatial constructs to assess the brain’s cognitive state concerning spatial elements, involving aspects like spatial perception and orientation in the brain. The relevant conclusions provide support for understanding the basic principles of human spatial cognition. Other scholars have approached from the perspective of architectural spatial scenes, investigating the impact of elements such as interior spaces and landmark buildings on brain activity. Unlike small and medium-scale spatial cognition research, urban spatial cognition studies focus more on large-scale spatial cognitive mechanisms, including wayfinding, path memory, and scene recognition.The aforementioned research has explored human brain activity responses in space through observational means like electroencephalography(EEG), enabling a deep analysis of the classic problem concerning the relationship between space and human cognition, which traditional architecture has long focused on. The spatial objects studied also encompass a variety of types, from abstract micro-spaces to buildings and further to urban open spaces. These studies have established a relatively mature research paradigm for architectural issues at both the object and methodological levels. By employing new technological means such as EEG monitoring, they have developed a set of methods for extracting and quantifying user perceptions and evaluations within space, providing technical and methodological support for analyzing related fundamental mechanisms. Building upon the analysis of brain mechanisms for spatial cognition, some research has further focused on the issue of how the spatial environment influences human emotions. In fields such as environmental psychology and healthy cities, the mechanisms linking space, behavior, and emotion have consistently garnered attention. Particularly, emotions and mental states induced by the environment, along with their corresponding impacts on physical and mental health, are current hot topics. Inspired by brain science theories and methods, some researchers have begun to examine the relationship between emotional health and brain activity mechanisms in environments, illustrating the impact of space on human cognitive health and emotions across multiple scales and types. This includes abilities like spatial orientation, navigation, and motor coordination within space, which subsequently affect psychological emotions and even social interactions. In recent years, some scholars have also explored brain-computer interaction and design technology methods. These studies involve interacting withcomputers and other devices through brain neural signals to explore theories and technical methods for spatial design or intervention. The integration of braincomputer intelligence and interactive design is a highly interdisciplinary field. Related research proposes a novel interdisciplinary approach. It can further explore practical applications supporting design interaction, achieving more direct human-computer design interaction or spatial use interaction, thereby enhancing the user experience in spatial design or use. These interdisciplinary studies can offer us insights. The path they embody – from basic to applied research, from internal mechanisms to health effects, and further to brain-computer interaction – is particularly worthy of our contemplation. The intrinsic thread of brain science crossover research is the integration of the trinity of “theoretical principles – demands – technology”. That is, it closely focuses on the core disciplinary issue of spatial brain cognition to analyze fundamental mechanisms. Based on this, it centers on demands such as human health and emotion, spatial quality improvement, and design participation/interaction, and combines cutting-edge technologies to explore methods and applications. This “theoretical principles-demands-technology” trinity also, to some extent, addresses the issue of scientization in architecture. It means both conducting frontier exploration through full interdisciplinary integration based on technological development, while simultaneously digging deep into theoretical depth, combining the two to interpret the intrinsic value and innovative potential of the architectural discipline.Furthermore, the main content of these crossover studies opens up a new field of research for us, namely the field of spatial brain science research concerning the “space – brain – machine” system. Inspired by advances in disciplines like brain science, it can take spatial brain science as a theme, actively exploring design theories and method systems influenced by fields like brain cognition and brain-computer interaction.
2026(1),63-71
DOI: 10.13791/j.cnki.hsfwest.20240924002
Abstract:
Pre-hospital Emergency Medical Services (EMS) represent the most time-critical component of urban public healthcare systems, as response speed and spatial coverage directly determine survival outcomes in acute and life-threatening conditions. With China experiencing rapid urbanization and unprecedented population mobility, cities are facing increasing pressure to maintain timely and effective emergency response. Using four first-tier cities as case studies, this research aims to construct a high-resolution, multi – source, data-driven evaluation framework to systematically quantify EMS accessibility and equity across urban regions. This study develops an advanced EMS accessibility model that integrates a 100-meter-resolution human settlement matrix, dynamic traffic conditions, and more than four million navigation-based origin – destination (OD) samples. Using these datasets across four representative traffic periods, the model produces high-precision spatiotemporal estimates of emergency accessibility for the four cities. In parallel, spatial equity and group equity are assessed using Theil index decomposition and income-linked linear regression models. Within this analytical framework, two core performance indicators are established: the population-weighted average EMS response time and the 12-minute isochrone population coverage rate. Collectively, these metrics allow for fine-scale comparisons across cities, districts, and urbanrural gradients, offering an integrated picture of service efficiency. To evaluate fairness, the study applies a Theil index decomposition approach to quantify spatial equity across administrative boundaries and uses linear regression—linked with spatialized income data derived from over 59 000 rental records—to measure group equity among socioeconomic strata. In addition, the integration of multi-source demographic, socioeconomic, and network-based mobility data enables cross-validation of urban EMS performance, ensuring that the model captures not only static spatial configurations but also dynamic behavioral patterns of urban residents. This significantly strengthens the robustness and transferability of the analytical framework.The results reveal clear spatiotemporal differences in EMS accessibility across the four megacities. During off-peak periods(00: 00), the cities show tightly clustered performance, with average response times ranging from 12.24 to 12.49 minutes and 12- minute isochrone coverage rates between 49.18% and 55.92%. However, congestion during peak periods dramatically reduces accessibility: response times rise to 13.49~15.64 minutes, and population coverage drops sharply to 25.05%~41.62%. Among all cities, Shenzhen exhibits the steepest decline, reflecting the combined impact of rapid population growth, dense road networks, and high traffic pressure. Spatial equity results show that inequalities remain deeply embedded in EMS service distribution. Shanghai exhibits the highest spatial inequity, with a total Theil index of 0.0949 at 00: 00, 94%~98% of which is attributed to pronounced differences between central districts and peripheral areas. Guangzhou displays a similar pattern of inequity, albeit at slightly lower intensity.Beijing and Shenzhen show more moderate inequity, yet both continue to demonstrate substantial disparities between urban cores, peri-urban districts, and rural fringes—particularly in response times exceeding 16 minutes in some outer-suburban zones.Urban-rural comparisons further highlight systemic disadvantage for townships and outer districts. At midnight, Shanghai’s urban-rural response-time gap reaches 2.08 minutes, followed by Guangzhou and Shenzhen, indicating structural rather than incidental inequality. Even in Beijing—the most balanced city—peri-urban gaps remain evident, reflecting supply-demand imbalances, road-network limitations, and geographic constraints.Group equity analysis demonstrates a robust and statistically significant association (P<0.001) between income levels and EMS accessibility across all four cities. In Shanghai, each 1% decline in income corresponds to a 0.054-minute increase in response time—the steepest gradient among the four. Guangzhou (0.042 minutes) and Beijing (0.040 minutes) follow closely, while Shenzhen shows the smallest but still meaningful gradient (0.016 minutes). These results suggest that—even in highly developed megacities—lower-income populations systematically face longer waiting times for emergency care, highlighting persistent socioeconomic vulnerability in the EMS system.Taken together, the findings reveal that while the EMS systems of China’s first-tier cities have achieved commendable progress in improving efficiency, they continue to exhibit substantial shortcomings in terms of equitable allocation. Persistent disparities across districts, between urban and rural areas, and among income groups indicate that efficiency-oriented planning alone cannot guarantee equitable emergency access.The study argues that single-indicator evaluation frameworks—such as Shanghai's well-known 12- minute citywide benchmark—are insufficient for capturing the multidimensional nature of EMS performance. Instead, a comprehensive evaluation system that integrates efficiency, spatial justice, and socioeconomic equity is urgently needed. The spatiotemporal modeling approach developed in this study—linking APIbased dynamic travel data, human settlement matrices, and inequality diagnostics—offers a transferable analytical tool that can be extended beyond EMS to other critical public-service systems such as healthcare delivery, firefighting response, disaster-relief coordination, and urban safety management.Ultimately, by revealing the structural mechanisms behind unequal EMS access, this study provides essential scientific evidence to support the optimization of China’s emergency response networks. It offers actionable insights for policymakers seeking to promote more equitable, resilient, and people-centered urban development in the context of rapid urbanization and increasing mobility demands.
Pre-hospital Emergency Medical Services (EMS) represent the most time-critical component of urban public healthcare systems, as response speed and spatial coverage directly determine survival outcomes in acute and life-threatening conditions. With China experiencing rapid urbanization and unprecedented population mobility, cities are facing increasing pressure to maintain timely and effective emergency response. Using four first-tier cities as case studies, this research aims to construct a high-resolution, multi – source, data-driven evaluation framework to systematically quantify EMS accessibility and equity across urban regions. This study develops an advanced EMS accessibility model that integrates a 100-meter-resolution human settlement matrix, dynamic traffic conditions, and more than four million navigation-based origin – destination (OD) samples. Using these datasets across four representative traffic periods, the model produces high-precision spatiotemporal estimates of emergency accessibility for the four cities. In parallel, spatial equity and group equity are assessed using Theil index decomposition and income-linked linear regression models. Within this analytical framework, two core performance indicators are established: the population-weighted average EMS response time and the 12-minute isochrone population coverage rate. Collectively, these metrics allow for fine-scale comparisons across cities, districts, and urbanrural gradients, offering an integrated picture of service efficiency. To evaluate fairness, the study applies a Theil index decomposition approach to quantify spatial equity across administrative boundaries and uses linear regression—linked with spatialized income data derived from over 59 000 rental records—to measure group equity among socioeconomic strata. In addition, the integration of multi-source demographic, socioeconomic, and network-based mobility data enables cross-validation of urban EMS performance, ensuring that the model captures not only static spatial configurations but also dynamic behavioral patterns of urban residents. This significantly strengthens the robustness and transferability of the analytical framework.The results reveal clear spatiotemporal differences in EMS accessibility across the four megacities. During off-peak periods(00: 00), the cities show tightly clustered performance, with average response times ranging from 12.24 to 12.49 minutes and 12- minute isochrone coverage rates between 49.18% and 55.92%. However, congestion during peak periods dramatically reduces accessibility: response times rise to 13.49~15.64 minutes, and population coverage drops sharply to 25.05%~41.62%. Among all cities, Shenzhen exhibits the steepest decline, reflecting the combined impact of rapid population growth, dense road networks, and high traffic pressure. Spatial equity results show that inequalities remain deeply embedded in EMS service distribution. Shanghai exhibits the highest spatial inequity, with a total Theil index of 0.0949 at 00: 00, 94%~98% of which is attributed to pronounced differences between central districts and peripheral areas. Guangzhou displays a similar pattern of inequity, albeit at slightly lower intensity.Beijing and Shenzhen show more moderate inequity, yet both continue to demonstrate substantial disparities between urban cores, peri-urban districts, and rural fringes—particularly in response times exceeding 16 minutes in some outer-suburban zones.Urban-rural comparisons further highlight systemic disadvantage for townships and outer districts. At midnight, Shanghai’s urban-rural response-time gap reaches 2.08 minutes, followed by Guangzhou and Shenzhen, indicating structural rather than incidental inequality. Even in Beijing—the most balanced city—peri-urban gaps remain evident, reflecting supply-demand imbalances, road-network limitations, and geographic constraints.Group equity analysis demonstrates a robust and statistically significant association (P<0.001) between income levels and EMS accessibility across all four cities. In Shanghai, each 1% decline in income corresponds to a 0.054-minute increase in response time—the steepest gradient among the four. Guangzhou (0.042 minutes) and Beijing (0.040 minutes) follow closely, while Shenzhen shows the smallest but still meaningful gradient (0.016 minutes). These results suggest that—even in highly developed megacities—lower-income populations systematically face longer waiting times for emergency care, highlighting persistent socioeconomic vulnerability in the EMS system.Taken together, the findings reveal that while the EMS systems of China’s first-tier cities have achieved commendable progress in improving efficiency, they continue to exhibit substantial shortcomings in terms of equitable allocation. Persistent disparities across districts, between urban and rural areas, and among income groups indicate that efficiency-oriented planning alone cannot guarantee equitable emergency access.The study argues that single-indicator evaluation frameworks—such as Shanghai's well-known 12- minute citywide benchmark—are insufficient for capturing the multidimensional nature of EMS performance. Instead, a comprehensive evaluation system that integrates efficiency, spatial justice, and socioeconomic equity is urgently needed. The spatiotemporal modeling approach developed in this study—linking APIbased dynamic travel data, human settlement matrices, and inequality diagnostics—offers a transferable analytical tool that can be extended beyond EMS to other critical public-service systems such as healthcare delivery, firefighting response, disaster-relief coordination, and urban safety management.Ultimately, by revealing the structural mechanisms behind unequal EMS access, this study provides essential scientific evidence to support the optimization of China’s emergency response networks. It offers actionable insights for policymakers seeking to promote more equitable, resilient, and people-centered urban development in the context of rapid urbanization and increasing mobility demands.
2026(1),72-78
DOI: 10.13791/j.cnki.hsfwest.20241115004
Abstract:
The health of adolescents is a pivotal cornerstone for social development. In the context of rapid urbanization and evolving educational paradigms, the physical and mental health of school-aged children has become a critical concern. However, current primary and secondary school construction and management lack a comprehensive, systematically structured health evaluation framework, leading to significant uncertainties and inefficiencies in practical implementation. Previous healthy school promotion efforts predominantly focused on health management strategies, including disease prevention programs, health education curricula, and medical service provisions. While these initiatives effectively enhanced students' health awareness and prevented common diseases, they overlooked the profound impact of the spatial environment on health promotion. The design of school buildings, classrooms, playgrounds, and other facilities often fails to incorporate health - promoting principles, contributing to prevalent student health issues such as myopia, obesity, musculoskeletal disorders, and mental health problems. This study is designed to fill this significant gap by constructing a comprehensive evaluation index system for healthy primary and secondary schools. The research has two overarching objectives: first, to provide evidence-based, quantifiable, and actionable guidance for school construction projects, enabling architects, planners, and educational administrators to make informed decisions; second, to establish a robust theoretical foundation for the formulation of the Evaluation Standards for Healthy Primary and Secondary Schools, which can serve as a benchmark for future school construction and management.This study aims to fill this gap by constructing a comprehensive evaluation index system for healthy primary and secondary schools. Its dual objectives are to provide evidence-based, quantifiable guidance for school construction projects, enabling informed decision - making for architects, planners, and administrators, and to establish a robust theoretical foundation for formulating the Evaluation Standards for Healthy Primary and Secondary Schools.To accurately determine the relative importance of each factor within the index system, ten experts with extensive experience in the fields of healthy building design, environmental health, and educational facility planning were invited to participate in a series of pairwise comparison exercises. The comparisons were conducted using the 1-9 scale method, a commonly used technique in AHP for quantifying subjective judgments. The collected data were then processed using the geometric mean method to ensure the reliability and validity of the results. Subsequently, the processed data were input into the yaahp 10.0 software to construct 46 judgment matrices. Through rigorous weight calculations and consistency testing procedures, the weight coefficients of each index were accurately determined, ensuring the scientific rigor of the index system.The research results unveil a clear hierarchical structure of importance among the indicators. At the criterion layer, the healthy environment emerges as the most critical factor, underscoring the paramount importance of creating a safe, clean, and healthy physical environment for students. This is closely followed by nutrition and diet, highlighting the significance of providing healthy food options in school canteens. Sports, environmental comfort, and humanistic care, while relatively less dominant, still form an integral part of the index system, contributing to the overall health and wellbeing of students. At the domain layer, the air environment is identified as the sole core domain,emphasizing the crucial role of air quality in school health. The water environment and food safety are classified as important domains, further highlighting the need to ensure the safety and quality of water and food provided in schools. In the indicator layer, air quality, food quality, and water quality constitute the core indicator group, which should be given top priority in school construction and management.In conclusion, the design and construction of healthy primary and secondary schools should adhere to the principle of “core indicator priority-full cycle management-multi-path collaboration”. This principle entails prioritizing the control of basic health elements, such as air, water, and food safety, through strategic site selection, the use of low-volatile organic compound (VOC) building materials, and optimized functional zoning. Full-cycle management, encompassing the entire process from initial planning and design to construction and long-term operation, is essential for maximizing health benefits at every stage. Multi-path collaboration, involving the integration of sports facilities into common areas, the creation of multifunctional learning spaces, and the promotion of social interaction, can significantly enhance space utilization efficiency and the intensity of health interventions. The evaluation index system developed in this study provides a solid scientific and quantitative basis for theoretical research, standard setting, and practical applications in the construction of healthy primary and secondary schools. It is expected to make significant contributions to improving the health and well-being of teachers and students, as well as promoting the standardized and sustainable development of healthy campus construction.
The health of adolescents is a pivotal cornerstone for social development. In the context of rapid urbanization and evolving educational paradigms, the physical and mental health of school-aged children has become a critical concern. However, current primary and secondary school construction and management lack a comprehensive, systematically structured health evaluation framework, leading to significant uncertainties and inefficiencies in practical implementation. Previous healthy school promotion efforts predominantly focused on health management strategies, including disease prevention programs, health education curricula, and medical service provisions. While these initiatives effectively enhanced students' health awareness and prevented common diseases, they overlooked the profound impact of the spatial environment on health promotion. The design of school buildings, classrooms, playgrounds, and other facilities often fails to incorporate health - promoting principles, contributing to prevalent student health issues such as myopia, obesity, musculoskeletal disorders, and mental health problems. This study is designed to fill this significant gap by constructing a comprehensive evaluation index system for healthy primary and secondary schools. The research has two overarching objectives: first, to provide evidence-based, quantifiable, and actionable guidance for school construction projects, enabling architects, planners, and educational administrators to make informed decisions; second, to establish a robust theoretical foundation for the formulation of the Evaluation Standards for Healthy Primary and Secondary Schools, which can serve as a benchmark for future school construction and management.This study aims to fill this gap by constructing a comprehensive evaluation index system for healthy primary and secondary schools. Its dual objectives are to provide evidence-based, quantifiable guidance for school construction projects, enabling informed decision - making for architects, planners, and administrators, and to establish a robust theoretical foundation for formulating the Evaluation Standards for Healthy Primary and Secondary Schools.To accurately determine the relative importance of each factor within the index system, ten experts with extensive experience in the fields of healthy building design, environmental health, and educational facility planning were invited to participate in a series of pairwise comparison exercises. The comparisons were conducted using the 1-9 scale method, a commonly used technique in AHP for quantifying subjective judgments. The collected data were then processed using the geometric mean method to ensure the reliability and validity of the results. Subsequently, the processed data were input into the yaahp 10.0 software to construct 46 judgment matrices. Through rigorous weight calculations and consistency testing procedures, the weight coefficients of each index were accurately determined, ensuring the scientific rigor of the index system.The research results unveil a clear hierarchical structure of importance among the indicators. At the criterion layer, the healthy environment emerges as the most critical factor, underscoring the paramount importance of creating a safe, clean, and healthy physical environment for students. This is closely followed by nutrition and diet, highlighting the significance of providing healthy food options in school canteens. Sports, environmental comfort, and humanistic care, while relatively less dominant, still form an integral part of the index system, contributing to the overall health and wellbeing of students. At the domain layer, the air environment is identified as the sole core domain,emphasizing the crucial role of air quality in school health. The water environment and food safety are classified as important domains, further highlighting the need to ensure the safety and quality of water and food provided in schools. In the indicator layer, air quality, food quality, and water quality constitute the core indicator group, which should be given top priority in school construction and management.In conclusion, the design and construction of healthy primary and secondary schools should adhere to the principle of “core indicator priority-full cycle management-multi-path collaboration”. This principle entails prioritizing the control of basic health elements, such as air, water, and food safety, through strategic site selection, the use of low-volatile organic compound (VOC) building materials, and optimized functional zoning. Full-cycle management, encompassing the entire process from initial planning and design to construction and long-term operation, is essential for maximizing health benefits at every stage. Multi-path collaboration, involving the integration of sports facilities into common areas, the creation of multifunctional learning spaces, and the promotion of social interaction, can significantly enhance space utilization efficiency and the intensity of health interventions. The evaluation index system developed in this study provides a solid scientific and quantitative basis for theoretical research, standard setting, and practical applications in the construction of healthy primary and secondary schools. It is expected to make significant contributions to improving the health and well-being of teachers and students, as well as promoting the standardized and sustainable development of healthy campus construction.
2026(1),79-84
DOI: 10.13791/j.cnki.hsfwest.20240428001
Abstract:
In the process of high-quality urban development, the implementation of digitallyempowered planning is an important innovation, and urban color planning needs to start from the operation requirements of the planning implementation system and strengthen the top-level design of planning and implementation. Urban color affects the style of a city, but digitalization and intelligence will empower the control of urban color will be a new management method. Combined with the characteristics of urban color planning and the problems in implementation in Xiong’an New Area, and from the perspective of digital governance, taking the automatic review of urban color control indicators into the BIM management platform as the starting point, the digital control logic and framework for the implementation of urban color planning are proposed, and a new mechanism for the implementation of urban color planning is formed through five aspects: the preparation of color planning guidelines for graded zoning, the establishment of a rigid index system, the formulation of model information mounting manuals, the construction of urban color planning control systems, and the improvement of implementation mechanisms. It is to realize three-dimensional fine control of urban color. Urban color is an important component of a city’s appearance. Color is one of the most recognizable elements of a city. When people perceive a city, the first thing they feel is the impact of its color. Traditional urban color management lacks the application of digital means for intelligent control. Through the review of academic literature related to urban color digitalization in recent years, it’s concluded that the control method of urban color has shifted from the hierarchical control of color units to digital and information platform control, ultimately achieving intelligent management of urban color and enhancing spatial governance capabilities. In terms of the urban color grading and zoning control approach, Chen Changyong believed that the planning is carried out through a threelevel control system of “city- urban district-color control unit’ to implement the color guidance of the urban spatial structure. In terms of quantitative control methods for urban colors, Yuan Lei proposed a shift from the traditional “qualitative guidance of colors” to “quantitative and demarcated control of colors”, implementing colors in urban spaces. In the exploration of digital control of urban color, Chen Changyong proposed extracting color information from images and videos, establishing a color information database of observation points, analyzing and summarizing the database information, extracting urban color maps, establishing a color planning object system based on the color map objects, and forming a professional compiler’s cognition of urban color through a series of technical means. Urban planning management departments encounter numerous challenges in the implementation of urban color planning. Many cities have yet to form a systematic and hierarchical color planning system, nor have they effectively integrated color planning with legal planning. Especially at the level of regulatory detailed planning, the lack of an effective control mechanism makes it difficult to form operational urban color control planning conditions. Although there are currently many studies on the implementation of urban color planning, most of them focus on planning compilation theories, quantitative analysis and other methods, with less attention paid to thedigital implementation paths and methods. Especially, research on the combination of three-dimensional BIM automated approval in the planning permission stage and urban color planning control is relatively scarce. It is imperative to empower urban color control with digital technology. A “one-map” information management platform for urban color should be established to quantify the results of color planning and store the data parameters in the spatial attribute database based on plots. Combined with the planning management information platform, it should be incorporated into the urban planning approval management. The establishment and operation of the implementation mechanism for urban color planning is a long-term task, and all the involved links and departments behind it need to achieve collaborative governance. Xiong’an New Area combines the three-dimensional BIM control features of the BIM management platform and its full-process and full-cycle approval system, it can achieve three-dimensional BIM urban color review. In accordance with the characteristics of the entire BIM approval process in Xiong’an New Area and in combination with the urban color planning control process, corresponding management systems should be formulated and effectively connected with each stage of control. Xiong’an New Area needs to have a brand-new mindset and action path. By integrating information systems with actual business operations, it should form an overall framework for the implementation and control of the urban color of Xiong’an New Area, promote the quality optimization of the overall urban appearance, and continuously improve the quality of people’s lives. At the same time, it provides more replicable and scalable experiences and practices for urban color planning and implementation control.
In the process of high-quality urban development, the implementation of digitallyempowered planning is an important innovation, and urban color planning needs to start from the operation requirements of the planning implementation system and strengthen the top-level design of planning and implementation. Urban color affects the style of a city, but digitalization and intelligence will empower the control of urban color will be a new management method. Combined with the characteristics of urban color planning and the problems in implementation in Xiong’an New Area, and from the perspective of digital governance, taking the automatic review of urban color control indicators into the BIM management platform as the starting point, the digital control logic and framework for the implementation of urban color planning are proposed, and a new mechanism for the implementation of urban color planning is formed through five aspects: the preparation of color planning guidelines for graded zoning, the establishment of a rigid index system, the formulation of model information mounting manuals, the construction of urban color planning control systems, and the improvement of implementation mechanisms. It is to realize three-dimensional fine control of urban color. Urban color is an important component of a city’s appearance. Color is one of the most recognizable elements of a city. When people perceive a city, the first thing they feel is the impact of its color. Traditional urban color management lacks the application of digital means for intelligent control. Through the review of academic literature related to urban color digitalization in recent years, it’s concluded that the control method of urban color has shifted from the hierarchical control of color units to digital and information platform control, ultimately achieving intelligent management of urban color and enhancing spatial governance capabilities. In terms of the urban color grading and zoning control approach, Chen Changyong believed that the planning is carried out through a threelevel control system of “city- urban district-color control unit’ to implement the color guidance of the urban spatial structure. In terms of quantitative control methods for urban colors, Yuan Lei proposed a shift from the traditional “qualitative guidance of colors” to “quantitative and demarcated control of colors”, implementing colors in urban spaces. In the exploration of digital control of urban color, Chen Changyong proposed extracting color information from images and videos, establishing a color information database of observation points, analyzing and summarizing the database information, extracting urban color maps, establishing a color planning object system based on the color map objects, and forming a professional compiler’s cognition of urban color through a series of technical means. Urban planning management departments encounter numerous challenges in the implementation of urban color planning. Many cities have yet to form a systematic and hierarchical color planning system, nor have they effectively integrated color planning with legal planning. Especially at the level of regulatory detailed planning, the lack of an effective control mechanism makes it difficult to form operational urban color control planning conditions. Although there are currently many studies on the implementation of urban color planning, most of them focus on planning compilation theories, quantitative analysis and other methods, with less attention paid to thedigital implementation paths and methods. Especially, research on the combination of three-dimensional BIM automated approval in the planning permission stage and urban color planning control is relatively scarce. It is imperative to empower urban color control with digital technology. A “one-map” information management platform for urban color should be established to quantify the results of color planning and store the data parameters in the spatial attribute database based on plots. Combined with the planning management information platform, it should be incorporated into the urban planning approval management. The establishment and operation of the implementation mechanism for urban color planning is a long-term task, and all the involved links and departments behind it need to achieve collaborative governance. Xiong’an New Area combines the three-dimensional BIM control features of the BIM management platform and its full-process and full-cycle approval system, it can achieve three-dimensional BIM urban color review. In accordance with the characteristics of the entire BIM approval process in Xiong’an New Area and in combination with the urban color planning control process, corresponding management systems should be formulated and effectively connected with each stage of control. Xiong’an New Area needs to have a brand-new mindset and action path. By integrating information systems with actual business operations, it should form an overall framework for the implementation and control of the urban color of Xiong’an New Area, promote the quality optimization of the overall urban appearance, and continuously improve the quality of people’s lives. At the same time, it provides more replicable and scalable experiences and practices for urban color planning and implementation control.
2026(1),85-91
DOI: 10.13791/j.cnki.hsfwest.20250222002
Abstract:
Against the backdrop of global energy shortages and escalating environmental challenges, enhancing the energy efficiency of public buildings and reducing their carbon emissions have become critical research topics in urban planning and architectural design. Public buildings are major energy consumers, and their operational-phase carbon emissions are influenced by the spatial configuration of surrounding neighborhoods. Taking Hefei’s Government District as a case study, this research explores the nonlinear relationship and interactive effects between neighborhood spatial form factors and public building carbon emissions. The study analyzes 93 public buildings within the district, calculating each building’s annual average carbon emissions based on actual electricity consumption data from 2023. To comprehensively quantify the impact of neighborhood spatial form, the study preliminarily selected ten morphological indicators derived from the “spatial form-microclimate-building energy consumption/carbon emissions” transmission mechanism. These indicators encompass both intrinsic building attributes (e.g., building area, average area-toperimeter ratio) and surrounding environmental factors (e. g., building density, green space ratio). After multicollinearity testing using tolerance and variance inflation factors, building density and total exterior wall area of surrounding buildings were excluded, leaving eight predictive indicators. Five typical regression models—Support Vector Regression（SVR）, Random Forest（RF）, Lightweight Gradient Boosting（LightGBM）, Categorical Boosting（CatBoost）, and Extreme Gradient Boosting（XGBoost）—were compared to determine the optimal model for predicting public building carbon emissions. The dataset underwent normalization and was split into an 80% training set and 20% test set. Model performance was evaluated using root mean square error (RMSE), mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2). To overcome the “black box” nature of complex models and enhance interpretability, the study employed the Shapley additive explanation (SHAP) framework, combining feature importance ranking with partial dependency plots for analysis. Performance evaluation demonstrated that the XGBoost model achieved the highest predictive accuracy on the test set, with an R2 of 0.896 > 0.749 (RF) > 0.680 (CatBoost) > 0.670 (SVR) > 0.659 (LightGBM). SHAP analysis revealed the relative importance of various spatial form indicators. Building area was identified as the most influential feature, with an average absolute SHAP value of 0.05, directly correlating with energy consumption activities and system scale. The next most influential features were the average building height, floor area ratio, and open space ratio. Road network density, average area-perimeter ratio, green space ratio, and sky openness exerted relatively minor impacts, with average absolute SHAP values below 0.01.Crucially, SHAP dependency plots from locally weighted regression smoothing revealed significant nonlinearity and threshold effects for several variables. For instance, the open space ratio positively influenced carbon emissions within the 0.64~0.70 range. The impact of floor area ratio shifts from negative to positive around a threshold of approximately 5.08, with the positive effect increasing as the value rises. The inflection point for average building height occurs around 12.16 m. Road network density exhibits a negative impact when exceeding 0.02 km/km2, potentially due to improved ventilation reducing cooling loads. Green space ratios exceeding 0.15 negatively impact carbon emissions, stabilizing after surpassing 0.3. The relationship between average area-to-perimeter ratio and emissions follows an inverted U-shape: positive effects occur between 6.90 m and 16.67 m, turning negative beyond 16.67 m. Building area exhibits a clear positive correlation with carbon emissions, particularly becoming more pronounced beyond 66 496.75 m2. In contrast, the relationships between building area, floor area ratio, and average building height with carbon emissions are closer to linear. Additionally, SHAP interaction analysis revealed key synergistic effects among variables. Average building height and floor area ratio exhibit a positive interaction, indicating that both at high values exacerbate carbon emissions— likely due to poor ventilation, enhanced heat island effects, and increased vertical transportation energy consumption. Open space ratio also interacts positively with sky openness, though in areas with low open space ratios, increasing sky openness yields minimal or slightly adverse emission reduction effects. A negative interaction exists between road network density and floor area ratio; a positive interaction occurs only when low road network density combines with high floor area ratio, increasing carbon emissions. Additionally, a positive interaction emerges when the average area-to-perimeter ratio is below 15 m and floor area ratio exceeds six, particularly in conjunction with high building floor area. In summary, this study demonstrates the effectiveness of the XGBoost-SHAP framework in predicting public building carbon emissions and deciphering the complex nonlinear effects of block spatial morphology. Key drivers include building area, average building height, floor area ratio, and open space ratio. The findings provide valuable insights and a quantitative basis for formulating targeted carbon reduction strategies for public buildings at the neighborhood scale.
Against the backdrop of global energy shortages and escalating environmental challenges, enhancing the energy efficiency of public buildings and reducing their carbon emissions have become critical research topics in urban planning and architectural design. Public buildings are major energy consumers, and their operational-phase carbon emissions are influenced by the spatial configuration of surrounding neighborhoods. Taking Hefei’s Government District as a case study, this research explores the nonlinear relationship and interactive effects between neighborhood spatial form factors and public building carbon emissions. The study analyzes 93 public buildings within the district, calculating each building’s annual average carbon emissions based on actual electricity consumption data from 2023. To comprehensively quantify the impact of neighborhood spatial form, the study preliminarily selected ten morphological indicators derived from the “spatial form-microclimate-building energy consumption/carbon emissions” transmission mechanism. These indicators encompass both intrinsic building attributes (e.g., building area, average area-toperimeter ratio) and surrounding environmental factors (e. g., building density, green space ratio). After multicollinearity testing using tolerance and variance inflation factors, building density and total exterior wall area of surrounding buildings were excluded, leaving eight predictive indicators. Five typical regression models—Support Vector Regression（SVR）, Random Forest（RF）, Lightweight Gradient Boosting（LightGBM）, Categorical Boosting（CatBoost）, and Extreme Gradient Boosting（XGBoost）—were compared to determine the optimal model for predicting public building carbon emissions. The dataset underwent normalization and was split into an 80% training set and 20% test set. Model performance was evaluated using root mean square error (RMSE), mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2). To overcome the “black box” nature of complex models and enhance interpretability, the study employed the Shapley additive explanation (SHAP) framework, combining feature importance ranking with partial dependency plots for analysis. Performance evaluation demonstrated that the XGBoost model achieved the highest predictive accuracy on the test set, with an R2 of 0.896 > 0.749 (RF) > 0.680 (CatBoost) > 0.670 (SVR) > 0.659 (LightGBM). SHAP analysis revealed the relative importance of various spatial form indicators. Building area was identified as the most influential feature, with an average absolute SHAP value of 0.05, directly correlating with energy consumption activities and system scale. The next most influential features were the average building height, floor area ratio, and open space ratio. Road network density, average area-perimeter ratio, green space ratio, and sky openness exerted relatively minor impacts, with average absolute SHAP values below 0.01.Crucially, SHAP dependency plots from locally weighted regression smoothing revealed significant nonlinearity and threshold effects for several variables. For instance, the open space ratio positively influenced carbon emissions within the 0.64~0.70 range. The impact of floor area ratio shifts from negative to positive around a threshold of approximately 5.08, with the positive effect increasing as the value rises. The inflection point for average building height occurs around 12.16 m. Road network density exhibits a negative impact when exceeding 0.02 km/km2, potentially due to improved ventilation reducing cooling loads. Green space ratios exceeding 0.15 negatively impact carbon emissions, stabilizing after surpassing 0.3. The relationship between average area-to-perimeter ratio and emissions follows an inverted U-shape: positive effects occur between 6.90 m and 16.67 m, turning negative beyond 16.67 m. Building area exhibits a clear positive correlation with carbon emissions, particularly becoming more pronounced beyond 66 496.75 m2. In contrast, the relationships between building area, floor area ratio, and average building height with carbon emissions are closer to linear. Additionally, SHAP interaction analysis revealed key synergistic effects among variables. Average building height and floor area ratio exhibit a positive interaction, indicating that both at high values exacerbate carbon emissions— likely due to poor ventilation, enhanced heat island effects, and increased vertical transportation energy consumption. Open space ratio also interacts positively with sky openness, though in areas with low open space ratios, increasing sky openness yields minimal or slightly adverse emission reduction effects. A negative interaction exists between road network density and floor area ratio; a positive interaction occurs only when low road network density combines with high floor area ratio, increasing carbon emissions. Additionally, a positive interaction emerges when the average area-to-perimeter ratio is below 15 m and floor area ratio exceeds six, particularly in conjunction with high building floor area. In summary, this study demonstrates the effectiveness of the XGBoost-SHAP framework in predicting public building carbon emissions and deciphering the complex nonlinear effects of block spatial morphology. Key drivers include building area, average building height, floor area ratio, and open space ratio. The findings provide valuable insights and a quantitative basis for formulating targeted carbon reduction strategies for public buildings at the neighborhood scale.
2026(1),92-98
DOI: 10.13791/j.cnki.hsfwest.20240815002
Abstract:
With the accelerating pace of global urbanization and the escalating severity of climate warming, urban thermal environment problems have become increasingly prominent, particularly the urban heat island effect and outdoor thermal comfort issues. Thermal comfort, as a crucial indicator for gauging the quality of the urban human settlement environment, has drawn escalating attention. Nevertheless, the current research on the influence of urban morphology on outdoor thermal comfort in the mid-temperate continental arid climate zone is relatively scarce. This study takes Urumqi as the object and explores the impact of urban morphology on outdoor thermal comfort through on-site mobile monitoring and relevant analyses, with the aim of providing a scientific basis for urban planning and the improvement of the human settlement environment in arid areas.The study selected a typical area in Shuimogou District of Urumqi as the research object, where the architectural forms are diverse, with high-rise and low-rise buildings interlaced. The experimental data were acquired through on-site mobile monitoring. The monitoring instruments were fixed on an electric vehicle and moved at a constant speed along the preset route, with fixed monitoring points established for data calibration. The monitoring was carried out in summer (from July 12th to 15th, 2023) and autumn (from October 11th to 13th, 2023), covering the morning, noon, and evening periods. Wet black globe temperature (WBGT) and heat index (HI) were employed as evaluation indicators for thermal comfort, and spatial and correlation analyses were conducted using ArcGIS software. The average WBGT in summer was 21.10℃ , and the average HI was 27.40℃; in autumn, the average WBGT was 13.41℃, and the average HI was 17.25℃. Overall, thermal comfort peaked at noon and was lower in the morning and evening. The seasonal variation of thermal comfort in autumn was greater than that in summer, mainly due to the shorter duration of sunlight and the faster rate of temperature decline in autumn. This indicates that the reduction in solar radiation has a more significant impact on thermal comfort in autumn. In summer, the low-value areas of thermal comfort were mainly concentrated in areas with high-rise buildings and superior greenery, while the high-value areas were distributed in areas with low-rise, dense buildings and low green coverage. In autumn, the low-value areas of thermal comfort were consistent with those in summer, but the highvalue areas were more complex, mainly influenced by the combined effects of building height, density, and green coverage. This implies that the influence of urban morphology on thermal comfort varies by season, and the roles of building height and green coverage differ under different seasonal climatic conditions. Air temperature (Ta), wind speed were significantly positively correlated with thermal comfort, while relative humidity (RH) was significantly negatively correlated. Among them, Ta had the most significant impact on thermal comfort. This suggests that in arid climate zones, air temperature is the key meteorological factor influencing thermal comfort, while the influence of humidity is relatively minor. In summer, the average building height (BH_mean), green coverage ratio (GCR), and sky view factor (SVF) were negatively correlated with thermal comfort, while the floor area ratio (FAR) and building density (BCR) were positively correlated; in autumn, BH_mean, BCR, and GCR were negatively correlated with WBGT, while FAR and SVF were positively correlated with WBGT. As the buffer radius increased, the correlation between urban morphology and thermal comfort gradually intensified. Thisindicates that the influence of urban morphology on thermal comfort varies by season, and the roles of building height and green coverage differ under different seasonal climatic conditions. This study demonstrates that the thermal comfort of Urumqi is significantly affected by meteorological factors and urban morphology. Air temperature is the key meteorological factor influencing thermal comfort, and the influence of urban morphology on thermal comfort varies by season. Areas with high-rise buildings and high green coverage have better thermal comfort in summer, but may have lower thermal comfort in autumn due to the "shadow effect". The study recommends that in urban planning, the height and density of buildings should be rationally controlled, green coverage should be increased, and the urban spatial layout should be optimized to enhance outdoor thermal comfort. Future research will further extend the monitoring period, covering more seasons and regions, to assess the impact of urban morphology on thermal comfort more comprehensively.
With the accelerating pace of global urbanization and the escalating severity of climate warming, urban thermal environment problems have become increasingly prominent, particularly the urban heat island effect and outdoor thermal comfort issues. Thermal comfort, as a crucial indicator for gauging the quality of the urban human settlement environment, has drawn escalating attention. Nevertheless, the current research on the influence of urban morphology on outdoor thermal comfort in the mid-temperate continental arid climate zone is relatively scarce. This study takes Urumqi as the object and explores the impact of urban morphology on outdoor thermal comfort through on-site mobile monitoring and relevant analyses, with the aim of providing a scientific basis for urban planning and the improvement of the human settlement environment in arid areas.The study selected a typical area in Shuimogou District of Urumqi as the research object, where the architectural forms are diverse, with high-rise and low-rise buildings interlaced. The experimental data were acquired through on-site mobile monitoring. The monitoring instruments were fixed on an electric vehicle and moved at a constant speed along the preset route, with fixed monitoring points established for data calibration. The monitoring was carried out in summer (from July 12th to 15th, 2023) and autumn (from October 11th to 13th, 2023), covering the morning, noon, and evening periods. Wet black globe temperature (WBGT) and heat index (HI) were employed as evaluation indicators for thermal comfort, and spatial and correlation analyses were conducted using ArcGIS software. The average WBGT in summer was 21.10℃ , and the average HI was 27.40℃; in autumn, the average WBGT was 13.41℃, and the average HI was 17.25℃. Overall, thermal comfort peaked at noon and was lower in the morning and evening. The seasonal variation of thermal comfort in autumn was greater than that in summer, mainly due to the shorter duration of sunlight and the faster rate of temperature decline in autumn. This indicates that the reduction in solar radiation has a more significant impact on thermal comfort in autumn. In summer, the low-value areas of thermal comfort were mainly concentrated in areas with high-rise buildings and superior greenery, while the high-value areas were distributed in areas with low-rise, dense buildings and low green coverage. In autumn, the low-value areas of thermal comfort were consistent with those in summer, but the highvalue areas were more complex, mainly influenced by the combined effects of building height, density, and green coverage. This implies that the influence of urban morphology on thermal comfort varies by season, and the roles of building height and green coverage differ under different seasonal climatic conditions. Air temperature (Ta), wind speed were significantly positively correlated with thermal comfort, while relative humidity (RH) was significantly negatively correlated. Among them, Ta had the most significant impact on thermal comfort. This suggests that in arid climate zones, air temperature is the key meteorological factor influencing thermal comfort, while the influence of humidity is relatively minor. In summer, the average building height (BH_mean), green coverage ratio (GCR), and sky view factor (SVF) were negatively correlated with thermal comfort, while the floor area ratio (FAR) and building density (BCR) were positively correlated; in autumn, BH_mean, BCR, and GCR were negatively correlated with WBGT, while FAR and SVF were positively correlated with WBGT. As the buffer radius increased, the correlation between urban morphology and thermal comfort gradually intensified. Thisindicates that the influence of urban morphology on thermal comfort varies by season, and the roles of building height and green coverage differ under different seasonal climatic conditions. This study demonstrates that the thermal comfort of Urumqi is significantly affected by meteorological factors and urban morphology. Air temperature is the key meteorological factor influencing thermal comfort, and the influence of urban morphology on thermal comfort varies by season. Areas with high-rise buildings and high green coverage have better thermal comfort in summer, but may have lower thermal comfort in autumn due to the "shadow effect". The study recommends that in urban planning, the height and density of buildings should be rationally controlled, green coverage should be increased, and the urban spatial layout should be optimized to enhance outdoor thermal comfort. Future research will further extend the monitoring period, covering more seasons and regions, to assess the impact of urban morphology on thermal comfort more comprehensively.
2026(1),99-108
DOI: 10.13791/j.cnki.hsfwest.20240518002
Abstract:
Urban transportation systems have a substantial potential for carbon emission reduction, particularly through promoting low-carbon travel modes such as nonmotorized travel (e.g., walking and cycling) and public transportation. Compared to car travel, these modes do not only reduce carbon emissions but also contribute positively to overall urban air quality and resident health. Based on this context, this paper develops a novel stratified assessment framework for urban low-carbon travel potential, introducing two distinct levels of assessment. The first level, termed “Tier 1 low-carbon travel potential,” represents the proportion of current motorized travelers who could realistically shift to non-motorized travel modes. The second level, “Tier 2 low-carbon travel potential,” indicates the proportion of car travelers who might switch to public transportation, thus providing a multi-layered approach for gauging cities’ carbon reduction opportunities within their transportation systems. This study hypothesizes that distance is the primary limiting factor affecting residents’ willingness to engage in nonmotorized travel over motorized travel, while factors such as connection convenience, detour requirements, and transfer intensity hinder public transportation use in favor of car travel. Therefore, this study defines quantitative parameters, including maximum acceptable distance for non-motorized travel and maximum acceptable strengths for public transportation connection, detour, and transfer. By comparing actual resident travel distances and intensities under these parameters in hypothetical scenarios, the study identifies and quantifies the populations in Shanghai and Wuhan that could potentially shift to each low-carbon travel tier. Further analysis examines trends in these potential shifts in relation to changes in residents’ acceptable thresholds for non-motorized distance and public transportation intensities. The relationship curves reveal an inverse “S” -shaped trend, with identified “rapid change zones” and “critical points” where lowcarbon travel potential undergoes significant shifts. Using Shanghai and Wuhan as case studies, the paper calculates the low-carbon travel potential for both cities, providing a graded and nuanced assessment that highlights specific characteristics of low-carbon travel potential and compares the differences between these two major Chinese cities. In terms of methodology, the research draws on 19 732 daily travel Origin-Destination (OD) survey samples from residents of Shanghai and Wuhan. These cities were chosen for their distinct geographical and infrastructural features: Shanghai, with its dense urban population and extensive public transportation network, serves as a prime example of ahighly developed transportation system. In contrast, Wuhan, known for its unique geography with intersecting rivers and numerous lakes, presents a case where natural barriers pose unique challenges for urban transportation development.To calculate potential low-carbon travel mode shifts, the study defines several key metrics based on OD data, such as the Non-motorized Travel Strength (Sn) for walking or cycling trips and various Public Transportation Strength, including Connection Strength (Sc), Detour Strength (Sd), and Transfer Strength (St). NTS is defined as the total distance traveled between origin and destination points via non-motorized means, while Public Transportation Strength metrics are calculated based on distances related to walking connections, route detours, and transfers encountered within public transportation networks. These metrics help quantify the feasibility of residents switching to low-carbon travel based on various cityspecific scenarios.The assessment approach introduces two classification levels for potential low-carbon travelers. In Tier 1, individuals are classified based on their maximum acceptable distance for non-motorized travel, allowing a distinction between residents who currently use motorized transport but could feasibly shift to walking or cycling. Tier 2 further differentiates travelers by considering public transportation as a lower-carbon alternative to car travel, using maximum acceptable strengths for Sc, Sd, and St. The stratified classification includes both “Active” and “Passive” low-carbon travelers within each tier, representing individuals who are either already engaging in low-carbon travel or could be encouraged to shift under the right conditions. The results of this analysis indicate that both cities exhibit significant low-carbon travel potential, although Shanghai’s potential generally surpasses that of Wuhan. Specifically, Shanghai shows a higher Tier 1 potential due to its developed non-motorized travel infrastructure, while its Tier 2 potential also outpaces Wuhan’s due to a higher proportion of car users. The comparative curve analysis shows that Shanghai’s and Wuhan’s Tier 1 potential curves nearly converge at higher thresholds, indicating similar travel behavior once non-motorized distances reach approximately 10 km. However, for Tier 2 potential, significant differences emerge based on connection and detour factors, with Shanghai residents displaying a higher tolerance for transfers and detours.The findings underscore specific areas for urban policy intervention. For Tier 1, enhancing the walking and cycling infrastructure within rapid change zones can potentially increase the proportion of residents who shift from motorized travel to non-motorized modes, thus maximizing carbon reduction potential. For Tier 2, optimizing public transportation accessibility—particularly by reducing transfer and detour requirements—can increase the attractiveness of public transportation as a viable alternative to car travel, with both Shanghai and Wuhan benefiting significantly.The study concludes that urban low-carbon travel potential follows an inverse “S” -shaped pattern, with key thresholds where strategic interventions may lead to substantial reductions in urban carbon emissions. The graded assessment approach provides urban planners with a practical framework to identify rapid change zones and prioritize specific infrastructural improvements to support low-carbon travel adoption. This research has significant implications for cities seeking to reduce carbon emissions through more efficient and sustainable urban transportation policies.
Urban transportation systems have a substantial potential for carbon emission reduction, particularly through promoting low-carbon travel modes such as nonmotorized travel (e.g., walking and cycling) and public transportation. Compared to car travel, these modes do not only reduce carbon emissions but also contribute positively to overall urban air quality and resident health. Based on this context, this paper develops a novel stratified assessment framework for urban low-carbon travel potential, introducing two distinct levels of assessment. The first level, termed “Tier 1 low-carbon travel potential,” represents the proportion of current motorized travelers who could realistically shift to non-motorized travel modes. The second level, “Tier 2 low-carbon travel potential,” indicates the proportion of car travelers who might switch to public transportation, thus providing a multi-layered approach for gauging cities’ carbon reduction opportunities within their transportation systems. This study hypothesizes that distance is the primary limiting factor affecting residents’ willingness to engage in nonmotorized travel over motorized travel, while factors such as connection convenience, detour requirements, and transfer intensity hinder public transportation use in favor of car travel. Therefore, this study defines quantitative parameters, including maximum acceptable distance for non-motorized travel and maximum acceptable strengths for public transportation connection, detour, and transfer. By comparing actual resident travel distances and intensities under these parameters in hypothetical scenarios, the study identifies and quantifies the populations in Shanghai and Wuhan that could potentially shift to each low-carbon travel tier. Further analysis examines trends in these potential shifts in relation to changes in residents’ acceptable thresholds for non-motorized distance and public transportation intensities. The relationship curves reveal an inverse “S” -shaped trend, with identified “rapid change zones” and “critical points” where lowcarbon travel potential undergoes significant shifts. Using Shanghai and Wuhan as case studies, the paper calculates the low-carbon travel potential for both cities, providing a graded and nuanced assessment that highlights specific characteristics of low-carbon travel potential and compares the differences between these two major Chinese cities. In terms of methodology, the research draws on 19 732 daily travel Origin-Destination (OD) survey samples from residents of Shanghai and Wuhan. These cities were chosen for their distinct geographical and infrastructural features: Shanghai, with its dense urban population and extensive public transportation network, serves as a prime example of ahighly developed transportation system. In contrast, Wuhan, known for its unique geography with intersecting rivers and numerous lakes, presents a case where natural barriers pose unique challenges for urban transportation development.To calculate potential low-carbon travel mode shifts, the study defines several key metrics based on OD data, such as the Non-motorized Travel Strength (Sn) for walking or cycling trips and various Public Transportation Strength, including Connection Strength (Sc), Detour Strength (Sd), and Transfer Strength (St). NTS is defined as the total distance traveled between origin and destination points via non-motorized means, while Public Transportation Strength metrics are calculated based on distances related to walking connections, route detours, and transfers encountered within public transportation networks. These metrics help quantify the feasibility of residents switching to low-carbon travel based on various cityspecific scenarios.The assessment approach introduces two classification levels for potential low-carbon travelers. In Tier 1, individuals are classified based on their maximum acceptable distance for non-motorized travel, allowing a distinction between residents who currently use motorized transport but could feasibly shift to walking or cycling. Tier 2 further differentiates travelers by considering public transportation as a lower-carbon alternative to car travel, using maximum acceptable strengths for Sc, Sd, and St. The stratified classification includes both “Active” and “Passive” low-carbon travelers within each tier, representing individuals who are either already engaging in low-carbon travel or could be encouraged to shift under the right conditions. The results of this analysis indicate that both cities exhibit significant low-carbon travel potential, although Shanghai’s potential generally surpasses that of Wuhan. Specifically, Shanghai shows a higher Tier 1 potential due to its developed non-motorized travel infrastructure, while its Tier 2 potential also outpaces Wuhan’s due to a higher proportion of car users. The comparative curve analysis shows that Shanghai’s and Wuhan’s Tier 1 potential curves nearly converge at higher thresholds, indicating similar travel behavior once non-motorized distances reach approximately 10 km. However, for Tier 2 potential, significant differences emerge based on connection and detour factors, with Shanghai residents displaying a higher tolerance for transfers and detours.The findings underscore specific areas for urban policy intervention. For Tier 1, enhancing the walking and cycling infrastructure within rapid change zones can potentially increase the proportion of residents who shift from motorized travel to non-motorized modes, thus maximizing carbon reduction potential. For Tier 2, optimizing public transportation accessibility—particularly by reducing transfer and detour requirements—can increase the attractiveness of public transportation as a viable alternative to car travel, with both Shanghai and Wuhan benefiting significantly.The study concludes that urban low-carbon travel potential follows an inverse “S” -shaped pattern, with key thresholds where strategic interventions may lead to substantial reductions in urban carbon emissions. The graded assessment approach provides urban planners with a practical framework to identify rapid change zones and prioritize specific infrastructural improvements to support low-carbon travel adoption. This research has significant implications for cities seeking to reduce carbon emissions through more efficient and sustainable urban transportation policies.
2026(1),109-116
DOI: 10.13791/j.cnki.hsfwest.20250403001
Abstract:
Autonomous vehicles (AVs) and urban air mobility (UAM) are widely regarded as major increments to future urban transportation, and their concurrent development is accelerating a transition from predominantly two-dimensional, surface-based mobility toward a three-dimensional, composite transport system. Yet the academic landscape remains fragmented: UAM studies have largely emphasized vertiport siting, capacity, airspace safety, cost, regulation, weather, and noise, while offering limited engagement with urban morphology and public-space design; conversely, AV and shared autonomous vehicle (SAV) research has generated substantial planning and design implications on parking, curb management, street reallocation, accessibility, and hub restructuring, but seldom integrates UAM nodes, low-altitude corridors, or operational constraints. As a result, key gaps persist in infrastructure interfaces, coordinated location planning, spatiotemporal energy and emissions profiles, embedding mechanisms within existing urban structures, and the broader question of how ground-air integration may jointly reshape the underlying logic of urban space and publicness. To respond to these gaps, this paper proposes a “systems integration” analytical framework that treats ground mobility, aerial mobility, and their coordination as an interdependent urban spatial system rather than parallel technological trajectories. Methodologically, the study conducts a systematic review and inductive synthesis of high-quality literature published between 2020 and 2025, supplemented by exploratory practice cases, planning research, and policy/industry reports to compensate for the temporal lag and scale limitations of academic publications. The authors retrieved literatures through keywords including “urban air mobility”, “ground transportation integration”, and “ground– air cooperation.” After multi-stage screening and eligibility assessment, 18 highly relevant and highly cited (≥10 citations) studies were selected for close analysis. The discussion is organized progressively across three layers—ground, air, and ground-air collaboration—to clarify how spatial mechanisms operate at each layer and how they couple into a three-dimensional distributed system.At the ground layer, AV-enabled sensing, cooperative decision-making, and precise control are shown to shift traffic management from coarse, forecast-based allocation toward high-frequency, fine-grained, real-time scheduling. In this context, curb space, lanes, parking, and logistics facilities become dynamically managed and convertible resources. Simulation evidence indicates that widespread SAV adoption can reduce long-term parking demand by roughly 80%-95%, implying significant landrelease potential and a need to replace static minimum parking requirements with operational rights, time-based allocation, and conversion mechanisms. Streets are reframed as “programmable public interfaces” whose functions can switch by time of day and scenario—prioritizing throughput and pickup/ drop-off in peaks while enabling markets, outdoor seating, or slow-mobility dominance in off-peak periods. This dynamic ground system is identified as a prerequisite for UAM to meaningfully connect with everyday urban life through standardized, interoperable interfaces. At the aerial layer, UAM
Autonomous vehicles (AVs) and urban air mobility (UAM) are widely regarded as major increments to future urban transportation, and their concurrent development is accelerating a transition from predominantly two-dimensional, surface-based mobility toward a three-dimensional, composite transport system. Yet the academic landscape remains fragmented: UAM studies have largely emphasized vertiport siting, capacity, airspace safety, cost, regulation, weather, and noise, while offering limited engagement with urban morphology and public-space design; conversely, AV and shared autonomous vehicle (SAV) research has generated substantial planning and design implications on parking, curb management, street reallocation, accessibility, and hub restructuring, but seldom integrates UAM nodes, low-altitude corridors, or operational constraints. As a result, key gaps persist in infrastructure interfaces, coordinated location planning, spatiotemporal energy and emissions profiles, embedding mechanisms within existing urban structures, and the broader question of how ground-air integration may jointly reshape the underlying logic of urban space and publicness. To respond to these gaps, this paper proposes a “systems integration” analytical framework that treats ground mobility, aerial mobility, and their coordination as an interdependent urban spatial system rather than parallel technological trajectories. Methodologically, the study conducts a systematic review and inductive synthesis of high-quality literature published between 2020 and 2025, supplemented by exploratory practice cases, planning research, and policy/industry reports to compensate for the temporal lag and scale limitations of academic publications. The authors retrieved literatures through keywords including “urban air mobility”, “ground transportation integration”, and “ground– air cooperation.” After multi-stage screening and eligibility assessment, 18 highly relevant and highly cited (≥10 citations) studies were selected for close analysis. The discussion is organized progressively across three layers—ground, air, and ground-air collaboration—to clarify how spatial mechanisms operate at each layer and how they couple into a three-dimensional distributed system.At the ground layer, AV-enabled sensing, cooperative decision-making, and precise control are shown to shift traffic management from coarse, forecast-based allocation toward high-frequency, fine-grained, real-time scheduling. In this context, curb space, lanes, parking, and logistics facilities become dynamically managed and convertible resources. Simulation evidence indicates that widespread SAV adoption can reduce long-term parking demand by roughly 80%-95%, implying significant landrelease potential and a need to replace static minimum parking requirements with operational rights, time-based allocation, and conversion mechanisms. Streets are reframed as “programmable public interfaces” whose functions can switch by time of day and scenario—prioritizing throughput and pickup/ drop-off in peaks while enabling markets, outdoor seating, or slow-mobility dominance in off-peak periods. This dynamic ground system is identified as a prerequisite for UAM to meaningfully connect with everyday urban life through standardized, interoperable interfaces. At the aerial layer, UAM
2026(1),117-124
DOI: 10.13791/j.cnki.hsfwest.20240910001
Abstract:
Against the background of increasingly frequent and unpredictable disaster risks faced by contemporary metropolises, resilience planning has emerged as a critical strategy for safeguarding urban security and sustainable development. As essential infrastructure constituting the “safety bottom line” of a city, urban emergency shelter spaces—specifically their spatial organization modes and network synergy efficacy—directly determine a city’s capacity for absorption, buffering, adaptation, and recovery under high-intensity perturbation scenarios. In this context, taking the main urban area of Zhengzhou City as the empirical research region, this study conducts a systematic investigation revolving around the structural characteristics, resilience measurement, and optimization strategies of the urban emergency shelter space network. The research aims to achieve three primary objectives: first, to identify the spatial organizational units and structural attributes of the emergency shelter space network; second, to construct a dual-scenario resilience measurement system encompassing both static and dynamic dimensions and conduct empirical assessments; and third, to propose resilience enhancement strategies based on a network perspective, thereby realizing the operationalization of planning interventions. Methodologically, the study adopts a complex network perspective to construct a weighted directed network composed of emergency shelter points. It designates three categories of shelter spaces defined by the planning system as network nodes, and establishes effective collaborative associations based on the maximum spatial-temporal linkage radius as network edges. Furthermore, a gravity model integrating shelter capacity and nodal distance is employed to construct edge weights, accurately reflecting the intensity of synergy between nodes. The study utilizes the Gephi modularity method to identify network clustering units (hereinafter referred to as “network clusters”). Structural characteristics are characterized at both the node and cluster levels using quantitative indicators such as weighted centrality and weighted clustering coefficients. Regarding resilience measurement, the study distinguishes between “static resilience” and “dynamic resilience”. The former primarily reflects the initial resilience level under existing facility scale and layout conditions, while the latter evaluates the system’s response and retention capabilities amidst node destruction based on the evolutionary trajectory of network efficiency under perturbation scenarios. Perturbation simulations are conducted using MATLAB to construct two distinct attack scenarios: “deliberate attacks”, which prioritize node removal based on centrality or clustering importance (simulating terrorist attacks or targeted destruction), and “random attacks”, which disregard node importance (simulating natural disasters or sudden failures). The dynamic resilience is characterized by the trend of network efficiency variation and the area under the curve following node failures. The empirical results identify three typical network cluster structural types “centralized structure”, “distributed structure”, and “simple structure”, which exhibit significant heterogeneity in spatial distribution, nodal composition, network tightness, and resilience performance. Specifically,centralized structure clusters are predominantly located in older urban districts, characterized by high node density. They rely on a few high-grade, large-scale shelters serving as hubs connecting numerous small and medium-sized nodes, exhibiting high clustering effects and short average association distances. However, they are highly dependent on key hub nodes and show the most distinct decline in resilience under deliberate attack scenarios. Distributed structure clusters are mainly found in new urban districts, featuring balanced node scales and strong synergistic capabilities. They possess comprehensive resilience advantages under deliberate attack scenarios, though their larger overall spatial scale necessitates high-quality linkage channels to guarantee synergy. Simple structure clusters are mostly situated in urban fringe areas, characterized by fewer nodes and incompletely formed structures; their resilience performance is constrained by connectivity and supply capacity, showing significant variability. Based on network modularity analysis, a total of 18 clusters were identified with an overall modularity coefficient Q=0.757, indicating good structural independence of the partition. Simulation results demonstrate that network efficiency declines significantly faster under deliberate attacks compared to random attacks. Furthermore, static resilience is found to be primarily correlated with capacity scale and density, whereas dynamic resilience is more influenced by network structural morphology, with a weak correlation observed between the two.
Against the background of increasingly frequent and unpredictable disaster risks faced by contemporary metropolises, resilience planning has emerged as a critical strategy for safeguarding urban security and sustainable development. As essential infrastructure constituting the “safety bottom line” of a city, urban emergency shelter spaces—specifically their spatial organization modes and network synergy efficacy—directly determine a city’s capacity for absorption, buffering, adaptation, and recovery under high-intensity perturbation scenarios. In this context, taking the main urban area of Zhengzhou City as the empirical research region, this study conducts a systematic investigation revolving around the structural characteristics, resilience measurement, and optimization strategies of the urban emergency shelter space network. The research aims to achieve three primary objectives: first, to identify the spatial organizational units and structural attributes of the emergency shelter space network; second, to construct a dual-scenario resilience measurement system encompassing both static and dynamic dimensions and conduct empirical assessments; and third, to propose resilience enhancement strategies based on a network perspective, thereby realizing the operationalization of planning interventions. Methodologically, the study adopts a complex network perspective to construct a weighted directed network composed of emergency shelter points. It designates three categories of shelter spaces defined by the planning system as network nodes, and establishes effective collaborative associations based on the maximum spatial-temporal linkage radius as network edges. Furthermore, a gravity model integrating shelter capacity and nodal distance is employed to construct edge weights, accurately reflecting the intensity of synergy between nodes. The study utilizes the Gephi modularity method to identify network clustering units (hereinafter referred to as “network clusters”). Structural characteristics are characterized at both the node and cluster levels using quantitative indicators such as weighted centrality and weighted clustering coefficients. Regarding resilience measurement, the study distinguishes between “static resilience” and “dynamic resilience”. The former primarily reflects the initial resilience level under existing facility scale and layout conditions, while the latter evaluates the system’s response and retention capabilities amidst node destruction based on the evolutionary trajectory of network efficiency under perturbation scenarios. Perturbation simulations are conducted using MATLAB to construct two distinct attack scenarios: “deliberate attacks”, which prioritize node removal based on centrality or clustering importance (simulating terrorist attacks or targeted destruction), and “random attacks”, which disregard node importance (simulating natural disasters or sudden failures). The dynamic resilience is characterized by the trend of network efficiency variation and the area under the curve following node failures. The empirical results identify three typical network cluster structural types “centralized structure”, “distributed structure”, and “simple structure”, which exhibit significant heterogeneity in spatial distribution, nodal composition, network tightness, and resilience performance. Specifically,centralized structure clusters are predominantly located in older urban districts, characterized by high node density. They rely on a few high-grade, large-scale shelters serving as hubs connecting numerous small and medium-sized nodes, exhibiting high clustering effects and short average association distances. However, they are highly dependent on key hub nodes and show the most distinct decline in resilience under deliberate attack scenarios. Distributed structure clusters are mainly found in new urban districts, featuring balanced node scales and strong synergistic capabilities. They possess comprehensive resilience advantages under deliberate attack scenarios, though their larger overall spatial scale necessitates high-quality linkage channels to guarantee synergy. Simple structure clusters are mostly situated in urban fringe areas, characterized by fewer nodes and incompletely formed structures; their resilience performance is constrained by connectivity and supply capacity, showing significant variability. Based on network modularity analysis, a total of 18 clusters were identified with an overall modularity coefficient Q=0.757, indicating good structural independence of the partition. Simulation results demonstrate that network efficiency declines significantly faster under deliberate attacks compared to random attacks. Furthermore, static resilience is found to be primarily correlated with capacity scale and density, whereas dynamic resilience is more influenced by network structural morphology, with a weak correlation observed between the two.
2026(1),125-132
DOI: 10.13791/j.cnki.hsfwest.2023111601
Abstract:
This study focuses on the resilient development of cities in the Yangtze River Delta region. Starting from the four core dimensions of economic resilience, social resilience, infrastructure resilience, and ecological resilience, a multi-dimensional and multi-level evaluation index system for urban resilience has been systematically established. The entropy weight-TOPSIS evaluation model, exploratory spatio-temporal data analysis, and obstacle degree model have been employed. The resilience level of cities in the Yangtze River Delta region from 2010 to 2021 was measured to deeply explore the spatio-temporal evolution characteristics and identify the key obstacle factors restricting the improvement of resilience, providing a scientific basis for the coordinated development of urban resilience in the region. It’s found that based on the characteristics of time evolution, the overall resilience level of cities in the Yangtze River Delta region showed a fluctuating upward trend from 2010 to 2021, and the extreme value of urban resilience also showed a continuous growth trend. This indicates that although the overall development level of resilience in each city within the Yangtze River Delta region has always shown a positive development trend. However, there are still obvious multi-polar distribution characteristics in the resilience levels of various cities within the region. From the spatial evolution characteristics, it can be seen that there are significant spatial differences in the resilience levels of cities in the Yangtze River Delta region from 2010 to 2021. Overall, it shows an unbalanced distribution feature of “low in the northwest and high in the southeast”, and has a strong agglomeration feature. Specifically, cities with relatively high resilience levels are mainly concentrated in two core areas: one is the economic belt along the Shanghai-Nanjing Line, starting from Hefei, passing through Nanjing, Changzhou, Wuxi, Suzhou and ending in Shanghai; the other is the urban belt along the Hangzhou Bay, with Hangzhou and Ningbo as the core, radiating to cities such as Shaoxing, Jiaxing and Zhoushan. In contrast, cities with lower resilience levels are mainly distributed in the northern part of Anhui Province (Suzhou, Suqian, Huainan, and Huaibei), but the resilience levels of each city still show varying degrees of upward trends. It is worth noting that during the research period, the spatial structure of the urban resilience level in the Yangtze River Delta region had certain variability characteristics, and this variability characteristic generally showed a trend of “gradually increasing from north to south”. Among them, cities with relatively high urban resilience levels and lengths are mainly located in the southern part of Zhejiang, the southern part of Jiangsu, and the central part of Anhui, while cities with relatively low lengths are mainly distributed in the southern and northern parts of Anhui and the central and northern parts of Jiangsu. In addition, the resilience of cities in the Yangtze River Delta region also shows a distinct “path dependence” feature. Data shows that 41.69% of cities are in the “LL” spatial form, meaning that their ownresilience levels are relatively low, and the resilience levels of surrounding cities are also low. This prominent phenomenon of low-value agglomeration indicates that although there is still considerable room for improvement in the overall resilience level of cities in the Yangtze River Delta region, it is still quite difficult to break the “low-value lock-in” pattern and achieve balanced development throughout the region. Based on the identification of obstacle factors, the ranking of the average obstacle degree of the first-level indicator of urban resilience in the Yangtze River Delta region from 2010 to 2021 is: ecological resilience > infrastructure resilience > economic resilience > social resilience, indicating that ecological resilience and infrastructure resilience are the core obstacles restricting the overall improvement of urban resilience in the Yangtze River Delta region. This is specifically reflected in indicators such as the density of urban drainage pipes (X23) and the comprehensive utilization rate of industrial solid waste (X27). From the perspective of the trend of time changes, the obstacle degrees of the four first-level indicators show differentiated characteristics: only the obstacle degree of ecological resilience shows an overall downward trend, while the obstacle degrees of infrastructure resilience, economic resilience and social resilience all show an upward trend, indicating that the impact of infrastructure resilience, economic resilience and social resilience on the development of urban resilience is becoming increasingly significant. In addition, there are also obvious regional differences in the obstacle factors among various cities within the triangular area. The city-level differences in the inhibitory effects of infrastructure resilience and ecological resilience on enhancing urban resilience levels are relatively obvious, while the city-level differences in the inhibitory effects of social resilience and economic resilience on enhancing urban resilience levels are relatively small.
This study focuses on the resilient development of cities in the Yangtze River Delta region. Starting from the four core dimensions of economic resilience, social resilience, infrastructure resilience, and ecological resilience, a multi-dimensional and multi-level evaluation index system for urban resilience has been systematically established. The entropy weight-TOPSIS evaluation model, exploratory spatio-temporal data analysis, and obstacle degree model have been employed. The resilience level of cities in the Yangtze River Delta region from 2010 to 2021 was measured to deeply explore the spatio-temporal evolution characteristics and identify the key obstacle factors restricting the improvement of resilience, providing a scientific basis for the coordinated development of urban resilience in the region. It’s found that based on the characteristics of time evolution, the overall resilience level of cities in the Yangtze River Delta region showed a fluctuating upward trend from 2010 to 2021, and the extreme value of urban resilience also showed a continuous growth trend. This indicates that although the overall development level of resilience in each city within the Yangtze River Delta region has always shown a positive development trend. However, there are still obvious multi-polar distribution characteristics in the resilience levels of various cities within the region. From the spatial evolution characteristics, it can be seen that there are significant spatial differences in the resilience levels of cities in the Yangtze River Delta region from 2010 to 2021. Overall, it shows an unbalanced distribution feature of “low in the northwest and high in the southeast”, and has a strong agglomeration feature. Specifically, cities with relatively high resilience levels are mainly concentrated in two core areas: one is the economic belt along the Shanghai-Nanjing Line, starting from Hefei, passing through Nanjing, Changzhou, Wuxi, Suzhou and ending in Shanghai; the other is the urban belt along the Hangzhou Bay, with Hangzhou and Ningbo as the core, radiating to cities such as Shaoxing, Jiaxing and Zhoushan. In contrast, cities with lower resilience levels are mainly distributed in the northern part of Anhui Province (Suzhou, Suqian, Huainan, and Huaibei), but the resilience levels of each city still show varying degrees of upward trends. It is worth noting that during the research period, the spatial structure of the urban resilience level in the Yangtze River Delta region had certain variability characteristics, and this variability characteristic generally showed a trend of “gradually increasing from north to south”. Among them, cities with relatively high urban resilience levels and lengths are mainly located in the southern part of Zhejiang, the southern part of Jiangsu, and the central part of Anhui, while cities with relatively low lengths are mainly distributed in the southern and northern parts of Anhui and the central and northern parts of Jiangsu. In addition, the resilience of cities in the Yangtze River Delta region also shows a distinct “path dependence” feature. Data shows that 41.69% of cities are in the “LL” spatial form, meaning that their ownresilience levels are relatively low, and the resilience levels of surrounding cities are also low. This prominent phenomenon of low-value agglomeration indicates that although there is still considerable room for improvement in the overall resilience level of cities in the Yangtze River Delta region, it is still quite difficult to break the “low-value lock-in” pattern and achieve balanced development throughout the region. Based on the identification of obstacle factors, the ranking of the average obstacle degree of the first-level indicator of urban resilience in the Yangtze River Delta region from 2010 to 2021 is: ecological resilience > infrastructure resilience > economic resilience > social resilience, indicating that ecological resilience and infrastructure resilience are the core obstacles restricting the overall improvement of urban resilience in the Yangtze River Delta region. This is specifically reflected in indicators such as the density of urban drainage pipes (X23) and the comprehensive utilization rate of industrial solid waste (X27). From the perspective of the trend of time changes, the obstacle degrees of the four first-level indicators show differentiated characteristics: only the obstacle degree of ecological resilience shows an overall downward trend, while the obstacle degrees of infrastructure resilience, economic resilience and social resilience all show an upward trend, indicating that the impact of infrastructure resilience, economic resilience and social resilience on the development of urban resilience is becoming increasingly significant. In addition, there are also obvious regional differences in the obstacle factors among various cities within the triangular area. The city-level differences in the inhibitory effects of infrastructure resilience and ecological resilience on enhancing urban resilience levels are relatively obvious, while the city-level differences in the inhibitory effects of social resilience and economic resilience on enhancing urban resilience levels are relatively small.
The methods and impacts of early diagnosis and evaluation in large-scale existing housing
renovation
2026(1),133-139
DOI: 10.13791/j.cnki.hsfwest.20240507001
Abstract:
The renovation of large-scale housing areas is a comprehensive process, in which systematic research of diagnostic evaluation to integrating information from multiple perspectives is considered as the key to optimizing decision-making. Although people are increasingly understanding its necessity, the methods that play a role in this process have not been fully studied. This paper focuses on the early diagnostic evaluation process in large-scale housing renovation, aiming to compare the current situation in China from an international perspective, sort out the process, content, and participation methods of diagnostic evaluation, and explore the impact and mechanism of early diagnostic evaluation in the renovation of housing areas.By comparison, it can be seen that compared with Sweden and Japan, the age of large-scale existing housing in China is generally shorter. The current target of large-scale renovation of existing housing in developed countries is mainly the Mass Housing built in the 1960s and 1970s, mainly using prefabricated large slab structures, managed by public or private real estate companies. China’s current renovation of existing housing mainly targets the multi-story residential areas built in the 1980s and 1990s, mainly using brick structure, the majority of residential properties are privately owned. Due to the difficulty caused by structural types and private property rights, it is a challenge for the large-scale housing renovation in China.There are significant differences in structure, property rights, and other aspects compared to large-scale housing renovation in developed countries. However, in the process of early diagnosis and evaluation of housing renovation, there are certain commonalities in terms of participants, participation methods, survey and evaluation content both domestically and internationally. By comparison, it is found that some parts worth learning from.It is not difficult to see from domestic and international research and practical experience that large-scale renovation of existing housing is usually a complex process. In order to achieve sustainable development of buildings and environment, comprehensive knowledge is needed to coordinate various perspectives and goals. Detailed basic investigations and diagnostic evaluations are conducted earlier to ensure the successful of projects. Based on the research and comparison, this paper proposes strategies and prospects from the following aspects. Firstly, the information of the housing is well preserved and can be easily found. Conducting a comprehensive investigation and evaluation of the existing housing area, it is important on the collection and search of original information. Developed countries have relatively complete systems for the preservation and retrieval of basic information on existing residential areas. Most urban construction databases, real estate companies, design units, etc. preserve original data, including design and construction information, photos of residential areas at the time of completion and different periods, resident type, family composition, etc., which can be publicly obtained through websites. Secondly, the existing characteristics should be respected. The biggest feature of renovation projects is the existing characteristics of the buildings and environment, and objective investigation and research of theexisting situation is the key to the success of renovation projects. The investigation and evaluation of existing housing areas require multi-faceted consultation and research to develop long-term sustainable renewal methods and development plans. Most of the cases listed in the article were initiated more than 2 years in advance, and tracking investigations and records were maintained throughout the entire update process to promptly identify and address issues, and adjust plans. Thirdly, the survey and evaluation methods should conducted by phase and hierarchy. The investigation and evaluation of large-scale existing housing areas is a complex process, therefore, phased research and evaluation are necessary. Different research contents may involve different participants, for example, in regional surveys, municipal units such as heating and power supply need to be involved. In the on-site observation and evaluation, architects are the main participants. During the survey process, residents are the main participants. At the same time, it also involves training for construction personnel. Therefore, phased investigation and evaluation can effectively ensure the progress of each step and integrate the complex issues of existing housing areas in reasonable. Fourth, professional diagnosis and multi-party participation. The participation of experts from multiple disciplines in diagnosis and research discussions is an effective guarantee for the success of investigations and evaluations in the early stage of the renovation of large-scale existing housing areas. The characteristic of pre-investigation and evaluation in the renovation process is the uncertainty of the problem, which largely relies on the judgment of professionals. In traditional architectural education in China, there is no involvement in related fields. Therefore, expanding the training scope of the architect profession and improving professional participation are also effective ways.
The renovation of large-scale housing areas is a comprehensive process, in which systematic research of diagnostic evaluation to integrating information from multiple perspectives is considered as the key to optimizing decision-making. Although people are increasingly understanding its necessity, the methods that play a role in this process have not been fully studied. This paper focuses on the early diagnostic evaluation process in large-scale housing renovation, aiming to compare the current situation in China from an international perspective, sort out the process, content, and participation methods of diagnostic evaluation, and explore the impact and mechanism of early diagnostic evaluation in the renovation of housing areas.By comparison, it can be seen that compared with Sweden and Japan, the age of large-scale existing housing in China is generally shorter. The current target of large-scale renovation of existing housing in developed countries is mainly the Mass Housing built in the 1960s and 1970s, mainly using prefabricated large slab structures, managed by public or private real estate companies. China’s current renovation of existing housing mainly targets the multi-story residential areas built in the 1980s and 1990s, mainly using brick structure, the majority of residential properties are privately owned. Due to the difficulty caused by structural types and private property rights, it is a challenge for the large-scale housing renovation in China.There are significant differences in structure, property rights, and other aspects compared to large-scale housing renovation in developed countries. However, in the process of early diagnosis and evaluation of housing renovation, there are certain commonalities in terms of participants, participation methods, survey and evaluation content both domestically and internationally. By comparison, it is found that some parts worth learning from.It is not difficult to see from domestic and international research and practical experience that large-scale renovation of existing housing is usually a complex process. In order to achieve sustainable development of buildings and environment, comprehensive knowledge is needed to coordinate various perspectives and goals. Detailed basic investigations and diagnostic evaluations are conducted earlier to ensure the successful of projects. Based on the research and comparison, this paper proposes strategies and prospects from the following aspects. Firstly, the information of the housing is well preserved and can be easily found. Conducting a comprehensive investigation and evaluation of the existing housing area, it is important on the collection and search of original information. Developed countries have relatively complete systems for the preservation and retrieval of basic information on existing residential areas. Most urban construction databases, real estate companies, design units, etc. preserve original data, including design and construction information, photos of residential areas at the time of completion and different periods, resident type, family composition, etc., which can be publicly obtained through websites. Secondly, the existing characteristics should be respected. The biggest feature of renovation projects is the existing characteristics of the buildings and environment, and objective investigation and research of theexisting situation is the key to the success of renovation projects. The investigation and evaluation of existing housing areas require multi-faceted consultation and research to develop long-term sustainable renewal methods and development plans. Most of the cases listed in the article were initiated more than 2 years in advance, and tracking investigations and records were maintained throughout the entire update process to promptly identify and address issues, and adjust plans. Thirdly, the survey and evaluation methods should conducted by phase and hierarchy. The investigation and evaluation of large-scale existing housing areas is a complex process, therefore, phased research and evaluation are necessary. Different research contents may involve different participants, for example, in regional surveys, municipal units such as heating and power supply need to be involved. In the on-site observation and evaluation, architects are the main participants. During the survey process, residents are the main participants. At the same time, it also involves training for construction personnel. Therefore, phased investigation and evaluation can effectively ensure the progress of each step and integrate the complex issues of existing housing areas in reasonable. Fourth, professional diagnosis and multi-party participation. The participation of experts from multiple disciplines in diagnosis and research discussions is an effective guarantee for the success of investigations and evaluations in the early stage of the renovation of large-scale existing housing areas. The characteristic of pre-investigation and evaluation in the renovation process is the uncertainty of the problem, which largely relies on the judgment of professionals. In traditional architectural education in China, there is no involvement in related fields. Therefore, expanding the training scope of the architect profession and improving professional participation are also effective ways.
Quantitative research of urban public space: Literature review on evaluation model of the
publicness
2026(1),140-148
DOI: 10.13791/j.cnki.hsfwest.20240821001
Abstract:
The term “public space”, as a distinct concept, first emerged in the sociological and political philosophical discourses of the 1950s. It was later introduced into the fields of architecture, urban design, and urban planning by scholars such as Lewis Mumford and Jane Jacobs. This new terminology arose from the inadequacy of existing concepts to address evolving social trends and ideologies. It marked a shift in urban studies from a utilitarian, function-driven perspective to one that prioritizes the humanistic and social value of space. The focus also transitioned from the concrete notion of “space” to the more abstract concept of the “public”, specifically the “publicness” of space. Public spaces are traditionally regarded as being provided and maintained by the public sector. However, in recent years, the growing involvement of the private sector has become increasingly common, resulting in a rising number of public spaces being dominated by private entities. The management of such spaces often tends to be exclusionary, with limited consideration for public interests. Consequently, some scholars have proclaimed the "end of public space" or the "end of public culture". The pervasive trends of privatization and commodification, combined with heightened security concerns, have led to stricter control over public spaces. Despite these challenges, some optimistic perspectives argue that effective management strategies can yield positive outcomes, and private sector participation in the provision and management of public spaces may offer a more suitable approach to organizing contemporary cities. The theoretical reflections on publicness have led to a quantitative turn in public space research, with three main implications. Firstly, it involves a shift from traditional qualitative descriptions to the quantitative measurement of publicness, which develops measurement models to verify arguments about the fall of the publicness. This quantitative approach allows researchers to assess whether urban development and practices have indeed neglected publicness, whether the public sector performs better in ensuring publicness, and whether privatization necessarily leads to its decline. Secondly, quantitative research enables a more explicit and objective comparative analyses of public spaces, which helps to identify specific and nuanced differences between them. Thirdly, through the development of quantitative models and indicators, theoretical discussions of publicness are integrated with the physical characteristics of real urban spaces. This bridges the gap between theory and practice, and makes the theories of publicness practicable in guiding spatial planning and design. Therefore, this paper reviewed existing quantitative models in public space studies and highlight their strengths and weaknesses to inspire future studies. Based on the role that the concept of publicness plays in these measurement models, this paper classifies the quantitative research on public space into three categories. The first category includes models that explore partial dimensions of publicness aimed at probing the prominent changes occurring in and around public spaces, such as increasing control, theming/fantasy, and Disneyfication. These changes fundamentally address core issues central to the concept of publicness. The second category consists of models designed to evaluate the quality of public space and generateuseful suggestions on how to improve it. In these models, characteristics of publicness are often implicitly regarded as components of “good” public space qualities. Consequently, the indicators used to assess the quality of public space share significant similarities with those used in models that directly evaluate publicness. The third category involves complete evaluations of publicness itself. This category is further concluded into three types: comprehensive models, simplified models, and dynamic models. Through a systematic review, the study finds that the indicators used to evaluate the publicness of public spaces are primarily developed around the dimensions of management, inclusiveness, and accessibility, while also aligning with specific local contexts. The grading criteria for these indicators place greater emphasis on the obligations and responsibilities of management as well as the rights of public space users. Finally, with advancements in AI technologies and the prevalence of smartphones and location-based services (LBS), it proposes two research directions for improving the quantitative models of public space. Firstly, future research could leverage multi-source big data, such as social media data and mobile phone signaling data, to better capture the utilization of public spaces. This approach would enable more precise measurements of public space usage, including user diversity, the spatiotemporal distribution of space utilization, and usage intensity. Such methods could enhance the objectivity of diversity measurement in existing models. Secondly, image semantic analysis could be utilized to identify spatial features related to publicness. Data from street view images, active sensing images, wearable devices, and other sources could be analyzed using AI and deep learning techniques. These technologies can automatically identify and classify public space features and elements, fostering more scientifically robust and data-driven research on public spaces.
The term “public space”, as a distinct concept, first emerged in the sociological and political philosophical discourses of the 1950s. It was later introduced into the fields of architecture, urban design, and urban planning by scholars such as Lewis Mumford and Jane Jacobs. This new terminology arose from the inadequacy of existing concepts to address evolving social trends and ideologies. It marked a shift in urban studies from a utilitarian, function-driven perspective to one that prioritizes the humanistic and social value of space. The focus also transitioned from the concrete notion of “space” to the more abstract concept of the “public”, specifically the “publicness” of space. Public spaces are traditionally regarded as being provided and maintained by the public sector. However, in recent years, the growing involvement of the private sector has become increasingly common, resulting in a rising number of public spaces being dominated by private entities. The management of such spaces often tends to be exclusionary, with limited consideration for public interests. Consequently, some scholars have proclaimed the "end of public space" or the "end of public culture". The pervasive trends of privatization and commodification, combined with heightened security concerns, have led to stricter control over public spaces. Despite these challenges, some optimistic perspectives argue that effective management strategies can yield positive outcomes, and private sector participation in the provision and management of public spaces may offer a more suitable approach to organizing contemporary cities. The theoretical reflections on publicness have led to a quantitative turn in public space research, with three main implications. Firstly, it involves a shift from traditional qualitative descriptions to the quantitative measurement of publicness, which develops measurement models to verify arguments about the fall of the publicness. This quantitative approach allows researchers to assess whether urban development and practices have indeed neglected publicness, whether the public sector performs better in ensuring publicness, and whether privatization necessarily leads to its decline. Secondly, quantitative research enables a more explicit and objective comparative analyses of public spaces, which helps to identify specific and nuanced differences between them. Thirdly, through the development of quantitative models and indicators, theoretical discussions of publicness are integrated with the physical characteristics of real urban spaces. This bridges the gap between theory and practice, and makes the theories of publicness practicable in guiding spatial planning and design. Therefore, this paper reviewed existing quantitative models in public space studies and highlight their strengths and weaknesses to inspire future studies. Based on the role that the concept of publicness plays in these measurement models, this paper classifies the quantitative research on public space into three categories. The first category includes models that explore partial dimensions of publicness aimed at probing the prominent changes occurring in and around public spaces, such as increasing control, theming/fantasy, and Disneyfication. These changes fundamentally address core issues central to the concept of publicness. The second category consists of models designed to evaluate the quality of public space and generateuseful suggestions on how to improve it. In these models, characteristics of publicness are often implicitly regarded as components of “good” public space qualities. Consequently, the indicators used to assess the quality of public space share significant similarities with those used in models that directly evaluate publicness. The third category involves complete evaluations of publicness itself. This category is further concluded into three types: comprehensive models, simplified models, and dynamic models. Through a systematic review, the study finds that the indicators used to evaluate the publicness of public spaces are primarily developed around the dimensions of management, inclusiveness, and accessibility, while also aligning with specific local contexts. The grading criteria for these indicators place greater emphasis on the obligations and responsibilities of management as well as the rights of public space users. Finally, with advancements in AI technologies and the prevalence of smartphones and location-based services (LBS), it proposes two research directions for improving the quantitative models of public space. Firstly, future research could leverage multi-source big data, such as social media data and mobile phone signaling data, to better capture the utilization of public spaces. This approach would enable more precise measurements of public space usage, including user diversity, the spatiotemporal distribution of space utilization, and usage intensity. Such methods could enhance the objectivity of diversity measurement in existing models. Secondly, image semantic analysis could be utilized to identify spatial features related to publicness. Data from street view images, active sensing images, wearable devices, and other sources could be analyzed using AI and deep learning techniques. These technologies can automatically identify and classify public space features and elements, fostering more scientifically robust and data-driven research on public spaces.
2026(1),149-155
DOI: 10.13791/j.cnki.hsfwest.20240911008
Abstract:
In response to the practical logic of urban and rural heritage preservation shift from the “material based” defense and control to the “people-oriented” cultural inheritance, during the inventory period, as well as the technical bottleneck of the analysis mode unsystematic and data mode incommensurable of visitor behaviors research in historic districts; the article based on the perspective of people-oriented renewal, and combines the “scene theory” and “bag of words model” to construct the “bag of scene words” method for multi modal analysis of visitor behaviors, in order to reveal the interaction mechanism between space and visitor behavior in historic district. This method constructs a centralized data systems and open research framework with multi data modality as input modality and multi analysis modality as output modality, as well as “bag of words labels” and “word semantics” models based on four-dimensional scene elements such as visitor group category, behavior category, time period, and spatial attributes. Among them, common activities and behaviors in historic districts are divided into six types: aesthetic, cognitive, experiential, leisure, shopping, and check-in; and the spatial system of historic districts is divided into two categories: street and alley spaces, and architectural spaces, as well as six subcategories: streets, alleys, squares, cultural spaces, commercial spaces, and residential spaces. Based on sample research, the article reveals the problems of conformity, haste, superficiality, and weak interactivity of visitors’ behavior in historic districts, as well as the spatiotemporal differentiations of “emphasizing commerce over culture”, “daily leisure, holiday rush” and “daytime strolling, night viewing”, the main manifestation is the polarization of visitor behavior trajectories in the district, concentrated in areas with rich scenic spots and lively environmental atmosphere such as streets, squares, and commercial spaces. Overall, consumer and superficial behaviors are the main ones, easily influenced by consumer culture and online marketing factors, with strong conformity, haste, and weak interactivity; daily behavior is distributed continuously, with a slow rhythm and strong autonomy, and is less affected by spatial factors; the distribution of holiday behaviors is clustered, with a rapid rhythm and significant conformity, and is strongly influenced by factors such as scenic spots popularity and online popularity; daytime behavior is highly cultural and in-depth, influenced by the landscape and historical resources factors in the district; nighttime behavior is characterized by obvious consumerism and superficiality, influenced by the vitality factors in the district such as sound and light environment. In addition, the behavior of visitors of different genders, origins, and ages in the district also shows differentiation in terms of independence, purposefulness, and vitality: the behaviors of male visitors present strong characteristics of cultural and autonomous, weak interactivity, and is influenced by historical resources and spatial quality factors. The behaviors of female visitors present characteristics ofconsumerism, conformity, and strong interactivity, which are influenced by factors such as spatial style and scenic spot popularity. The behaviors of local visitors present characteristics of leisurely, weak purposefulness, and strong interactivity, emphasizing the feeling of spatial atmosphere, and is influenced by factors such as spatial quality, cultural significance, and vitality. The behaviors of non-local visitors present characteristics of haste, strong purposefulness, and weak interactivity; they pay attention to scenic spot check-in and historical cognition, and are influenced by factors such as scenic spot popularity and identification. Young visitors have diverse behavior types and high vitality, influenced by landscape and cultural activities. Middle aged visitors have a single type of behavior, low vitality, and are influenced by humanistic values and environmental quality factors. The behavior types of elderly visitors are significantly different and their vitality is higher, influenced by cultural values and spatial vitality factors. Based on the aforementioned analysis, the article proposes a humanistic renewal strategy for target space intervention, flowing scene composition, and differential scene creation, including multimodal scene creation and renewal methods such as “aesthetic education scene, cultural inheritance scene, deep experience scene, artistic life scene, daily interaction scene, fashionable cultural tourism scene, and traditional festival scene”. The above content aims to enrich and expand the research theory on visitor behavior in historic districts, and promote the connotative and humanistic transformation of preservation and renewal practices in historic districts.
In response to the practical logic of urban and rural heritage preservation shift from the “material based” defense and control to the “people-oriented” cultural inheritance, during the inventory period, as well as the technical bottleneck of the analysis mode unsystematic and data mode incommensurable of visitor behaviors research in historic districts; the article based on the perspective of people-oriented renewal, and combines the “scene theory” and “bag of words model” to construct the “bag of scene words” method for multi modal analysis of visitor behaviors, in order to reveal the interaction mechanism between space and visitor behavior in historic district. This method constructs a centralized data systems and open research framework with multi data modality as input modality and multi analysis modality as output modality, as well as “bag of words labels” and “word semantics” models based on four-dimensional scene elements such as visitor group category, behavior category, time period, and spatial attributes. Among them, common activities and behaviors in historic districts are divided into six types: aesthetic, cognitive, experiential, leisure, shopping, and check-in; and the spatial system of historic districts is divided into two categories: street and alley spaces, and architectural spaces, as well as six subcategories: streets, alleys, squares, cultural spaces, commercial spaces, and residential spaces. Based on sample research, the article reveals the problems of conformity, haste, superficiality, and weak interactivity of visitors’ behavior in historic districts, as well as the spatiotemporal differentiations of “emphasizing commerce over culture”, “daily leisure, holiday rush” and “daytime strolling, night viewing”, the main manifestation is the polarization of visitor behavior trajectories in the district, concentrated in areas with rich scenic spots and lively environmental atmosphere such as streets, squares, and commercial spaces. Overall, consumer and superficial behaviors are the main ones, easily influenced by consumer culture and online marketing factors, with strong conformity, haste, and weak interactivity; daily behavior is distributed continuously, with a slow rhythm and strong autonomy, and is less affected by spatial factors; the distribution of holiday behaviors is clustered, with a rapid rhythm and significant conformity, and is strongly influenced by factors such as scenic spots popularity and online popularity; daytime behavior is highly cultural and in-depth, influenced by the landscape and historical resources factors in the district; nighttime behavior is characterized by obvious consumerism and superficiality, influenced by the vitality factors in the district such as sound and light environment. In addition, the behavior of visitors of different genders, origins, and ages in the district also shows differentiation in terms of independence, purposefulness, and vitality: the behaviors of male visitors present strong characteristics of cultural and autonomous, weak interactivity, and is influenced by historical resources and spatial quality factors. The behaviors of female visitors present characteristics ofconsumerism, conformity, and strong interactivity, which are influenced by factors such as spatial style and scenic spot popularity. The behaviors of local visitors present characteristics of leisurely, weak purposefulness, and strong interactivity, emphasizing the feeling of spatial atmosphere, and is influenced by factors such as spatial quality, cultural significance, and vitality. The behaviors of non-local visitors present characteristics of haste, strong purposefulness, and weak interactivity; they pay attention to scenic spot check-in and historical cognition, and are influenced by factors such as scenic spot popularity and identification. Young visitors have diverse behavior types and high vitality, influenced by landscape and cultural activities. Middle aged visitors have a single type of behavior, low vitality, and are influenced by humanistic values and environmental quality factors. The behavior types of elderly visitors are significantly different and their vitality is higher, influenced by cultural values and spatial vitality factors. Based on the aforementioned analysis, the article proposes a humanistic renewal strategy for target space intervention, flowing scene composition, and differential scene creation, including multimodal scene creation and renewal methods such as “aesthetic education scene, cultural inheritance scene, deep experience scene, artistic life scene, daily interaction scene, fashionable cultural tourism scene, and traditional festival scene”. The above content aims to enrich and expand the research theory on visitor behavior in historic districts, and promote the connotative and humanistic transformation of preservation and renewal practices in historic districts.
2026(1),156-163
DOI: 10.13791/j.cnki.hsfwest.20251128004
Abstract:
Military reclamation industrial heritage constitutes a distinctive and irreplaceable component of China’s industrial heritage system. Formed under specific historical conditions associated with frontier development, national defense, and the institutional framework of the Xinjiang Production and Construction Corps, this type of heritage integrates industrial production, collective organization, social governance, and everyday life. Unlike conventional industrial heritage shaped primarily by technological evolution or industrial typology, military reclamation industrial heritage embodies a highly intertwined structure of historical missions, institutional practices, spatial organization, and collective memory. However, in current conservation and adaptive reuse practices, such heritage is often addressed through generalized industrial heritage evaluation frameworks, resulting in oversimplified value recognition and insufficiently targeted renewal strategies. In particular, existing approaches tend to focus on comprehensive value scores while paying limited attention to how different value dimensions interact and how evaluation results can effectively guide conservation decision-making and design interventions. This study aims to construct an integrated conservation and utilization framework for military reclamation industrial heritage that links value assessment with strategy generation. By responding to the specific historical and cultural characteristics of military reclamation heritage, the research seeks to overcome the limitations of score-oriented evaluation approaches and to establish a more operational and decisionoriented methodology for conservation and adaptive reuse. The study emphasizes that, for heritage types characterized by strong institutional backgrounds and collective memory, evaluation results should not merely serve as a basis for ranking value levels, but should instead function as a mechanism for guiding differentiated conservation interventions and renewal strategies. Based on a comprehensive review of existing literature on industrial heritage conservation and value assessment, this paper establishes a threedimensional evaluation framework consisting of historical value, humanistic value, and intrinsic value. These three dimensions correspond respectively to the historical and institutional background of heritage formation, the social and cultural meanings embedded in collective memory and everyday practices, and the physical condition and spatial characteristics of the built fabric. Rather than treating these dimensions as isolated attributes, the framework emphasizes their interrelated structure, reflecting the holistic nature of military reclamation industrial heritage as a “production – life – organization – memory” system. To operationalize this framework, the study employs the Analytic Hierarchy Process (AHP) to determine indicator weights and applies the Fuzzy Comprehensive Evaluation Method to quantify the performance of heritage sites across the three value dimensions. The methodological procedures are applied to a case study of the Nanshan Cement Plant in Shihezi City, a representative military reclamation industrial heritage site that preserves a relatively complete industrial spatial structure but faces significant constraints related to physical deterioration and reuse feasibility. The evaluation results indicate that,while the site demonstrates strong historical value and moderate humanistic value, its intrinsic value is comparatively constrained due to structural degradation and safety concerns. Beyond determining an overall evaluation level, this study introduces value structure analysis as a key step for interpreting evaluation results and translating them into conservation and renewal decisions. The comprehensive evaluation level is used to define the baseline and priority of conservation intervention, while the value structure—namely, the relative dominance and imbalance among historical, humanistic, and intrinsic values—serves as the primary basis for determining intervention intensity and strategic orientation. As illustrated by the value-structure-oriented technical framework proposed in this study, sites with different value structures require differentiated conservation approaches, even when their comprehensive evaluation levels are similar. The case analysis indicates that the Nanshan Cement Plant should be identified as a military reclamation industrial heritage site characterized by constrained intrinsic value, for which large-scale restoration or high-intensity functional reuse would involve substantial risks and implementation costs. In response to this value structure, the study proposes a conservation strategy oriented toward overall spatial preservation and differentiated intervention. Priority is given to retaining key industrial structures, production-related spatial relationships, and site-scale integrity, while low-intensity and reversible design measures are adopted to support the interpretation of historical narratives and the continuation of collective memory. This strategy emphasizes minimum necessary intervention, addresses essential structural safety requirements, and preserves the legibility of the industrial system at the site level.The research findings further confirm that value structure analysis functions as a critical intermediary mechanism linking value assessment with strategy formulation. By explicitly associating evaluation outcomes with conservation intervention intensity and renewal design orientation, the proposed framework helps to avoid homogenized reuse approaches and reduces the risk of overlooking socially significant but less visually prominent heritage values. Overall, this study contributes to the methodological advancement of industrial heritage conservation by illustrating how multi-dimensional value assessment can be systematically translated into practical and decision-oriented conservation tools. The framework provides a transferable reference for the conservation and adaptive reuse of military reclamation industrial heritage, as well as other industrial heritage types shaped by complex historical, institutional, and social contexts.
Military reclamation industrial heritage constitutes a distinctive and irreplaceable component of China’s industrial heritage system. Formed under specific historical conditions associated with frontier development, national defense, and the institutional framework of the Xinjiang Production and Construction Corps, this type of heritage integrates industrial production, collective organization, social governance, and everyday life. Unlike conventional industrial heritage shaped primarily by technological evolution or industrial typology, military reclamation industrial heritage embodies a highly intertwined structure of historical missions, institutional practices, spatial organization, and collective memory. However, in current conservation and adaptive reuse practices, such heritage is often addressed through generalized industrial heritage evaluation frameworks, resulting in oversimplified value recognition and insufficiently targeted renewal strategies. In particular, existing approaches tend to focus on comprehensive value scores while paying limited attention to how different value dimensions interact and how evaluation results can effectively guide conservation decision-making and design interventions. This study aims to construct an integrated conservation and utilization framework for military reclamation industrial heritage that links value assessment with strategy generation. By responding to the specific historical and cultural characteristics of military reclamation heritage, the research seeks to overcome the limitations of score-oriented evaluation approaches and to establish a more operational and decisionoriented methodology for conservation and adaptive reuse. The study emphasizes that, for heritage types characterized by strong institutional backgrounds and collective memory, evaluation results should not merely serve as a basis for ranking value levels, but should instead function as a mechanism for guiding differentiated conservation interventions and renewal strategies. Based on a comprehensive review of existing literature on industrial heritage conservation and value assessment, this paper establishes a threedimensional evaluation framework consisting of historical value, humanistic value, and intrinsic value. These three dimensions correspond respectively to the historical and institutional background of heritage formation, the social and cultural meanings embedded in collective memory and everyday practices, and the physical condition and spatial characteristics of the built fabric. Rather than treating these dimensions as isolated attributes, the framework emphasizes their interrelated structure, reflecting the holistic nature of military reclamation industrial heritage as a “production – life – organization – memory” system. To operationalize this framework, the study employs the Analytic Hierarchy Process (AHP) to determine indicator weights and applies the Fuzzy Comprehensive Evaluation Method to quantify the performance of heritage sites across the three value dimensions. The methodological procedures are applied to a case study of the Nanshan Cement Plant in Shihezi City, a representative military reclamation industrial heritage site that preserves a relatively complete industrial spatial structure but faces significant constraints related to physical deterioration and reuse feasibility. The evaluation results indicate that,while the site demonstrates strong historical value and moderate humanistic value, its intrinsic value is comparatively constrained due to structural degradation and safety concerns. Beyond determining an overall evaluation level, this study introduces value structure analysis as a key step for interpreting evaluation results and translating them into conservation and renewal decisions. The comprehensive evaluation level is used to define the baseline and priority of conservation intervention, while the value structure—namely, the relative dominance and imbalance among historical, humanistic, and intrinsic values—serves as the primary basis for determining intervention intensity and strategic orientation. As illustrated by the value-structure-oriented technical framework proposed in this study, sites with different value structures require differentiated conservation approaches, even when their comprehensive evaluation levels are similar. The case analysis indicates that the Nanshan Cement Plant should be identified as a military reclamation industrial heritage site characterized by constrained intrinsic value, for which large-scale restoration or high-intensity functional reuse would involve substantial risks and implementation costs. In response to this value structure, the study proposes a conservation strategy oriented toward overall spatial preservation and differentiated intervention. Priority is given to retaining key industrial structures, production-related spatial relationships, and site-scale integrity, while low-intensity and reversible design measures are adopted to support the interpretation of historical narratives and the continuation of collective memory. This strategy emphasizes minimum necessary intervention, addresses essential structural safety requirements, and preserves the legibility of the industrial system at the site level.The research findings further confirm that value structure analysis functions as a critical intermediary mechanism linking value assessment with strategy formulation. By explicitly associating evaluation outcomes with conservation intervention intensity and renewal design orientation, the proposed framework helps to avoid homogenized reuse approaches and reduces the risk of overlooking socially significant but less visually prominent heritage values. Overall, this study contributes to the methodological advancement of industrial heritage conservation by illustrating how multi-dimensional value assessment can be systematically translated into practical and decision-oriented conservation tools. The framework provides a transferable reference for the conservation and adaptive reuse of military reclamation industrial heritage, as well as other industrial heritage types shaped by complex historical, institutional, and social contexts.
2026(1),164-170
DOI: 10.13791/j.cnki.hsfwest.20240402010
Abstract:
China is undergoing a transition from the stage of high-speed growth to the stage of highquality development, and the rapid development of cities has, to a certain extent, led to the problem of the convergence of urban physical and spatial environments and the lack of cultural connotations. Border cities have unique natural landscapes and built environments, where diverse cultures exchange and learn from each other. The quality of their landscape is subject to the internal drive of new urbanization construction centered on human beings and the external constraints of the border image exhibition simultaneously. As the window of national consciousness image dissemination, border cities are the key areas for urban landscape construction. As there is a gap between the current situation of the urban landscape of border cities and the development needs, special attention needs to be paid to the protection and continuation of the urban landscape characteristics of border cities in the process of urban design and planning, focusing on strengthening the expression of the unique culture and urban spiritual connotation of the region in the urban landscape.The public is not only the core of organizing the development of other market elements in border cities, but also the main point of action for cultural cognition and communication, forging the sense of Chinese national community in the border area, and the main body of urban landscape perception. As the state attaches more importance to the human environment, quantitatively evaluating the quality of urban and rural landscapes based on the public perspective and optimizing the design to meet the public needs has become an important development direction of landscape construction.Therefore, this study selects 18 land border cities in Heilongjiang Province for empirical analysis, analyzes the characteristics of border cities, constructs a partial least squares structural equation evaluation model for the perception of border cities, determines the evaluation system for the perception of border cities, and calculates the results of the evaluation of the appearance of border cities in Heilongjiang Province, to put forward targeted strategies for the improvement of the appearance of the application. The method mainly involves identifying the scope of public perceivable characteristic landscape elements quantifying the public perception of the landscape quality of the border cities, and further proposing how to protect and enhance the characteristic landscape elements of the border cities in the optimization strategy.The results of this study are as follows. Firstly, from the results of the indicator weights of the evaluation system of characteristic landscape perception, the weights of the role of various characteristic landscape elements on the overall border city landscape perception decrease in the following order: urban construction style perception, ecological landscape perception, cultural landscape perception, and national border landscape perception. The enhancement of the perception of the characteristic features of border cities is based on a good urban physical and spatial environment, and secondly, due to the differences in geography and the different levels of urban construction, theperception level of different cities and different types of characteristic features varies, and the distribution of the evaluation results of the perception of the characteristic features of the border cities is consistent with the characteristics of the spatial distribution of each type of feature element. Therefore, it is concluded that the landscape of border cities in Heilongjiang Province has the characteristics of prominent single characteristic landscape element points, continuous type characteristic landscape elements, and concentrated and continuous parts of characteristic landscape resources, and optimization suggestions are put forward based on the characteristic analysis.Based on the spatial characteristics of border cities that generally have a prominent characteristic landscape element, the study proposes to determine the positioning of the landscape image of each border city at the global level and to construct viewing points for the border regional center city, the important node city at the border, and the border city with general characteristics. According to the spatial characteristics of the continuous distribution of a certain type of distinctive landscape elements in the border cities, the study proposes to build a distinctive landscape system of the border cities according to type and to construct landscape perception lines, namely, the boundary river ecological landscape support belt, the northern border townscape construction belt, and the multicultural landscape integration belt. Based on the spatial characteristics of the concentration of some of the characteristic landscape resources, the study proposes to organize the regional system development of border cities in the form of clusters and to form a border town system with the border prefectural cities as the core, the border county cities and ports as the nodes, and towns and villages as the support for each other. This study provides objective support for the quantitative analysis and optimization of the quality of the landscape of border cities, to provide references for the exploration of related theories and the practice of the human environment in border cities.
China is undergoing a transition from the stage of high-speed growth to the stage of highquality development, and the rapid development of cities has, to a certain extent, led to the problem of the convergence of urban physical and spatial environments and the lack of cultural connotations. Border cities have unique natural landscapes and built environments, where diverse cultures exchange and learn from each other. The quality of their landscape is subject to the internal drive of new urbanization construction centered on human beings and the external constraints of the border image exhibition simultaneously. As the window of national consciousness image dissemination, border cities are the key areas for urban landscape construction. As there is a gap between the current situation of the urban landscape of border cities and the development needs, special attention needs to be paid to the protection and continuation of the urban landscape characteristics of border cities in the process of urban design and planning, focusing on strengthening the expression of the unique culture and urban spiritual connotation of the region in the urban landscape.The public is not only the core of organizing the development of other market elements in border cities, but also the main point of action for cultural cognition and communication, forging the sense of Chinese national community in the border area, and the main body of urban landscape perception. As the state attaches more importance to the human environment, quantitatively evaluating the quality of urban and rural landscapes based on the public perspective and optimizing the design to meet the public needs has become an important development direction of landscape construction.Therefore, this study selects 18 land border cities in Heilongjiang Province for empirical analysis, analyzes the characteristics of border cities, constructs a partial least squares structural equation evaluation model for the perception of border cities, determines the evaluation system for the perception of border cities, and calculates the results of the evaluation of the appearance of border cities in Heilongjiang Province, to put forward targeted strategies for the improvement of the appearance of the application. The method mainly involves identifying the scope of public perceivable characteristic landscape elements quantifying the public perception of the landscape quality of the border cities, and further proposing how to protect and enhance the characteristic landscape elements of the border cities in the optimization strategy.The results of this study are as follows. Firstly, from the results of the indicator weights of the evaluation system of characteristic landscape perception, the weights of the role of various characteristic landscape elements on the overall border city landscape perception decrease in the following order: urban construction style perception, ecological landscape perception, cultural landscape perception, and national border landscape perception. The enhancement of the perception of the characteristic features of border cities is based on a good urban physical and spatial environment, and secondly, due to the differences in geography and the different levels of urban construction, theperception level of different cities and different types of characteristic features varies, and the distribution of the evaluation results of the perception of the characteristic features of the border cities is consistent with the characteristics of the spatial distribution of each type of feature element. Therefore, it is concluded that the landscape of border cities in Heilongjiang Province has the characteristics of prominent single characteristic landscape element points, continuous type characteristic landscape elements, and concentrated and continuous parts of characteristic landscape resources, and optimization suggestions are put forward based on the characteristic analysis.Based on the spatial characteristics of border cities that generally have a prominent characteristic landscape element, the study proposes to determine the positioning of the landscape image of each border city at the global level and to construct viewing points for the border regional center city, the important node city at the border, and the border city with general characteristics. According to the spatial characteristics of the continuous distribution of a certain type of distinctive landscape elements in the border cities, the study proposes to build a distinctive landscape system of the border cities according to type and to construct landscape perception lines, namely, the boundary river ecological landscape support belt, the northern border townscape construction belt, and the multicultural landscape integration belt. Based on the spatial characteristics of the concentration of some of the characteristic landscape resources, the study proposes to organize the regional system development of border cities in the form of clusters and to form a border town system with the border prefectural cities as the core, the border county cities and ports as the nodes, and towns and villages as the support for each other. This study provides objective support for the quantitative analysis and optimization of the quality of the landscape of border cities, to provide references for the exploration of related theories and the practice of the human environment in border cities.
2026(1),171-179
DOI: 10.13791/j.cnki.hsfwest.20240919005
Abstract:
Guan Zhong Basin is a relatively closed geomorphic unit. It is found that the natural and artificial elements have special geomorphic imprints. However, a few studies have analyzed the city and farmland difference characteristic under its influence from the perspective of whole-scale and secondary geomorphic differentiation. Through comparative analysis, field investigation, literature research, induction and deduction, and the combination of qualitative and quantitative methods, using ArcGIS software, the article analyzes the pattern and morphology differentiation characteristics of secondary geomorphic types by using object-type topographic factors, analyzes the city siting and farmland exploitation differentiation characteristics with secondary geomorphic types as the framework.In terms of geomorphic differentiation characteristics, from the perspective of geomorphic spatial pattern, it is found that the plain, tableland and mountain show uneven and symmetrical oval nesting and ladder climbing characteristics with the Weihe River as the axis in both horizontal and vertical directions, based on using morphological factors such as the width and average relative elevation of various landforms on the south and north sides of the Weihe River. From the perspective of geomorphic spatial morphology, it is found that the mountain fold morphology and the tableland erosion morphology also present obvious uneven and symmetrical characteristics based on the morphological factors such as saddle point, summit point, ridgeline, valley line and gully line.In terms of siting characteristics of ancient cities based on geomorphic differentiation, from the perspective of macro selection, the layout of the cities presents an expansion process from the tail of low and flat tableland to the positive area of plain, to concave-convex joint area in the middle cut or sloping tableland at higher elevation. From the micro-city foundation point, it is coupled with the scale and combination of “flat land and hill or tableland”, because of the similar landform morphology in the north and south of the Wei River, there are four city foundation modes of two sides, such as on the top of tableland, on the slope of tableland, landmark on the top of tableland and adjacent to tableland.In terms of farmland exploitation characteristics based on geomorphic differentiation, from the perspective of the key spatial transfer of farmland exploitation, the overall farmland showed an expansion trend from the low and flat tableland, the plain with fresh water in central and western Guanzhong Area, to the plain with salt water and sand in central and eastern Guanzhong Area, and then to the sloping tableland at high altitude. With the enhancement of the ability of soil and water management and micro-geomorphic modification, the farmland irrigation system has been built on the tableland and plain, and the unusable land such as mountain and flood land have been exploited. The farmland area and irrigation area in north of Weihe River is larger than the area in south of Weihe River. From the perspective of farmland structure, coupled with the scale and density of mountain fold, tableland-plain erosion form, there are three types summarized, such as long rectangular plots of flood land area, wide rectangular plots of flat tableland and plain area, and terrace of steep tableland or mountain area.Through the analysis of the siting of ancient cities and farmland exploitation from the perspective of geomorphic differentiation, it can be found that there are also very close couplingcharacteristics between the two, including the coordination between the macro-constituency of ancient cities and the key space of farmland exploitation, the dependence of cities on farmland, and the identity of using principles of geomorphic form between the specific city siting and the structure of farmland.The above methods or conclusions can provide guidance for the study of the particularity and correlation between similar natural and artificial elements, and also provide enlightenment for the protection and utilization of the element ontology and the continuation and externingzine of the methods and rules.
Guan Zhong Basin is a relatively closed geomorphic unit. It is found that the natural and artificial elements have special geomorphic imprints. However, a few studies have analyzed the city and farmland difference characteristic under its influence from the perspective of whole-scale and secondary geomorphic differentiation. Through comparative analysis, field investigation, literature research, induction and deduction, and the combination of qualitative and quantitative methods, using ArcGIS software, the article analyzes the pattern and morphology differentiation characteristics of secondary geomorphic types by using object-type topographic factors, analyzes the city siting and farmland exploitation differentiation characteristics with secondary geomorphic types as the framework.In terms of geomorphic differentiation characteristics, from the perspective of geomorphic spatial pattern, it is found that the plain, tableland and mountain show uneven and symmetrical oval nesting and ladder climbing characteristics with the Weihe River as the axis in both horizontal and vertical directions, based on using morphological factors such as the width and average relative elevation of various landforms on the south and north sides of the Weihe River. From the perspective of geomorphic spatial morphology, it is found that the mountain fold morphology and the tableland erosion morphology also present obvious uneven and symmetrical characteristics based on the morphological factors such as saddle point, summit point, ridgeline, valley line and gully line.In terms of siting characteristics of ancient cities based on geomorphic differentiation, from the perspective of macro selection, the layout of the cities presents an expansion process from the tail of low and flat tableland to the positive area of plain, to concave-convex joint area in the middle cut or sloping tableland at higher elevation. From the micro-city foundation point, it is coupled with the scale and combination of “flat land and hill or tableland”, because of the similar landform morphology in the north and south of the Wei River, there are four city foundation modes of two sides, such as on the top of tableland, on the slope of tableland, landmark on the top of tableland and adjacent to tableland.In terms of farmland exploitation characteristics based on geomorphic differentiation, from the perspective of the key spatial transfer of farmland exploitation, the overall farmland showed an expansion trend from the low and flat tableland, the plain with fresh water in central and western Guanzhong Area, to the plain with salt water and sand in central and eastern Guanzhong Area, and then to the sloping tableland at high altitude. With the enhancement of the ability of soil and water management and micro-geomorphic modification, the farmland irrigation system has been built on the tableland and plain, and the unusable land such as mountain and flood land have been exploited. The farmland area and irrigation area in north of Weihe River is larger than the area in south of Weihe River. From the perspective of farmland structure, coupled with the scale and density of mountain fold, tableland-plain erosion form, there are three types summarized, such as long rectangular plots of flood land area, wide rectangular plots of flat tableland and plain area, and terrace of steep tableland or mountain area.Through the analysis of the siting of ancient cities and farmland exploitation from the perspective of geomorphic differentiation, it can be found that there are also very close couplingcharacteristics between the two, including the coordination between the macro-constituency of ancient cities and the key space of farmland exploitation, the dependence of cities on farmland, and the identity of using principles of geomorphic form between the specific city siting and the structure of farmland.The above methods or conclusions can provide guidance for the study of the particularity and correlation between similar natural and artificial elements, and also provide enlightenment for the protection and utilization of the element ontology and the continuation and externingzine of the methods and rules.
2026(1),180-186
DOI: 10.13791/j.cnki.hsfwest.20241027001
Abstract:
Rural revitalization is a crucial measure to promote rural development in China, and the compilation of village planning serves as a policy tool to achieve rural revitalization. The shallow mountain area of the northern foothills of the Qinling Mountains, acting as the ecological barrier to the south of the Guanzhong Plain urban agglomeration, holds significant ecological, landscape, economic, and cultural value. However, the villages in this region face the realistic predicaments of severe spatial conflicts, an urgent need for the transformation of the development model of construction land use, and insufficient collaborative efficiency of multi-stakeholder planning. To address these issues, the study introduces the theory of Organic Renewal and constructs a theoretical model that covers the entire “production-living-ecological" space, village construction space, and relationships among multiple stakeholders. The model systematically integrates the mechanisms of organic order restoration, modern function compounding, and multi-stakeholder collaborative governance from three aspects: macro-scale, micro-scale, and safeguard systems, forming a complete innovation system for planning compilation. By clarifying the boundaries of the “production-living-ecological” space, formulating zoning control guidelines, and establishing a supervision mechanism, the organic order of the three spaces is restored, and the conflict between ecological protection and development is alleviated. Meanwhile, by enabling functional compatibility of land and buildings and sharing of space and time, modern functions are compounded in villages to release usable space. Additionally, through mutual consultation, assistance, and benefit, multi-stakeholder governance is coordinated to build a new type of rural social order. Taking Liyukou Village in Huyi District, Xi’an as an example, the study further explores the specific path of village planning. As a typical village in the shallow mountain area of the northern foothills of the Qinling Mountains, Liyukou Village faces the dual pressures of ecological protection and village development. The specific planning path includes restoring the order of the three spaces with ecological protection as the premise. The order of ecological and production spaces is restored by weaving a green network of forest land and farmland, the order of living space is restored by improving public service facilities in the village, and the order of the three spaces is coordinated by formulating zoning control guidelines. At the same time, by integrating the village’s basic resources, guiding space reorganization in phases, and softly embedding modern industrial functions, the quality of rural life and cultural-tourism space is optimized, and the value of rural basic resources is increased. In addition, by integrating collaborative governance from multiple parties, including the village, government, and society, the full-chain management mechanism is improved, the internal development momentum of the village is gathered, and the construction of multi-stakeholder collaborative organizations is promoted. Specifically, the measures for restoring the organic order of the three spaces include: conserving the ecological and productive base, weaving a network of farmland, forest land, and rural roads to enhance the stability and service functions of the ecosystem; improving the quality of livable life by perfecting public service facilities in the village, optimizing the quality of living space, and strengthening the industrial support system; balancingthe order of the three spaces by formulating zoning control guidelines and clarifying the main functions of each space through a control system of "rigid constraints+flexible guidance" to coordinate ecological protection and construction activities. The measures for compounding modern functions include: integrating the village's basic resources and guiding space reorganization in phases. By reasonably clearing abandoned homesteads, the orderly reorganization of existing land is achieved. Modern industrial functions are softly embedded to revitalize idle resources, improve the utilization efficiency of rural basic resources, and establish a reward mechanism and a paid-exit mechanism for the revitalization of homesteads, providing institutional guarantees for the integration of village resources. The measures for collaborative governance of multiple stakeholders include: integrating village-enterprise linkage to achieve resource sharing and industrial interaction. A multi-party collaborative relationship among farmers, government, market, and planners is established, clarifying a multi-party co- construction mechanism with farmers as the main body to ensure the integrity and scientific nature of planning content. The full-chain management mechanism is improved to ensure the implementation of recent construction. The "compilation-review-implementation-evaluation" management system is perfected to supervise the compilation, implementation, and updating of project construction at various stages, ensuring dynamic updates of planning and construction results and effective connection with higher-level planning. Taking the shallow mountain area of the northern foothills of the Qinling Mountains as an example, the model proposes innovative planning compilation ideas in zoning control, facility configuration, and villager self-governance, providing a theoretical framework and implementation path for the planning practice of similar villages in the same area.
Rural revitalization is a crucial measure to promote rural development in China, and the compilation of village planning serves as a policy tool to achieve rural revitalization. The shallow mountain area of the northern foothills of the Qinling Mountains, acting as the ecological barrier to the south of the Guanzhong Plain urban agglomeration, holds significant ecological, landscape, economic, and cultural value. However, the villages in this region face the realistic predicaments of severe spatial conflicts, an urgent need for the transformation of the development model of construction land use, and insufficient collaborative efficiency of multi-stakeholder planning. To address these issues, the study introduces the theory of Organic Renewal and constructs a theoretical model that covers the entire “production-living-ecological" space, village construction space, and relationships among multiple stakeholders. The model systematically integrates the mechanisms of organic order restoration, modern function compounding, and multi-stakeholder collaborative governance from three aspects: macro-scale, micro-scale, and safeguard systems, forming a complete innovation system for planning compilation. By clarifying the boundaries of the “production-living-ecological” space, formulating zoning control guidelines, and establishing a supervision mechanism, the organic order of the three spaces is restored, and the conflict between ecological protection and development is alleviated. Meanwhile, by enabling functional compatibility of land and buildings and sharing of space and time, modern functions are compounded in villages to release usable space. Additionally, through mutual consultation, assistance, and benefit, multi-stakeholder governance is coordinated to build a new type of rural social order. Taking Liyukou Village in Huyi District, Xi’an as an example, the study further explores the specific path of village planning. As a typical village in the shallow mountain area of the northern foothills of the Qinling Mountains, Liyukou Village faces the dual pressures of ecological protection and village development. The specific planning path includes restoring the order of the three spaces with ecological protection as the premise. The order of ecological and production spaces is restored by weaving a green network of forest land and farmland, the order of living space is restored by improving public service facilities in the village, and the order of the three spaces is coordinated by formulating zoning control guidelines. At the same time, by integrating the village’s basic resources, guiding space reorganization in phases, and softly embedding modern industrial functions, the quality of rural life and cultural-tourism space is optimized, and the value of rural basic resources is increased. In addition, by integrating collaborative governance from multiple parties, including the village, government, and society, the full-chain management mechanism is improved, the internal development momentum of the village is gathered, and the construction of multi-stakeholder collaborative organizations is promoted. Specifically, the measures for restoring the organic order of the three spaces include: conserving the ecological and productive base, weaving a network of farmland, forest land, and rural roads to enhance the stability and service functions of the ecosystem; improving the quality of livable life by perfecting public service facilities in the village, optimizing the quality of living space, and strengthening the industrial support system; balancingthe order of the three spaces by formulating zoning control guidelines and clarifying the main functions of each space through a control system of "rigid constraints+flexible guidance" to coordinate ecological protection and construction activities. The measures for compounding modern functions include: integrating the village's basic resources and guiding space reorganization in phases. By reasonably clearing abandoned homesteads, the orderly reorganization of existing land is achieved. Modern industrial functions are softly embedded to revitalize idle resources, improve the utilization efficiency of rural basic resources, and establish a reward mechanism and a paid-exit mechanism for the revitalization of homesteads, providing institutional guarantees for the integration of village resources. The measures for collaborative governance of multiple stakeholders include: integrating village-enterprise linkage to achieve resource sharing and industrial interaction. A multi-party collaborative relationship among farmers, government, market, and planners is established, clarifying a multi-party co- construction mechanism with farmers as the main body to ensure the integrity and scientific nature of planning content. The full-chain management mechanism is improved to ensure the implementation of recent construction. The "compilation-review-implementation-evaluation" management system is perfected to supervise the compilation, implementation, and updating of project construction at various stages, ensuring dynamic updates of planning and construction results and effective connection with higher-level planning. Taking the shallow mountain area of the northern foothills of the Qinling Mountains as an example, the model proposes innovative planning compilation ideas in zoning control, facility configuration, and villager self-governance, providing a theoretical framework and implementation path for the planning practice of similar villages in the same area.
2026(1),187-194
DOI: 10.13791/j.cnki.hsfwest.20240814004
Abstract:
With the advancement of China’s ecological civilization construction, the productionliving- ecological space, as the spatial carrier for human activities, has gradually become the core link for regulating the interaction between the human system and the natural environment. Especially in regions with complex landforms and fragile ecosystems, such as the gully areas of the Loess Plateau, the production-living-ecological spaces within the region are significantly constrained by natural conditions, and the ecological effects brought about by spatial evolution exhibit distinct regional particularities. Therefore, in the context of the comprehensive establishment of the national spatial planning system, analyzing and summarizing the research progress on the ecological effects of production, living, and ecological spaces at home and abroad can help to deeply understand the interaction mechanism of space and its impact on regional sustainable development, reveal the diversity and regularity of ecological effects at different regions and scales, and provide important references for the optimization of national spatial planning in ecologically fragile areas. This study aims to comprehensively compare the research status and hotspots in the field of production-livingecological space and its ecological effects at home and abroad. By using bibliometric tools such as Bibliometrix and CiteSpace, and by reviewing 1 000 English-language articles from the WOS database and 1 138 Chinese-language articles from the CNKI database from 1998 to 2023, an academic map of the ecological effects of the production-living-ecological space is drawn. Through the methods of co-citation network, keyword co-occurrence clustering, and trend analysis, the spatiotemporal evolution patterns of this field are revealed from three dimensions: research progress, method evolution, and practical application. In terms of research hotspots, foreign keywords focus on areas such as “land use, spatio-temporal changes in land use, ecosystems, and climate change”, while domestic research started later and mainly focuses on “production-living-ecological space, ecological effects, national spatial planning, and spatial optimization”. In terms of research progress, the intensity of cooperation, continuity, systematicness, and interdisciplinarity of foreign research are significantly higher than those of domestic research. The evolution process of foreign research has gone through static, dynamic to comprehensive integration stages, and multiple spatio-temporal scale comprehensive simulation models have been established; domestic research is more concentrated on single-scale studies, such as administrative units and geographical units.The research findings are as follows 1) international research has shifted from spatio-temporal changes in land use to humanland coupling systems under climate change, with biodiversity conservation and ecosystem service assessment becoming recent focuses; Chinese research follows three stages, “space identificationspatio- temporal evolution-ecological effect evaluation”, which is highly consistent with the development of the national spatial planning system and environmental policies. 2) Research methodshave broken through the limitations of traditional static data, gradually introducing high-resolution remote sensing images, multi-temporal historical land use data, and socio-economic statistics, enhancing the ability to identify the dynamic evolution of the production-living-ecological space. At the same time, by combining multi-scale modeling techniques, simulation frameworks suitable for different spatial scales have been constructed, achieving refined analysis from spatial pattern identification to ecological effect evaluation, significantly improving the timeliness and practicality of research. 3) Practical applications show a deepening feature of “single-space control-dynamic process simulation-focus on special geographical units”, and the collaborative research on human-land relations in special geographical units such as river basins is becoming a future trend. How to construct a three-dimensional collaborative analysis framework of “topography-hydrology-human activities” in typical geographical units such as river basins and form a research paradigm for the collaborative mechanism of human-land relations in special geomorphic areas is becoming a frontier direction in national spatial planning optimization.
With the advancement of China’s ecological civilization construction, the productionliving- ecological space, as the spatial carrier for human activities, has gradually become the core link for regulating the interaction between the human system and the natural environment. Especially in regions with complex landforms and fragile ecosystems, such as the gully areas of the Loess Plateau, the production-living-ecological spaces within the region are significantly constrained by natural conditions, and the ecological effects brought about by spatial evolution exhibit distinct regional particularities. Therefore, in the context of the comprehensive establishment of the national spatial planning system, analyzing and summarizing the research progress on the ecological effects of production, living, and ecological spaces at home and abroad can help to deeply understand the interaction mechanism of space and its impact on regional sustainable development, reveal the diversity and regularity of ecological effects at different regions and scales, and provide important references for the optimization of national spatial planning in ecologically fragile areas. This study aims to comprehensively compare the research status and hotspots in the field of production-livingecological space and its ecological effects at home and abroad. By using bibliometric tools such as Bibliometrix and CiteSpace, and by reviewing 1 000 English-language articles from the WOS database and 1 138 Chinese-language articles from the CNKI database from 1998 to 2023, an academic map of the ecological effects of the production-living-ecological space is drawn. Through the methods of co-citation network, keyword co-occurrence clustering, and trend analysis, the spatiotemporal evolution patterns of this field are revealed from three dimensions: research progress, method evolution, and practical application. In terms of research hotspots, foreign keywords focus on areas such as “land use, spatio-temporal changes in land use, ecosystems, and climate change”, while domestic research started later and mainly focuses on “production-living-ecological space, ecological effects, national spatial planning, and spatial optimization”. In terms of research progress, the intensity of cooperation, continuity, systematicness, and interdisciplinarity of foreign research are significantly higher than those of domestic research. The evolution process of foreign research has gone through static, dynamic to comprehensive integration stages, and multiple spatio-temporal scale comprehensive simulation models have been established; domestic research is more concentrated on single-scale studies, such as administrative units and geographical units.The research findings are as follows 1) international research has shifted from spatio-temporal changes in land use to humanland coupling systems under climate change, with biodiversity conservation and ecosystem service assessment becoming recent focuses; Chinese research follows three stages, “space identificationspatio- temporal evolution-ecological effect evaluation”, which is highly consistent with the development of the national spatial planning system and environmental policies. 2) Research methodshave broken through the limitations of traditional static data, gradually introducing high-resolution remote sensing images, multi-temporal historical land use data, and socio-economic statistics, enhancing the ability to identify the dynamic evolution of the production-living-ecological space. At the same time, by combining multi-scale modeling techniques, simulation frameworks suitable for different spatial scales have been constructed, achieving refined analysis from spatial pattern identification to ecological effect evaluation, significantly improving the timeliness and practicality of research. 3) Practical applications show a deepening feature of “single-space control-dynamic process simulation-focus on special geographical units”, and the collaborative research on human-land relations in special geographical units such as river basins is becoming a future trend. How to construct a three-dimensional collaborative analysis framework of “topography-hydrology-human activities” in typical geographical units such as river basins and form a research paradigm for the collaborative mechanism of human-land relations in special geomorphic areas is becoming a frontier direction in national spatial planning optimization.
2026(1),195-199
DOI: 10.13791/j.cnki.hsfwest.20241227001
Abstract:
Rural homestays serve as a pivotal component of rural tourism, and their healthy development plays a crucial role in revitalizing idle rural resources and optimizing the rural industrial structure. In Shaanxi Province, the development of rural homestays has achieved remarkable results. This paper takes rural homestays in Shaanxi Province as the object and uses the Multiscale Geographically Weighted Regression (MGWR) model to explore the influencing factors and spatial scale effects on their prices. The results show that: 1) The spatial distribution of rural homestays in Shaanxi Province exhibits significant imbalance, characterized by localized clustering and a “one core, one sub-core, and three nodes”. In the Guanzhong region, the Greater Xi’an area serves as the primary agglomeration hub, radiating to neighboring counties such as Lantian, Lintong, and Mei County. Weinan City has a relatively independent secondary agglomeration nucleus of rural homestays surrounding the Huashan Scenic Area. Additional clusters of homestays are observed in Linyou County, Liquan County, and Baota District, though at a smaller scale. The quantity and scale of rural homestays at different price levels follows a “pyramid” structure, with significant differences in spatial distribution. Low-priced homestays have the widest distribution range, showing a continuous and extensive distribution pattern. Medium-priced ones are concentrated in the areas surrounding Xi’an, forming a certain scale of agglomeration. High-priced ones are mainly located in the northern foothills of the Qinling Mountains, with only a few scattered points in southern Shaanxi. 2) The influencing factors of rural homestay prices exhibit spatial scale effects. The bandwidths of per capita GDP and the completeness of activity facilities are 567 and 568, respectively, indicating that they are global factors with almost no spatial heterogeneity. The intensity of their influence on rural homestay prices generally shows a pattern of being higher in the south and lower in the north. The bandwidths of room area and whether a deposit is required are 49 and 43, respectively, suggesting that they are local variables with significant spatial heterogeneity in their impact on prices. Their influence is mainly concentrated in the northern foothills of the Qinling Mountains and some areas in southern Shaanxi. The bandwidths of factors such as the density of high-grade highways, the completeness of infrastructure, and architectural features range from 100 to 130. These factors have a moderate influence range, mainly concentrated in Xi’an, Baoji, and other places, and there is no obvious spatial distribution pattern in the magnitude of their influence coefficients. 3) An analysis from the three dimensions of the regional macro-background, neighbourhood environmental characteristics, and the physical characteristics of homestays, it can be seen that the physical characteristics of homestays have the greatest impact on rural homestay prices, with hardware facilities having a more significant effect than soft services. The macro-regional characteristics also have a relatively high impact on rural homestay prices, among which the density of high-grade highways and per capita GDP are particularly influential. However, neighbourhood environmental characteristics have no significant influence on theprices of rural homestays. 4) At the county level, the density of high-grade highways, per capita GDP, and whether a deposit is required are negatively correlated with the prices of rural homestays. On the other hand, factors such as room size, the completeness of infrastructure, and the completeness of activity facilities have a positive promoting effects on rural homestay prices. The conclusions of this paper provide theoretical support and practical guidance for the healthy and efficient development of rural tourism and the overall revitalization of rural areas in Shaanxi. Based on the spatial distribution pattern of rural homestay prices and the spatial heterogeneity of influencing factors, this paper proposes several recommendations from two aspects: enhancing the physical characteristics of homestays and optimizing their spatial layout. For instance, in terms of improving the physical characteristics of homestays, in line with the market positioning of rural homestays, different price rural homestays should offer differentiated activity facilities. Moreover, the spatial layout should be optimized following the logical approach of “driven by homestay clusters and connected by major axes”. These suggestions aim to provide useful support for local governments in guiding the scientific pricing of rural homestays, optimizing homestays layout, improving service quality, and enhancing the competitiveness of the rural tourism market. The conclusions of this paper provide theoretical support and practical guidance for the healthy and efficient development of rural tourism and the overall revitalization of rural areas in Shaanxi Province. The research findings also provide valuable insights for other regions facing similar challenges in rural tourism development, serving as a reference for policy-making and practical applications in the fields of rural homestay management and rural tourism promotion.
Rural homestays serve as a pivotal component of rural tourism, and their healthy development plays a crucial role in revitalizing idle rural resources and optimizing the rural industrial structure. In Shaanxi Province, the development of rural homestays has achieved remarkable results. This paper takes rural homestays in Shaanxi Province as the object and uses the Multiscale Geographically Weighted Regression (MGWR) model to explore the influencing factors and spatial scale effects on their prices. The results show that: 1) The spatial distribution of rural homestays in Shaanxi Province exhibits significant imbalance, characterized by localized clustering and a “one core, one sub-core, and three nodes”. In the Guanzhong region, the Greater Xi’an area serves as the primary agglomeration hub, radiating to neighboring counties such as Lantian, Lintong, and Mei County. Weinan City has a relatively independent secondary agglomeration nucleus of rural homestays surrounding the Huashan Scenic Area. Additional clusters of homestays are observed in Linyou County, Liquan County, and Baota District, though at a smaller scale. The quantity and scale of rural homestays at different price levels follows a “pyramid” structure, with significant differences in spatial distribution. Low-priced homestays have the widest distribution range, showing a continuous and extensive distribution pattern. Medium-priced ones are concentrated in the areas surrounding Xi’an, forming a certain scale of agglomeration. High-priced ones are mainly located in the northern foothills of the Qinling Mountains, with only a few scattered points in southern Shaanxi. 2) The influencing factors of rural homestay prices exhibit spatial scale effects. The bandwidths of per capita GDP and the completeness of activity facilities are 567 and 568, respectively, indicating that they are global factors with almost no spatial heterogeneity. The intensity of their influence on rural homestay prices generally shows a pattern of being higher in the south and lower in the north. The bandwidths of room area and whether a deposit is required are 49 and 43, respectively, suggesting that they are local variables with significant spatial heterogeneity in their impact on prices. Their influence is mainly concentrated in the northern foothills of the Qinling Mountains and some areas in southern Shaanxi. The bandwidths of factors such as the density of high-grade highways, the completeness of infrastructure, and architectural features range from 100 to 130. These factors have a moderate influence range, mainly concentrated in Xi’an, Baoji, and other places, and there is no obvious spatial distribution pattern in the magnitude of their influence coefficients. 3) An analysis from the three dimensions of the regional macro-background, neighbourhood environmental characteristics, and the physical characteristics of homestays, it can be seen that the physical characteristics of homestays have the greatest impact on rural homestay prices, with hardware facilities having a more significant effect than soft services. The macro-regional characteristics also have a relatively high impact on rural homestay prices, among which the density of high-grade highways and per capita GDP are particularly influential. However, neighbourhood environmental characteristics have no significant influence on theprices of rural homestays. 4) At the county level, the density of high-grade highways, per capita GDP, and whether a deposit is required are negatively correlated with the prices of rural homestays. On the other hand, factors such as room size, the completeness of infrastructure, and the completeness of activity facilities have a positive promoting effects on rural homestay prices. The conclusions of this paper provide theoretical support and practical guidance for the healthy and efficient development of rural tourism and the overall revitalization of rural areas in Shaanxi. Based on the spatial distribution pattern of rural homestay prices and the spatial heterogeneity of influencing factors, this paper proposes several recommendations from two aspects: enhancing the physical characteristics of homestays and optimizing their spatial layout. For instance, in terms of improving the physical characteristics of homestays, in line with the market positioning of rural homestays, different price rural homestays should offer differentiated activity facilities. Moreover, the spatial layout should be optimized following the logical approach of “driven by homestay clusters and connected by major axes”. These suggestions aim to provide useful support for local governments in guiding the scientific pricing of rural homestays, optimizing homestays layout, improving service quality, and enhancing the competitiveness of the rural tourism market. The conclusions of this paper provide theoretical support and practical guidance for the healthy and efficient development of rural tourism and the overall revitalization of rural areas in Shaanxi Province. The research findings also provide valuable insights for other regions facing similar challenges in rural tourism development, serving as a reference for policy-making and practical applications in the fields of rural homestay management and rural tourism promotion.
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.