Abstract:The non-visual effects of light, distinct from its role in supporting visual perception, exert profound and multifaceted influences on human physical and mental health, a connection that has become increasingly central to the design needs of healthy building light environments. In the context of rapid urbanization and modern lifestyles, humans now spend over 90% of their time indoors, where artificial lighting has replaced natural sunlight as the primary source of daily light exposure. This shift has disrupted the ancient synchronization between human circadian rhythms and the natural light-dark cycle, highlighting the urgency of addressing non-visual light effects in built environments. However, despite growing attention from architecture, neuroscience, and public health fields, in-depth exploration of the underlying mechanisms of these effects and the construction of systematic theoretical frameworks remain insufficient. Existing research often focuses on isolated aspects (e.g., single light parameters or specific health outcomes) rather than integrating physiological, psychological, and environmental factors, leaving critical gaps in guiding evidence-based lighting design.By systematically sorting out the scientific research progress of light’ s non-visual effects over the past three decades, from early discoveries of melanopsin-containing intrinsically photosensitive retinal ganglion cells (ipRGCs) in the 2000s to recent longitudinal studies on long-term light exposure, this paper comprehensively explores the types of effects on human physiology and psychology. Physiologically, non-visual light effects primarily regulate the hypothalamic-pituitaryadrenal (HPA) axis and the pineal gland’s melatonin secretion: for instance, short-wavelength blue light (460-480 nm) can suppress melatonin production by up to 50% under moderate illuminance (300 lux), thereby delaying the circadian phase and disrupting sleep-wake cycles. Chronically disrupted circadian rhythms have been linked to a higher risk of metabolic disorders (e. g., obesity, type 2 diabetes), cardiovascular diseases, and even certain cancers. Psychologically, the paper highlights potential effects on alertness, sleep quality, and emotional states: morning exposure to highilluminance (≥1 000 lux) white light has been shown to improve subjective alertness by 20%~30% and reduce daytime sleepiness in office workers, while prolonged exposure to low-illuminance, warmspectrum light in the evening may increase symptoms of anxiety and depression by altering serotonin levels in the brain.Furthermore, the paper summarizes the key elements in building light environments that modulate these non-visual effects, including illuminance level, spectral composition, exposure duration, and timing of exposure, and clarifies the laws governing how these elements shape internal physiological and psychological responses. Illuminance, for example, exhibits a dose-response relationship with non-visual effects: below 50 lux, non-visual impacts are negligible, but effects intensify as illuminance increases (peaking at 1 000-2 000 lux for alertness regulation). Spectral composition is equally critical: blue light (400-500 nm) is the most potent trigger for non-visual responses due to its high absorption by ipRGCs, whereas red light (600-700 nm) has minimal effects on circadian rhythms and melatonin. Exposure timing also plays a decisive role: light exposure in the morning advances the circadian clock (promoting early sleep-wake cycles), while evening light delays it, explaining why excessive screen time (rich in blue light) before bed is a major contributor toinsomnia in modern populations.The paper also provides a comprehensive overview of evaluation models for light environment non-visual effects, including the Circadian Stimulus (CS) model, the melanopic Equivalent Daylight Illuminance (mEDI) model, and the Mean Euclidean Weighted Stimulus (MEWS) model, and conducts a comparative analysis of their thresholds and application effects. The CS model, developed by the Lighting Research Center (LRC), quantifies light’s ability to regulate circadian rhythms with a threshold of 0.3 (indicating sufficient circadian stimulation for healthy adults); however, it fails to account for individual differences in age (e.g., elderly individuals require 30-50% higher illuminance to achieve the same CS value) or retinal health. The mEDI model, by contrast, normalizes non-visual effects to equivalent daylight levels, making it more intuitive for architects but less accurate for artificial lights with atypical spectra (e.g., warm white LEDs). The MEWS model addresses some of these limitations by integrating both circadian and alertness responses, but its complexity limits its practical application in routine design. Common challenges across models include the lack of data on long-term effects (e.g., 5+ years of exposure) and insufficient consideration of vulnerable populations (e.g., shift workers, individuals with circadian rhythm disorders).The primary purpose of this paper is to fill these theoretical and practical gaps by providing a scientific basis for health-oriented building lighting design strategies. For example, in residential settings, the paper recommends dynamic lighting systems that adjust spectral composition (reducing blue light after 8 PM) and illuminance (gradually dimming in the evening) to align with human circadian rhythms. In office environments, it suggests morning high-illuminance (1 500 lux) light exposure to enhance productivity and afternoon moderate-illuminance (500 lux) to avoid over-stimulation. In healthcare facilities, it proposes tailored lighting for patients with sleep disorders (e.g., bright morning light therapy for insomnia) and for night-shift nurses (e.g., low-blue light during night shifts to preserve circadian health). By translating scientific findings into actionable design guidelines, this research aims to realize healthy human settlement light environments, reducing the burden of light-related chronic diseases and improving public health outcomes. Ultimately, this work responds to the strategic needs of “Healthy China” by integrating environmental design with public health, contributing to the construction of a society where built environments actively support, rather than compromise and human health.

Abstract:Classroom lighting profoundly affects students’ visual health, learning efficiency, and psychological comfort, yet conventional design standards based on illuminance and correlated color temperature (CCT) overlook the critical role of spatial luminance distribution. Since luminance directly stimulates the retina, it better represents actual visual experience, but existing studies rarely quantify how luminance distribution features interact with CCT to shape subjective atmosphere preference. This study addresses this gap by systematically investigating the combined effects of spatial luminance gradients, mean luminance, and CCT on preference ratings under static self-study tasks, aiming to develop a predictive model that supports refined classroom lighting design. A controlled experiment was conducted in a variable-space chamber configured as a 12×6×4 m classroom. Eighteen LED luminaires with tunable CCT (2 700-6 000 K) and dimmable output were installed, and wall reflectances were varied using replaceable curtain fabrics. Thirty-six experimental conditions were generated by combining three CCT levels (3 000, 4 300, 5 500 K), three desk illuminance levels (300, 500, 1 000 lx), and four wall reflectance coefficients (0.6-0.9). Luminance distributions were captured at a seated student’s eye height using a Konica CA-2000 color luminance meter. After preprocessing with a region-growing algorithm, the visual field was divided into a 5×5 grid, yielding 25 regional mean luminances. From these, 16 directional luminance gradients (D11 to D82) were defined along eight radial directions at two distance steps, together with mean luminance (Lm), central luminance (Lc), and standard deviation (Ld), resulting in 20 candidate physical variables plus CCT. Subjective preference data were collected from 16 healthy university students (8 male, 8 female, aged 22-26) using a 5-point Likert scale after a 10-minute simulated reading task. Each participant evaluated all 36 conditions in random order, producing 576 valid responses. To identify the most influential predictors, both Pearson correlation and maximal information coefficient (MIC) were applied. Pearson correlations showed no significant linear relationships (p> 0.05), whereas MIC values revealed strong nonlinear associations: CCT ranked highest (MIC=0.92), followed by several gradients (D31, D41, D52, D62 at 0.53) and Lm (0.46). This clear discrepancy confirmed that the relationship between physical parameters and psychological preference is inherently nonlinear. To reduce multicollinearity among luminance features—inevitable due to global dimming—hierarchical clustering was performed on the 19 non-CCT variables using average linkage. The dendrogram identified three major clusters; after eliminating redundant members, four core variables were retained: CCT, Lm, the forward luminance gradient (D31, center-to-front-background difference), and the lower-left peripheral gradient (D82). These variables capture the dominant baseline effect of CCT, the overall brightness level, the spatial contrast in the primary viewing direction, and a secondary peripheral correction, respectively. Visualization of the data revealed strong interactive effects. Under 3 000 K, preference ratings increased nearly linearly with L? from 40 to 100cd/cm2, indicating that higher luminance compensates for the low-CCT induced drowsiness. However, under 4 300 K and 5 500 K, preference peaked at L? ≈ 70-80 cd/cm2 and then flattened or declined, demonstrating saturation and diminishing returns. Similarly, the effect of D?? reversed with CCT: positive under 3 000 K (enhancing spatial layering), neutral under 4 300 K, and negative under 5 500 K when D31 exceeded 80 cd/cm2, suggesting that high CCT combined with strong gradients increases visual stress. These patterns confirm that luminance features do not act independently but are deeply modulated by the CCT context. To quantitatively model these nonlinear and interactive relationships, a polynomial regression was formulated with centered CCT (to reduce collinearity), quadratic CCT2 term, linear Lm, D31, and D82, and an interaction term CCTadj×D31. The fitted model achieved excellent performance: R2= 0.912 (adjusted R2=0.894), with overall F-test p < 0.001. The negative coefficient for CCT2 confirmed the inverted-U shape, while the significant negative interaction coefficient (p <0.001) quantitatively proved that the contribution of D31 diminishes as CCT increases. The final equation provides a practical tool for predicting atmosphere preference from easily measurable or designable variables. The model also enables a clear mapping from design parameters to environmental features. CCT is primarily set by light source selection, with 4 300 K recommended as the optimal baseline. L? is controlled via dimming and luminaire count, with a saturation point around 70-80 cd/cm2 under neutral/cool CCTs. D31 is adjusted through front wall reflectance and luminaire optics: moderate enhancement under low CCT to improve spatial depth, but smoothing under high CCT to avoid glare and discomfort. D82, as a secondary factor, can be managed via side-wall materials. This mapping establishes a quantitative design workflow from inputs to predicted preference, enabling iterative optimization. In conclusion, this study demonstrates that classroom lighting preference is governed by strong nonlinear interactions between CCT and spatial luminance distribution, not by any single linear factor. The proposed model, with 91.2% explanatory power, successfully integrates these complexities and offers a scientific basis for intelligent, human-centric lighting control. The findings advocate for moving beyond uniform illuminance standards toward adaptive strategies that tailor luminance gradients according to CCT, ultimately enhancing visual comfort and well-being in educational environments.

Abstract:Current lighting standards are predominantly formulated based on visual performance, lacking quantitative evidence and intervention thresholds for the non-visual biological effects of long-term dynamic light exposure, especially circadian rhythm regulation, under extreme environments and special medical scenarios. This study aims to elucidate the dose-response relationships between light environments with varying spectral and temporal characteristics and physiological rhythms as well as cognitive rehabilitation across all age groups, and to establish an evidence-based framework for healthy lighting design.The research adopts a multi-modal data fusion strategy across multiple field sites. At China’s Zhongshan Station in Antarctica, an extreme polar night environment with approximately 58 consecutive days of darkness during winter, a 12-year longitudinal intervention study was conducted. The “Antarctic Health Human Factors Cabin” was deployed, and 13 winter-over expedition members (mean age 39.00±9.02 years) participated in the experiment, receiving dynamic circadian lighting interventions including morning arousal and pre-sleep relaxation protocols. Results demonstrated that the intervention significantly improved sleep quality, with PSQI scores decreasing by 13.45% and POMS scores decreasing by 4.09%, indicating significant alleviation of negative emotions. Core body temperature rhythm phases were effectively recalibrated to healthier circadian patterns. In medical rehabilitation settings, the study investigated three distinct application scenarios. First, in intensive care units (ICU), a cross-modal audio-visual intervention paradigm was developed for patients with disorders of consciousness (DOC), integrating blue light stimulation with personalized music to activate brainstem reticular formation through ipRGC pathways and evoke autobiographical memory. A pilot experiment involving 27 healthy subjects confirmed that blue light combined with high-familiarity music produced an 84.4% super-additive arousal effect (p=0.017) compared to the control group. Second, in stroke rehabilitation wards, a 24-hour dynamic lighting system was implemented with morning high-illuminance high-color-temperature stimulation (melanopic EDI ≥1000 lx), daytime neutral illumination (melanopic EDI ≥250 lx), and nighttime low-illuminance warm light (melanopic EDI ≤10 lx). A prospective single-blind randomized controlled trial involving 33 stroke patients (17 intervention, 16 control) over a 20-day period revealed that the intervention group showed significantly greater improvement in Morningness-Eveningness Questionnaire (MEQ-SA) scores (p<0.05) and significantly elevated nocturnal salivary melatonin levels (p<0.05), indicating phase advancement toward a morning-type circadian pattern. Third, in medical wellness centers, dynamic full-color lighting was systematically explored for emotional regulation, with subjective evaluations and multi-modal physiological indicators (ECG, EDA, EEG) demonstrating that dynamic colored light outperformed static white light in enhancing pleasure, satisfaction, and perceived restorativeness. For all-age populations, differentiated intervention strategies were developed. In children and adolescents, the study synthesized evidence on myopia prevention through low-intensity long-wavelength red light (Zhou et al., 9-month intervention, 105 participants), full-spectrum indoor lighting (Bao et al., 12-month intervention, 45 participants), and vitamin D synthesis associated with sufficient sunlight exposure (Yazar et al., 946 young adults), demonstrating that light exposure contributes to myopia control through multiple pathways including retinal dopamine regulation and vitamin D metabolism. For elderly populations (over 320 million in China), a laboratory-to-home validationapproach was adopted with 76 participants and 647 saliva samples collected over a three-month period. Results revealed that pre-sleep melanopic EDI at ≤50 lx fell within a physiological inert zone, causing no clinically significant melatonin suppression, while the effective detection rate of dim light melatonin onset (DLMO) was significantly lower in elderly populations compared to younger cohorts. For postpartum women with depressive tendencies (EPDS≥9), a 28- day home-based lighting intervention with 30 participants demonstrated significant improvements in EPDS and POMS scores, with stable improvements in subjective emotional states, sleep duration, sleep quality, and salivary melatonin levels observed after two weeks. For aircraft cabin environments, on-site measurements revealed uneven illuminance distribution and low daytime melanopic EDI levels. A scenario-based dynamic lighting strategy was proposed covering all flight phases: boarding with dynamic colored light (blue-orange combinations) to alleviate flight anxiety, daytime cruising with high color temperature and high m-EDI white light to maintain alertness, nighttime cruising with low-illuminance long-wavelength red light to preserve circadian stability, and descent with progressively increasing illuminance and color temperature to facilitate smooth awakening and circadian re-synchronization. To optimize spectral power distribution (SPD) for circadian effects, five lighting scenarios were tested using a four-primary-color mixing method with 16 participants. Eye-tracking metrics including blink frequency, eye closure duration, and pupil diameter were measured, combined with the psychomotor vigilance task (PVT) and subjective visual comfort assessments. Results demonstrated that short-wavelength-dominant high-melanopic lighting reduced fatigue and sleepiness but decreased visual comfort, while long-wavelength-dominant low-melanopic lighting improved subjective comfort but reduced alertness and response speed, highlighting the need for balancing circadian stimulation with visual comfort. Through the above multi-scenario empirical studies, this research establishes an evidence-based healthy lighting design framework and quantifies the efficacy boundaries of light intervention across different populations and environments, providing scientific foundations for optimizing lighting standards in both extreme and daily living conditions.

Abstract:Outdoor lighting in old university campuses plays a dual role in ensuring nighttime safety and reconstructing spatial order, yet many existing campuses still suffer from fragmented lighting organization, ambiguous illumination zoning, and insufficient correspondence between lighting hierarchy and functional spatial structure. To address these problems, this study introduces the theories of spatial continuity and circle-layer organization into campus outdoor lighting planning, and takes Zone B of Chongqing University as a representative case. Based on field investigation, illuminance and luminance measurements, nighttime image comparison, functional zoning analysis, and pedestrian-flow heat-map observation, the study establishes a systematic lighting renewal framework for old campus environments characterized by complex spatial textures, historical architectural resources, and mixed nighttime activities. The investigation shows that the existing lighting environment in Zone B is dominated by scattered functional lighting and lacks an integrated spatial organization strategy. Most key building fa?ades are not independently illuminated and rely mainly on road lighting or interior light spill for nighttime visibility. Road lighting is uneven in several sections, while some pedestrian paths, green-space edges, and transitional areas contain dark zones or visual blind spots. In addition, abrupt changes in brightness and color temperature between adjacent spaces weaken the coherence of the nighttime visual sequence. These problems indicate that the existing lighting system has not yet formed a clear relationship between spatial hierarchy, behavioral intensity, cultural recognition, and visual guidance.To respond to these deficiencies, the study proposes a four-level circle-layer lighting system guided by two core design concepts: sequence synergy and hierarchy matching. Sequence synergy, derived from spatial continuity theory, emphasizes the construction of a continuous lighting sequence through the coordinated organization of buildings, roads, squares, landscape nodes, and pedestrian routes. In this framework, the road system is regarded as the linear skeleton that connects different spatial layers and supports visual continuity, wayfinding, and nighttime safety. Hierarchy matching, derived from circle-layer theory, emphasizes the establishment of differentiated lighting levels corresponding to functional attributes, spatial roles, and nighttime activity intensity. Rather than defining the campus core according to geometric centrality, this study identifies the lighting hierarchy on the basis of spatial use, pedestrian concentration, and behavioral characteristics. Accordingly, the sports field and surrounding gathering spaces are defined as the first layer, historical and cultural building areas as the second layer, teaching and research areas as the third layer, and living-service areas as the fourth layer.On this basis, a differentiated gradient control strategy is developed. For buildings, structures, entrance signs, sculptures, and other vertical interfaces, fa?ade luminance is designed to decrease progressively from the core to the periphery: no less than 8 cd/m2 in the first layer, 3-5 cd/m2 in the second layer, 2-3 cd/m2 in the third layer, and 0.5-1 cd/m2 in the fourth layer. Horizontal spaces such as sports venues, gathering squares, and roads are excluded from this fa?ade luminance controlsystem and should instead comply with the corresponding illuminance standards for functional activities and traffic safety. In terms of color temperature, the proposed strategy establishes a gradual transition from high arousal to high comfort. The first layer adopts neutral to slightly cool light of 4 000-4 500 K to enhance visual clarity, spatial recognition, and safety in high-density activity areas. The second layer uses 3 000 K warm-white light to reveal the texture of redbrick fa?ades and strengthen the historical atmosphere of the campus. The third layer adopts 4 000 K neutral warm-white light to support teaching, research, and road safety while maintaining a stable visual environment. The fourth layer uses warm yellow light of 2 700-3 000 K to reduce nighttime visual stimulation and create a quiet, comfortable, and low-interference residential atmosphere.The lighting method is also organized as a progressive spatial sequence. In the first layer, high-pole or medium-pole luminaires are used to provide broad lighting coverage for large-scale spaces, while concealed floodlights and buried luminaires highlight important nodes and reinforce the main visual axis. In the second layer, small-angle linear grazing, wall washing, and soft floodlighting are applied to emphasize material texture and establish cultural visual anchors. In the third layer, cut-off road luminaires, landscape lights, courtyard lights, and controlled interior light are combined to maintain basic visibility and spatial transition. In the fourth layer, low-position luminaires, shielded fixtures, grass lights, and concealed footlights are used to restrict light below the eye line, reduce spill light, and protect the residential environment from excessive visual disturbance. The results indicate that the proposed strategy can effectively address the lighting planning difficulties of old university campuses caused by complex spatial structures, mixed functional demands, and fragmented lighting facilities. By coordinating luminance hierarchy, color-temperature rhythm, lighting methods, and road-based spatial continuity, the strategy improves the visual connection between core and peripheral areas, enhances the nighttime recognition of key buildings, reduces visual discontinuity, and supports safer pedestrian movement. More importantly, the study demonstrates that the integration of spatial continuity theory and circle-layer theory can transform campus lighting planning from the isolated application of technical indicators into a systematic spatial design process that simultaneously considers safety, function, cultural expression, visual order, and environmental comfort. The proposed circle-layer boundaries and lighting parameters are not fixed templates, but can be recalibrated according to the functional layout, historical context, pedestrian behavior, and nighttime use characteristics of different campuses. Therefore, this research provides a theoretical framework and practical references for the stock renewal of outdoor lighting in comparable old university campuses.

Abstract:Under the background of healthy cities and stock renewal, functional lighting plays an important role in ensuring nighttime outdoor activities, promoting mood and health. Therefore, it is necessary to explore the examination works and systematically sort out the evaluation methods of functional lighting. At present, the evaluation of functional lighting at the medium and macro scales is mostly based on summarizing micro node conclusions, which is difficult to fully connect with the spatial layout, business distribution, public behavior needs, and potential of urban lighting. Compared to complex urban environments (including multiple influencing variables), university campus, due to its highly introverted and autonomous characteristics, could provide a relatively ideal and simplified environment for the refinement of functional lighting evaluation methods, which could facilitate more efficient discussions on optimizing evaluation methods and provide support for subsequent research on functional lighting evaluation in complex urban environments.This study uses multi-source data methods to evaluate roads and open spaces in campus by obtaining users’ cognition of the nighttime environment through online questionnaires, creating a cognitive map based on campus night perception through subjective evaluation and on-site interviews, measuring the minimum illuminance and illuminance uniformity using a Konica Minolta T-10 illuminance meter to quantitatively evaluate the campus functional lighting by comparing it with industry standards. And Perform Kernel density analysis using Points of Interest (POI) were used to identify potential heat zones in campuses under different POI types, then campus hot zone identification and verification were completed through drone (Dji air3) imaging. Conclusions received are as follows. On an overall level, the campus functional lighting is insufficient and difficult to meet the needs of daily outdoor activities. At the level of management and maintenance, there are widespread problems such as roads without lights, lights not turning on, and light source attenuation, corresponding maintenance work should be optimized. At the level of behavioral characteristics, a. the dormitory area is an important factor affecting evening vitality, and there is an urgent need to improve the activity path and venue lighting centered on the dormitory area in the future; b. The student prefer open spaces with better lighting quality, and attention should be paid to the improvement of functional lighting in such places. At the level of venue potential, a. Numerous open spaces on campus have (varying degrees of) nighttime activity potential, but the current low-quality lighting has had a negative impact on this. Improving lighting quality to promote campus nighttime public life is an important aspect of future work; b. The insufficient functional lighting has led to the longterm vacancy of open spaces and the neglect of such spaces during maintenance, resulting in significant waste of public spaces in terms of site utilization and cultural promotion, which should be given attention from both management and maintenance aspects. Regarding research methods　Comparing traditional methods (questionnaire + cognitive map + indicator measurement) with optimization methods (POI + drone). In terms of basic problem analysis, both methods are applicable. The weak points in lighting obtained by traditional methods can be effectively identified through optimization methods, indicating the feasibility of identifying micro objects or features through optimization methods, which can more efficiently complete the research and analysis of medium and large-scale objects. In terms of the correlation between campus business formats and nighttime vitality, the advantage of traditional methods lies in their ability to effectively identify detailed differences between different regions, while optimization methods can establish spatial connections between regions (such as paths, scales, etc.),which is of great significance in subsequent mid and macro level researches. In the evaluation of micro objects, traditional methods can intuitively obtain the lighting changes inside the field and the perceptual changes caused by them, which has advantages in micro research. Optimization methods are better at discovering the distribution of similar problems within the scope and drawing common conclusions. This indicates that both methods are effective in determining basic problems, typical objects, etc. However, in terms of spatial layout, path connections, and common problem sorting, the optimization method can significantly improve work efficiency by leveraging its scale advantage to draw systematic conclusions simultaneously. In future similar evaluation work, by combining the two, a multi-source data evaluation method that takes into account both macro and micro needs will be formed, which will provide effective support for the development of lighting evaluation work.

Abstract:With advancing research on human settlements, nighttime light environment assessment is transitioning from regulation-driven to quality-oriented approaches. This study innovatively integrates multidimensional evaluation methods, including night sky observation, ground-based measurements, and human perception, to conduct a comparative analysis of nighttime light environments across multiple parameters and spatial scales. The research focuses on China’s first international dark sky community and a typical urban residential area.The research methodology primarily focuses on three aspects: sky observation (including the night sky layer and canopy layer), ground-based measurements, and public perception. First, the hierarchical structure of urban nighttime light environments is preliminarily divided into three layers: the urban night sky layer, the urban canopy layer, and the urban surface layer. In the sky observation component, emphasis is placed on the night sky layer and the canopy layer. For the night sky layer, observations are conducted using a digital camera equipped with a fisheye lens to capture full-sky data, with brightness conversion performed using the SM system and DiCaLum software. For the canopy layer, vertical visualization analysis is employed, and observations are divided into four phases in a time-series approach: daylight illumination, daylight-to-artificial lighting transition, artificial lighting, and stable artificial lighting. A long-focal-length LMK imaging luminance meter, tripod, and laptop-based full-sky observation system are used to photograph and extract data from the nighttime light environment, generating luminance distribution maps to reveal the regular variations in the overall urban canopy light environment. Second, ground-based light environments are measured using instruments such as SQM, CL-500, and luminance meters. Metrics include illuminance (ground-level horizontal illuminance, 1.5-meter-height horizontal illuminance, and ambient illuminance), uniformity, color temperature, color rendering index, glare level, spectrum, and LoNNe index. Measurements are taken by grid division (approximately 50 m) based on residential layouts and road scales, while avoiding direct light interference from luminaires. Finally, perceptual evaluation of the light environment is conducted, comprising questionnaire surveys and objective environmental quantification. The questionnaire survey covers diverse age groups, genders, and educational backgrounds to ensure result objectivity. Perceptual evaluations (safety, comfort, and brightness perception) employ a four-point Likert scale (0-3 points). Objective environmental quantification (vegetation coverage, traffic volume, and spatial scale) uses a 0-2-point scale. Key findings include: 1）Urban residential areas exhibit severe uplighting, leading to higher night sky brightness, whereas the dark sky community shows lower brightness due to its mountainous terrain effectively blocking light pollution from the city center, demonstrating the efficacy of dark sky reserve construction. The temporal trends of canopy nighttime brightness in both areas are broadly consistent: under natural lighting, the night sky and canopy layers exhibit high and stable brightness, while the surface layer remains dim due to inactive artificial lighting; during transitional lighting, brightness in the night sky and canopy layers gradually decreases, with fluctuations in the surface layer; in the artificial lighting phase, surface layer brightness variability increases, while the night sky and canopy layers stabilize below 0.1 cd/m2. 2) Significant differences exist between the dark sky community and Dalian Wanda Huafuin ground illuminance, 1.5 m height illuminance, and uniformity: the dark sky community has lower illuminance but comparable safety and comfort ratings, along with superior energy efficiency. Its billboard color temperature averages below 3000 K, with brightness ~100 cd/m2 —far lower than Dalian’s urban average. Despite similar perceived brightness, the dark sky community’s spectrum promotes plant photosynthesis more effectively, whereas Wanda Huafu’s light sources have higher blue light proportions, potentially affecting melatonin secretion. 3) Nighttime activity frequency is higher in Shenzhen’s dark sky community than in Wanda Huafu. Safety and comfort in Wanda Huafu are primarily influenced by illuminance, vegetation density, and traffic volume, whereas the dark sky community is more affected by illuminance, LoNNe indices, and spatial scale. A perception model based on empirical data further confirms that ground horizontal illuminance positively impacts light environment evaluations in both areas, while Wanda Huafu’s vegetation coverage and the dark sky community’s spatial scale exhibit negative effects.

Abstract:Against the backdrop of increasingly severe population aging, which presents profound challenges to socioeconomic systems globally, the issue of uneven distribution of elderly care service resources has become critically prominent, particularly in rapidly urbanizing contexts. Conducting an indepth, multidimensional investigation into the configuration rationality of elderly care facilities and the spatial equity of their layout is therefore of paramount importance for effectively safeguarding the fundamental needs of the growing elderly demographic and actively promoting the equitable allocation of finite social public resources.This research is grounded in a comprehensive analysis of 2,057 institutional and community-based home care facilities located within Suzhou, establishing equity and efficiency as the foundational dual pillars of its analytical framework. The investigation leverages the advanced computational and spatial visualization capabilities of Geographic Information Systems (GIS) to conduct a systematic quantification and sophisticated graphical representation of equity manifested in the geographical distribution of these facilities. To ensure a multi-faceted assessment, the evaluation is strategically organized around three pivotal dimensions: the quantitative and qualitative availability of service resources, the geographical accessibility for the elderly population, and the spatial efficiency of service coverage. Methodologically, the research integrates established spatial statistical tools, including the Gini coefficient, a classical measure of inequality, and the more granular Two-Step Floating Catchment Area (2SFCA) method, which calculates service provider-to-population ratios within defined service areas.To further identify the key factors influencing the equity of elderly care facility layout, a structured analytical framework comprising 14 carefully selected indicators was constructed. This framework incorporated both socioeconomic data (such as per capita GDP, average housing prices, and per capita disposable income) and built-environment data (including land use mix, density of medical facilities, and spatial centrality of commercial areas). Subsequently, analytical tools including the Geodetector and the Geographically Weighted Regression (GWR) model were applied to investigate the causes of spatial differentiation in the equity of elderly care facility distribution. The Geodetector was employed to assess the explanatory power of various influencing factors on the spatial variation of layout equity, while the GWR model, which accounts for spatial heterogeneity, facilitated the analysis of how the effects of these factors vary across different geographical regions. The study results reveal three principal findings. First, the overall Gini coefficient of 0.369 7 for the distribution of elderly care facility resources relative to the elderly population in Suzhou indicates a relatively equitable allocation, although significant disparities persist in certain areas. Accessibility to facilities remains comparatively poor in northern river-adjacent regions and southern Wujiang District. While facility coverage in Suzhou’s urban core is generally high, severe service area overlaps are observed in several sub-districts, reflecting inefficient resource distribution. Second, per capita GDP demonstrates a positive correlation with all three evaluated dimensions: service resources, accessibility, and coverage. Conversely, population density exerts a negative influence on the equity of service resource distribution and accessibility. Third,Geographically Weighted Regression (GWR) results confirm that six indicators—per capita GDP, population density, road network density, medical facility density, bus stop density, and land use mix—exhibit spatial heterogeneity in their effects on layout equity. These factors demonstrate bidirectional influences on comprehensive equity, with varying impacts across different geographical contexts. The findings generated by this study possess significant practical applicability as well as substantive theoretical value. From a practical standpoint, the results offer scientifically rigorous references and evidence-based guidance for optimizing the spatial arrangement of elderly care facilities and for informing the development of future-oriented elderly care planning strategies in Suzhou. By identifying specific gaps and inefficiencies in resource distribution, the research empowers decision-makers to implement targeted interventions, thereby enhancing the overall fairness, equity, and operational efficiency of the city’s elderly care service system. On a theoretical level, the well-defined research framework and the comprehensive analytical methodology employed—which systematically integrates GIS technology with a suite of advanced quantitative tools, including the Gini coefficient, the Two-Step Floating Catchment Area (2SFCA) method, the Geodetector, and the Geographically Weighted Regression (GWR) model—provide innovative perspectives and robust methodological benchmarks for conducting equity analyses of other geographical phenomena and spatial distributions. This approach offers fresh conceptual ideas and applicable procedural models for investigating the fairness inherent in the allocation of various public facilities, such as schools, hospitals, and other essential services, thereby significantly enriching the application scope and analytical power of spatial analysis methodologies within the broader field of public service resource allocation research.

Abstract:In the context of the “Healthy China” strategy driving high-quality development in the construction sector, the evaluation of health-oriented sports facilities has become a benchmark for assessing the quality of sports architecture. However, most existing evaluation systems primarily focus on the physical performance of buildings, with homogenized weighting schemes that fail to satisfy the multifaceted requirements of the public-service nature of sports architecture and the differentiated concerns of multiple user groups. Consequently, these systems are insufficient in addressing user concerns and diverse needs across different population groups. Compared with other building types, sports buildings serve multiple scenarios such as sports events, daily training, public fitness, and spectator activities. Their spatial functions are highly composite, and their user composition is relatively complex. Different user groups differ significantly in spatial use patterns, behavioral characteristics, and health concerns. Among them, sportsmen are more concerned with factors directly related to sports performance and safety, such as field conditions, sports equipment, technical support, and thermal comfort. Audiences pay more attention to the comfort and convenience of the viewing process, including sightlines, acoustic conditions, circulation organization, and seating experience. Such differences directly affect the perceived importance of evaluation indicators. Therefore, how to identify and respond to group differences has become a key issue in healthy sports building evaluation, as well as an important premise for improving the scientific rigor of weight assignment. To address this issue, this study conducts a user demand survey based on the Kano model and the Analytic Hierarchy Process (AHP). By examining the perspectives of both audiences and sportsmen, this study addresses the complex challenge of assigning evaluation weights in health-oriented sports facilities and introduces a differentiated weighting approach for evaluation indicators. Specifically, an evaluation indicator system for healthy sports buildings is established, including five first-level indicators and fifteen second-level indicators. On this basis, the AHP method is used to determine the initial weights of the indicators through expert consultation, pairwise comparison, and consistency testing, with the participation of 36 experts related to sports building design and research. In this process, AHP provides a relatively stable expert-based weighting structure, ensuring the disciplinary logic and professional rationality of the evaluation system. Meanwhile, the Kano model further captures users’ differentiated demand attributes and makes it possible to incorporate group preference into the weighting process, thereby improving the realism and applicability of evaluation results in multi-user contexts. The combination of the two methods allows the weighting system to reflect both expert judgment and user perception, rather than relying solely on a universal technical framework. Then, the Kano model is introduced to identify the differentiated demand preferences of audiences and sportsmen. 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In this way, the original homogeneous weighting system is transformed into a more targeted weighting framework that can respond to the actual needs of different users. The results show that there are clear differences between audiences and sportsmen in the final weights of healthy sports building evaluation indicators. For audiences, indicators related to the viewing process and spectator experience show higher importance after optimization, such as spectator sightline, close-range viewing, and reverberation and speech clarity. For sportsmen, indicators such as thermal and humidity environment, wind environment, field area, sports equipment, and sports craftsmanship are given higher importance, while some audience-oriented indicators are identified as indifferent demands and removed from the final weighting results. The comparison indicates that the two groups present different concern priorities and value orientations in healthy sports building evaluation. These findings also suggest that the evaluation of healthy sports buildings should not be regarded merely as a technical assessment of building performance, but as a comprehensive process that responds to differentiated use scenarios and health e

Abstract:To study the impact of urban park landscape spatial design structure on human thermal comfort in urban parks, this paper conducts both subjective and objective surveys of the thermal perception of heterogeneous landscape spaces in Haizhu Wetland Park, a city park located in the highdensity central urban area of a megacity, during the summer. The study uses a thermal sensation walking survey experiment. Fourteen participants and three experimental staff members, each carrying sensor devices, walked along a pre-designed route with 10 survey points set along the route for collecting both subjective and objective data. The experimental backpacks of the three participants were innovatively equipped with three types of integrated devices that can monitor multiple meteorological factors, becoming a mobile meteorological monitoring tool serving both the route and survey points. The survey points were categorized based on pavement material, vegetation type, shading conditions, and proximity to water, maximizing the diversity and typicality of the urban park landscape environment. The study considers the objective thermal comfort evaluation indicator Physiologically Equivalent Temperature (PET) and uses the experimental participants’ simultaneous thermal sensation voting (TSV) as a subjective evaluation standard. The research investigates the correlation and impact of both indices with landscape spatial elements within a certain range of the park. The park landscape elements are divided into three categories: herbaceous plants, shrubs, and trees, with indices such as vegetation coverage, canopy density, trunk diameter, tree height, and shading ratio. Other indicators include road material proportion, road width, ground reflectivity, proximity to water, and water area proportion. Through synchronized investigation experiments of these landscape elements, the study analyzes the independent variables related to both subjective and objective thermal comfort evaluations. The results show that there are microclimatic differences in thermal environments between different wetland landscape spaces. The key meteorological factors influencing thermal comfort in Haizhu Wetland Park’s summer landscape space are average radiant temperature, black globe temperature, and wind speed at noon. Specifically, within the landscape spaces, the proximity to water and paving elements have a significant impact on thermal comfort in the morning, while tree shading has the most significant impact at noon. In the evening, proximity to water has a notable effect on thermal comfort. Additionally, microclimate variations dominate the heterogeneous landscape space's thermal comfort differences. At noon, there are clear differences in thermal sensation between plaza and forested areas, as well as between natural and artificial shading. The proximity to water and the permeability of pavement structures also have significant differences in their effect on thermal comfort in the morning and evening. The study further finds that intermittent shading design along pathways may lead to discrepancies between subjective and objective thermalcomfort evaluations.The main conclusions are as follows　1) the spatial distribution of subjective and objective thermal sensation was higher and fluctuated greatly at noon, and was significantly improved in both artificial and natural shade Spaces; 2) square/understory space, shady/artificially shaded space had significant differences in TSV (Subjective thermal comfort), and adjacent/non-adjacent water space had significant differences in objective thermal sensation PET (Objective thermal comfort); 3) ranking of subjective and objective thermal sensation of various factors in landscape space from low to high: tree shading＜Artificial constructed pavilion＜Vine trellises provide shade; Herbaceous low space ＜ Arbor open space＜Shrub open space; 4) tree coverage, tree height and ground reflectance contributed the most negatively to subjective and objective thermal sensation TSV and PET.

Abstract:The hierarchical allocation and spatial organization of medical resources in metropolitan regions have emerged as critical challenges for regional integration, particularly in addressing the disparities between administrative boundaries and actual healthcare-seeking patterns. This study employs an innovative methodology integrating mobile phone signaling data with hospital service hierarchy analysis to investigate cross-boundary medical travel within the Wuhan Metropolitan Area (WMA). Through systematic classification of 505 medical institutions into four tiers based on service coverage (provinciallevel: 2; metropolitan-level: 13; municipal-level: 198; county-level: 292), combined with analysis of 943, 872 cross-city medical trips in 2020, the research reveals fundamental characteristics of inter-jurisdictional healthcare mobility. Hospital service hierarchy analysis demonstrates significant spatial disparities in resource distribution. Provincial-level hospitals (Tongji Hospital and Union Hospital affiliated with Huazhong University of Science and Technology) serve 80% of townships but account for only 3.12% of total service capacity, with 22% of their patients originating from outside Wuhan. Municipal-level hospitals show uneven distribution, concentrated in Wuhan (133 of 198), while Xianning possesses only 2 such facilities despite its demographic significance. County-level institutions, though numerically dominant (292), handle merely 26.24% of total demand, with 96% of townships generating less than 0.1% demand for these facilities. Cross-city medical flows exhibit distinct spatial patterns. Wuhan dominates as the primary destination, receiving 42.04% of total cross-city trips, particularly from Ezhou (25.23% of Ezhou's outflow) and Xiaogan. Ezhou demonstrates the highest cross-city medical dependency (41.2% outflow rate), predominantly directed to Huanggang, Huangshi, and Wuhan. Conversely, Xianning’ limited municipal-level hospital resources correlate with substantial centripetal flows to Wuhan (89.9% of Xianning’s total outflow). The “Wuhan-Ezhou-Huanggang-Huangshi” corridor accounts for 63.7% of total metropolitan-level medical interactions, confirming core-periphery dynamics in healthcare accessibility. Transportation mode analysis reveals road dominance (90% of trips), with peripheral townships showing higher road dependency (355 townships >95% road usage). Rail transportation proves marginal (maximum 53% in 25 townships), concentrated along Wuhan-Xiaogan (10.2% rail share) and Wuhan-Ezhou-Huangshi corridors (8.7%), while other rail-connected corridors like Wuhan-Tianmen-Qianjiang show minimal medical utilization (2.1%). Spatial disparities in travel metrics emerge starkly: urban core townships average 20km/30min trips versus peripheral areas exceeding 100km/120min, with 26 edge townships enduring >60km journeys. Geographically Weighted Regression (GWR) analysis uncovers multi-scale influencing mechanisms. The model for total cross-regional medical trips achieves high explanatory power (R2 =0.92), identifying significant negative correlations with population density (β =-1.7487) and distance to municipal centers (β=-0.1696). This confirms that sparsely populated areas distant from urban cores generate higher cross-boundary demand. Travel duration analysis (R2 =0.72) demonstrates positive associations with distances to municipal (β=0.1885) and county centers (β=0.4314), revealing compounded accessibility challenges for rural populations. Contrary to expectations, transportation infrastructure metrics (rail station proximity, trunk road density) show insignificant impacts on travel time. The study identifies three critical mismatches: 1) Spatial concentration of high-tier hospitals in Wuhan createsimbalanced demand pressures, with provincial-level facilities absorbing 22% non-local patients; 2) Administrative boundary proximity intensifies cross-city flows, as 317 border townships exhibit >90% municipal-level hospital dependency; 3) Transportation infrastructure development fails to alleviate rural accessibility gaps, evidenced by persistent long-duration trips in 26 peripheral townships despite rail availability. Methodological limitations stem from data constraints, the absence of individual socioeconomic attributes restricts analysis of hospital selection mechanisms, while service capacity metrics lack clinical outcome dimensions. Future research should integrate electronic medical records with mobility data to capture decision-making processes and service quality influences. These findings necessitate strategic interventions: strengthening municipal-level hospital capabilities in underserved regions like Xianning; optimizing referral networks along high-flow corridors; and implementing targeted transportation-medical integration in peripheral zones with travel durations exceeding 60 minutes. The research demonstrates that metropolitan medical integration requires transcending administrative divisions through evidence-based resource allocation aligned with actual patient mobility patterns, providing a replicable framework for regional healthcare planning in developing contexts.

Abstract:The construction of high-quality urban communities holds significant innovative importance for the urbanization process aligned with China’s modernization goals. Among the core dimensions of such development, the integration of economic, social, and environmental factors is essential. Traditional community renewal studies often treat these dimensions in isolation, lacking a systematic understanding of their dynamic synergy. This study addresses this gap by proposing a multidimensional collaborative framework based on the High-quality System Integration Model (HSIM). The framework follows a three-stage structure— “element identification, measurement analysis, and technical evaluation”—to achieve the dynamic coordination of economic, social, environmental, spatial, and technological dimensions in urban community renewal. Theoretically, this study advances the existing literature by providing a global collaborative framework that integrates five core dimensions: engineering construction, ecological environment, spatial function, socio-economy, and energy low-carbon. It moves beyond static indicator systems by incorporating dynamic weighting mechanisms and empirically examining how technological optimization drives structural shifts in dimension priorities. Methodologically, the study employs factor analysis and dynamic weighting based on panel data from the Binhai New Area in Tianjin. A total of 20 secondary indicators were selected across the five dimensions, following international standards such as the Dow Jones Sustainability Index (DJSI) and ESG frameworks, as well as domestic guidelines. Data were collected from multiple sources, including planning documents, statistical yearbooks, and spatial analyses using Python-based data extraction and spatial syntax methods. Empirical analysis was conducted across ten functional zones in the Binhai community, including residential areas, eco-parks, cultural tourism zones, industrial parks, and central business districts. The KMO measure (0.521) and Bartlett’s test of sphericity (p < 0.001) confirmed the suitability of the data for factor analysis. The first five principal components accounted for 97.487% of the total variance, leading to the identification of five key technical factors: engineering construction, ecological environment, spatial function, socio-economy, and energy low-carbon. Factor scores were calculated for each functional zone, revealing significant variation in performance across dimensions.The findings reveal several key insights. Firstly, the study demonstrates that under controlled development intensity, dynamic optimization of factor measurements leads to a 19.6% improvement in the comprehensive performance of the planning scheme. Notably, the contribution weights of the engineering construction and ecological environment dimensions increased by 21.3% and 18.7%, respectively, indicating a structural shift from growth-oriented to quality-oriented renewal logic. Second, key performance indicators showed substantial improvements: regional carbon emission intensity decreased by 23.8%, while average public service accessibility increasedby 31.5%. These results validate the effectiveness of the HSIM framework in enabling measurable and comparable outcomes. Third, the factor score rankings across functional zones reveal differentiated synergy pathways. For instance, the Blue Economic Core Area ranked highest in comprehensive performance (score: 1.203), excelling in engineering construction and socio-economic factors, while the China-Singapore Eco-Demonstration Base performed best in ecological environment and low-carbon energy factors. In contrast, areas such as the Tanggu Leisure Experience Zone exhibited low scores across all dimensions, highlighting the need for targeted interventions rather than one-size-fits-all strategies. The study makes several theoretical and practical contributions. Theoretically, it advances urban renewal research from a static, dimension-listing approach to a dynamic “synergy dynamics” paradigm. By quantifying the shifting weights of dimensions under technological optimization, the study provides an empirically grounded model of systemic transformation in high-quality community development. Practically, the HSIM framework offers a replicable decision-support tool for planners. It enables the diagnosis of synergy bottlenecks, the prioritization of dimension-specific interventions, and the simulation of performance outcomes under alternative design scenarios. In the Binhai case, the final optimized planning scheme achieved a 23.8% reduction in carbon intensity and a 31.5% increase in service accessibility, demonstrating the operational value of the framework.In conclusion, this study confirms that multidimensional synergy in urban community renewal is not a static configuration but a dynamic process driven by technological optimization. The HSIM framework provides both a theoretical lens and a practical methodology for understanding and guiding this process. Future research may extend the model to diverse geographic and institutional contexts, integrate it with urban information modeling (CIM) and national spatial planning systems, and explore its potential for real-time simulation and adaptive governance in smart city development.

Abstract:The persistent shortcomings of conventional residential design, rooted in the static partitioning of space into predetermined “functional rooms”, underscore an urgent need for a paradigm shift toward more adaptive and behaviorally responsive architectural solutions. This study addresses this challenge by proposing a fundamental reorientation in spatial organization: from static, function-based zoning to dynamic clustering derived from the correlations between micro-user behaviors. The primary objective is to enhance both the precision of spatial division and the dynamic adaptability of residential layouts through a novel, quantitative design methodology. To achieve this, the research integrates the Design Structure Matrix (DSM) and the Fuzzy C-Means (FCM) clustering algorithm, constructing a scientifically rigorous framework to translate behavioral patterns into optimal spatial modules.Current research in residential spatial organization follows two predominant paths, each with significant limitations. First, a component-based path, focuses on the standardization of physical elements like furniture and building components. While it provides a clear, hierarchical system for spatial decomposition and addresses “how to construct precisely”, it inherently treats space as an assembly of static objects, failing to respond to the dynamics of user behavior and needs. Consequently, it cannot answer “why this organization is optimal”. Second, a behavior-based path, seeks to establish spatial modules by analyzing behavioral units and their spatiotemporal patterns. However, this approach has largely remained qualitative or conceptual, constrained by limitations in behavior data acquisition and the lack of a quantitative, computable model to effectively convert behavioral insights into spatial design. This gap often forces designers to revert to empirical “functional bubble diagrams” without genuine scientific generation capabilities. Fundamentally, the prevailing paradigm remains one of “naming rooms for functions” rather than “organizing space for behaviors”. To bridge this critical gap, this study develops and applies an integrated analytical model combining DSM and FCM. The process begins with the deconstruction of traditional functional rooms into a fine-grained spectrum of micro-behaviors. A comprehensive database of residential behaviors is constructed, alongside a four-dimensional spatial correlation index model that quantifies the relationships between these behavioral spaces. The DSM is employed to systematically map and structure these correlations. Subsequently, the FCM clustering algorithm processes this quantitative dataset, grouping the subdivided behavioral spaces into modules based on the strength of their interconnections. The clustering is optimized to identify the scheme with the highest modularity, ensuring that the resulting groupings exhibit strong internal cohesion and clear external boundaries. Applied specifically to residential indoor space design, the method decomposes activities into 35 distinct micro-behavioral types. Through the computational clustering process, these are synthesized into 15 optimized general behavioral space modules (e. g., modules integrating closely linked behaviors that might traditionally be separated across a “kitchen”, “dining”, and “storage” room). A comparative evaluation between these newly generated modules and traditional functional zoning reveals the clear superiority of the behavior-correlation strategy. The new modules demonstrate significant advantages across multiple quantitative metrics: enhanced modularity (indicating betterinternal coherence), greater typological diversity, improved combinability for flexible layout generation, and a more rational hierarchical structure. This evidence effectively verifies that a clustering strategy driven by behavioral correlations yields a spatial organization system with inherently better design properties than one based on a priori functional labels.The core contribution of this research is the proposal, development, and validation of the “behaviorcorrelation clustering” method as a scientifically robust alternative to traditional functional zoning. By shifting the foundational unit of design from the room to the behavior pattern, the study provides a quantifiable and reusable technical support system for modular architectural design practice. It advances spatial organization theory by introducing a model that clarifies behavior types, quantifies spatial precision, and scientifically manages correlations. The constructed hierarchical structure of behavioral space offers a practical reference framework for architectural design, one that can be applied to modular product design and continuously refined with dynamic market or user data.Finally, this study establishes a generalizable model for behavioral space analysis. Future research will focus on the empirical validation of design quality improvements through application in typical residential units, assessing outcomes in spatial efficiency, behavior-flow fit, and user adaptability. Furthermore, the model’s flexibility allows for the integration of survey data from specific user groups as new parameters, enabling highly customized spatial design and significantly expanding the methodology’s applicability. This pathway promises to transform residential space design from a practice of static compartmentalization into a responsive, user-centered, and scientifically-informed process.

Abstract:Urban villages (chengzhongcun) constitute a unique distinctive spatial phenomenon produced during China’s rapid urbanization. These settlements formed through the expansion of urban built-up areas into collectively owned rural land, reveal a complex interaction between land systems, migration flows, and urban development pressures. For a long time, urban villages served as crucial spaces for accommodating immigrant populations and supporting urban economic growth. Simultaneously, they have become focal points of urban governance and redevelopment policies. As China's urban development gradually shifted from large-scale expansion to stock-oriented urban renewal, urban village transformation has become a key issue in both academic research and planning practice. In this context, it is necessary to systematically review the development of urban village research, clarify the evolution of academic understanding, and understand how the research agenda responds to policy and social changes. This study aims to examine the historical trajectory and cognitive shifts in Chinese urban village research. By reviewing academic literature published between 2002 and 2025, this paper analyzes the evolution of research themes, theoretical perspectives, and methodological approaches in this field. Its goal is to reveal the dynamic process by which urban village research has shifted from descriptive observation to more systematic theoretical exploration, while identifying the key drivers shaping this shift.Methodologically, this study combines bibliometric analysis with qualitative literature interpretation. Datasets of academic publications on urban villages from major Chinese academic databases were collected and screened. Quantitative bibliometric techniques were employed to examine publication trends, keyword co-occurrence, institutional distribution, and research networks. These analyses revealed the temporal evolution of research hotspots and the structural characteristics of academic communities involved in urban village research. Based on this, qualitative thematic analysis was conducted to explain the conceptual development and theoretical orientation of the literature. By integrating quantitative mapping and qualitative synthesis, this study reconstructed the historical process of urban village research and identified major shifts in academic focus.The results show that urban village research has undergone a gradual transition from early phenomenological description to more comprehensive theoretical construction. Initial research focused primarily on identifying and describing the spatial and institutional characteristics of urban villages. With the strengthening of redevelopment policies and urban governance reforms, research focus gradually expanded to issues such as land policy, redevelopment strategies, spatial restructuring, and community governance. Over time, an interdisciplinary perspective has become increasingly prominent, integrating insights from urban planning, geography, sociology, economics, and governance studies. Recent research has further introduced new themes such as sustainable urban regeneration, digital technologies, and community engagement. A key finding of this study is that policy interventions have played a pivotal role inshaping the trajectory of research on urban villages. Major policy initiatives and redevelopment projects have repeatedly triggered shifts in research agendas, prompting scholars to move from descriptive narratives toward more systematic and interdisciplinary analyses. The interplay between policy practice and academic inquiry has significantly influenced the processes of knowledge production within this field. Based on a synthesis of literature trends, this study proposes an analytical framework that explains the development of urban village research through three interconnected dimensions: demand, mechanisms, and evolution. The demand dimension reflects the socioeconomic motivations driving the transformation of urban villages, including housing needs, the restructuring of land values, and the pressures of urban expansion. The mechanisms dimension highlights the interplay among policy instruments, economic forces, and spatial restructuring processes, which ultimately shape the outcomes of redevelopment efforts. The evolution dimension emphasizes the adaptive transformation of redevelopment strategies across various levels of governance and through the application of diverse planning instruments. Collectively, these dimensions provide a structured perspective for understanding the dynamic processes underlying the transformation of urban villages.This study contributes to the existing literature by elucidating the academic trajectory and research dynamics of urban villages in China. It underscores the role of policy-driven transformations in shaping academic inquiry and demonstrates the growing importance of interdisciplinary approaches in comprehending complex urban phenomena. From a broader perspective, these findings deepen our systemic understanding of urban villages within the context of China’s rapid urban transformation and serve as a reference point for future academic research. Furthermore, the insights derived from this review carry implications that extend beyond the Chinese context. Although urban villages are deeply rooted in China’s specific institutional framework, the issues they embody, such as informal housing provision, land governance, and community transformation, are widely observed in rapidly urbanizing regions across the globe. Consequently, the experiences of urban village transformation in China may contribute to broader international discussions regarding urban informality, governance innovation, and sustainable urban regeneration. By tracing the academic evolution of urban village research and synthesizing its theoretical developments, this study establishes a knowledge foundation for future research directions, policy formulation, and practical approaches to urban renewal.

Abstract:Urban basic education schools have long been a decisive factor in residential relocation, housing choice, and neighborhood differentiation among Chinese families. Since the 1990s, major Chinese cities have established School Districts (SDs) policies to allocate compulsory education opportunities according to residential location, thereby linking schooling rights, housing markets, and urban spatial governance. Although SDs were initially introduced to stabilize enrollment order, promote nearby schooling, and respond to the rising demand for basic education during rapid urbanization, they have increasingly become a key mechanism through which scarce high-quality education resources are spatially distributed and socially contested. In the context of inter-school competition, rising housing prices, demographic restructuring, and urban regeneration, SDs have generated socio-spatial consequences beyond the education system itself. They shape household mobility strategies, reinforce or mitigate residential segregation, affect housing capitalization, and influence urban life circles, community identity, and everyday access to public services. Therefore, SDs provide an important entry point for understanding how education resources participate in the production of urban spatial heterogeneity in contemporary China. This study systematically reviews the origin, evolution, institutional logic, and current research status of urban SDs in China. Drawing on literature from urban planning, geography, education policy, sociology, public administration, and real estate studies, it reconstructs the historical trajectory through which SDs shifted from an administrative enrollment arrangement to a spatial institution with significant distributive effects. The review first clarifies the policy background of SDs, including compulsory education, nearby admission, enrollment-boundary adjustment, and the relationship between school allocation and residential qualification. It then examines how SDs have been conceptualized in existing research, particularly as school catchment areas, education service zones, institutional boundaries, housing market signals, and socio-spatial units embedded in urban governance. On this basis, the study synthesizes major analytical themes, including education equity, access to high-quality schools, school-district housing premiums, residential sorting, class reproduction, neighborhood differentiation, and coordination between public service provision and spatial planning. Existing studies have made important contributions to revealing the economic and social impacts of SDs. They demonstrate that high-quality schools are capitalized into housing prices, giving rise to school-district housing markets and reinforcing the unequal capacity of families to access educational opportunities through residential choice. Other studies emphasize the role of policy design, enrollment rules, school reputation, parental expectations, and informal information networks in shaping the perceived value of SDs. Research also shows that SDs are not passive containers of school resources; rather, they reorganize urban space by influencing household location decisions, community composition, and the spatial distribution of educational advantage. Nevertheless, the literature remains fragmented in concepts, scales, methods, and theoretical explanations. Many studies focus either on housing price premiums or on education policy evaluation, while the generative mechanisms of SDs as socio-spatialinstitutions remain insufficiently examined. In particular, limited attention has been paid to how school quality, historical accumulation, policy adjustment, parental mobility, housing market dynamics, and neighborhood transformation jointly produce differentiated SDs. This review identifies three major gaps. Firstly, the formation mechanism of SDs should be examined beyond formal enrollment boundaries. SDs are generated through the interaction of school location, education resource allocation, administrative regulation, market valuation, and family strategies. Their social meanings and spatial effects are reconstructed through policy change, reputation circulation, housing transactions, and demographic mobility. Secondly, the socio-spatial effects of SDs should be analyzed across multiple scales. At the micro scale, SDs influence household relocation, housing purchase, commuting routines, and children’s daily activity spaces. At the neighborhood scale, they reshape community stratification, housing turnover, public service demand, and local social networks. At the urban scale, they contribute to uneven development, education-resource concentration, and spatial polarization. Thirdly, the relationship between SDs and urban regeneration remains underexplored. In many Chinese cities, older central neighborhoods may possess prestigious schools but constrained physical environments, whereas newly developed areas may have better built environments but weaker school reputations. These mismatches suggest that SDs should be understood through the changing relationship between educational resources, built environments, and redevelopment trajectories.Based on these findings, this study proposes future research directions. Future studies should move from static descriptions of school districts toward mechanism-oriented analysis of how education resources shape urban spatial differentiation. They should integrate quantitative spatial analysis, longitudinal housing transaction data, school quality indicators, demographic data, and qualitative evidence on parental perception and policy implementation. Greater attention should be paid to the distinction between actual school quality, socially perceived reputation, and spatially accessible educational opportunity, because these dimensions may diverge and produce different forms of socio-spatial mismatch. Moreover, SDs research should be connected with life-circle planning and public service evaluation. By incorporating school accessibility, daily mobility, neighborhood facilities, and residential affordability into an integrated framework, planners can better assess whether basic education resources are equitably embedded in everyday urban life. Overall, this study argues that SDs are not merely technical enrollment zones, but socio-spatial institutions that mediate the relationship between education, housing, family mobility, and urban transformation. It provides a conceptual foundation for rethinking the role of basic education schools in urban spatial production and offers planning implications for building more equitable, accessible, and integrated public service systems in contemporary Chinese cities.

Abstract:Urban forest garden residences, characterized by the incorporation of sky gardens within mid- to high-rise apartment buildings, play a pivotal role in advancing the concept of Quality Housing. These residences do not only facilitate a transition in housing paradigms, from merely providing a place to live to fostering a high-quality living environment, but also achieve synergistic benefits for both ecological sustainability and residential quality. Since the launch of the inaugural project in Chengdu in 2018, the development of such residences in mainland China has progressed from initial conceptual exploration to practical implementation, expanding from localized pilot initiatives to widespread to nationwide adoption. Currently, these residences have been established across all provincial-level administrative regions and have extended to some third- and fourth-tier cities and counties. Despite the issuance of the “Urban Forest Garden Residential Building Design Standard” by the China Association for Engineering Construction Standardization in 2021, many related projects do not comply with the standard’s requirements. Overall, the development of urban forest garden residences in mainland China confronts three principal challenges: the absence of comprehensive regulatory frameworks and inconsistent management standards; ambiguous delineation of responsibilities coupled with inadequately defined collaboration mechanisms; and insufficient integration of planning alongside homogeneous incentive measures. In contrast, since the 1990s, Singapore and Hong Kong have developed numerous garden residences equipped with sky gardens to address the dual challenges of high population density and land scarcity, and have accumulated extensive experience in the development and governance of such residences. Specifically, Singapore’s experience encompasses a government-led, multi-stakeholder cogovernance mechanism, stringent multi-level regulatory policies, and multi-dimensional flexible guidance measures. Hong Kong’s experience is characterized by a management mechanism involving collaboration between the government and industry associations, as well as comprehensive and refined regulatory policies. It is important to note, however, that garden residences in Singapore and Hong Kong are predominantly government-funded, whereas in mainland China, urban forest garden residences typically operate under a market-oriented model and are positioned as premium, upgradeoriented products. Furthermore, unlike garden residences in Singapore and Hong Kong, where gardens serve as public open spaces, urban forest garden residences in mainland China present greater challenges for supervision, as their gardens are located within private units. Consequently, there is an urgent need to develop more effective regulatory policies, collaborative mechanisms, and incentive measures. This study integrates the governance mechanisms and regulatory policies of garden residences in Singapore and Hong Kong with the exploratory efforts of mainland Chinese cities regarding accountability allocation and policy instruments, to propose a development governance framework specifically tailored to the institutional contexts of mainland China. Key recommendationsof this framework include refining regulations to incorporate detailed management requirements, strengthening collaboration mechanisms through clarified divisions of responsibility, and enhancing incentive measures to improve guidance effectiveness. Specifically, it is recommended that national-level regulations and policies be established to standardize the definition, technical standards, planning approval procedures, ownership registration and transfer protocols, and maintenance management responsibilities related to sky gardens. Local governments should develop regulatory and standard systems tailored to their specific conditions, emphasizing technical standards, such as spatial parameters, safety requirements, and greening configuration, and planning management aspects, including the clarification of calculation rules for floor area ratio, green space ratio, building spacing, and building density. Furthermore, it is advisable to incorporate these residences into the territorial spatial planning system, encompassing master plans, specialized plans, and detailed plans. Regarding collaboration mechanisms, it is recommended that these incorporate inter-ministerial coordination and engagement with local responsible institutions. This should include clear delineation of the comprehensive management procedures and the responsibilities of all involved entities, including municipal departments, property owners, and property service companies, throughout the entire process from planning approval to operation and maintenance. In terms of incentive measures, it is recommended that local governments develop differentiated incentive policy frameworks tailored to local realities, encompassing factors such as floor area ratio and floor area incentives, technical standards and design guidelines, market incentives and financial support, as well as demonstration projects and awards. Additionally, the exploration of a unified incentive system at regional and national levels is encouraged. Future research could advance from both technical and institutional perspectives. For example, studies might investigate technical systems for sky gardens across various climate zones, conduct quantitative evaluations of policy effectiveness, and examine improvements to the ownership system of sky gardens and supporting measures. Given that most garden residences in Singapore and Hong Kong are public housing, it is significant to further analyze these models to address current limitations regarding the target user group of urban forest garden residences and to promote the concept of inclusive housing. In conclusion, this study aims to provide a comprehensive reference for the holistic and detailed management of urban forest garden residences, encompassing all stages from development and construction to operation, maintenance, and supervision. Additionally, it seeks to contribute to the extant academic literature in this field.

Abstract:Low-carbon economy constitutes a critical pathway to achieving China’s dual carbon goals and a core driver of high-quality economic development, integrating environmental sustainability with long-term economic growth momentum. As a major energy province and a key national comprehensive energy security base, Shaanxi Province bears unshirkable political responsibilities for ensuring stable energy supply—its abundant fossil energy reserves and strategic geographical location make it an indispensable pillar of national energy security, while also imposing the arduous task of reconciling energy production with low-carbon transition. Based on panel data of 10 prefecture-level cities in Shaanxi from 2011 to 2022, this study constructs a comprehensive evaluation index system for low-carbon economic development, incorporating 33 basic indicators across six interconnected dimensions: energy structure, low-carbon industry, low-carbon innovation, low-carbon society, lowcarbon environment, and economic development. The entropy weight method is adopted for objective evaluation, as it quantifies indicator weights based on information entropy without subjective biases, ensuring the reliability of the low-carbon development level measurement. On this basis, three quantitative methods are employed to explore regional characteristics: the Dagum Gini coefficient and its decomposition method to identify sources of regional disparities; kernel density estimation to visualize the dynamic evolution of development level distributions; and two classic spatial convergence models to test long-term trends in regional disparity. Finally, the Quadratic Assignment Procedure (QAP) is utilized to examine the intrinsic mechanisms of regional differences, leveraging its advantage in addressing spatial dependence in cross-sectional data. The empirical findings are as follows　first, from 2011 to 2022, the low-carbon economic development level of Shaanxi Province as a whole, its three major regions, and all 10 prefecture-level cities exhibited a steady upward trend. This progress is attributed to the implementation of national low-carbon strategies, regional industrial structure optimization, and increased investment in energy conservation and environmental protection. Notably, however, unbalanced development persisted across regions and cities, stemming from disparities in resource endowments, industrial bases, technological capabilities, and policy implementation effects. Secondly, the overall regional disparity in Shaanxi’s low-carbon economic development showed a gradual expanding trend. Decomposition results of the Dagum Gini coefficient indicate that inter-regional disparity is the primary source of overall imbalance, as divergent development conditions and resource allocation across regions lead to heterogeneous growth trajectories. Among these, the gap between Guanzhong and Southern Shaanxi is particularly prominent, reflecting significant differences in economic foundation, technological innovation capacity, and industrial transformation speed between the two regions. Thirdly, regarding convergence characteristics: σ -convergence is absent in Shaanxi as a whole, Guanzhong, and Northern Shaanxi, meaning the relative gap in low-carbon development among cities in these regions did not narrowover time. In contrast, Southern Shaanxi exhibits significant σ-convergence, driven by coordinated development policies and ecological protection efforts that reduce intra-regional disparities. Furthermore, Shaanxi Province, Guanzhong, and Southern Shaanxi all demonstrate absolute β-convergence, indicating lagging cities have faster low-carbon development growth rates and the potential to catch up with leading cities over time. Guanzhong’s convergence speed is significantly faster than that of Southern Shaanxi, primarily due to its advantages in talent aggregation, technological spillover, and industrial agglomeration, which accelerate the diffusion of low-carbon technologies and models. Fourth, QAP analysis results reveal that except for low-carbon industry, development disparities in the other five dimensions exert a significant positive impact on low-carbon economic development gaps. Among these factors, low-carbon innovation has the strongest effect, underscoring that the uneven distribution of innovation resources is the key driver of regional disparities.

Abstract:Amid accelerating globalization and intensifying regional integration, national borders are increasingly less restrictive to the circulation of capital, labor, information, and other production factors. As these flows become more transnational and interjurisdictional, cross-border regions have gradually shifted from peripheral spaces at the margins of state territories to strategic frontiers for regional cooperation, economic coordination, and spatial reorganization. These regions function not merely as boundary zones but as arenas in which multiple institutional systems, governance arrangements, and development strategies intersect. Consequently, cross-border regions have attracted growing scholarly attention within debates on regional governance, state spatial restructuring, and multi-scalar institutional coordination.A similar transformation has been unfolding in China under the national strategy of coordinated regional development. Historically, administrative boundary areas within China were often regarded as marginal spaces characterized by fragmented governance structures and limited economic interaction. In recent decades, however, these boundary regions have increasingly been repositioned as platforms for promoting regional integration and collaborative development. Through infrastructure connectivity, industrial cooperation, and institutional coordination, these areas have begun to play a more active role in facilitating interjurisdictional collaboration. Despite these developments, systematic research on cross-border spatial governance in the Chinese context remains limited. Existing studies rarely examine the governance challenges generated by complex multi-scalar institutional arrangements, or the mechanisms by which these challenges are addressed through institutional experimentation and governance innovation. Against this background, this paper investigates cross-border spatial governance in the Guangdong-Hong Kong- Macao Greater Bay Area (GBA), one of the most dynamic and institutionally complex regional integration projects in contemporary China. The GBA is characterized not only by dense economic networks and rapid urbanization but also by the distinctive institutional framework of “One Country, Two Systems”, which generates diversity in legal systems, administrative arrangements, and policy regimes across the region. These characteristics make the GBA a valuable case for examining the dynamics of cross-border governance in contexts of institutional heterogeneity.The study focuses on several boundary regions within the GBA, including Guangzhou – Foshan, Shenzhen – Hong Kong, Zhuhai–Macao, and Shenzhen–Dongguan, as well as a series of cross-border cooperation platforms that have emerged in these areas over recent decades. From the perspective of scale restructuring, the paper seeks to understand how cross-border cooperation in the GBA has evolved since China's reform and opening-up and how governance mechanisms have adapted to the challenges of coordinating across administrative and institutional scales.Methodologically, the research adopts a qualitative case study approach that integrates policy document analysis with semi-structured interviews with keyactors involved in regional governance. National strategies, regional planning documents, and local development policies were reviewed to reconstruct the institutional evolution of cross-border cooperation in the GBA. In addition, interviews with policymakers, planners, and institutional stakeholders provide insights into the governance processes shaping cross-border collaboration. The analysis identifies a multi-stage evolution of cross-border cooperation in the Greater Bay Area since the late 1970s. Early stages were characterized primarily by pragmatic economic interactions driven by market forces and policy experimentation. Over time, cross-border collaboration gradually expanded into more institutionalized forms of cooperation, including planning coordination, infrastructure integration, and spatial policy alignment. Despite these advances, cross-border governance in the GBA continues to face challenges associated with multi-scalar institutional arrangements.The study identifies three scalar dilemmas that structure contemporary cross-border governance in the region. First, there are divergences in strategic development objectives across administrative levels and jurisdictions, which complicate the alignment of policy priorities. Second, governance scales are often asymmetrical, as participating jurisdictions differ in institutional authority, planning systems, and regulatory capacities. Third, effective cross-jurisdictional coordination mechanisms remain incomplete, leading to fragmented governance practices and institutional friction in the implementation of cross-border initiatives. In response to these challenges, governance innovations have gradually emerged within the GBA. Cross-border cooperation zones and pilot platforms have served as experimental spaces for testing new governance arrangements. Flexible planning approaches have been introduced to mediate mismatches between governance scales and facilitate coordination across administrative systems. Furthermore, multi-level institutional innovations have enabled new forms of collaboration that transcend traditional jurisdictional boundaries.By conceptualizing these dynamics through a scalar analytical lens, this paper contributes to the literature on cross-border regional governance and state spatial restructuring. It demonstrates how processes of scale restructuring generate governance tensions and opportunities for institutional experimentation in cross-border regions. Empirically, the findings provide insights into the evolving governance landscape of the GBA and illustrate how interactions between institutional diversity, scalar reconfiguration, and policy innovation shape cross-border spatial governance.More broadly, the study offers implications for advancing integrated regional development in China and other contexts characterized by institutional heterogeneity. The experience of the Greater Bay Area suggests that effective cross-border governance requires not only stronger institutional coordination across administrative boundaries but also adaptive governance mechanisms capable of navigating multi-scalar complexities. By highlighting these governance dynamics, the paper contributes theoretical insights and practical lessons for understanding and managing cross-border regional cooperation in an increasingly interconnected world.

Abstract:Coordinating the relationship between resource and environmental carrying capacity and economic development is a necessary measure for human beings to pursue sustainable development. With the rise of central Yunnan, the rapid development of northeast Yunnan, the opening development of Yunnan border and the comprehensive development of western Yunnan, the regional high-quality development spatial pattern has gradually formed. Around the coupling and coordination relationship between high-quality development and resource and environmental carrying capacity, Scientific measure the level of high quality development and the level of resource and environmental carrying capacity in Yunnan from 2010 to 2020, further reveal the evolution trend and driving factors of the spatial and temporal pattern of the two coupling and coordination relationship, to provide scientific decision-making basis for high-quality development of Yunnan and coordinated development of resources and environment, promote high-quality development and resource and environment coordination, using the entropy-topsis model, coupled coordination degree model, spatial autocorrelation, random forest and other methods. This paper analyzes the evolution characteristics and driving factors such as the comprehensive level of resource and environmental carrying capacity, the coupling and coordinated differentiation characteristics, the spatial distribution and the correlation mode of Yunnan in 2010 to 2020. The results show that: 1) from 2010 to 2020, the provincial high-quality development index increased from 0.300 to 0.575, and the resource and environmental carrying capacity index increased from 0.295 to 0.758, showing an overall upward trend. 2) From2010 to 2020, the coupled coordination degree of high-quality development and resource and environmental carrying capacity will increase from 0.545 to 0.812, and the coordination type will rise from barely coordinated to highly coordinated development. 3) The type of coupling coordination at the city level is at a low level. In 2010, only Kunming was in the intermediate and coordinated development type, Qujing was on the verge of disorder and decline type, and the other 14 cities were all in the intermediate disorder and decline type. By 2020, the level of coupling coordination will be mainly improved in central Yunnan, Yuxi and Honghe Prefecture will be upgraded to the verge of disorder and decline, and Qujing will be improved to barely coordinated development. 4) The spatial distribution of coupling coordination degree is different in different years. From 2010 to 2015, there was only one high value cluster area, mainly distributed in Kunming and Qujing, and the high/low value aggregation in other states and cities was not significant. By 2020, there is a significant spatial heterogeneity, with one high value cluster area and one low value cluster area. Among them, the high-value cluster areas are mainly distributed in the central Yunnan province, including Kunming, Qujing, Yuxi and other regional units. The low-value anomaly area is distributed in Dali Prefecture in western Yunnan Province.5)From 2010 to 2020, the spatial autocorrelation degree of coupling and coordination was enhanced, mainly between high development level-high bearing capacity and low development level-low bearing capacity. Kunming regional high development level-high bearing capacity type, Zhaotong regional low development level-low bearing capacity type is relatively stable. In 2010, Kunming region was high development level-high bearing capacity, low development level-low bearing capacity is mainly distributed in Zhaotong, Qujing, Honghe, Wenshan and other regional units, while other cities were not significant. In 2015, the regional distribution of high development level-high bearing capacity was stable in Kunming, while the distribution range of low development levellow bearing capacity was decreased, mainly distributed in Zhaotong, Qujing, Honghe and other regional units, while the other cities and cities were not significant. In 2020, the high development level of distribution-high bearing capacity greatly expanded, including Kunming, Qujing, Honghe, reflects the high quality development level. 6) Support high quality development and resources and environment bearing capacity of the variables of coupling coordinate the main driving factors for tourism foreign exchange income (x20), per capita GDP (x21), sewage treatment (x51), tourism revenue (x19), mainly comes from the open development system, followed by Shared development and environmental bearing capacity system, drivers present obvious spatial differentiation characteristics. From the point of unit, Kunming, Yuxi Zhaotong, Honghe, Wenshan, Dehong prefecture, pu’er region of high quality development and resources and environmental bearing capacity coupling coordination factors mainly comes from resource bearing capacity system, Qujing, Chuxiong, Nujiang, Diqing, Baoshan and other areas of high quality development and resource and environment bearing capacity coupling coordination factors mainly comes from environmental bearing capacity system, Lijiang, Lincang, Dali prefecture, Xishuangbanna high quality development and resources and environmental bearing capacity coupling coordination factors mainly comes from the open development system. With the obvious spatial differentiation of driving factors and the gradient change of main driving factors, open development and shared development drive the high-quality development of the province; environmental carrying capacity plays an important supporting role and further promotes the coordinated development of high-quality development and resource and environmental carrying capacity.

Abstract:The optimization of block?level urban space from a walking?oriented perspective is of profound and enduring significance for enhancing urban travel efficiency, promoting low?carbon and sustainable mobility, and improving the overall quality, livability, and resilience of the human settlement environment. As cities worldwide increasingly embrace the vision of walkable, human?scale neighborhoods and compact urban forms, a systematic, comprehensive, and operational understanding of how block spaces can be optimized to facilitate and incentivize pedestrian activity has become both a theoretical imperative and an urgent practical necessity for planners and decision?makers. However, existing review studies in this domain have predominantly concentrated on delineating the evolution of theoretical frameworks and developmental trajectories of walking and pedestrian research, whereas comparatively insufficient attention has been devoted to the concrete spatial optimization methods, advanced analytical techniques, and implementable planning models that can directly inform, guide, and evaluate real?world planning and design practice. To address this issue, this study employs a combination of systematic literature research and logical analysis to review, refine, and reflect upon the optimization system of block spaces under the guidance of walking travel, following an integrated analytical logic of “theoretical foundation-problem orientationmethodological support-pattern extraction-optimization practice”. First, the paper integrates multi?dimensional theoretical foundations, including Environmental Behavior Theory, the Hierarchy of Walking Needs, and the 5D Built Environment Theory (density, diversity, design, destination accessibility, and distance to transit), in order to systematically deconstruct and articulate the cumulative effect, feedback mechanisms, and spiral?upward logic of walking?oriented block space optimization. This conceptual logic emphasizes that optimization is not a one?time, static intervention but a continuous, iterative process of feedback, learning, adjustment, and refinement. On this basis, the study establishes a comprehensive and logically coherent methodological system categorized into three hierarchical levels. “Epistemology” focuses on scientific cognition and knowledge acquisition through multi?source big data (such as GPS trajectories, mobile signaling data, and street?view images) to achieve precise, fine?grained measurement of pedestrian behavior patterns and environmental characteristics. “Interpretation” delves into deep attribution analysis using statistical models, machine?learning algorithms, and rigorous causal identification methods to reveal and quantify the mechanisms linking the built environment to walking propensity and behavioral responses. “Prediction” utilizes multi?scenario simulation tools such as Agent?Based Modeling (ABM), Virtual Reality (VR), and related digital simulation platforms to pre?evaluate, compare, and optimize the potential impacts of alternative planning interventions. Furthermore, the research systematically summarizes and refines four dominant optimization patterns: Land?Use Regulation, which focuses on structural optimization and functional mixing to enhance land?useefficiency and spatial compactness; Network Connectivity, which aims to optimize the topology and continuity of walking paths to break spatial silos, reduce fragmentation, and improve overall accessibility; Functional Enrichment, which ensures that the supply of daily services and public facilities aligns with the concept of the “15?minute community life circle” to meet diverse resident needs in terms of living, working, and leisure; and Environmental Enhancement, which targets the improvement of micro?scale visual elements, greenery, and street furniture to foster social interaction, walking comfort, perceived safety, and psychological well?being. These four models are illustrated and validated through international benchmarks such as Barcelona’s Superblocks and New York’s Complete Streets, as well as localized Chinese innovations exemplified by Shanghai’s community life circles and other emerging neighborhood?scale experiments. The review identifies and highlights that the prevailing paradigm of walking?oriented optimization is undergoing a profound shift from singular, project?based physical renovations toward integrated, systemic social?spatial governance and coordinated policy design. Finally, the paper proposes that future research should focus on three key directions: Multidisciplinary Synergy, to more fully integrate insights from psychology, public health, transportation engineering, and data science into a shared research agenda; Integrated Technical Methods, to move from simple correlation analysis toward robust causal inference and dynamic feedback evaluation using digital twin technologies and high?resolution urban models; and Multi?scale Spatial Linkage, to resolve the scale?dependent biases and mismatches in planning and to ensure that micro?node improvements at the street and block level meaningfully contribute to macro?network resilience and citywide equity. By fostering an organic unity between theoretical deepening and practical application, this study provides a solid scientific foundation and a strategic roadmap for creating more walkable, sustainable, inclusive, and human?centric urban block environments in the future.

Abstract:University residential colleges have become a transformative model in higher education, fostering holistic student development by bridging the gap between living and learning. Rooted in the concept of living-learning collaboration, residential colleges seek to redefine student residential areas as educational spaces that nurture intellectual, social, and emotional growth. However, the implementation of this concept in Chinese universities remains limited due to the lack of a wellestablished education system and the dominance of traditional residential models that prioritize basic living functions. This paper takes the residential college system of Yale University—a pioneer and exemplar in this field—as a case study, aiming to explore its development history, operational mechanisms, and spatial design strategies, and to extract insights applicable to the Chinese context. Yale’ s residential colleges, with nearly a century of history, are not merely living quarters but are intentionally designed as integrated learning environments. They embody a revival of the early “collegiate way of living”, in which students and faculty members share communal life, meals, academic discourse, and cultural experiences. Yale’s system evolved through three distinct phases: the initial construction of ten colleges in the 1930s with enclosed courtyards and Gothic architectural styles; the experimental modernist designs of the 1960s, and the completion of Benjamin Franklin and Pauli Murray Colleges in 2017, which combine traditional aesthetics with modern spatial programming. At the institutional level, Yale’s residential colleges are positioned as educational entities that operate alongside, but independently from, academic departments. While departments oversee specialized instruction and degree programs, residential colleges are tasked with providing social support, academic advising, and co-curricular enrichment. Each college houses around 400 undergraduates and is led by a Head of College and a Dean—both faculty members who live in the college and engage closely with students. Additional roles, such as residential fellows, writing tutors, and peer mentors, form a supportive ecosystem that fosters living-learning collaboration. In terms of spatial environment design, Yale’s residential colleges exemplify how architectural planning can support educational goals. The newly built colleges employ a holistic design approach that organizes functions into three main categories: daily life spaces, educational activity spaces, and logistical support spaces. Rather than separating living and learning, the design emphasizes functional integration. Student and faculty residences are strategically placed to encourage informal interaction; dining halls serve not only as eating areas but also as primary social hubs, around which academic and recreational spaces are clustered; and education-related facilities such as libraries, lounges, and studios are interwoven throughout the colleges to facilitate spontaneous engagement and informal learning. Moreover, the design introduces composite space strategies, where traditional daily life spaces are endowed with multiple uses. Student suites are configured as shared apartments to balance privacy and community. Heads of College residences double as administrative, social, and ceremonial spaces; and the Buttery—originally a small student-run eatery—has evolved into a multifunctional venue for informal learning, gatherings, and creative activities. These hybridized spaces encouragestudents to blur the lines between everyday life and academic inquiry, making learning a continuous and ambient process.A crucial element of the spatial strategy is atmosphere creation rooted in a sense of belonging and cultural identity. The colleges use inward-facing courtyards of varying scales to create intimate, protected environments amidst the urban campus. Natural elements, such as green courtyards and varied landscaping, enhance the sensory experience and promote emotional well-being. Culturally, the architectural language maintains continuity with Yale’s historic campus through materials like brick and stone, while decorative elements—such as stained glass, symbolic carvings, and thematic motifs—reflect Yale’s traditions, local heritage, and prominent alumni, turning the built environment into an immersive cultural narrative. Drawing on Yale’s experience, the paper offers several implications for the development of residential colleges in China. First, it emphasizes the importance of clearly defining the institutional role of residential colleges within the broader university structure. Establishing living-learning collaboration as a core educational objective requires alignment across spatial design, curriculum activities, and personnel structure. Second, Chinese universities are encouraged to move beyond the “patchwork” approach—where living and learning spaces are simply juxtaposed—and instead adopt a more immersive and integrative model. This includes using daily life space organization to foster seamless transitions, expanding the functional capacity of daily spaces to allow for diverse educational activities, and creating atmospheres with a sense of belonging and cultural meaning. Ultimately, this study underscores that residential colleges, when supported by a coherent educational system and thoughtfully designed spaces, can serve as dynamic platforms for interdisciplinary learning, social development, and cultural transmission. By translating and adapting the lessons from Yale’s model, Chinese universities can reimagine student residential areas not merely as places to live, but as vital educational spaces that contribute to the formation of well-rounded, engaged, and self-directed graduates.

Abstract:In the context of the carbon peaking and carbon neutrality initiative, enhancing the operational carbon performance of university teaching buildings has emerged as an urgent engineering imperative. These buildings demonstrate significant temporal variability, as their carbon emissions are influenced by academic calendars, class timetables, examination periods, holidays, weather conditions, and fluctuating occupancy levels. Short-term forecasting can facilitate operational scheduling and campus carbon management. Long short-term memory networks are extensively employed for building time-series prediction; however, their application in university teaching buildings has not been adequately investigated. Existing research seldom evaluates the combined impacts of training data volume, occupancy feature resolution, and computational cost, and there is limited evidence regarding hybrid architectures. This study aims to bridge these gaps by systematically comparing LSTM and several LSTM-based hybrid models for short-term operational carbon emission prediction in university teaching buildings.The case study pertains to a cluster of teaching buildings at a university in Guangzhou, China, which is situated in the hot-summer and warm-winter climate zone. The building complex is primarily composed of ordinary classrooms and offices. These buildings predominantly rely on purchased electricity as the main operational energy source, without any gas consumption or on-site renewable energy generation. Hourly electricity data for the years 2023 and 2024 were acquired from the campus logistics service center and transformed into hourly carbon emissions by utilizing the electricity emission factor. The study established a dataset that integrates hourly carbon emissions, occupancy data, and meteorological variables.A significant contribution resides in the development of high-resolution occupancy inputs specifically designed for teaching buildings. Classroom occupancy was reconstructed from course and examination schedules and adjusted according to attendance assumptions. Self-study occupancy and staff presence were obtained from field surveys carried out during teaching weeks, pre-examination periods, examination weeks, holidays, summer and winter vacations, and the Spring Festival closure period. Meteorological inputs were extracted from the ERA5 reanalysis dataset. Pearson correlation analysis retained dry-bulb temperature, relative humidity, and shortwave radiation. Variance inflation factor testing verified that the selected variables did not display serious multicollinearity. After missing-value handling, dataset partitioning, normalization, and sliding-window processing, the data were employed for multi-input single-step forecasting with a 24-hour look-back window and a one-hour forecasting horizon.Six models were assessed within a unified training strategy. The baseline model was an independent LSTM. Subsequently, five hybrid variants were constructed to explore diverse approaches for enhancing sequence learning. A convolutional neural network module was positioned either prior to or subsequent to the LSTM toinvestigate whether local pattern extraction is more advantageous at the input phase or the feature phase. An attention module was incorporated after the LSTM to accentuate informative time steps. Moreover, two composite architectures, namely CNN-ATT- LSTM and LSTM-ATT-CNN, were designed to examine potential synergies among convolution, attention, and recurrent learning. All models were trained with optimized hyperparameters under identical experimental conditions. Performance was evaluated using the coefficient of determination, root mean square error, mean absolute error, mean absolute percentage error, and computational time. Each model was independently executed twenty times for each data condition, and mean values were reported.The findings demonstrate that the suitability of the model is highly contingent upon data availability and management objectives. When the training data encompass a period of one year or less, the CNN-LSTM model exhibits the optimal trend fitting, while the baseline LSTM attains the highest numerical precision. This implies that a limited amount of historical data suffices for the baseline LSTM to generate stable point estimates, whereas the front-end convolution is more effective in capturing short-term fluctuations and cyclical patterns. When the data span extends beyond one year, the CNN-ATT-LSTM model presents the best overall performance. In comparison with the baseline LSTM, it enhances the coefficient of determination by approximately 0.02, reduces the root-mean-square error (RMSE) by around 15%, and decreases the mean absolute error (MAE) by roughly 12%. Moreover, it incurs a lower computational cost, with an average runtime approximately 0.4 times that of the baseline LSTM under the one-year data condition and 0.6 times under the two-year data condition. Generally, a greater volume of historical data enhances trend consistency, as evidenced by higher coefficients of determination under the two-year condition. Nevertheless, larger datasets do not ensure lower absolute errors for every architectural model, suggesting that data expansion and model structure interact in a non-trivial way. From the perspective of engineering deployment, a differentiated selection strategy is advisable. When historical data are scarce and the task accentuates point prediction accuracy, the baseline LSTM remains a viable option. When the task places priority on trend tracking or rapid rolling forecasting, CNN-LSTM is more appropriate under limited-data circumstances. For buildings with relatively comprehensive long-term data, CNN-ATT-LSTM presents the most wellbalanced solution in terms of accuracy, robustness, and deployment cost. These findings offer guidance for model selection in campus building energy management systems.This research is confined to a relatively homogeneous cluster of teaching buildings within a single climate region. The generalizability of the conclusions to other types of campus buildings necessitates further verification. Future research could explore transfer learning under small-sample conditions, more refined spatiotemporal features, and integration with building energy management systems, and thus enhancing the control of operational carbon in higher education facilities.

Abstract:Urban and rural planning is an interdisciplinary and practice-oriented applied discipline, in which practical teaching and final-year projects serve as the core components for assessing the effectiveness of undergraduate education. Against the backdrop of disciplinary convergence and the new engineering education initiative, joint thesis designs in urban and rural planning have become a vital vehicle for inter-institutional exchange, teaching reform and disciplinary development. Drawing on online data collection and practical experience, this paper systematically reviews the implementation of joint thesis designs in urban and rural planning across the country in recent years. Joint thesis designs in China began in 2011. The initiative launched in 2013 by six universities, including Tsinghua University, set a precedent, and since 2017, a three-tiered nested network of educational collaboration—comprising national, regional and provincial levels—has gradually taken shape. By the end of 2024, there were over 20 national joint graduation project alliances, covering more than 100 universities across 28 provinces and municipalities. Of the 61 universities that have passed professional accreditation, 53 are participating in these initiatives; however, the academic community has yet to conduct systematic research on the implementation of joint thesis designs nationwide. To this end, taking the period from 2011 to 2024 as the research timeframe and 2024 as the key node, the study utilized Ucinet 6.0 software to construct a university cooperation network. A systematic analysis was conducted across dimensions including temporal evolution, spatial distribution, network relationships, core characteristics and development trends, aiming to reveal the developmental patterns of joint thesis designs and provide references for promoting their high-quality development and reforming urban and rural planning education. The research findings indicate that, over time, the number of times universities participated in joint thesis designs has shown rapid linear growth, rising from 7 instances in 2011 to 184 in 2024. The widespread adoption of online teaching during the pandemic further accelerated this expansion. National consortia were the first to establish a stable teaching framework, whilst regional and provincial consortia have developed rapidly since 2016; the three complement and support the diversified development of planning education nationwide. In the spatial dimension, participating universities exhibit distinct patterns of differentiation and regional clustering. Participation is particularly high in eastern regions such as Beijing, Jiangsu, Zhejiang and Guangdong, whilst central and western regions including Shaanxi, Sichuan, Chongqing and Hunan have performed notably well. Significant clustering effects are evident in regions such as the Beijing-Tianjin-Hebei, Yangtze River Delta, Guangdong-Hong Kong-Macao, Chengdu-Chongqing and Shaanxi-Gansu clusters. Social network analysis shows that each university undertakes different link functions in the network, and the degree centrality can effectively reflect the breadth of university cooperation. Some non-traditional universities have become the core nodes of the network with high participation and openness. The degree centrality level is significantly positively correlated with the passing rate of professional evaluation. The passing rate of high centrality universities is 92.8%, which plays a leading role in the joint completion. In terms of network density, the density of the national consortium is 0.2460, the structure is close and stable, and constitutes the overall network skeleton; after superimposing regional and provincial networks, the overall density drops to 0.1037, showing an unbalanced state. In terms of core characteristics, national-level joint thesis designs are guided by innovation and cutting-edge exploration, benchmarking against international standards and focusing on complex issues such as urban regeneration and heritage conservation; regional and provincial-level joint thesis designs, on the other hand, are rooted in local characteristics and closely aligned with regional development strategies—for instance, the Chengdu-Chongqing region focuses on rural revitalization, whilst the Guangdong-Hong Kong-Macao Greater Bay Area explores spatial collaborative governance. The study further identifies three major development trends: firstly, a shift from discipline-centric approaches to cross-disciplinary collaboration, with the professional composition expanding from a single discipline of planning to a multidisciplinary matrix encompassing urban planning, architecture, landscape architecture, geographic information systems and environmental studies; secondly, a transition from inter-institutional cooperation to a multi-faceted integration of industry-education and government-university partnerships; thirdly, an upgrade from technical training to a response to national strategies, with project themes shifting from traditional spatial design to align with national strategies such as rural revitalization, regional coordination, the “dual carbon” goals and healthy cities. Lastly, this paper suggests ways to improve the teaching quality of joint thesis designs: changing the pedagogical philosophy from a “teacher-student” relationship to “co-production of knowledge”; changing the teaching methods from one-way instruction to collaborative innovation; changing the teaching content from incremental planning to improving the quality of current developments; changing the course topics from grand narratives to a human-centered approach; and changing the career orientation from spatial form to integrated governance. In order to promote a thorough advancement in undergraduate urban and rural planning education, this change seeks to conform to the demands of the Central Urban Work Conference and the emergence of new engineering specialties while consistently improving cooperative mechanisms and instructional efficacy.

Abstract:Chinese historical gardens represent material carriers of traditional Chinese gardening philosophy, concepts, and knowledge, embodying ancient Chinese understanding of the universe and the pursuit of an ideal living environment. These meticulously designed landscapes serve as invaluable cultural heritage sites that integrate aesthetic principles, philosophical thought, and horticultural expertise developed over millennia. However, a significant gap exists between public perception and these gardens’ profound historical, cultural, and artistic significance. Contemporary visitors often lack the contextual knowledge necessary to fully appreciate the sophisticated design principles, symbolic meanings, and cultural narratives embedded within these spaces. A notable lack of professional and effective methods, approaches, and content to guide garden appreciation activities further exacerbates this interpretive challenge, limiting the public’s ability to engage meaningfully with these cultural treasures. Information technology offers promising potential solutions and innovative tools to address these pressing challenges in heritage interpretation and visitor engagement. This study focuses on the “Spring Clouds over Jade-Islet” (Qiong-Dao-Chun-Yin) within Beijing’s Beihai Park as a comprehensive case study, investigating the multifaceted problems associated with public cognition and interpretation methods for such culturally significant sites. Through a systematic comparative analysis of various immersive technology characteristics and capabilities, augmented reality (AR) emerges as the most suitable primary tool for exploring innovative methods to present the intrinsic value and deep cultural connotations of historical gardens to contemporary audiences. Furthermore, this research aims to construct a novel, integrated system and comprehensive application framework for multi-source data fusion in both the academic research and public presentation of historical gardens, utilizing cutting-edge AR technology to bridge temporal and cultural gaps. The research methodology strategically combines rigorous historical textual research with contemporary digital surveying and precision mapping techniques to delineate the exact scenic scope and spatial boundaries of “Spring Clouds over Jade-Islet” during the historically significant Qianlong period (1736-1796), creating a more accurate and detailed architectural plan than previously available. This interdisciplinary approach involves sophisticated computer modeling to simulate the historically documented water accumulation scene of the Dragon Pond (Longchi), while simultaneously examining the complex spatial relationships and profound cultural connotations of “Spring Clouds over Jade-Islet” within the broader contextual framework of Beihai Imperial Garden’s comprehensive landscape design philosophy—which specifically incorporates linking “weather transitions ( 阴晴)” with agricultural practices and livelihood concerns, reflecting the Emperor’s agrarian-focused governance ideology that carries significantly broader conceptual dimensions compared to earlier scholars’ purely cloudscape depictions, while also integrating this scenic composition into the garden’s overarching spatial narrative of cloud formation and rainfall induction—and underlyingConfucian and Taoist philosophical underpinnings. The study leverages advanced computer-structured data application development methodologies to establish a comprehensive garden appreciation content system that strives to approximate and digitally restore the original design intentions of ancient Chinese landscape architects, thereby providing modern visitors with intuitive tools for understanding these sophisticated historical design concepts and cultural meanings. A detailed technical case study examines the practical AR implementation process for the Dragon Pond water simulation within the “Spring Clouds over Jade- Islet” scenery reconstruction. This complex technical process encompasses meticulous digital 3D modeling of the historical Dragon Pond structure, achieved through advanced photogrammetric reconstruction techniques that capture precise geometric and textural details. Subsequently, sophisticated hydrological water accumulation simulation is performed based on comprehensive inundation analysis data and historical rainfall patterns. Finally, immersive AR scene construction techniques are employed to create compelling visual representations that showcase the intended historical scene: the pond gradually filling with rainwater following seasonal storms, with only the symbolic dragon’s head and nostrils remaining visible above the water surface. This carefully crafted visual representation aims to express the profound artistic conception of the “hidden dragon” (潜龙, Qianlong), a culturally potent symbol in Chinese philosophy representing untapped potential, latent transformative power, and the crucial initial nurturing stages of growth and development, perfectly aligning with the renewal symbolism of spring and the northeast Gen (?) Trigram position’s philosophical significance in Chinese cosmology.This research directly addresses the current insufficiency of comprehensive studies focused specifically on content system construction for AR applications tailored to historical garden interpretation and visitor engagement. It particularly emphasizes the demonstration and effective dissemination of ontological value connotations inherent to these culturally significant landscapes, ensuring that deeper meanings are accessible to diverse audiences. The research findings hold substantial academic value and practical importance for the protection, sustainable utilization, and ongoing scholarly research related to historical gardens throughout China and similar cultural heritage sites globally. Moreover, this study provides a valuable methodological reference framework for interpreting the essence of Chinese civilization and cultural philosophy through the strategic application of contemporary digital technologies and intelligent systems. This investigation is strategically situated within the contemporary era of rapid “big data, artificial intelligence, cloud computing, and mobile internet” technological development and their progressive integration into digitalized smart cities and cultural-tourism sector innovations. The research explores how emerging information technologies can significantly enhance public understanding of complex urban historical layers while facilitating beneficial, sustainable interactions between contemporary society and traditional cultural environments. AR technology, as a representative example of new quality productive forces in the cultural heritage preservation sector, demonstrates potential for enhanced intelligent manufacturing of cultural interpretation equipment, sophisticated intelligent upgrades for heritage site management systems, and the development of innovative consumption scenarios arising from the strategic integration of cultural preservation and tourism industries. The practical application of AR technology in this context is strategically positioned to integrate the enduring vitality of cultural artifacts and historical sites into contemporary daily life, effectively reintegrate traditional cultural knowledge into modern societal discourse, and create deep, lasting resonance with people’s evolving cultural consciousness and identity.

Abstract:Town-plan always records of the development process of urban physical forms, and cultural influences from different periods will leave their unique material remains in the urban landscape. At the same time, once a stable town-plan is formed, it becomes the most conservative morphological complex, especially the street-system within it. The sample is that within the same development period, new areas can show the influence of contemporary culture, economic activities, and the characteristics of the times; while changes shown in the old areas are slow and insufficient, the original street system and corresponding social activities have become stable through mutual adaptation, this street-system is precisely the foundation for forming different morphological areas within the same city.The functional organization and urban landscape of builtup areas in cities are cumulative records of urban development. Therefore, tracing and exploring the potential formation process of existing urban forms, analyzing and interpreting them, has become the core work of urban form research. Various regions developed in the same city at different times formed differentiated morphological frameworks due to different cultural influences experienced. The evolutionary research method is often used to study the town-plan by dividing the morphological areas, revealing the influencing factors formed by different morphological areas, and thus explaining their current morphological characteristics.The urban form of the Macao Peninsula is a “miniature epic between mountains and sea” , on a narrow promontory of less than 10 square kilometers, more than four hundred years of collision between Chinese and Western cultures, land reclamation, and high-density living have jointly carved out a collaged, three-dimensional, and composite urban landscape. Based on relevant research literature in urban morphology, the density of the street system, and the characteristics of the historical development and evolution of Macau, this study divides the Macau Peninsula into 4 morphological region (from region A to D).Previous studies on urban morphology largely focused on macro perspectives such as street systems, plot combinations, and the building fabric. Based on the interest in the urban fabric formed by individual buildings and urban morphological elements around them, this research takes an architectural perspective and selects the relationship between church buildings in the Macau Peninsula and their surrounding urban form as the object of study. Through qualitative analysis, the urban fabric around the (church) buildings is divided into three types: embedded type, surrounded type, and single type. In the embedded type, the churches connected to the surrounding buildings closely, and the main facade constitute the important nodes of the urban public space and townscape-the churches are the protagonist of the street landscapeIn the surrounded type the function of churches as urban landscapes is weakened, and the churches connect with courtyards. The courtyards at the entrance of the churches are not the open space for the city street. In the single type, the church occupied a whole plot. Each facade of the church participates in the landscape of the street. At this time, the mutual influence between church and the urban landscape is enormous. Research indicates that the urban fabric around the churches on the Macau Peninsula has been accompanied by the establishment and development of the city for nearly five centuries. As individual buildings, their scale had not changed significantly, but the urban fabric formed by them and the surrounding urban form elements are different significantly. These differences are firstly significantly correlated with the morphological region inwhich the churches are located. Churches located in region A are embedded type (C01, C02, and C04-C07); churches located in region B and C form mostly are surrounded type. C10 in region C, due to its construction time in early 21st centuries, exhibits single type. It can be seen that the time of being build is also one of the influencing factors of urban fabric.The study shows that the relationship of the (church) building and their surrounding urban morphological elements varies from “semi-open-closed-fully open” due to differences in the urban morphological region they are located in and the eras when they were built. This research provides a new perspective for heritage protection research and expands the scope of methodology in urban form studies. The division of morphological region is one of the basic methods of urban morphology research, and the comparative study of different morphological region within the same city can more effectively reveal the driving forces behind the formation of urban morphology.

Abstract:High-quality window views have a significant impact on the public health of indoor occupants. Window views from an indoor perspective are typically characterized by a composition of features that include natural elements such as greenery, sky, and water, alongside artificial elements such as urban streets, buildings, and vehicles. The study of window views enables urban planners to re-evaluate the interactive spatial arrangements and the spatial interpenetration between artificial and natural environmental elements within urban spaces from a new perspective. The research is based on a comprehensive review and selection of literature, systematically analyzing 96 English publications from the Web of Science (WOS) core collection database. This article summarizes the research content and methodologies, revealing patterns and distributions in the international study of urban building window views, and providing valuable references and insights for future research. The results indicate that in terms of current design standards and guidelines, relevant frameworks are primarily initiated and developed by developed countries such as the United Kingdom and the United States. These frameworks are often integrated into building daylighting and energy performance assessment systems but fail to provide systematic and comprehensive quantifiable indicators to guide window view design. In terms of research settings and participant selection, discussions most frequently focus on window views at the small scale of individual buildings, particularly in low-rise and mid-rise residential and office buildings. However, high-rise and super high-rise buildings have received comparatively less attention in existing studies. Participant groups are predominantly university students, with limited consideration for diverse populations, and some experiments face challenges such as insufficient exposure durations for participants. In terms of research content, studies primarily focus on two dimensions: the health-related impacts of window views and the quantitative assessment of window view quality. Within the health dimension, existing research explores the relationships between window view characteristics such as emotional states, visual preferences, productivity, and behavior. Regarding quality assessment, studies concentrate on aspects like types of window view features, field of view, and clarity indicators, but relevant studies only partially address the complex interactions among windows, indoor and outdoor conditions, and occupants. In terms of applied techniques, research on the health benefits of window views primarily relies on methods such as laboratory simulations, online surveys, and field studies to construct scenarios. The assessment of window view quality focuses on traditional approaches like manual photo scoring and questionnaire evaluations. However, there is a notable lack of large-scale and continuous studies on urban window view quality. Finally, to address the identified research gaps, three future research directions are proposed. Regarding research settings and participant groups, future studies should expand the exploration of interactions and relationships between diverse populations and window views across various building types. Emphasis should be placed on advancing complex urban studies within the context of high-rise, high-density environments. Additionally, it is essential to strengthen long-term tracking and evaluation of participant groups, conducting longitudinal studies to examine the dynamic effects of window view characteristics on human perception. Such research should also explore planning and design strategies to maximize thebenefits of window view utilization. Regarding research content, further investigation is needed into the mechanisms underlying the relationship between window views and health outcomes. Moreover, experimental designs should be expanded to incorporate multi-sensory conditions for a more comprehensive understanding of these interactions. The mediating effects of window views on psychological benefits for individuals remain unclear. Future research should integrate multi-sensory conditions to further explore the interactions among various visual characteristics of window views. Additionally, pathways of psychological benefits under different combinations of view characteristics should be analyzed to deepen understanding in this area. In the development of evaluation systems and standards for window views, it is crucial to integrate the combined impacts of view content, view visibility, and view clarity. These factors should be systematically analyzed and incorporated into a framework that employs graded and categorized weighted calculations based on the functional attributes of buildings. By adopting this approach, window view quality can be effectively quantified across varying scenarios and scales, providing a standardized methodology to assess and compare window view characteristics in diverse architectural contexts. In terms of applied techniques, it is essential to enhance the precision of digital model construction, integrating the effects of complex environmental factors such as indoor and outdoor lighting optimization and seasonal landscape changes. Future studies should focus on developing advanced image editing algorithms capable of simulating variations in weather and seasonal conditions. Furthermore, efforts should be made to improve the fidelity of digital models in representing environmental variables, including architectural facade details, traffic flow, and greenery characteristics. Such advancements would significantly enhance the applicability of digital models for evaluating window views in dynamic and context-sensitive scenarios.