| 摘要: |
| 基于已有“街道城市主义”研究中以
街道为个体的城市空间分析、统计和模拟的
框架体系，论文以大数据分析为手段，以贵
阳市老城区核心区域街道为样本，运用街道
活力定量评价的指标体系，分别探索公共服
务性街道、商业性街道、居住性街道、交通
性街道和混合性街道活力的外在表征，研究
各类街道活力构成因素的量化关系。研究数
据表明，与行政中心、商业中心、学校、公园
等高频使用公共服务设施的关联距离和街
道功能密度是影响街道活力的主要因素，其
中与商业中心的关联度及距离是对各类街道
活力影响最大的因素。此外，研究发现一个
有悖于直观判断的结果，南明河对于研究范
围内的街道活力具有抑制作用。 |
| 关键词: 街道活力 大数据定量分析 功能密
度 功能混合度 贵阳老城区 |
| DOI：10.13791/j.cnki.hsfwest.20210312 |
| 分类号: |
| 基金项目:国家自然科学基金（51678087）；国家自然科学基
金青年基金（51708275） |
|
| Quantified Analysis on Affecting Factors of Urban Street Vigor Based on Big-Data |
|
XING Zhong,CHEN Zilong,GU Yuanyuan,BAI Jiani,YAO Yao
|
| Abstract: |
| Unlike roads, which emphasize traffic capacity, streets emphasize communication and
recreation. Street environment also plays a decisive role in the quality of life and comfort of urban
residents. Walking is one of the most basic behaviors of human beings since walking upright.
However, with the continuous progress of urbanization in China, the number of roads dominated
by car behavior is increasing, the number of streets providing pedestrian recreation for residents is
decreasing, which leads to the decrease of convenience and risk of residents’ life and the decrease of
street vitality. Based on the theoretical basis of urban streetism and referring to the research method
of quantitative evaluation of street vitality and analysis of influencing factors, taking Chengdu as
an example by Long Ying and Zhou Yin, this paper selects the old urban area of Guiyang, which is
quite different from Chengdu in terms of topography and socio-economic development To explore
the influencing factors of street vitality in western mountainous cities. Combined with the spatial
characteristics of the old urban area of Guiyang, this study added commercial facilities, educational
facilities, mountain green space and city river and other related factors in the construction of the
evaluation index system, trying to study the degree of correlation between street vitality and the
public service facilities and open space frequently used by urban residents, Evaluation factors can
be added to open the link.
By means of big data analysis and taking the streets in the core area of the old urban
area of Guiyang City as samples, this paper explores the external representation of the vitality
of public service streets, commercial streets, residential streets, traffic streets and mixed
streets respectively by using the index system of quantitative evaluation of street vitality,
and studies the quantitative relationship between the constituent factors of all kinds of street
vitality. The results show that: 1) the nearest distance to the administrative center, commercial
center, school and park and the functional density of the street are the main factors affecting
the vitality of the street; 2) The main influencing factors of different types of streets are
different. For example, public service streets are the most sensitive to the distance from the
nearest “connection” (the road section is the optional connection path to the commercial
center); 3) The vitality of commercial streets is greatly affected by the nearest distance to the
administrative center, commercial center, school and park, among which the nearest distance
to the commercial center is the most sensitive; 4) Residential streets are greatly affected by
the nearest distance to the administrative center, commercial center and park and the function
density, among which the nearest distance to the commercial center is the most sensitive; 5) Traffic streets are not affected by the function mix degree and the nearest distance to Nanming River, but they are not sensitive to other vitality
factors; 6) Mixed streets are most sensitive to the nearest distance to the commercial center. In practice, in addition to the limited factors of
Administrative Center campus and Natural River, it is an effective way to improve the street vitality by increasing the function density and
function mixing degree of the streets for all streets. For residential, commercial and public service streets, in addition to the functional density
and functional mixing degree, the ecological transformation of negative space can effectively improve its vitality by increasing the green space of
the city, such as Corner Park. For traffic streets, not only the density of bus stops should be increased, but also the function mixing degree of the
streets will have a good effect on the street vitality. In addition, the density of bus stops has little influence on the vitality of all types of streets.
So other means can be tried to improve the vitality of urban streets from the traffic level, such as building a slow-moving system in the city, and
improving the continuity, diversity and safety of pedestrian environment. It is necessary to point out that the nearest distance from Nanming
River has no influence on the vitality of traffic and mixed streets, but also has a restraining effect on the vitality of Public Service Street,
commercial street and residential street. This is contrary to intuitive judgment. Nanming River is the urban water system of old Guiyang City,
and the historical protection building Jiaxiu building is located on it. As an important resource of human settlements, the street vitality should
be actively promoted. However, according to the research results of this paper, Nanming River has not played an appropriate role in the old
Guiyang city. The author has found that the reasons are lack of hydrophilicity and accessibility of riverbank, monotonous ecological landscape
and deterioration of water body. The results can provide useful references for the treatment of human settlements in the surrounding areas of
Nanming River |
| Key words: Street Vigor Quantified Analyses based on Big-Data Function Density Function-mixture Degree Old-Town of Guiyang City |
