基于众源地理数据的居住环境空间分异研究——以武汉市为例  

Study of the Spatial Differentiation of the Residential Environment Based on Crowd Sourcing Geographic Data——A Case Study of Wuhan

作　　者：龚婧媛 孙海燕[1] 钱志坚 GONG Jingyuan;SUN Haiyan;QIAN Zhijian(School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China)

机构地区：[1]武汉大学测绘学院

出　　处：《测绘地理信息》2019年第6期11-15,共5页Journal of Geomatics

基　　金：国家重点研发计划(2017YFC1405300)

摘　　要：以网络爬虫获取的房屋众源地理数据为基础,以居住小区为研究单元,结合绿化率、容积率和物业费3项指标对各居住小区内部环境进行评价,利用GIS技术结合多组群分异指数D(m)和空间修正多组群分异指数SD(m)模型,研究武汉市的居住环境空间分异情况。结果表明,武汉市居住环境评分在小区尺度上呈现出较强的自相关性,且高值聚类区主要分布在非城市中心的湖泊周围。城市居住环境的空间分异现象受区域特征、地价、自然条件与生态环境等因素影响,武汉市中心城区、各辖区及3条环线之间的居住环境分异现象均不明显。Based on the crowd sourcing geographic data that obtained by web crawler technology, and using residential quarter as the basic spatial unit, Combined with the residential quarters’ greening rate, floor area ratio and property costs to evaluate the internal environment of each residential area, using multi-group dissimilarity index(D(m)), spatial-modified multi-group dissimilarity index(SD(m)) and GIS technology, this paper reveals the spatial differentiation of residential environment in Wuhan. The results indicate that: at residential quarter level, the residential environment has demonstrated a strong spatial autocorrelation. High-high clusters are concentrated in some lakes away from the city center. Spatial differentiation of urban residential environment is affected by regional characteristics, land price, natural conditions and ecological environment, and spatial differentiation of residential environment in the center area of Wuhan and every district are not obvious.

关 键 词：众源地理数据 居住空间分异 居住小区 分异度 武汉 

分 类 号：P208[天文地球—地图制图学与地理信息工程] TU984[天文地球—测绘科学与技术]