基于社会属性的北京市居民居住与就业空间集聚特征

制度转型期，中国城市居民社会空间发生了新的变化，居民居住和就业空间组织也变得更为复杂，并引起了广泛关注。基于2010 年问卷调查数据，采用缓冲区、最近邻层次聚类和Ripley K函数等空间分析方法对北京城市不同社会属性居民的居住和就业空间分布特征进行实证分析。研究发现：① 总体上，北京城市居民居住和就业空间圈层分异明显。在各圈层内部，不同人群的居住和就业空间分布比例亦存在相对差异；职住空间错位程度表明距市中心15 km左右是城市就业功能和居住功能主导地位转化的分界线；职住平衡度整体上呈现出由内圈层到外圈层递减的趋势，但高收入阶层和年轻白领的职住平衡度相对较低。② 不同人群居住与就业空间集聚特征存在明显差异。一般平民居住和就业均呈散点状集聚；年轻打工族居住和就业集聚区域紧邻，主要集聚在四环以内的城市东部区域；高收入阶层居住呈现“小集中、大分散”集聚特征，就业集聚区多集中在四环以内的城市东部和西北部区域；年轻白领居住集聚区呈现城市西部条带状和东部散点状相结合特征，就业集聚区主要在中关村和CBD为中心的两条轴状区域。③ 不同人群居住和就业空间集聚的尺度特征较为相似，呈现随距离增加“先增后减”变化趋势，但距离阈值存在差异。表现为高收入群体居住空间可选范围较小，一般平民就业空间可选范围较小，而年轻白领居住和就业空间可选范围均较大。

Spatial clustering analysis of residential and employment distribution in Beijing based on their social characteristics

Along with the changes of urban residents' social space during China's institutional transition period, a wide concern has been aroused on the even more complicated spatial organization of residence and employment. Based on residential survey data of Beijing in 2010, several spatial analysis methods were applied to analyze characteristics of spatial distribution of residence and employment of different social groups in Beijing, such as the buffer analysis, the nearest neighbor clustering and Ripley K functions. The results indicated that spatial differentiation of residence and employment in Beijing was significant. Furthermore, relative differences on proportions of spatial distribution of residence and employment of different social groups also existed in the interior space of residence or employment. Degree of spatial mismatch showed that the circle of about a 15-km distance from Tian'anmen was the boundary of function dominant areas of employment and residence. Meanwhile, degree of jobs-housing balance presented a decreasing trend from inner city to outer layers as a whole, while that of high income groups and young white-collar workers was lower than the other two groups. Besides, spatial agglomeration of residence and employment for different groups also presented different characteristics. For common citizens, residential and employment locations were scattered in distribution. For young migrant workers, cluster locations of their living and working spaces were quite adjacent to each other, which were mainly concentrated in the eastern region of the city. Residential locations of high income groups were mostly separated, but their employment locations were relatively centered in the eastern and northwestern parts of the city. At the same time, distribution of young white-collars' living spaces displayed a band-like clustering in the west but scattered in the east, while their working spaces were mainly agglomerated in two axis regions centered on Zhongguancun and CBD respectively. Spatial agglomeration characteristics of residential and employment locations for different groups were similar in case of scales, revealing a trend of "increase at first but decrease later" with the increase of their distance from clustering center, although their distance thresholds were different. This difference suggested that high income groups had limited optional range on their residential locations and common citizens had minimum optional range on their employment locations, but the young white-collars showed maximum optional range on both residential and employment locations.