A spatial autocorrelation analysis of the residents' living distribution by groups in Beijing based on their social characteristics
Received date: 2009-06-23
Revised date: 2010-03-24
Online published: 2010-05-20
On the background of continued expansion and population growth of Beijing, the distribution of people's spatial living is becoming more and more important and gets increased emphasis by researchers. Based on the large-scale survey in 2005, this study used the method of ecological factor analysis and spatial autocorrelation analysis to give the spatial living distribution of different groups of residents in eight districts and the suburbs of five representative regions including a total of 134 communities. Using the ways of Principal Component Analysis and Cluster Analysis, the thesis tries to identify all the residents' characteristics into two main integrated factors, which are the level of potential for the future and the level of existing standard of living. Then the paper divides all the residents into five groups with those factors, i.e., the groups of low-potential and poor-status persons (type I), high-potential and poor-status persons (type II), high-potential and medium-status persons (type III), medium-potential and medium-status persons (type IV) and high-potential and excellent-status persons (type V). By using spatial autocorrelation analysis, the paper reveals that the groups of types II, IV and V people have the most significant living aggregation from the view of global spatial autocorrelation. From the view of local spatial autocorrelation, the article finds that the groups of types I and II people obviously cluster to the eastern and northeastern parts of the city. The group of type I has the largest proportion in the communities of Heizhuanghu, Tongzhou and Dougezhuang. The group of type II is concentrated in a fan-shaped region with Dongzhimen Street as the center. Most people of type IV live in the inner city. The groups of types V and III people are scattered, and settled mostly in Tiantongyuan and Sijiqing.
Key words： residents’ group; spatial autocorrelation; Beijing; social characteristics
YU Jian-hui, ZHANG Wen-zhong . A spatial autocorrelation analysis of the residents' living distribution by groups in Beijing based on their social characteristics[J]. GEOGRAPHICAL RESEARCH, 2010 , 29(5) : 820 -829 . DOI: 10.11821/yj2010050006
[1] 马清裕, 陈田, 牛亚菲, 等. 北京城市贫困人口特征、成因及其解困对策. 地理研究, 1999, 18(4): 400~406.
[2] 冯健, 周一星, 王晓光, 等. 1990年代北京郊区化的最新发展趋势及其对策. 规划研究, 2004, 28(3): 13~29.
[3] 冯健, 周一星. 北京都市区社会空间结构及其演化(1982~2000). 地理研究, 2003, 22(4): 465~483.
[4] 鲁奇, 吴佩林, 鲁礼新, 等. 北京流动人口特征与经济发展关系的区域差异. 地理学报, 2005, 60(5): 851~862.
[5] 《奥运会与北京流动人口》课题组. 2008年奥运会与北京的流动人口问题. 北京社会科学, 2004, (2): 8~17.
[6] 冯晓英. 北京地区流动人口的演变及其特征. 北京党史, 1999, (1): 12~16.
[7] King L J, Golledge R G. Cities, Space, and Behavior: The Elements of Urban Geography. Englewood Cliffs, NJ: Prentice Hall, 1978, 22~24.
[8] 徐旳, 朱喜钢, 李唯. 西方城市社会空间结构研究回顾及进展. 地理科学进展, 2009, 28(1): 93~102.
[9] Lo C P. Changes in the ecological structure of Hong Kong 1961~1971: A comparative analysis. Environment and Planning A, 1975, (7): 941~963.
[10] Lo C P. The evolution of the ecological structure of Hong Kong: Implications for planning and future development. Urban Geography, 1986,7 (4): 311~335.
[11] Hsu Y A, Pannell C W. Urbanization and residential spatial structure in Taiwan. Pacific Viewpoint, 1982, 23: 22~52.
[12] 许学强, 胡华颍, 叶嘉安. 广州市社会空间的因子生态分析. 地理学报, 1989, 44(4): 385~397.
[13] 顾朝林, 王法辉,刘贵利. 北京城市社会区分析. 地理学报, 2003, 58(6): 917~926.
[14] 徐旳, 汪珠, 朱喜钢, 等. 南京城市社会区空间结构——基于第五次人口普查数据的因子生态分析. 地理研究, 2009, 28(2): 484~498.
[15] 张晓旭, 冯宗宪. 中国人均GDP的空间相关与地区收敛:1978~2003. 经济学(季刊), 2008, 7(2): 399~414.
[16] 宋鸿, 陈晓玲. 运用空间自相关分析了中国入境旅游增长空间格局. 世界地理研究, 2006, 15(1): 99~106.
[17] 宋萍, 卞羽, 洪伟, 等. 武夷山风景名胜区游客区域分布的空间自相关分析. 热带地理, 2008,28(3): 283~287.
[18] 张文忠, 刘旺, 孟斌. 北京市区居住环境的区位优势度分析. 地理学报, 2005,60(1): 115~121.
[19] 王宏远, 樊杰. 北京的城市发展阶段对新城建设的影响. 规划研究, 2007, 31(3): 20~24.
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