学术
摘 要:
社区作为城市内部空间尺度单元之一，作为人类的活动中心，居住环境备受人们关注，因此对其进行定量分析是目前城市研究的热点之一。采用GIS、空间数据探索性分析和网格计算相结合的方法，选取上海市外环以内131个街镇社区作为研究对象，对其内部居住环境的空间格局进行探索性分析研究。通过研究发现，社区居住环境是不同因子相互联系、相互作用的结果，其在空间上的分布相应地表现出局部的差异性和整体上的趋同性。并从空间联系的角度出发，提出了对研究区各个社区在空间上布局和规划的方案。[著者文摘]
文章出处:
《地理科学》-2008年28卷1期 -51-58页
分 类 号:
文献标识码:
A
文章编号:
1000-0690（2008）01-0051-08
Knowledge Discovery and Spatial Data Exploring Analysis for Community＇s Residential Environment
AI Bin, XU Jian-Hua , LI Xia, ZHUO Li （ 1. School of Geography and Planning, SUN Yat-Sen University, Guangzhou, Guangdong 510275 ; 2. Department of Geography, East China Normal University, Shanghai, 200062）
Abstract:
At present, as an important scale in the research field of GIS, community is attracted to many scholars. One of the hot spots to study is residential environment. Based on this, method integrated with GIS, spatial data analysis and grid computing to study community＇ s residential environment were proposed in this paper for knowledge discovery of spatial pattern. Selecting 131 streets in downtown of Shanghai as samples, firstly, 23 indices were chosen and fuzzy BP model was used to evaluate the quality of residential environment, secondly, spatial exploring analysis including global and local analysis was used. Several conclusions were drawn： community＇ s residential environment is influenced by different variables, which will result in special pattern in the space. In old core urban area, overall residential environment is general lower than other periphery area mainly for higher population density and too less vegetation coverage; on the other hand, due to the relationship between the variables, residential environment shows local dissimilarity and global similarity. Finally, according to the spatial autocorrelation of residential environment among the communities, strategies for planning the layout of communities were put forward in this paper.[著者文摘]
Key words:
GIS; exploring analysis; grid computing ; residential environment ; spatial pattern
基金资助:
国家自然科学基金项目（40371092）、“985工程”GIS与遥感的地学应用科技创新平台项目（1052032004JD0006）资助.
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