基于GIS-SDA的居民点空间分布研究  

Study on Distribution Patterns of Settlements Based on GIS-SDA

作　　者：闫庆武[1] 卞正富[1] 

机构地区：[1]中国矿业大学环境与测绘学院

出　　处：《地理与地理信息科学》2008年第3期57-61,共5页Geography and Geo-Information Science

基　　金：国家自然科学基金项目(50574095);教育部新世纪优秀人才支持计划资助项目(NCET-04-0487);徐州师范大学自然科学基金项目(06XLB12)

摘　　要：空间数据分析(SDA)与GIS相结合是研究地理现象空间分布规律的重要方法。借助1994年和2004年两期RS图像,得到徐州市居民点空间分布数据,运用GIS-SDA方法研究徐州市1994年和2004年的居民点空间分布模式,并总结了11年间居民点空间分布的动态演变规律。通过最近邻距离分析(运用R统计量)得出徐州市居民点空间分布总体上呈现集聚趋势,且2004年的集聚程度比1994年低;通过计算居民点空间分布的K函数值,发现随着研究尺度的变化,1994年和2004年的居民点空间分布集聚程度均出现先增后降过程。运用核函数与泰森多边形法计算两个年份的居民点密度分布,核函数法能够从总体上反映徐州市居民点密度空间分布的地域差异,而泰森多边形法对居民点密度空间分布的细部差异较敏感。Spatial data analysis （SDA） and GIS play a key role in modeling spatial data. In this paper,the database of Xuzhou settlement distribution which is set up by RS images of 1994 and 2004 is employed to study the spatial distribution characteristics of settlements in Xuzhou with the method of GIS-SDA. The following conclusions can be drawn. By using nearest neighbor analysis and Ripley＇s K function, the clumped pattern of spatial distribution of settlements in Xuzhou is found. The conclusion that the degree of settle- ment agglomeration is decreased in research period can be drawn by the analysis of R index. The Ripley＇s K function indicates that as the investigation scale increasing the degree of settlement agglomeration would be first increased then decreased. Based on method of kernel estimation and Thiessen polygons, the settlement density in Xuzhou is computed. Compared with the two methods, the method of kernel estimation can model the whole change tendency of settlement distribution in Xuzhou clearly, the method of Thiessen polygons is sensitive to local spatial difference of distribution of settlements in Xuzhou

关 键 词：GIS 点模式分析 空间分析 居民点格局 徐州 

分 类 号：K901.8[历史地理—人文地理学] P208[天文地球—地图制图学与地理信息工程]