自然科学版
陕西师范大学学报(自然科学版)
资源与环境科学
基于常住人口分布的城市主副中心识别方法——以西安市为例
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米瑞华1, 石英2*
(1 陕西师范大学 国际商学院, 陕西 西安 710119; 2 陕西省社会科学院, 陕西 西安 710065)
米瑞华,女,博士研究生,主要研究方向为人口空间结构分析.E-mail:rice221@163.com.
摘要:
利用西安市第六次人口普查常住人口街道(乡、镇)数据,基于西安市建设用地类型,利用ArcGIS10.0软件生成500 m格网人口密度图,绘制常住人口密度等值线,根据等值线值和等值线所围面积计算备择中心人口规模,结合城市主副中心的定义和经济特征设计筛选条件,辅以城市人口密度模型系数,研究识别城市主副中心数量和位置的一般性方法.研究显示,西安市有唯一主中心(钟楼主中心)和5个城市副中心(小寨副中心、西高新副中心、张家堡副中心、土门副中心和纺织城副中心),各主副中心的坐标位置得以识别和标注.本方法用于城市人口密度模型研究中能够修正模型系数偏误,也可应用于城市规划、商业、公共服务选址等领域.
关键词:
地理信息系统; 城市主中心; 副中心; 常住人口分布; 西安市
收稿日期:
2013-06-03
中图分类号:
C922
文献标识码:
A
文章编号:
1672-4291(2014)03-0097-06
基金项目:
国家社会科学基金资助项目(10BSH006).
Doi:
Identifying method of CBD and sub-CBD based on the distribution of resident population
MI Ruihua1, SHI Ying2*
(1 College of International Business, Shaanxi Normal University, Xi′an 710119,Shaanxi,China; 2 Shaanxi Social Sciences Academy, Xi′an 710065,Shaanxi,China)
Abstract:
The population density distribution map with 500×500 grids is generated by the ArcGIS10.0 software based on the map of land use type and the resident population data of the sixth census data of Xi′an city. The resident population density contours is rendered to calculate the population scale of the alternative CBD or sub-CBD by measuring the areas which are enclosed by the contours. According to the definition and the economic characteristics of CBD and sub-CBD, the screening conditions are designed, and assisted with the coefficients of the urban population density models and the judgments by the authors, a general method to identify the number and location of the CBD and sub-CBD is proposed. Results show that there is only one CBD in Xi′an city (the CBD of Bell Tower), as well as five sub-CBDs (the sub-CBD of Xiaozhai, Xigaoxin, Zhangjiabao, Tumen and Fangzhicheng), and the numbers and positions of CBD and sub-CBDs are identified and labeled. The method can help to correct the bias of the coefficients of urban population density model, and also can be applied in the city designing as well as site selection in the commercial and the public service fields.
KeyWords:
geographic information system(GIS); central business district(CBD); sub-CBDs; distribution of resident population; Xi′an city