首页 | 本学科首页   官方微博 | 高级检索  
     

基于矢量网格的城市土地利用邻里模式研究
引用本文:李也,龚咏喜,张兆东,冯长春. 基于矢量网格的城市土地利用邻里模式研究[J]. 地理学报, 2018, 73(11): 2236-2249. DOI: 10.11821/dlxb201811014
作者姓名:李也  龚咏喜  张兆东  冯长春
作者单位:1. 北京大学城市与环境学院,北京 1008712. 哈尔滨工业大学(深圳)深圳市城市规划与决策仿真重点实验室,深圳 5180553. 哈尔滨工业大学(深圳)建筑学院,深圳 518055
基金项目:国家自然科学基金项目(41771169, 41371169);国土资源部公益性行业科研专项(201511010-3A);广东省科技计划项目(2013B040401003)
摘    要:城市土地利用的空间分布特征一直是城市地理和城市规划领域关注的重点问题,对城市土地利用空间模式的研究有助于理解城市系统的运行状态。在分析现有城市空间结构和城市土地利用模式的基础上,从两个方面对现有基于富集因子的分析方法提出改进,一是采用矢量网格以减少分析的误差,二是采用斜网格和曼哈顿距离来对空间临近关系进行界定。采用这一方法对深圳市2015年6类城市土地利用数据进行分析,得到邻里尺度上各类用地之间富集度随距离变化的3种模式。模式I中,同类用地间的富集度在短距离内较大,且其值随着距离的增加而减小并趋于0,表明同类用地间在较短距离内相互吸引,而吸引力随着距离增加而减弱。在不同类型用地间的模式II和模式III中,富集度在较短距离内为负值,但是在模式II中,富集度随着距离的增加而逐渐增加并趋于0,表明不同用地间短距离内相互排斥,且排斥作用随着距离增加而减弱;而在模式III中,富集度则随着距离增加而快速上升到正值,然后逐渐下降并趋于0,表明不同类型用地在较短距离内相互排斥,但随着距离增加很快变为相互吸引,最后吸引力随着距离增加慢慢减弱。结果表明,相对于基于栅格网的分析方法,基于矢量斜网格的分析方法能够显著降低分析误差。

关 键 词:城市土地利用  邻里模式  富集因子  矢量网格  
收稿时间:2017-09-29

On the neighborhood patterns of urban land use using vector grids
LI Ye,GONG Yongxi,ZHANG Zhaodong,FENG Changchun. On the neighborhood patterns of urban land use using vector grids[J]. Acta Geographica Sinica, 2018, 73(11): 2236-2249. DOI: 10.11821/dlxb201811014
Authors:LI Ye  GONG Yongxi  ZHANG Zhaodong  FENG Changchun
Affiliation:1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
2. Shenzhen Key Laboratory of Urban Planning and Decision Making, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, Guangdong, China
3. School of Architecture, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, Guangdong, China;
Abstract:The spatial distribution of urban land use is an important issue in urban geography and urban planning, and the research on the spatial patterns of urban land use could help us to understand the status of urban systems. We reviewed the research progress on urban spatial structure and urban land use patterns, and we improved the existing methods of enrichment factors from two aspects to analyze the neighborhood patterns of urban land use. The first was to adopt vector grids instead of raster grids to decrease errors, and the second was to use fastigiated grids and Manhattan distance to measure the neighborhood. We used the proposed method to analyze six types of urban land uses in Shenzhen in 2015 and identified three neighborhood patterns that revealed the variation of enrichment degrees between different types of urban land uses with respect to distance. Pattern I showed that the enrichment degree between the same urban land use type was high over short distances and became low over increasing distances, indicating the attraction of the same type of urban land use within short distances and the decrease of attraction over long distances. The value of the enrichment degree between different types of land uses was negative over short distances in both Pattern II and Pattern III. In Pattern II the enrichment degree gradually increased to 0 when the distance increased, demonstrating the repulsion between different types of land uses over short distances and the decrease of repulsion over long distances. In Pattern III the enrichment degree increased quickly to a positive value, then decreased gradually to 0, which revealed repulsion between different types of land uses over short distances, and the interaction became attraction over long distance. Compared with the method based on raster grids, the proposed method based on fastigiated vector grids can reduce the error of neighborhood patterns of urban land uses.
Keywords:urban land use  neighborhood pattern  enrichment factor  vector grid  
点击此处可从《地理学报》浏览原始摘要信息
点击此处可从《地理学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号