地理学报 ›› 2005, Vol. 60 ›› Issue (1): 143-150.doi: 10.11821/xb200501016

• 区域环境 • 上一篇    下一篇

西安城市扩张及其驱动力分析

吴宏安1, 蒋建军1, 周杰2, 张海龙1, 张丽1, 艾莉2   

  1. 1. 南京师范大学地理科学学院, 南京 210097;
    2. 中国科学院地球环境研究所黄土与第四纪地质国家重点实验室, 西安 710075
  • 收稿日期:2004-07-05 修回日期:2004-11-09 出版日期:2005-01-25 发布日期:2010-09-09
  • 作者简介:吴宏安 (1981-),男,安徽枞阳人,硕士研究生,主要从事遥感与GIS的有关研究工作。E-mail: wha_105@sina.com
  • 基金资助:

    欧盟资助项目 (ICA4-CT-2002-10004); 中国科学院知识创新工程项目 (KZCX3-SW-146)

Dynamics of Urban Expansion in Xi'an City Using Landsat TM/ETM+ Data

WU Hong'an1, JIANG Jianjun1, ZHOU Jie2, ZHANG Hailong1, ZHANG Li1, AI Li2   

  1. 1. The College of Geography Science, Nanjing Normal University, Nanjing 210097, China;
    2. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, CAS, Xi'an 710075, China
  • Received:2004-07-05 Revised:2004-11-09 Online:2005-01-25 Published:2010-09-09
  • Supported by:

    Sustainable Agroecosystem Management and Development of Rural-Urban Interaction in Regions and Cities of China (SUSDEV-CHINA), No.ICA4-CT-2002-10004; Knowledge Innovation Project of Chinese Academy of Sciences, No.KZCX3-SW-146

摘要:

随着人口的增长与经济的发展,尤其我国西部城市在西部大开发的背景下,大中城市的扩张十分明显,深刻地影响城市周边的生态环境。如何快速准确地获取城市扩张信息,并分析其驱动力机制,对于指导城市规划,优化西部生态环境与可持续发展都具有十分重要的意义。作者分别采用了监督分类法和归一化裸露指数 (NDBI) 法提取了西安市的城市边界信息,并对二者进行对比分析,认为监督分类法提取的城市边界信息较为准确。在此基础上通过对相关统计资料的分析,认为西安市城区快速扩张与西部大开发以来西安市固定资产投资额的大幅增加以及经济的快速发展有密切的关系,此外人口的增加、交通等基础设施的发展也是重要的驱动因素。

关键词: NDBI, 驱动力机制, 西安市, 城市扩张, 监督分类法

Abstract:

In this study, we extracted urban boundary of Xi'an with supervised classification and Normalized Difference Barren Index (NDBI), respectively. Supervised classification is the most common method in obtaining land use/cover information. In this study, after data pre-processing, training samples were selected according to spectral features. Unlike conventional classification of land use/cover, in this paper, only two classifications of land cover were chosen, which were urban areas and non-urban areas. This could avoid the urban areas from the effects of too many classes, so that the urban areas could avoid being divided into too many classes. Then maximum likelihood classification was used to map the land use/cover of Xi'an. NDBI is an index like NDVI (Normalized Difference Vegetation Index), which can reflect the information of barrens on the ground. As the spectrum of built-up area is similar to barrens, NDBI is used to obtain urban built-up information. Like NDVI, it is defined as NDBI = (band5-band4)/(band5+band4). By comparing the two different methods, we find that the urban boundary derived from TM image using supervised classification is more accurate than that using NDBI, because the image of NDBI contains not only urban information but also barrens. What's more, it is difficult to distinguish them. Thus, we achieved urban expansion of Xi'an from 2000 to 2003 using supervised classification. Through the analysis of urban boundary of Xi'an in 2000 and 2003, it shown that during the three years, urban expansion in Xi'an was very quick. The urban area of Xi'an in 2000 was 253.37 km2, but in 2003 it reached 358.60 km2, an annual average increase rate of 12.3%. By analyzing related statistics of Xi'an, we drew the conclusion that the rapid urban expansion in Xi'an has been closely related to the fast growth of social capital assets investment and economic development of the Xi'an city since great development of western China. The statistic data show that during the three years from 2000 to 2003, the social capital assets investment rose from 23.2 billion RMB to 47.9 billion RMB, and the GDP of the city of Xi'an grew to 94.0 billion RMB from 64.3 billion RMB. In addition, the increase of population and the development of infrastructure like traffics are also important factors to it.

Key words: urban expansion, supervised classification, NDBI, driving force, Xi’an