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耕地系统可持续发展的空间影响因子分析
引用本文:钱峻屏,叶树宁,李岩.耕地系统可持续发展的空间影响因子分析[J].遥感技术与应用,2002,17(2):93-98.
作者姓名:钱峻屏  叶树宁  李岩
作者单位:(广州地理研究所,广东广州 510070)
摘    要:可持续发展的理念已经被人们普遍接受,然而,从概念到操作、从理论到实践,并非一蹴而就。其中最关键的问题就是建立一个可操作、具有实用性的指标体系,从而使可持续发展的理论和模式能够具体应用于指导实际工作。探讨将遥感对地观测数据、GIS空间数据和常规统计数据相结合,构建可持续发展指标体系的基本思路及方法,提出采用基于耕地单元的区域统计和基于空间特征的聚类分析方法,并进一步分析了各种空间特征及空间结构对耕地系统可持续发展的影响,从而为建立可持续发展的定量综合分析模型提供了一个思路。

关 键 词:可持续发展  空间统计分析  遥感  地理信息系统(GIS)  
文章编号:1004-0323(2002)02-0093-06
修稿时间:2001年12月28

A Zonal Spatial Statistic Method Applied to the Study of Sustainable Development of Agricultural Land
QIAN Jun\|ping,YE Shu\|ning,LI Yan.A Zonal Spatial Statistic Method Applied to the Study of Sustainable Development of Agricultural Land[J].Remote Sensing Technology and Application,2002,17(2):93-98.
Authors:QIAN Jun\|ping  YE Shu\|ning  LI Yan
Affiliation:(Guangzhou Institute of Geography,Guangzhou510070,China)
Abstract:Sustainable development (SD) has been accepted as a philosophical concept for long time. In this article, an integrated SD criteria system and an operable SD analysis method was set up on purpose of enable quantitative SD study of agricultural land. Firstly, data from RS, GIS and normal statistic department, which mainly focus on the spatial features of agricultural land, was integrated to construct a synthetical SD criteria system. Then, a series of plot\|based spatial analysis and zonal statistics methods, which worked under ERDAS and ARC/INFO, was used to evaluate the spatial background feature of each land parcel. After that, SPSS was used to perform statistic analysis, such as dimension reduction and cluster analysis, on the large amount of dataset resulting from spatial analysis. Finally, the fast growing city of Guangdong Province, Dongguan was chosen as the sample area to evaluate its land\|use change from 1988~1998. Some objective, quantitative and spatial\|characteristic conclusion was calculated about the SD status of the agricultural land in Dongguan, These valuable results greatly enable our further understanding of the SD status of our living environment.
Keywords:Sustainable development  Spatial statistics  Remote sensing  GIS
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