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将模糊物元模型与地理信息系统相结合,用于生态环境敏感性和土地利用规划分布。

Combining a fuzzy matter-element model with a geographic information system in eco-environmental sensitivity and distribution of land use planning.

机构信息

Institute of Remote Sensing & Information System Application, Zhejiang University, Hangzhou 310029, China.

出版信息

Int J Environ Res Public Health. 2011 Apr;8(4):1206-21. doi: 10.3390/ijerph8041206. Epub 2011 Apr 18.

DOI:10.3390/ijerph8041206
PMID:21695036
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3118885/
Abstract

Sustainable ecological and environmental development is the basis of regional development. The sensitivity classification of the ecological environment is the premise of its spatial distribution for land use planning. In this paper, a fuzzy matter-element model and factor-overlay method were employed to analyze the ecological sensitivity in Yicheng City. Four ecological indicators, including soil condition,, water condition,, atmospheric conditions and biodiversity were used to classify the ecological sensitivity. The results were categorized into five ranks: insensitive, slightly sensitive, moderately sensitive, highly sensitive and extremely sensitive zones. The spatial distribution map of environmental sensitivity for land use planning was obtained using GIS (Geographical Information System) techniques. The results illustrated that the extremely sensitive and highly sensitive areas accounted for 14.40% and 30.12% of the total area, respectively, while the moderately sensitive and slightly sensitive areas are 25.99% and 29.49%, respectively. The results provide the theoretical foundation for land use planning by categorizing all kinds of land types in Yicheng City.

摘要

可持续的生态环境发展是区域发展的基础。生态环境的敏感性分类是土地利用规划进行空间分布的前提。本文采用模糊物元模型和因子叠加法,对宜城市的生态敏感性进行了分析。选取土壤条件、水分条件、大气条件和生物多样性等四个生态指标对生态敏感性进行分级,将生态敏感性分为不敏感、轻度敏感、中度敏感、高度敏感和极度敏感五个等级。利用 GIS(地理信息系统)技术获得了土地利用规划环境敏感性的空间分布图。结果表明,极度敏感区和高度敏感区分别占总面积的 14.40%和 30.12%,中度敏感区和轻度敏感区分别占 25.99%和 29.49%。该结果为宜城市各类土地类型的土地利用规划提供了理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/827a37505546/ijerph-08-01206f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/3279d19227c6/ijerph-08-01206f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/42c60b1693a8/ijerph-08-01206f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/91ca2648e35a/ijerph-08-01206f3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/827a37505546/ijerph-08-01206f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/3279d19227c6/ijerph-08-01206f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/42c60b1693a8/ijerph-08-01206f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/91ca2648e35a/ijerph-08-01206f3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6de/3118885/827a37505546/ijerph-08-01206f4.jpg

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