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林业自然地理的模糊聚类区划
引用本文:刘羿,佘光辉,刘安兴,张国江. 林业自然地理的模糊聚类区划[J]. 浙江林学院学报, 2008, 25(4): 422-426
作者姓名:刘羿  佘光辉  刘安兴  张国江
作者单位:1. 南京林业大学森林资源与环境学院,江苏南京,210037;国家林业局调查规划设计院,北京,100714
2. 南京林业大学森林资源与环境学院,江苏南京,210037
3. 浙江省森林资源监测中心,浙江杭州,310020
基金项目:国家自然科学基金资助项目
摘    要:依照相关区划原则,选取林业数据中的有林地、灌木林地、无林地和非林地等4个指标,采用模糊聚类法对研究地浙江省范围内67个县级行政单位实施区划分类,其目的是用数学方法对林业自然地理的量化因子进行数量化研究分析。根据聚类结果将全省分为5个类型,其结果与研究地的自然地理状况基本相符。研究表明:基于模糊聚类的林业自然地理区划是可行的,进一步根据国民经济与社会发展各部门的要求,加入相关的专业数据,可以得到更为综合的区划结果。以行政单位作为区划单元得到的结果,有利于各级政府的决策和对自然资源的总体把握。

关 键 词:森林经理学  区划  模糊聚类  林地数据  浙江

Fuzzy cluster based on nature geographic regionalization of forest
Affiliation:LIU Yi, SHE Guang-hui, LIU An-xing, ZHANG Guo-jiang( 1. College of Forest Resources and Environment, Nanjing Forestly University, Nanjing 210037, Jiangsu, China; 2. Academy of Forest Inventoly and Planning, State Forestly Administration, Beijing 100714, China; 3. Zhejiang Monitoring Center of Forest Resources, Hangzhou 310020, Zhejiang, China)
Abstract:According to related regionalization principles, this research selected four indices including the area of forest land, shrubbery, non-stocked land and non-forestry land. Based on the principle of fuzzy cluster analysis, 67 counties in Zhejiang Province were clustered into 5 groups. The results basically accorded with the actual condition. The results indicated that it was feasible to regionalize by fuzzy cluster. And other data were added to accomplish some more complicated regionalization. The regionalization results were meaningful for governments to make decision and manage the nature resource when it was partitioned by administrative unit.
Keywords:forest management  regionalization  fuzzy cluster  forest data  Zhejiang Province
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