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基于RS的黄土高原天然林资源时空动态变化分析
引用本文:赵鹏祥,强建华,张会儒,陈国领. 基于RS的黄土高原天然林资源时空动态变化分析[J]. 林业科学研究, 2007, 20(3): 307-311
作者姓名:赵鹏祥  强建华  张会儒  陈国领
作者单位:西北农林科技大学林学院,陕西,杨凌,712100;中国林业科学研究院资源信息研究所,北京,100091
基金项目:国家林业局天然林保护工程重点技术研究及试验示范课题
摘    要:
以黄土高原天然林典型分布地区黄龙山林业局蔡家川林场为研究对象,以1997年和2004年两期TM(专题制图仪)影像为主要数据源,结合同年的森林资源二类调查资料,在遥感数字图像处理系统支持下,研究了该林场天然林资源的时空变化.结果表明,1997年至2004年之间,该林杨优势树种面积增加,其中栎类增加了1.8%,油松增加了8.4%,杨树增加了6.7%;同时,其水平空间分布也发生了一定的变化;森林覆盖率增加了16.9%;林地类型之间发生了明显的动态变化,其中,55.5%的采伐迹地变成了油松林地,21.1%的采伐迹地变成了杨类林地.这些明显变化与天然林保护工程的实施有着密切的联系.

关 键 词:遥感  天然林资源  动态变化
文章编号:1001-1498(2007)03-0307-05
收稿时间:2006-04-10
修稿时间:2006-04-10

Dynam ic Spatial-temporalChanges Analysis ofNatural ForestResources Based on RS
ZHAO Peng-xiang,QIANG Jian-hu,ZHANG Hui-ru and CHEN Guo-ling. Dynam ic Spatial-temporalChanges Analysis ofNatural ForestResources Based on RS[J]. Forest Research, 2007, 20(3): 307-311
Authors:ZHAO Peng-xiang  QIANG Jian-hu  ZHANG Hui-ru  CHEN Guo-ling
Affiliation:1. College of Forestry, Northwest Sci-Tech of Agriculture and Forestry University, Yangling 712100,Shaanxi, China; 2. Research Institute of Resource and Information Techniques,CAF, Beijing 100091 ,China
Abstract:
This paper studied the dynamic spatial-temporal changes of natural forest resources based on RS . Caijiachuan Forest Farm, as the typical region of distribution of natural forest,was the research object , the TM images of 1997and 2004 as the main data sources, with the survey data and suppored by IMAGE software ,the authors studied the dynamic spatial-temporal changes of this area. The results showed that the area of dominant tree increased from 1997 to 2004, for example, the oak increased by 1.8%, Chinese pine increased by 8.4%, poplar increased by 6.7% ; Meanwhile, spatial distribution has changed ;forest coverage ratio increased by approximately 16.9% ;obvious dynamic change has been occurred, such as 55.5% of cutting land was covered by Chinese pine and 21.1% was covered by poplar. These obviously changes has close relation with the implementation of the natural forest protection project.
Keywords:remote sensing    natural forest resources    dynamic changes
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