文献类型：期刊文献

中文题名：基于3S技术的天保区植被变化监测方法研究

英文题名：Vegetation Change Monitoring for the Natural Forest Protection Based on Spatial Analysis Techniques

作者：陈巧[1] 陈永富[1] 鞠洪波[1]

第一作者：陈巧

机构：[1]中国林业科学研究院资源信息研究所

年份：2013

卷号：26

期号：6

起止页码：736-743

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：中央级公益性科研院所基本科研业务费专项资金(项目编号:CAFYBB2012020)

语种：中文

中文关键词：TM遥感影像;天然林保护工程区;空间分析技术;土地利用分类;植被覆盖度

外文关键词：Landsat TM image; natural forest protection area; spatial analysis techniques; land-use classification;vegetation fraction

分类号：S771.8

摘要：以甘肃省清水县天然林保护区植被时空变化为研究对象,以2期Landsat TM遥感影像为主要信息源,以植被面积和植被覆盖度为监测指标,采用最大似然方法进行监督分类获得土地利用分类图和植被面积,采用NDVI像元二分法获得植被覆盖度图。利用空间分析和统计分析方法将土地利用分类图和植被覆盖度图进行空间叠加分析,揭示研究区1996—2004年间土地利用和植被覆盖度的数量变化和空间变化特征,并对天保区与非天保区以及不同天保区内部的差异进行对比分析。研究结果表明:1996年—2004年间甘肃省清水县天然林保护区森林面积和植被覆盖度得到了明显改善,且天保区优于非天保区;不同类型天保区植被变化状况有差异,3种类型天然林保护区中以重点生态保护区植被改善状况最为显著。
The number and spatiotemporal change characters of the vegetation in natural forest protection area of Qingshui County, Gansu Province, were investigated and the external and internal differences during the period of 1996 to 2004 were compared with two indicators： the vegetation area which came from the land-use classification map by the maximum likelihood classification （MLC） and the vegetation fraction by the NDVI dimidiate pixel model based on two Thematic Mapper （TM） images, by using spatial analysis and statistical techniques. The results indi- cated that the forest area and the vegetation fraction improved more evidently in the natural forest protection area than in the other area during the period of 1996 to 2004 in the study area. In addition, the degree of the vegetation change differed among different types of the natural forest protection area, the key ecological reserve area of the nat- ural forest protection showed the most remarkable improvement. The results of the study suggest that this method is feasible and ecosystem conditions of the natural forest protection area have been improved as the result of the imple- mentation of classified management policies.