文献类型：期刊文献

中文题名：遥感数据分析林区的植被和土壤侵蚀特征

英文题名：Analysis of Vegetation and Soil Erosion for Forest Areas Using Remote Sensing Data

作者：谭炳香[1] 杜纪山[2]

第一作者：谭炳香

机构：[1]中国林业科学研究院资源信息研究所;[2]国家林业局退耕还林工程管理中心

年份：2006

卷号：42

期号：4

起止页码：7-11

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：948项目"数字林业"关键技术引进(2001-13)。

语种：中文

中文关键词：遥感数据;植被因子;土壤侵蚀;流域分析;USLE模型

外文关键词：remote sensing data; vegetation factor; soil erosion; drainage area analysis; USLE model

分类号：S771.8

摘要：以大兴安岭根河林业局潮查林场为试验区,选择合适时间和空间分辨率的卫星遥感TM数据,从中提取植被类型等有关特征及其空间分布等信息,并将有关的信息转化为通用水土流失方程(USLE)中的地面覆盖因子,计算试验区的土壤侵蚀量,进行侵蚀强度区分,生成土壤侵蚀强度图。结果表明:试验区的水土流失主要受坡度的影响。土壤侵蚀强度图与林相图进行空间叠加分析,获得土壤侵蚀严重的小班分布,从而为试验区的水土保持和流域管理提供依据。
Vegetation coverage plays an important role in decreasing soil loss, protecting environment and improving the standard of living. Therefore. it is very necessary to dynamically estimate the soil erosion in forest areas for guiding the environment protection activities. As the main information resources, remote sensing data can be applied widely for soil erosion estimation. In this paper, the main study focus on the methods of extracting landuse types by using remote sensing data, and estimating soil erosion using revised universal soil loss equation （RUSLE）, for Chaocha forest area, Genhe Forestry Bureau of Inner Mongolia. Firstly, the land-use map of the site area was obtained using TM image. Secondly, slope map was created from digital elevation model （DEM）. Thirdly, the flow accumulation for the site was calculated using DEM data with AreVeiw software, and then compute the slope length-slope factor and average soil loss. Finally, based on the soil erosion intensity classification, soil erosion intensity map was obtained. The soil erosion and its spatial distribution were quantitatively analysed. The result shows that under present conditions, about 90% of the land in the site area was classified as stable, while 10 percent was at the level of high erosion or greater. The main deciding factor in this area was slope.