华南地质2023，Vol.39Issue(4)：704-712,9.DOI:10.3969/j.issn.2097-0013.2023.04.011
基于改进RUSLE模型的西南土石山区水土流失评价
Evaluation of Soil and Water Loss in the Rocky Mountain Area of Southwest China Based on Improved RUSLE Model:Taking Longshan County,Hunan Province as an Example
摘要
Abstract
The RUSLE model,the vegetation management factor C of which is improved based on Landsat re-mote sensing images and the Normalized Mountain Vegetation Index(NDMVI),is used to estimate soil ero-sion from 2000 to 2020 in Longshan County,Hunan Province.The aim is to quickly and scientifically evalu-ate the changes in soil erosion in the study area,and provide a scientific basis for soil erosion control in south-western rocky mountainous areas represented by Longshan County.The NDMVI value range in 2000 in-creased by 0.3158 compared to the Normalized Vegetation Index(NDVI),and the NDMVI value range in 2020 increased by 0.2076 compared to NDVI,with significant increases.This indicates that it is easier to use ND-MVI to distinguish features and eliminate complex terrain impacts.Through image comparison,it can be seen that it is better to use NDMVI to distinguish land features than NDVI,and the accuracy of extracting urban land,water bodies,and other land features is higher,especially in areas with undulating terrain and shaded slopes,which can better invert vegetation cover management factors.The vegetation cover management fac-tor C within mountain vegetation index correction can be used to more accurately distinguish land features,especially in areas with undulating terrain and shaded slopes.This method can be effectively applied to the monitoring and evaluation of soil and water loss in southwestern mountainous areas,achieving rapid and quantitative monitoring of dynamic changes.关键词
土壤侵蚀/RUSLE/NDMVI/植被覆盖管理因子/西南土石山区Key words
soil erosion/RUSLE/NDMIV/vegetation cover and management factor/rocky mountain area of Southwest China分类
天文与地球科学引用本文复制引用
龙思佳,汤媛媛,戴亮亮,乔双,樊旺东,佘雄,孔巍巍..基于改进RUSLE模型的西南土石山区水土流失评价[J].华南地质,2023,39(4):704-712,9.基金项目
中国地质调查局项目(DD20211576) （DD20211576）
