DocumentCode :
2706705
Title :
Estimation of the USLE cover and management factor C using satellite remote sensing: A review
Author :
Zhang, Weiwei ; Zhang, Zengxiang ; Liu, Fang ; Qiao, Zhuping ; Hu, Shunguang
Author_Institution :
Inst. of Remote Sensing Applic., Chinese Acad. Sci., Beijing, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
1
Lastpage :
5
Abstract :
Soil erosion has been one of the worldwide environmental disasters which severely threaten the sustainable development of socio-economic, natural resources, and the environment. The Universal Soil Loss Equation (USLE) is the most widely used model to quantify soil erosion. The cover and management factor C is perhaps the most important USLE factor because it represents conditions that can most easily be managed to reduce erosion. Satellite remote sensing can contribute through providing spatial data to assessment of C factor. Thus, many studies have been launched during the past 40 years. The paper mainly discusses the spatial data that is extracted from remote sensing images for estimating C factor: (1) land cover classification map, (2) image bands or ratios, (3) vegetation indices, (4) vegetation coverage. It is concluded that satellite remote sensing has been indispensible in C factor studies and its application need to penetrate deeply in future.
Keywords :
disasters; erosion; hydrological techniques; soil; terrain mapping; vegetation mapping; USLE cover estimation; USLE factor assessment; USLE management factor C; environmental disasters; image bands; image ratios; land cover classification map; remote sensing images; satellite remote sensing; soil erosion quantification; spatial data; sustainable development; universal soil loss equation; vegetation coverage; vegetation indices; Agriculture; Earth; Mathematical model; Remote sensing; Satellites; Soil; Vegetation mapping; C factor; USLE; semote Sensing; vegetation coverage; vegetation index;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics, 2011 19th International Conference on
Conference_Location :
Shanghai
ISSN :
2161-024X
Print_ISBN :
978-1-61284-849-5
Type :
conf
DOI :
10.1109/GeoInformatics.2011.5980735
Filename :
5980735
Link To Document :
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