• 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