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作 者:ZHANG Hengming, WANG Qingli, DAI Limin, Guofan Shao, TANG Una, WANG Shunzhong & GU Huiyan Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China Graduate University of Chinese Academy of Sciences, Beijing 100101, China Department of Forestry and Natural Resources, Purdue University, Lafayette IN47901, USA Northeast Forestry University, Harbin 150040, China
出 处:《Science China(Technological Sciences)》2006年第z1期160-166,共7页中国科学(技术科学英文版)
摘 要:Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by forest management practices was studied at Jianchang Forest Farm. The GIS provided means of input data generation required by RUSLE model and allowed a spatial assessment of the erosion hazard over the study area. Four exposed soil proportion scenarios of 5%, 10%, 20% and 30% were tested with the GIS-based RUSLE model to evaluate soil erosion hazard. The predicted soil erosion potentials were classified into five categories in order to provide valuable aids for management planning.Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by forest management practices was studied at Jianchang Forest Farm. The GIS provided means of input data generation required by RUSLE model and allowed a spatial assessment of the erosion hazard over the study area. Four exposed soil proportion scenarios of 5%, 10%, 20% and 30% were tested with the GIS-based RUSLE model to evaluate soil erosion hazard. The predicted soil erosion potentials were classified into five categories in order to provide valuable aids for management planning.
关 键 词:GEOGRAPHIC information system RUSLE soil erosion forest management.
分 类 号:TP399[自动化与计算机技术—计算机应用技术]
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