Among the models used to assess water erosion,the RUSLE model is commonly used.Policy makers can act on cover(C-factor)and conservation practice(P-factor)to reduce erosion,with less costly action on soil surface chara...Among the models used to assess water erosion,the RUSLE model is commonly used.Policy makers can act on cover(C-factor)and conservation practice(P-factor)to reduce erosion,with less costly action on soil surface characteristics.However,the widespread use of vegetation indices such as NDVI does not allow for a proper assessment of the C-factor in drylands where stones,crusted surfaces and litter strongly influence soil protection.Two sub-factors of C,canopy cover(CC)and soil cover(SC),can be assessed from phytoecological measurements that include gravel-pebbles cover,physical mulch,annual and perennial vegetation.This paper introduces a method to calculate the C-factor from phytoecological data and,in combination with remote sensing and a geographic information system(GIS),to map it over large areas.A supervised classification,based on field phytoecological data,is applied to radiometric data from Landsat-8/OLI satellite images.Then,a C-factor value,whose SC and CC subfactors are directly derived from the phytoecological measurements,is assigned to each land cover unit.This method and RUSLE are implemented on a pilot region of 3828 km^(2) of the Saharan Atlas,composed of rangelands and steppe formations,and intended to become an observatory.The protective effect against erosion by gravel-pebbles(50%)is more than twice that of vegetation(23%).The C-factor derived from NDVI(0.67)is higher and more evenly distributed than that combining these two contributions(0.37 on average).Finally,priorities are proposed to decision-makers by crossing the synthetic map of erosion sensitivity and a decision matrix of management priorities.展开更多
文摘Among the models used to assess water erosion,the RUSLE model is commonly used.Policy makers can act on cover(C-factor)and conservation practice(P-factor)to reduce erosion,with less costly action on soil surface characteristics.However,the widespread use of vegetation indices such as NDVI does not allow for a proper assessment of the C-factor in drylands where stones,crusted surfaces and litter strongly influence soil protection.Two sub-factors of C,canopy cover(CC)and soil cover(SC),can be assessed from phytoecological measurements that include gravel-pebbles cover,physical mulch,annual and perennial vegetation.This paper introduces a method to calculate the C-factor from phytoecological data and,in combination with remote sensing and a geographic information system(GIS),to map it over large areas.A supervised classification,based on field phytoecological data,is applied to radiometric data from Landsat-8/OLI satellite images.Then,a C-factor value,whose SC and CC subfactors are directly derived from the phytoecological measurements,is assigned to each land cover unit.This method and RUSLE are implemented on a pilot region of 3828 km^(2) of the Saharan Atlas,composed of rangelands and steppe formations,and intended to become an observatory.The protective effect against erosion by gravel-pebbles(50%)is more than twice that of vegetation(23%).The C-factor derived from NDVI(0.67)is higher and more evenly distributed than that combining these two contributions(0.37 on average).Finally,priorities are proposed to decision-makers by crossing the synthetic map of erosion sensitivity and a decision matrix of management priorities.
