of land cover on the erosion in agricultural areas in northern part of Jor
ectively. The differences in soil loss between years were notable giving a clear es in LULC affect considerably the soil erosion
satellite images in time and more rainfall data, if available, would result in more accurate estimations from the model.
4. Conclusion
This study assesses the impact dan in 1992 and 2009. The overall methodology involved the use of the RUSLE model in a GIS
environment to create and compare soil erosion maps of 1992 and 2009 aiming at the identification of soil erosion changes that occurred due to land cover change. The RUSLE model was combined with GIS techniques to analyze the soil loss rates and their distribution under different land uses. The RUSLE model was successfully applied and the C factor was successfully derived from NDVI, resulting in mean erosion loss of 9.53 and 8.97 t/ha/yr for 1992 and 2009 resp
indication that chang rate. A series of