GIS AND REMOTE SENSING INTEGRATION FOR SOIL EROSION ASSESSMENT BASED ON A RUSLE MODEL IN UPNM CATCHMENT

Abstract

 Soil erosion is the main threat that causes land deterioration and is one of the ultimate problems of the twenty-first century. Our study aims to determine soil erosion at the Universiti Pertahanan Nasional Malaysia (UPNM) catchment using an integrated Geographic Information System (GIS) and remote sensing (RS) utilizing the Revised Universal Soil Loss Equation (RUSLE) model. The parameters for the model are soil erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover (C), and practice of land management (P), which are prepared using the varied input datasets in the ArcGIS software. The final maps model was the nearest sampled, and the soil erosion rate was calculated using an algebra map in ArcGIS. The results show that the soil erosion at the catchment is spatially varied between 0 and 99.1 t ha^-1 yr^-1. The rate of soil erosion was lower than 2.3 t ha^-1 yr^-1, estimated to be about 43% of the UPNM area, i.e., the highest percent of soil erosion. Moreover, the highest soil erosion is 43.5 to 99.1 t ha^-1 yr^-1. Overall, the findings described the spatial pattern of soil eroded within the catchment. Thus, the proposed integrated model is useful for explaining the erosion process within the river and land system of a small area.