Abstract
Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the assessment of soil erosion even more difficult. Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors. RUSLE considers rainfall (R), topography (LS), soil erodibility (K), cover management (C), and support practice (P) as important factors affecting soil erosion. In the past few years, RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing. In this paper, an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided, placing an emphasis on related successes and challenges. This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges. Future research, however, must pay special attention to error assessment of remote sensing-derived RUSLE parameters.
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