Soil erosion is one of the most serious land degradation problems all over the world, causing irreversible
land quality reduction. In this paper, we modify the Revised Universal Soil Loss Equation (RUSLE) model
by replacing the factors of slope length and gradient with Sediment Transport Index (STI). The Digital
Elevation Model, terrain parameters, Normalized Difference Vegetation Index (NDVI), and rainfall data are
used as inputs to the model. Along with the application of remote sensing techniques and ground survey
measurements, erosion susceptibility maps are produced. The revised models are then used to obtain the
optimal estimate of soil erosion susceptibility at Alianello of southern Italy, which is prone to soil erosion.
The soil loss estimated from the modified RUSLE model shows a large spatial variance, ranging from 10
to as much as 7000 ton ha?1 yr?1. The high erosion susceptible area constitutes about 46.8% of the total
erosion area, and when classified by land cover type, 33% is “mixed bare with shrubs and grass”, followed
by 5.29% of “mixture of shrubs and trees”, with “shrubs” having the lowest percentage of 0.06%. In terms
of slope types, very steep slope accounts for a total of 40.90% and belongs to high susceptibility, whereas
flat slope accounts for only 0.12%, indicating that flat topography has little effect on the erosion hazard. As
far as the geomorphologic types are concerned, the type of “moderate steep–steep slopes with moderate to
severe erosion” is most favorable to high soil erosion, which comprises about 9.34%.
Finally, we validate the soil erosion map from the adapted RUSLE model against the visual interpretation
map, and find a similarity degree of 71.9%, reflecting the efficiency of the adapted RUSLE model in mapping
the soil erosion in this study area.