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Soil erosion is a major environmental concern because of its devastating effects on agriculture and food production worldwide. In our research, we developed a sophisticated and effective model to predict soil erosion risk and developed a risk map to aid decision making to address earth surface degradation as a means to preserve soil. We describe the modeling process adopting the ICONA (Instituto Nacional para la Conservacion de la Naturaleza) model, in conjunction with an Analytic Hierarchy Process referred to as the AHP, together with the application of a geodatabase and remote sensing data for the Rudbar basin, Guilan Province, Iran. The basin is highly sensitive to soil erosion. With advances in remote sensing and GIS, challenges of conventional methods can be overcome such as the time-consuming and data-intensive identification of soil erosion-prone areas. The land slope, the lithofacies, land-use/cover, vegetation cover, and a digital elevation model (DEM) were our key layer input ....