Estimation of soil erosion using common empirical models has long been an active research topic. Nevertheless, application of those models at basin scale is still a challenge due to data availability and quality. In this study, the Revised Universal Soil Loss Equation (RUSLE) and the Unit Stream Power-based Soil Erosion/Deposition (USPED) were applied and compared to determine the spatial distribution of soil erosion of a coastal watershed in Basilicata, southern Italy. A comprehensive approach that integrates ancillary data, digital terrain model, products derived from satellite remote sensing (multi-temporal Landsat imagery) and GIS techniques was adopted to identify major factors influencing soil erosion. Soil loss and soil erosion/deposition maps were produced. The study provided a reliable prediction of soil erosion rates and definition of erosion-prone areas within the watershed.
Modelling spatially-distributed soil erosion through remotely-sensed data and GIS
AIELLO, ANTONELLO;CANORA, Filomena
2014-01-01
Abstract
Estimation of soil erosion using common empirical models has long been an active research topic. Nevertheless, application of those models at basin scale is still a challenge due to data availability and quality. In this study, the Revised Universal Soil Loss Equation (RUSLE) and the Unit Stream Power-based Soil Erosion/Deposition (USPED) were applied and compared to determine the spatial distribution of soil erosion of a coastal watershed in Basilicata, southern Italy. A comprehensive approach that integrates ancillary data, digital terrain model, products derived from satellite remote sensing (multi-temporal Landsat imagery) and GIS techniques was adopted to identify major factors influencing soil erosion. Soil loss and soil erosion/deposition maps were produced. The study provided a reliable prediction of soil erosion rates and definition of erosion-prone areas within the watershed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
