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. © 2014 Springer International Publishing.

Modelling spatially-distributed soil erosion through remotely-sensed data and GIS

Adamo M;
2014

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. © 2014 Springer International Publishing.
2014
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Inglese
ICCSA
8582 LNCS
372
385
http://www.scopus.com/inward/record.url?eid=2-s2.0-84904870326&partnerID=q2rCbXpz
GIS
Remote sensing
RUSLE
Soil erosion
USPED
3
none
Aiello, A; Adamo, M; Canora, F
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/272559
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