The study evaluates the impact of intensive vine cultivation on soil erosion near Verona, in the Monteforte d’Alpone area, with an innovative technique consisting of the multi-temporal analysis of DEMs derived from photogrammetry and LiDAR. By applying the Revised Universal Soil Loss Equation (RUSLE) model to a 1981 DTM generated through photogrammetry of aerial photos and to a LiDAR-derived DTM from 2008, the study analyses changes in soil erosion over time. The mean potential soil erosion rates calculated for the study area are 20.95 (Mg ha⁻¹ yr⁻¹) in 1981 and 15.72 (Mg ha⁻¹ yr⁻¹) in 2008, which are 20 and 15 times higher, respectively, than the thresholds considered sustainable in a comparable European-scale analysis. The results have been compared with DEMs generated in summer 2024 by drone-based photogrammetry and LiDAR, to evaluate accuracy and verify the correlation between erosion predictions and present field conditions. The application of RUSLE modelling to estimate soil erosion yielded consistent results across the years 1981, 2008 and 2024, that were corroborated by observations carried out in the field, demonstrating it is possible to generate high-resolution DEMs from aerial photogrammetry, which are suitable for the application of soil erosion models, such as RUSLE.

Soil Erosion And Intensive Agriculture (Lessini Veronesi, NE Italy): Multi-Temporal Modelling On DEMs From Photogrammetry And Lidar

Sandro Rossato;
2025

Abstract

The study evaluates the impact of intensive vine cultivation on soil erosion near Verona, in the Monteforte d’Alpone area, with an innovative technique consisting of the multi-temporal analysis of DEMs derived from photogrammetry and LiDAR. By applying the Revised Universal Soil Loss Equation (RUSLE) model to a 1981 DTM generated through photogrammetry of aerial photos and to a LiDAR-derived DTM from 2008, the study analyses changes in soil erosion over time. The mean potential soil erosion rates calculated for the study area are 20.95 (Mg ha⁻¹ yr⁻¹) in 1981 and 15.72 (Mg ha⁻¹ yr⁻¹) in 2008, which are 20 and 15 times higher, respectively, than the thresholds considered sustainable in a comparable European-scale analysis. The results have been compared with DEMs generated in summer 2024 by drone-based photogrammetry and LiDAR, to evaluate accuracy and verify the correlation between erosion predictions and present field conditions. The application of RUSLE modelling to estimate soil erosion yielded consistent results across the years 1981, 2008 and 2024, that were corroborated by observations carried out in the field, demonstrating it is possible to generate high-resolution DEMs from aerial photogrammetry, which are suitable for the application of soil erosion models, such as RUSLE.
2025
Istituto di Geoscienze e Georisorse - IGG - Sede Secondaria Padova
978-88-8080-765-0
RUSLE, soil erosion, DEM, photogrammetry
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Descrizione: Soil Erosion And Intensive Agriculture (Lessini Veronesi, NE Italy): Multi-Temporal Modelling On DEMs From Photogrammetry And Lidar.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/583078
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