The dissertation aims to assess the impact of intensive vine cultivation on soil erosion near Verona, in the Monteforte d’Alpone area, through a multi-temporal analysis of digital elevation models (DEMs) derived from photogrammetry and LiDAR (Light Detection and Ranging). By applying the RUSLE (Revised Universal Soil Loss Equation) model to a 1981 DEM generated through photogrammetry of aerial photos and to a LiDAR-derived DEM from 2008, the study analyzes changes in soil erosion over time. The mean 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 from RUSLE were compared with current DEMs, created using drone-based photogrammetry and LiDAR, to evaluate accuracy and verify the correlation between erosion predictions and actual conditions. The study demonstrated the suitability of generating high-resolution DEMs from aerial photogrammetry for RUSLE application. Using this model to estimate soil erosion in 1981 and 2008 yielded consistent results, corroborated by observations carried out on the field. The multi-temporal analysis highlighted variations linked to changes in land use and slope reshaping interventions. The main challenges were related to the availability of historical data, while DEM resolution and accuracy proved critical for reliable results. In the future, a more precise calculation of the K and P factors could enhance the model’s reliability, supporting sustainable land management planning.
La tesi si propone di valutare l’impatto della coltivazione intensiva della vite sull’erosione del suolo nei pressi di Monteforte d’Alpone, in provincia di Verona, attraverso un’analisi multi-temporale su modelli digitali del terreno (DEM) ottenuti tramite fotogrammetria e LiDAR (Light Detection and Ranging). Applicando il modello RUSLE (Revised Universal Soil Loss Equation) a un DEM del 1981, ottenuto tramite fotogrammetria da foto aeree, e a uno derivato da LiDAR del 2008, si analizza la variazione di erosione del suolo nel tempo. L’erosione media stimata sull’area studio è di 20,95 (Mg ha⁻¹ yr⁻¹) per il 1981 e di 15,72 (Mg ha⁻¹ yr⁻¹) per il 2008, valori rispettivamente di 20 e 15 volte superiori a quello ritenuto sostenibile da uno studio analogo condotto a livello europeo. I risultati prodotti da RUSLE sono stati confrontati con i modelli digitali del terreno attuali, generati tramite fotogrammetria e LiDAR da drone, per valutarne l'accuratezza e verificare la corrispondenza tra le previsioni di erosione e le condizioni reali. Lo studio ha dimostrato che è possibile ottenere un DEM ad alta risoluzione da fotogrammetria di foto aeree su cui applicare RUSLE. L’utilizzo di questo modello per stimare l’erosione del suolo, prima nel 1981 e poi nel 2008, ha prodotto risultati coerenti con riscontri attuali. Infatti, l’analisi multi-temporale ha evidenziato variazioni legate ai cambiamenti d’uso del suolo e agli interventi sui versanti. Le criticità principali riguardano la reperibilità dei dati storici, mentre l’accuratezza e la risoluzione del DEM si sono confermate cruciali. In futuro, un calcolo più preciso dei parametri K e P potrebbe migliorare l’affidabilità del modello, supportando una pianificazione territoriale sostenibile.
L’erosione del suolo in un contesto di agricoltura intensiva nei Lessini Veronesi: modellistica multi-temporale su DEM da fotogrammetria e LiDAR
RIGON, BARBARA
2023/2024
Abstract
The dissertation aims to assess the impact of intensive vine cultivation on soil erosion near Verona, in the Monteforte d’Alpone area, through a multi-temporal analysis of digital elevation models (DEMs) derived from photogrammetry and LiDAR (Light Detection and Ranging). By applying the RUSLE (Revised Universal Soil Loss Equation) model to a 1981 DEM generated through photogrammetry of aerial photos and to a LiDAR-derived DEM from 2008, the study analyzes changes in soil erosion over time. The mean 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 from RUSLE were compared with current DEMs, created using drone-based photogrammetry and LiDAR, to evaluate accuracy and verify the correlation between erosion predictions and actual conditions. The study demonstrated the suitability of generating high-resolution DEMs from aerial photogrammetry for RUSLE application. Using this model to estimate soil erosion in 1981 and 2008 yielded consistent results, corroborated by observations carried out on the field. The multi-temporal analysis highlighted variations linked to changes in land use and slope reshaping interventions. The main challenges were related to the availability of historical data, while DEM resolution and accuracy proved critical for reliable results. In the future, a more precise calculation of the K and P factors could enhance the model’s reliability, supporting sustainable land management planning.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/80192