Land degradation is a phenomenon that describes the degradation of soil quality, the causes are multiple, some dynamics related to agriculture have particularly influenced the process of degradation. Specifically, agricultural overexploitation with unsustainable practices and the abandonment of agricultural land can cause pedological alterations of the most superficial layers of the soil that with intense rainfall and trigger the process of soil erosion. The aim of this work is to evaluate the dynamics and relationships between erosion processes and land cover changes. The approach employed is based on GIS and remote sensing. An initial analysis involved the application of the Revised Universal Soil Loss Equation (RUSLE) model to calculate soil erosion on an annual basis. The resulting data were then processed through a Getis-Ord local autocorrelation index to produce a persistent erosion map. The resulting dataset was compared to land cover classes of arable and brownfield areas. Finally, an attempt was made to quantify and test the relationships between erosion rate and the period of abandonment. Models and survey techniques have been applied in a rural area of Basilicata Region (South Italy) using exclusively a GIS Free and Open-Source Software and remote sensing approach.
Towards Quantifying Rural Environment Soil Erosion: RUSLE Model and Remote Sensing Based Approach in Basilicata (Southern Italy)
Santarsiero V;Lanorte A;
2022
Abstract
Land degradation is a phenomenon that describes the degradation of soil quality, the causes are multiple, some dynamics related to agriculture have particularly influenced the process of degradation. Specifically, agricultural overexploitation with unsustainable practices and the abandonment of agricultural land can cause pedological alterations of the most superficial layers of the soil that with intense rainfall and trigger the process of soil erosion. The aim of this work is to evaluate the dynamics and relationships between erosion processes and land cover changes. The approach employed is based on GIS and remote sensing. An initial analysis involved the application of the Revised Universal Soil Loss Equation (RUSLE) model to calculate soil erosion on an annual basis. The resulting data were then processed through a Getis-Ord local autocorrelation index to produce a persistent erosion map. The resulting dataset was compared to land cover classes of arable and brownfield areas. Finally, an attempt was made to quantify and test the relationships between erosion rate and the period of abandonment. Models and survey techniques have been applied in a rural area of Basilicata Region (South Italy) using exclusively a GIS Free and Open-Source Software and remote sensing approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.