Integrating USLE and RPA-Derived Products for Soil Loss Estimation in Regenerating Vegetation Areas
Description
This dataset contains geospatial and analytical data used to assess soil erosion dynamics in an area with regenerating vegetation in Franca-SP, Brazil. It includes data from the application of the Universal Soil Loss Equation (USLE) over a 62-year period and volumetric analyses derived from Remotely Piloted Aircraft (RPA) imagery. Variables include land use and cover, rainfall erosivity, vegetation regeneration status, and erosion volumes estimated by both empirical and photogrammetric methods. The dataset enables comparative evaluation between USLE-based estimates and volumetric assessments, supporting research on soil erosion processes, vegetation recovery, and environmental monitoring strategies.
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This dataset contains geospatial and analytical data used to evaluate soil erosion dynamics in an area of regenerating vegetation in Franca, São Paulo State, Brazil. It comprises data from the application of the Universal Soil Loss Equation (USLE) over a 62-year period, as well as volumetric analyses derived from Remotely Piloted Aircraft (RPA) imagery. Variables include rainfall erosivity, soil erodibility, slope length and steepness human interventions and conservation practices, and erosion volumes estimated by both empirical and photogrammetric methods. The dataset enables comparative assessments between USLE-based estimates and volumetric measurements, supporting research on soil erosion processes, vegetation recovery, and environmental monitoring strategies. 1. Data Sources Geospatial Data: The spatial data for the study area were obtained from multiple sources, including the Cartography and Geography Institute (ICG), the Brazilian Institute of Geography and Statistics (IBGE), Google Earth Engine, and RPA imagery. Within the study area, five erosion-prone sites were selected for detailed analyses. Rainfall Erosivity (R Factor): Rainfall erosivity data were calculated based on precipitation records from the National Institute of Meteorology (INMET), using monthly and annual precipitation data for the study area over the analyzed period. Soil Erodibility (K Factor): Pedological data were derived from the Soil Susceptibility Atlas of the State of São Paulo; Slope Length and Steepness (LS Factor): This factor was calculated using contour lines and elevation points vectorized from historical 1:10,000-scale maps produced by the Geographic and Cartographic Institute (ICG); Human Interventions and Conservation Practices (CP Factor): Land-use data for the CP factor were obtained through semi-automatic classification of imagery from the study area; 2. Data Processing Different methods and software tools were used for data processing: QGIS 3.36.3: For processing all USLE factors. Agisoft Metashape: For processing drone imagery and performing volumetric calculations. Microsoft Excel: For calculating the R Factor and conducting result analyses.
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Funding
Fundação de Amparo à Pesquisa do Estado de São Paulo
23/16724-0
Coordenação de Aperfeicoamento de Pessoal de Nível Superior
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