Dynamics of linear erosion processes in São Paulo State urban areas
Description
Dataset Description This dataset contains geospatial data used to investigate the dynamics of linear erosion processes in urban areas of São Paulo State, Brazil. The dataset includes spatial information on various factors influencing erosion, such as geomorphology, geology, pedology (soil types), land use, rainfall erosivity, and geomorphometric variables (elevation, slope, aspect, and curvature). 1. Data Sources: Geospatial Data: The erosion features (ravines and gullies) were mapped by the Technological Research Institute (IPT) in 2012, based on primary cartographic material, satellite imagery (CBERS-2B), and field visits. The dataset includes 1,398 erosion spots identified within urban areas of São Paulo State. Land Use Data: Land use data were obtained from the IPT (2012) and the MapBiomas Project (2010), which provides land cover classifications for Brazil. Rainfall Erosivity Data: Rainfall erosivity data were derived from Ricardi and Lima (2022), based on spatial extrapolations from rain gauge stations across São Paulo State. Geomorphometric Data: Digital Elevation Models (DEMs) from the Brazilian Farming Information Center (CATI, 2016), based on NASA’s Shuttle Radar Topography Mission (SRTM) and ASTER GDEM V2, were used to extract variables like elevation, slope, aspect, profile curvature, and plan curvature. 2. Data Processing: The dataset includes processed variables that were used to model and analyze linear erosion processes through machine learning techniques, specifically the Classification and Regression Trees (CART) algorithm. The data were preprocessed in the ArcGIS Pro 2.8.3 environment, where they were reclassified and integrated for use in erosion susceptibility analysis. 3. Variables Included in the Dataset: Erosion Features: Spatial locations of ravines and gullies in urban areas of São Paulo State. Material of Origin: Geomorphology, geology, and pedology information for each erosion feature. Land Use: Categories for upstream and downstream land use, as well as land cover data. Rainfall Erosivity: Spatial distribution of rainfall erosivity values across São Paulo State. Geomorphometric Variables: Elevation, slope, aspect, profile curvature, and plan curvature data extracted from the DEM. 4. Purpose and Application: This dataset was created to support the analysis of urban erosion processes and their driving factors. It can be used by researchers and practitioners in urban planning, environmental management, and landscape ecology to assess erosion susceptibility, plan for soil conservation, and inform sustainable urban development practices. The dataset also provides valuable insights into the application of GIS and machine learning techniques for spatial data analysis.
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1. Data Sources: Geospatial Data: The erosion features (ravines and gullies) were mapped by the Technological Research Institute (IPT) in 2012, based on primary cartographic material, satellite imagery (CBERS-2B), and field visits. The dataset includes 1,398 erosion spots identified within urban areas of São Paulo State. Land Use Data: Land use data were obtained from the IPT (2012) and the MapBiomas Project (2010), which provides land cover classifications for Brazil. Rainfall Erosivity Data: Rainfall erosivity data were derived from Ricardi and Lima (2022), based on spatial extrapolations from rain gauge stations across São Paulo State. Geomorphometric Data: Digital Elevation Models (DEMs) from the Brazilian Farming Information Center (CATI, 2016), based on NASA’s Shuttle Radar Topography Mission (SRTM) and ASTER GDEM V2, were used to extract variables like elevation, slope, aspect, profile curvature, and plan curvature. 2. Data Processing: The dataset includes processed variables that were used to model and analyze linear erosion processes through machine learning techniques, specifically the Classification and Regression Trees (CART) algorithm. The data were preprocessed in the ArcGIS Pro 2.8.3 environment, where they were reclassified and integrated for use in erosion susceptibility analysis.
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Funding
National Council for Scientific and Technological Development
311393/2021-7
Coordenação de Aperfeicoamento de Pessoal de Nível Superior
88887.658530/2021-00