Integration of Remote Sensing Data (Sentinel-2 and Alos Palsar) for Geological Prospecting of Limestone in the Apiaí/SP Region
DOI:
https://doi.org/10.11137/1982-3908_2026_49_70043Keywords:
Geological mapping, Remote sensing, Principal component analysisAbstract
The Digital Image Processing (DIP) of satellite data constitutes a fundamental tool for the extraction and analysis of geospatial information, with multidisciplinary applications in remote sensing, precision agriculture, geology, and environmental studies. Among the DIP techniques applied to geological mapping, Principal Component Analysis (PCA) and RGB composites stand out for their efficiency in distinguishing different lithological bodies. The main objective of this study was, therefore, to consolidate the results of advanced DIP by combining multispectral imagery from the MSI/Sentinel-2 sensor with radar data derived from Alos Palsar. The research area is located in the municipality of Apiaí, in the Ribeira Valley (Southwest of SP), within the Ribeira Meridional Belt. The adopted methodology integrated MSI/Sentinel-2 and Alos Palsar data, primarily processed in the QGIS digital image processing plugins. For spectral enhancement, PCA and RGB composites were applied, complemented by Hillshade analysis for morpho-structural extraction. The synthesis of these products was then finalized in a GIS environment (ArcGIS). The integration of these multi-sensor datasets resulted in the mapping of six principal lithological units. The Limestone areas were delimited with high precision, taking advantage of the spectral contrast generated by PCA2 and the RGB composites. Additionally, the rugosity and Hillshade analysis revealed a strong NE-SW structural control governing the distribution of these units. The final geological map and the limestone potential map, validated through field campaigns, demonstrated the efficacy of the methodology for the accurate identification of lithological targets in areas of high vegetation density.
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