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This case study highlights the importance of resampling to standardize images from different satellites with varying resolutions, especially in the monitoring of environmental phenomena such as wildfires and atmospheric pollutants. Considering the diverse orbits, capture periods, and spatial resolutions of satellites, resampling becomes essential for effective analyses. Classical resampling methods, such as Nearest Neighbor, can be employed to standardize resolutions and enable accurate comparisons. The study focuses on heat source data from the Program Queimadas (INPE) in the Brazilian Pantanal biome and atmospheric data from the Copernicus Data Space (ESA) Sentinel-5P satellite. The results indicate that resampling effectively standardizes the data scale and highlights the correlation between heat sources and aerosol levels, aiding in air quality assessments. The study emphasizes the necessity of resampling in the integration of satellite data to improve air quality monitoring and provide crucial insights into the effects of wildfires on atmospheric conditions.
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