Sentinel-2 image analysis in mapping forest formations in the municipality of Uberaba-MG
DOI:
https://doi.org/10.14808/sci.plena.2023.129901Keywords:
Random Forest, Google Earth Engine, MapBiomasAbstract
Deforestation of native forests has been the focus of discussions around the world due to the negative impact provided in various sectors, such as agriculture, water supply, climate change, among others. The use of satellite mapping technologies is crucial for monitoring deforestation and its causes, enabling more effective actions in forest protection. The objective of this study was to analyze the use of images from the Sentinel-2 satellite to map forest formations in Uberaba, Minas Gerais. For this, we used the processing of data in the cloud from Google Earth Engine (GEE). Supervised classification of images between 2016 and 2019 was performed using the Random forest algorithm. The results were compared with MapBiomas data, as it is the most consolidated mapping project on a national scale. The results show that the area occupied by forest formations is equivalent, on average, to 12.22% of the total area of the municipality. When comparing the results obtained in the present study with MapBiomas, it is noted that there was similarity between the two mappings in most of the study area Sentinel-2 images were effective in mapping forest formations and data processing in GEE made the process faster.
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Copyright (c) 2024 Alex Garcez Utsumi, Nubya Martins de Almeida Oliveira, Nadia Guimarães Sousa
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