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Spatio-Temporal Deep Learning Approach to Map Deforestation in Amazon Rainforest.

, , , , , and . IEEE Geosci. Remote. Sens. Lett., 18 (5): 771-775 (2021)

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Evaluation Of The Optimal Image Segmentation Parameters For Deforestation Mapping Using The Shepherd Method., , , , , and . GEOINFO, page 81-89. MCTI/INPE, (2023)Automated cloud coverage analysis with Brazil Data Cube., , , , , , and . GEOINFO, page 204-209. MCTIC/INPE, (2021)Applying A Phenological Object-Based Image Analysis (Phenobia) for Agricultural Land Classification: A Study Case in the Brazilian Cerrado., , , , , , , , , and 1 other author(s). IGARSS, page 1078-1081. IEEE, (2020)Deteccao e delimitacao automatica de corpos hidricos em imagens Sentinel-2: uma proposta de integracao do algoritmo Fmask aos indices espectrais NDWI e MNDWI., , , , and . GEOINFO, page 340-345. MCTIC/INPE, (2017)Improvements to Expectation-Maximization Approach for Unsupervised Classification of Remote Sensing Data., , , , and . GEOINFO, page 3-11. INPE, (2007)Segmentation of optical remote sensing images for detecting homogeneous regions in space and time., , , , , , , , and . GEOINFO, page 40-51. MCTIC/INPE, (2017)Remote sensing image information mining applied to burnt forest detection in the Brazilian Amazon., and . GEOINFO, page 322-333. MCTIC/INPE, (2017)Image Processing Techniques for Automatic Registration: Applications in PAN/CBERS-4., , , , , , , and . GEOINFO, page 388-393. MCTI/INPE, (2023)Object-based image analysis for urban land cover classification in the city of Campinas - SP, Brazil., , , , , , and . JURSE, page 1-4. IEEE, (2015)Potential of Using Sentinel-1 Data to Distinguish Targets in Remote Sensing Images., , , , , , and . ICCSA (4), volume 11622 of Lecture Notes in Computer Science, page 563-576. Springer, (2019)