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Produção, visualização e análise de grandes volumes de imagens de sensoriamento remoto modeladas como cubos de dados multidimensionais para todo o território brasileiro.

An analysis of the influence of the number of observations in a random forest time series classification to map the forest and deforestation in the Brazilian Amazon

by L. S. Vieira¹, G. R. Queiroz¹, and E. H. Shiguemori² ¹Earth Observation and Geoinformatics Division, National Institute for Space Research, INPE, São José dos Campos 12227-010, Brazil²Surveillance and Reconnaissance Division, Institute for Advanced Studies, IEAv, São José dos Campos 12228-001, Brazil DOI: https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-721-2022 Publisher: ISPRS | Published: 30 May 2022 © Author(s) 2022. This work …

Spatiotemporal segmentation of satellite image time series using self-organizing map

by B. L. C. Silva¹, F. C. Souza¹, K. R. Ferreira¹, G. R. Queiroz¹, and L. A. Santos¹ 1National Institute for Space Research (INPE), Brazil DOI: https://doi.org/10.5194/isprs-annals-V-3-2022-255-2022 Publisher: ISPRS | Published: 17 May 2022 © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License. Abstract Nowadays, researchers have free access to an unprecedentedly …

Building earth observation data cubes on aws

by K. R. Ferreira¹, G. R. Queiroz¹, R. F. B. Marujo¹, and R. W. Costa¹ 1National Institute for Space Research (INPE), Brazil DOI: https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-597-2022 Publisher: ISPRS | Published: 30 May 2022 © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License. Abstract Image time series analysis and machine learning methods have been widely …

Brazil Data Cube - 2019 - 2022