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Production, visualization and analysis of large volumes of remote sensing images modeled as multidimensional data cubes for the entire Brazilian territory.

Using time series and machine learning techniques to classify agricultural areas in petrolina-pe

by BRITO, Pedro1; CARVALHO, Herica2; CHAVES, Michel3; SANTOS, Rafael1 1National Institute for Space Research (INPE) 2Renato Archer Information Technology Center 3Universidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP) XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/uso-de-series-temporais-e-tecnicas-de-machine-learning-para-classificar-areas-ag Publisher: Proceedings XXI Brazilian Remote Sensing Symposium | Published on 13 April 2025 Abstract The objective of this study was to evaluate …

WTSS-QGIS: an extension for retrieving and visualizing satellite image time series in the QGIS environment

by ANJOS, Abner1; VIEIRA, Fabiana Zioti1; COSTA, Raphael Willian da1; QUEIROZ, Gilberto Ribeiro de1; FERREIRA, Karine Reis1; CHO, David Fernando1. 1National Institute for Space Research (INPE) XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/wtss-qgis-uma-extensao-para-recuperacao-e-visualizacao-de-series-temporais-de-im Publisher: Proceedings XXI Brazilian Remote Sensing Symposium | Published on 13 April 2025 Abstract This article describes the development of a plugin for retrieving …

Integration of Radar and Optical Data for Identifying Tropical Forest Disturbances

by SOUZA, Felipe Carvalho de1; CAMARA, Gilberto1; CARLOS, Felipe1; FREITAS, Ana Larissa Ribeiro De1; SIMOES, Rolf3; FERREIRA, Karine Reis1; GIULIANI, Gregory4; REICHE, Johannes5. 1National Institute for Space Research (INPE) 2Group on Earth Observations – GEO 3OpenGeoHub Foundation – OGH 4University of Geneva – Switzerland 5Wageningen University XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/integration-of-radar-and-optical-data-for-identifying-tropical-forest-disturbanc Publisher: Proceedings XXI Brazilian …

Detecting atypical agricultural patterns in rural credit applications based on satellite image time series

by SILVA, Baggio Luiz de Castro e1; FERREIRA, Karine Reis1; QUEIROZ, Gilberto Ribeiro de1; ADAMI, Marcos1; KÖRTING, Thales Sehn1. 1National Institute for Space Research (INPE) XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/detectando-padroes-atipicos-de-agricultura-em-aplicacoes-de-credito-rural-basead Publisher: Proceedings XXI Brazilian Remote Sensing Symposium | Published on 13 April 2025 Abstract This paper presents a methodology for detecting atypical patterns in agricultural …

Cataloging GOES Satellite Images in INPE’s Georeferenced Information Base

by UBA, Douglas Messias1; QUEIROZ, Gilberto Ribeiro de1; VINHAS, Lubia1 1National Institute for Space Research (INPE) XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/catalogacao-de-imagens-dos-satelites-goes-na-base-de-informacoes-georreferenciad Publisher: Proceedings XXI Brazilian Remote Sensing Symposium | Published on 13 April 2025 Abstract BIG, an acronym for Georeferenced Information Base,is an institutional program under development at INPE. Its goal is to build a …

A Web Service for Phenology Metrics Extraction from Big Earth Observation Data

by SANSIGOLO, Gabriel1; FERREIRA, Karine Reis2; QUEIROZ, Gilberto Ribeiro de2; ADAMI, Marcos2; KÖRTING, Thales Sehn2 1 Funcate 2National Institute for Space Research (INPE) XXI Brazilian Remote Sensing Symposium: https://proceedings.science/sbsr-2025/trabalhos/a-web-service-for-phenology-metrics-extraction-from-big-earth-observation-data Publisher: Proceedings XXI Brazilian Remote Sensing Symposium | Published on 13 April 2025 Abstract Phenology is the study of timing recurrent biological events,being an important indicator of …

Evaluating Forest Disturbance Detection Methods based on Satellite Image Time Series for Amazon Deforestation Alerts

by Mota, F. B. D. S.1, Ferreira, K. R.1, and Escada, M. I. S1 1National Institute for Space Research (INPE) DOI: https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-357-2024 Publisher: ISPRS | Published: 2024, November 7th © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License. Abstract This study explores automated detection methods of forest disturbances using satellite image …

The HARMONIZE Project and the EODCtHRS Architecture: An Earth Observation Data Cube tuned for Health Response Systems

by Adeline M. Maciel2, Marcos L. Rodrigues1, Yuri D. M. Nunes1, Luana B. da Luz1, Ana P. Dal’Asta1, Gilberto R. Queiroz1, Karine R. Ferreira1, Sidnei João S. Sant’Anna 1, Maria Isabel S. Escada1, Ana Claudia R. Vitor1, Christovam Barcellos3, Cláudia T. Codeço3, Diego R. Xavier3, Vanderlei P. de Matos3, Raphael de F. Saldanha3, Abner E. …

Paper on Brazil Data Cube tool wins award at XXI Brazilian Symposium on Remote Sensing

The paper entitled “A Web Service for Phenology Metrics Extraction from Big Earth Observation Data” received one of the best paper awards during the XXI Brazilian Symposium on Remote Sensing (SBSR), held from April 13 to 16, 2025, in Salvador, Bahia. The award highlights the relevance of the Brazil Data Cube project’s geoinformatics research aligned …

Brazil Data Cube’s team attended the XXI Brazilian Symposium on Remote Sensing in 2025

The Brazil Data Cube team actively participated in the XXI Brazilian Symposium on Remote Sensing (SBSR 2025), in Salvador, Bahia, from April 13 to 16. During the event, the team was involved in various activities, starting on April 12, when the mini-course “Earth Observation Data Cubes and Image Time Series Analysis” was given, lasting 8 …

Brazil Data Cube - 2019 - 2025