Copernicus Sentinel-2/MSI Level-2A product over Brazil. Level-2A product provides orthorectified surface reflectance images (Bottom-Of-Atmosphere - BOA). This dataset is provided as Cloud Optimized GeoTIFF (COG).

Copernicus Sentinel-2/MSI Level-2A product over Brazil. Level-2A product provides orthorectified surface reflectance images (Bottom-Of-Atmosphere - BOA).

Copernicus Sentinel-2/MSI Level-1C product over Brazil. Level-1C product provides orthorectified Top-Of-Atmosphere (TOA) reflectance images.

Earth Observation Data Cube generated from Copernicus Sentinel-2/MSI Level-2A product over Brazil. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 10 meters of spatial resolution, reprojected and cropped to BDC_SM grid Version 2 (BDC_SM V2), considering a temporal compositing function of 16 days using the Least Cloud Cover First (LCF) best pixel approach.

Sentinel-2 image mosaic of Brazilian Yanomami Indigenous Territory with 10m of spatial resolution. The mosaic was prepared to support the partnership between the INPE's Health Information Investigation Laboratory (LiSS) and the ICIT-FIOCRUZ Health Information Laboratory (LIS) a multi-institutional body coordinated by Fiocruz and the ministry of health, by creating a health situation database of the Yanomami Indigenous Land. The false color composition is based on the MSI bands 11, 8A and 4 assigned to RGB channels. The temporal composition encompasses 06-months of images, starting in April 2019 and ending in September 2022, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 15000 Sentinel-2 scenes and was generated based on an existing data cube of Sentinel-2 images.

Sentinel-2 image mosaic of Brazilian Cerrado biome with 10m of spatial resolution. The mosaic was prepared in support of TerraClass project. The false color composition is based on the MSI bands 8, 4 and 3 assigned to RGB channels. The temporal composition encompasses 04-months of images, starting in june 2022 and ending in September 2022, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 14000 Sentinel-2 scenes and was generated based on an existing data cube of Sentinel-2 images.

Sentinel-2 image mosaic of Brazilian Paraíba State with 10m of spatial resolution. The mosaic was prepared to support the partnership between the INPE's Health Information Investigation Laboratory (LiSS) and the Federal University of Paraíba's Public Policy Studies Program for Early Childhood Education (NEPPS) by supporting the development of the COVID 19/PB Platform: Relations between Health, Territory and Social Protection in times of sanitary crisis, which created the Platform Covid-19/Paraíba: Social and Health Indicator Observatory for SUS and SUAS management. The false color composition is based on the MSI bands 8, 4 and 3 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in November 2019 and ending in January 2020, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 800 Sentinel-2 scenes and was generated based on an existing Sentinel-2 image collection.

Kd data generated based Semi-Analytical Algorithm developed by Maciel et al. (2020) (https://doi.org/10.1016/j.isprsjprs.2020.10.009). The underwater light field modeling is essential for the understanding of biogeochemical processes, such as photosynthesis, carbon fluxes, and sediment transports in inland waters. Water-column light attenuation can be quantified by the diffuse attenuation coefficient of the downwelling irradiance (Kd). This dataset represents the Kd estimate for a Sentinel-2/MSI time-series at Curuai Lake region - Lower Amazon floodplains. This time-series data was generated for 66 Sentinel-2/MSI scenes (08/2015 to 09/2019) during the research paper titled Mapping of diffuse attenuation coefficient in optically complex waters of amazon floodplain lakes. This product was funded by the Brazilian Development Bank (BNDES), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

Sentinel-2 image mosaic of Brazilian Cerrado biome with 10m of spatial resolution. The mosaic was prepared in support of TerraClass project. The false color composition is based on the MSI bands 8, 4 and 3 assigned to RGB channels. The temporal composition encompasses 02-months of images, starting in November 2023 and ending in April 2024, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 14000 Sentinel-2 scenes and was generated based on an existing data cube of Sentinel-2 images.

Sentinel-2 image mosaic of Brazilian Amazon biome with 10m of spatial resolution. The mosaic was prepared in support of TerraClass project. The false color composition is based on the MSI bands 11, 8A and 4 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in june 2022 and ending in August 2022, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 15000 Sentinel-2 scenes and was generated based on an existing data cube of Sentinel-2 images.