CBERS-4A/WFI image mosaic of Brazil Paraíba State with 55m of spatial resolution. The mosaic was prepared in order to demonstrate the technological capabilities of the Brazil Data Cube project tools. The false color composition is based on the WFI bands 16, 15 and 14 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in July 2020 and ending in September 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 50 CBERS-4A scenes and was generated based on an existing CBERS-4A/WFI image collection.

This land cover classification refers to a study area in Mato Grosso state, in the Cerrado biome. For this map, the CBERS-4/WFI monthly data cube was used, with a spatial resolution of 64 meters, using the best pixel composition function named as Least Cloud Cover First (LCF), which was previously named Stack in BDC older versions. This experiment uses the time series of an agricultural calendar year, from September 2018 to August 2019, extracted from the CBERS-4/WFI data cube. The input datacube was CBERS-4 (WFI) Cube Identity - v001, which was deprecated. The classification was made using 852 samples (Annual Crop: 257; Natural Vegetation: 245; Pasture: 216; Semi-Perennial Crop: 134) and the following data cube bands: bands red, green, blue, and near-infrared along with the EVI, NDVI, GEMI, GNDVI, NDWI2, PVR indices. We trained a multi-layer perceptron for a deep learning classification network to classify the data cube using sits R package. This product was funded by the Brazilian Development Bank (BNDES).

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.

CBERS-2B/CCD - Level-2 Digital Number product. Level 2 products have radiometric correction and geometric correction using satellite ephemeris and attitude data (system correction).

CBERS-4/MUX - Level-4 Surface Reflectance product over Brazil and part of South America. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG).

Esta coleção reúne imagens ópticas adquiridas pelos sensores WFI (Wide Field Imager), embarcados nos satélites do INPE: CBERS-4, CBERS-4A e AMAZONIA-1. As imagens referem-se às regiões de Franca (SP), Franca Nordeste (SPNE) e partes da Amazônia brasileira, com destaque para o monitoramento de áreas naturais, queimadas, cobertura de nuvens e corpos hídricos. Os arquivos seguem um padrão de nomenclatura que codifica informações como a localidade (ex.: Franca_AMAZONIA, Franca_SP), o sensor utilizado, a data da imagem (AAAAMMDD), órbita / ponto, o nível de processamento (ex.: L4), composições espectrais (ex.: BAND4321, BAND16151413) e tipo de processamento (ex.: RegAWFI). Os dados estão disponíveis nos formatos .tif e .png.

This collection contains images from the pancromatic sensor on board the satellite CBERS-4 over Brazil. The data is processed by the Disasters Charter and provided as Cloud Optimized GeoTIFF (COG). This products has three spectral bands: Green, Red and NIR.

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).

This land cover classification refers to a study area in Goiás state, in the Cerrado biome. For this map, the CBERS-4/WFI monthly data cube was used, with a spatial resolution of 64 meters, using the best pixel composition function named as Least Cloud Cover First (LCF), which was previously named Stack in BDC older versions. This experiment uses the time series of an agricultural calendar year, from September 2018 to August 2019, extracted from the CBERS-4/WFI data cube. The input datacube was CBERS-4 (WFI) Cube Identity - v001, which was deprecated. The classification was made using 701 samples (Annual Crop: 299; Natural: 202; Pasture: 200) and the following data cube bands: red, green, blue, and near-infrared (NIR) along with the NDVI and EVI indices. We trained a multi-layer perceptron for a deep learning classification network to classify the data cube using sits R package. This product was funded by the Brazilian Development Bank (BNDES).

CBERS-4/MUX - Level-2 Digital Number. Level 2 products have radiometric correction and geometric correction using satellite ephemeris and attitude data (system correction).