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Open AccessArticle

Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products

Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), Avenida dos Astronautas, 1758, Jardim da Granja, Sao Jose dos Campos, SP 12227-010, Brazil
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Remote Sens. 2020, 12(24), 4033; https://doi.org/10.3390/rs12244033
Received: 4 November 2020 / Revised: 3 December 2020 / Accepted: 4 December 2020 / Published: 9 December 2020
(This article belongs to the Special Issue State-of-the-Art Remote Sensing in South America)
Recently, remote sensing image time series analysis has being widely used to investigate the dynamics of environments over time. Many studies have combined image time series analysis with machine learning methods to improve land use and cover change mapping. In order to support image time series analysis, analysis-ready data (ARD) image collections have been modeled and organized as multidimensional data cubes. Data cubes can be defined as sets of time series associated with spatially aligned pixels. Based on lessons learned in the research project e-Sensing, related to national demands for land use and cover monitoring and related to state-of-the-art studies on relevant topics, we define the requirements to build Earth observation data cubes for Brazil. This paper presents the methodology to generate ARD and multidimensional data cubes from remote sensing images for Brazil. We describe the computational infrastructure that we are developing in the Brazil Data Cube project, composed of software applications and Web services to create, integrate, discover, access, and process the data sets. We also present how we are producing land use and cover maps from data cubes using image time series analysis and machine learning techniques. View Full-Text
Keywords: analysis-ready data; data cubes; image time series analysis; machine learning; land use and cover mapping analysis-ready data; data cubes; image time series analysis; machine learning; land use and cover mapping
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MDPI and ACS Style

Ferreira, K.R.; Queiroz, G.R.; Vinhas, L.; Marujo, R.F.B.; Simoes, R.E.O.; Picoli, M.C.A.; Camara, G.; Cartaxo, R.; Gomes, V.C.F.; Santos, L.A.; Sanchez, A.H.; Arcanjo, J.S.; Fronza, J.G.; Noronha, C.A.; Costa, R.W.; Zaglia, M.C.; Zioti, F.; Korting, T.S.; Soares, A.R.; Chaves, M.E.D.; Fonseca, L.M.G. Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. Remote Sens. 2020, 12, 4033. https://doi.org/10.3390/rs12244033

AMA Style

Ferreira KR, Queiroz GR, Vinhas L, Marujo RFB, Simoes REO, Picoli MCA, Camara G, Cartaxo R, Gomes VCF, Santos LA, Sanchez AH, Arcanjo JS, Fronza JG, Noronha CA, Costa RW, Zaglia MC, Zioti F, Korting TS, Soares AR, Chaves MED, Fonseca LMG. Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. Remote Sensing. 2020; 12(24):4033. https://doi.org/10.3390/rs12244033

Chicago/Turabian Style

Ferreira, Karine R.; Queiroz, Gilberto R.; Vinhas, Lubia; Marujo, Rennan F.B.; Simoes, Rolf E.O.; Picoli, Michelle C.A.; Camara, Gilberto; Cartaxo, Ricardo; Gomes, Vitor C.F.; Santos, Lorena A.; Sanchez, Alber H.; Arcanjo, Jeferson S.; Fronza, José G.; Noronha, Carlos A.; Costa, Raphael W.; Zaglia, Matheus C.; Zioti, Fabiana; Korting, Thales S.; Soares, Anderson R.; Chaves, Michel E.D.; Fonseca, Leila M.G. 2020. "Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products" Remote Sens. 12, no. 24: 4033. https://doi.org/10.3390/rs12244033

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