Medindo o Brasil a partir do espaço: tecnologias de big data e inteligência artificial

Autores

DOI:

https://doi.org/10.5380/atoz.v10i3.81966

Palavras-chave:

Big data, Artificial intelligence, Technological innovation, Data cube, Brazil Data Cube

Resumo

A Dr.ª Karine Reis Ferreira e o Dr. Gilberto Ribeiro de Queiroz respondem questões sobre o projeto de pesquisa Brazil Data Cube, sua finalidade, impacto e relação com inteligência artificial e big data.

Biografia do Autor

Karine Reis Ferreira, Instituto Nacional de Pesquisas Espaciais -INPE, São José dos Campos, SP, Brasil

PhD in Applied Computing by the National Institute for Space Research (INPE), Brazil. I work at INPE with research in Geoinformatics and developing geographical information systems, such as TerraLib and TerraBrasilis (http://terrabrasilis.dpi.inpe.br/). I am professor of the Applied Computing Graduate Course at INPE and my main research topic is representation, processing and analysis of spatiotemporal and big Earth observation data. From 2019, I am the technical manager of the Brazil Data Cube project (http://brazildatacube.org/).

Referências

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. & et al. (2020a). Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. Remote Sensing. 2020,12, 4033, doi:10.3390/rs12244033

Ferreira, K. R., Queiroz, G. R., Camara G., Souza, R. C. M., Vinhas, L., Marujo, R. F. B., Simoes, R. E. O., Noronha, C. A. F., Costa, R. W. & et al. (2020b). Using Remote Sensing Images and Cloud Services on AWS to Improve Land Use and Cover Monitoring. In: LAGIRS 2020: 2020 Latin American GRSS & ISPRS Remote Sensing Conference. Santiago de Chile, Chile, March 22-26.

Giuliani, G., Chatenoux, B., De Bono, A., Rodila, D., Richard, J.P., Allenbach, K., Dao, H. & Peduzzi, P. (2017). Building an Earth Observations Data Cube: Lessons Learned from the SwissData Cube (SDC) on Generating Analysis Ready Data (ARD). Big Earth Data, 1, 100–117, doi:10.1080/20964471.2017.1398903.

Gomes, V.C., Queiroz, G.R. & Ferreira, K.R. (2020). An Overview of Platforms for Big Earth Observation DataManagement and Analysis. Remote Sensing, 12, 1253. doi: 10.3390/rs12081253.

Gomes, V. C. F., Carlos, F. M., Queiroz, G. R., Ferreira, K. R., & Santos, R. (2021). ACCESSING AND PROCESSING BRAZILIAN EARTH OBSERVATION DATA CUBES WITH THE OPEN DATA CUBE PLATFORM, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 153–159, doi: 10.5194/isprs-annals-V-4-2021-153-2021.

Killough, B. & et al. (2019) The Impact of Analysis Ready Data in the Africa Regional Data Cube. In Proceedings of the IGARSS 2019—2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July–2 August 2019; IEEE: Piscataway, NJ, USA, 2019; pp. 5646–5649, doi:10.1109/IGARSS.2019.8898321

Lewis, A., Oliver, S., Lymburner, L., Evans, B., Wyborn, L., Mueller, N., Raevksi, G., Hooke, J., Woodcock, R., Sixsmith, J. & et al. (2017). The Australian Geoscience Data Cube—Foundations and Lessons Learned. Remote Sens. Environ., 202, 276–292, doi:10.1016/j.rse.2017.03.015.13.

Picoli, M. C. A., Simoes, R., Chaves, M., Santos, L. A., Sanchez, A., Soares, A., Sanches, I. D., Ferreira, K. R. & Queiroz, G. R. (2020). CBERS DATA CUBE: A POWERFUL TECHNOLOGY FOR MAPPING AND MONITORING BRAZILIAN BIOMES. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. , v.V-3-2020, p.533 – 539, doi: 10.5194/isprs-annals-V-3-2020-533-2020

Santos, L.A., Ferreira, K.R., Camara, G., Picoli, M.C.A. & Simoes, R.E. (2021a). Quality Control and Class Noise Reduction of Satellite Image Time Series. ISPRS J. Photogramm. Remote Sens. 2021, 177, 75–88, doi:10.1016/j.isprsjprs.2021.04.014.

Santos, L.A., Ferreira, K.R, Picoli, M., Camara, G., Zurita-Milla, R. & Augustijn, E.-W. (2021b). Identifying Spatiotemporal Patterns in Land Use and Cover Samples from Satellite Image Time Series. In: Remote Sensing Journal. v. 13, p. 974, 2021. doi: 10.3390/rs13050974

Simoes, R., Camara, G., Queiroz, G., Souza, F., Andrade, P.R., Santos, L., Carvalho, A. & Ferreira, K. (2021). Satellite Image Time Series Analysis for Big Earth Observation Data. Remote Sensing. v.13, p.2428, doi: 10.3390/rs13132428.

Soille, P., Burger, A., De Marchi, D., Kempeneers, P., Rodriguez, D., Syrris, V. & Vasilev, V. (2018) A versatile data-intensive computing platform for information retrieval from big geospatial data. Future Generation Computer Systems, v. 81, p. 30–4, doi: 10.1016/j.future.2017.11.007.

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Publicado

2021-08-31

Como Citar

Ferreira, K. R., & Queiroz, G. R. de. (2021). Medindo o Brasil a partir do espaço: tecnologias de big data e inteligência artificial. AtoZ: Novas práticas Em informação E Conhecimento, 10(3), 1–4. https://doi.org/10.5380/atoz.v10i3.81966

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Seção

Dossiê temático: Entrevista