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E-Sensing: big earth observation data analytics for land use and land cover change information

Grant number: 14/08398-6
Support type:Research Grants - eScience and Data Science Program - Thematic Grants
Duration: January 01, 2015 - December 31, 2018
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Gilberto Camara Neto
Grantee:Gilberto Camara Neto
Home Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). São José dos Campos, SP, Brazil
Co-Principal Investigators:João Vianei Soares ; Leila Maria Garcia Fonseca ; Lúbia Vinhas ; Maria Isabel Sobral Escada
Assoc. researchers: Camilo Daleles Rennó ; Emiliano Ferreira Castejon ; Gilberto Ribeiro de Queiroz ; Ieda Del'Arco Sanches ; Julio Cesar Lima Dalge ; Karine Reis Ferreira Gomes ; Luis Eduardo Pinheiro Maurano ; Marisa da Motta ; Pedro Ribeiro de Andrade Neto ; Ricardo Cartaxo Modesto de Souza ; Silvana Amaral Kampel ; Taise Farias Pinheiro ; Thales Sehn Körting
Associated grant(s):16/50495-4 - Land use change impacts of increased bioenergy demand in Brazil, AP.R
16/14545-7 - Geobia 2016, AR.EXT
Associated scholarship(s):18/03769-7 - Machine learning methods for dense satellite image time series analysis, BP.TT
16/23750-3 - Use of remote sensing images time series for monitoring Brazilian Agriculture, BP.PD
16/16968-2 - Using time series satellite imagery to monitor deforestation and degradation in the Amazon rainforest, BP.PD
16/08719-2 - Spatiotemporal data analysis methods, BP.DR

Abstract

The project addresses a key scientific problem: How can we use e-science methods and techniques to substantially improve the extraction of land use and land cover change information from big Earth Observation data sets in an open and reproducible way? In response to this challenge, our project will conceive, build and deploy a completely new type of knowledge platform for organization, access, processing and analysis of big Earth Observation data. We will show that this knowledge platform allows scientists to produce information in a completely new way. Since our platform is fully based on open source software, we will also show that it promotes data sharing and reproducibility of results. (AU)

Articles published in Agência FAPESP about the research grant
FAPESP issues new call for eScience multidisciplinary research proposals 

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MACIEL, ADELINE MARINHO; CAMARA, GILBERTO; VINHAS, LUBIA; ARAUJO PICOLI, MICHELLE CRISTINA; BEGOTTI, RODRIGO ANZOLIN; FERREIRA GOMES DE ASSIS, LUIZ FERNANDO. A spatiotemporal calculus for reasoning about land-use trajectories. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, v. 33, n. 1, p. 176-192, 2019. Web of Science Citations: 1.
ARAUJO PICOLI, MICHELLE CRISTINA; CAMARA, GILBERTO; SANCHES, IEDA; SIMOES, ROLF; CARVALHO, ALEXANDRE; MACIEL, ADELINE; COUTINHO, ALEXANDRE; ESQUERDO, JULIO; ANTUNES, JOAO; BEGOTTI, RODRIGO ANZOLIN; ARVOR, DAMIEN; ALMEIDA, CLAUDIO. Big earth observation time series analysis for monitoring Brazilian agriculture. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v. 145, n. B, p. 328-339, NOV 2018. Web of Science Citations: 3.
COSTA, WANDERSON SANTOS; GARCIA FONSECA, LEILA MARIA; KORTING, THALES SEHN; BENDINI, HUGO DO NASCIMENTO; MODESTO DE SOUZA, RICARDO CARTAXO. Spatio-Temporal Segmentation Applied to Optical Remote Sensing Image Time Series. IEEE Geoscience and Remote Sensing Letters, v. 15, n. 8, p. 1299-1303, AUG 2018. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.
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