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Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

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Instituto do Homem e Meio Ambiente da Amazônia (Imazon), Belém 66055-200, Brazil
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Instituto de Pesquisa Ambiental da Amazônia (Ipam), Brasília 70863-520, Brazil
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Programa de Pós-Gradução em Geografia Física, Faculdade de Filosofia, Letras e Ciências Humanas, Universidade de São Paulo, São Paulo 05508-000, Brazil
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Image Processing and GIS Laboratory (LAPIG), Federal University of Goiás (UFG), Goiania 74001-970, Brazil
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Agrosatélite Geotecnologia Aplicada Ltda, Florianópolis 88050-000, Brazil
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Centro de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre 91501-970, Brazil
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WRI Brasil, São Paulo 05422-030, Brazil
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Instituto Tecnológico Vale, Universidade Federal do Pará, Belém 66055-090, Brazil
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Ecostage, São Paulo 01402-002, Brazil
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Programa de Pós-Graduação em Modelagem em Ciências da Terra e do Ambiente, Universidade Estadual de Feira de Santana, Feira de Santana 44031-460, Brazil
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Solved—Solutions in Geoinformation, Belém 66077-830, Brazil
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Terras App Solutions, Belém 66055-050, Brazil
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ArcPlan, São Paulo 04026-001, Brazil
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Departamento Interdisciplinar, Universidade Federal do Rio Grande do Sul, Tramandaí 95590-000, Brazil
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Associação Plantas do Nordeste, Recife 50731-280, Brazil
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JVN SIQUEIRA—ME, Belém 66010-000, Brazil
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MHR Sales Consultoria, Belém 66010-000, Brazil
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MapBiomas, Observatório do Clima, São Paulo 05418-060, Brazil
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Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(17), 2735; https://doi.org/10.3390/rs12172735
Received: 16 July 2020 / Revised: 17 August 2020 / Accepted: 18 August 2020 / Published: 25 August 2020
Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil. View Full-Text
Keywords: land use; land cover change; Landsat; random forest; time-series; Brazilian biomes land use; land cover change; Landsat; random forest; time-series; Brazilian biomes
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MDPI and ACS Style

Souza, C.M., Jr.; Z. Shimbo, J.; Rosa, M.R.; Parente, L.L.; A. Alencar, A.; Rudorff, B.F.T.; Hasenack, H.; Matsumoto, M.; G. Ferreira, L.; Souza-Filho, P.W.M.; de Oliveira, S.W.; Rocha, W.F.; Fonseca, A.V.; Marques, C.B.; Diniz, C.G.; Costa, D.; Monteiro, D.; Rosa, E.R.; Vélez-Martin, E.; Weber, E.J.; Lenti, F.E.B.; Paternost, F.F.; Pareyn, F.G.C.; Siqueira, J.V.; Viera, J.L.; Neto, L.C.F.; Saraiva, M.M.; Sales, M.H.; Salgado, M.P.G.; Vasconcelos, R.; Galano, S.; Mesquita, V.V.; Azevedo, T. Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine. Remote Sens. 2020, 12, 2735. https://doi.org/10.3390/rs12172735

AMA Style

Souza CM Jr., Z. Shimbo J, Rosa MR, Parente LL, A. Alencar A, Rudorff BFT, Hasenack H, Matsumoto M, G. Ferreira L, Souza-Filho PWM, de Oliveira SW, Rocha WF, Fonseca AV, Marques CB, Diniz CG, Costa D, Monteiro D, Rosa ER, Vélez-Martin E, Weber EJ, Lenti FEB, Paternost FF, Pareyn FGC, Siqueira JV, Viera JL, Neto LCF, Saraiva MM, Sales MH, Salgado MPG, Vasconcelos R, Galano S, Mesquita VV, Azevedo T. Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine. Remote Sensing. 2020; 12(17):2735. https://doi.org/10.3390/rs12172735

Chicago/Turabian Style

Souza, Carlos M., Jr., Julia Z. Shimbo, Marcos R. Rosa, Leandro L. Parente, Ane A. Alencar, Bernardo F.T. Rudorff, Heinrich Hasenack, Marcelo Matsumoto, Laerte G. Ferreira, Pedro W.M. Souza-Filho, Sergio W. de Oliveira, Washington F. Rocha, Antônio V. Fonseca, Camila B. Marques, Cesar G. Diniz, Diego Costa, Dyeden Monteiro, Eduardo R. Rosa, Eduardo Vélez-Martin, Eliseu J. Weber, Felipe E.B. Lenti, Fernando F. Paternost, Frans G.C. Pareyn, João V. Siqueira, José L. Viera, Luiz C.F. Neto, Marciano M. Saraiva, Marcio H. Sales, Moises P.G. Salgado, Rodrigo Vasconcelos, Soltan Galano, Vinicius V. Mesquita, and Tasso Azevedo. 2020. "Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine" Remote Sensing 12, no. 17: 2735. https://doi.org/10.3390/rs12172735

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