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dc.contributor.authorSouza Junior, Carlospt_BR
dc.contributor.authorShimbo, Julia Zaninpt_BR
dc.contributor.authorRosa, Marcos Reispt_BR
dc.contributor.authorParente, Leandro L.pt_BR
dc.contributor.authorAlencar, Ane A.pt_BR
dc.contributor.authorRudorff, Bernardo Friedrich Theodorpt_BR
dc.contributor.authorHasenack, Heinrichpt_BR
dc.contributor.authorMatsumoto, Marcelopt_BR
dc.contributor.authorFerreira, Laerte G.pt_BR
dc.contributor.authorSouza Filho, Pedro Walfir Martins ept_BR
dc.contributor.authorOliveira, Sergio W. dept_BR
dc.contributor.authorRocha, Washingtonpt_BR
dc.contributor.authorFonseca, Antônio Victorpt_BR
dc.contributor.authorMarques, Camila B.pt_BR
dc.contributor.authorDiniz, Cesar G.pt_BR
dc.contributor.authorCosta, Diego Pereirapt_BR
dc.contributor.authorMonteiro, Dyedenpt_BR
dc.contributor.authorRosa, Eduardo R.pt_BR
dc.contributor.authorVélez Martin, Eduardopt_BR
dc.contributor.authorWeber, Eliseu Josept_BR
dc.contributor.authorLenti, Felipe Eduardo Brandãopt_BR
dc.contributor.authorPaternost, Fernando F.pt_BR
dc.contributor.authorPareyn, Frans Germain Corneelpt_BR
dc.contributor.authorSiqueira, Joãopt_BR
dc.contributor.authorViera, José L.pt_BR
dc.contributor.authorFerreira Neto, Luiz Carlospt_BR
dc.contributor.authorSaraiva, Marciano M.pt_BR
dc.contributor.authorSales, Marcio H.pt_BR
dc.contributor.authorSalgado, Moisés P. G.pt_BR
dc.contributor.authorVasconcelos, Rodrigopt_BR
dc.contributor.authorGalano, Soltanpt_BR
dc.contributor.authorMesquita, Vinicius Vieirapt_BR
dc.contributor.authorAzevedo, Tassopt_BR
dc.date.accessioned2020-11-13T04:21:34Zpt_BR
dc.date.issued2020pt_BR
dc.identifier.issn2072-4292pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/215029pt_BR
dc.description.abstractBrazil 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.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofRemote Sensing. Basel. Vol. 12, n. 17 (2020), 27 p.pt_BR
dc.rightsOpen Accessen
dc.subjectUso da terrapt_BR
dc.subjectSolopt_BR
dc.subjectBiomaspt_BR
dc.subjectLandsatpt_BR
dc.subjectBrasilpt_BR
dc.titleReconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Enginept_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001117848pt_BR
dc.type.originEstrangeiropt_BR


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