Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/215029 |
Resumo: | 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. |
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Souza Junior, CarlosShimbo, Julia ZaninRosa, Marcos ReisParente, Leandro L.Alencar, Ane A.Rudorff, Bernardo Friedrich TheodorHasenack, HeinrichMatsumoto, MarceloFerreira, Laerte G.Souza Filho, Pedro Walfir Martins eOliveira, Sergio W. deRocha, WashingtonFonseca, Antônio VictorMarques, Camila B.Diniz, Cesar G.Costa, Diego PereiraMonteiro, DyedenRosa, Eduardo R.Vélez Martin, EduardoWeber, Eliseu JoseLenti, Felipe Eduardo BrandãoPaternost, Fernando F.Pareyn, Frans Germain CorneelSiqueira, JoãoViera, José L.Ferreira Neto, Luiz CarlosSaraiva, Marciano M.Sales, Marcio H.Salgado, Moisés P. G.Vasconcelos, RodrigoGalano, SoltanMesquita, Vinicius VieiraAzevedo, Tasso2020-11-13T04:21:34Z20202072-4292http://hdl.handle.net/10183/215029001117848Brazil 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.application/pdfengRemote Sensing. Basel. Vol. 12, n. 17 (2020), 27 p.Uso da terraSoloBiomasLandsatBrasilReconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth EngineEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001117848.pdf.txt001117848.pdf.txtExtracted Texttext/plain98203http://www.lume.ufrgs.br/bitstream/10183/215029/2/001117848.pdf.txt642192b4feeb349d7668982df17905a0MD52ORIGINAL001117848.pdfTexto completo (inglês)application/pdf5877771http://www.lume.ufrgs.br/bitstream/10183/215029/1/001117848.pdf2d18b93e5b93fb4b54e91109cce57ec6MD5110183/2150292023-08-23 03:30:10.636417oai:www.lume.ufrgs.br:10183/215029Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-08-23T06:30:10Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
title |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
spellingShingle |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine Souza Junior, Carlos Uso da terra Solo Biomas Landsat Brasil |
title_short |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
title_full |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
title_fullStr |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
title_full_unstemmed |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
title_sort |
Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine |
author |
Souza Junior, Carlos |
author_facet |
Souza Junior, Carlos Shimbo, Julia Zanin Rosa, Marcos Reis Parente, Leandro L. Alencar, Ane A. Rudorff, Bernardo Friedrich Theodor Hasenack, Heinrich Matsumoto, Marcelo Ferreira, Laerte G. Souza Filho, Pedro Walfir Martins e Oliveira, Sergio W. de Rocha, Washington Fonseca, Antônio Victor Marques, Camila B. Diniz, Cesar G. Costa, Diego Pereira Monteiro, Dyeden Rosa, Eduardo R. Vélez Martin, Eduardo Weber, Eliseu Jose Lenti, Felipe Eduardo Brandão Paternost, Fernando F. Pareyn, Frans Germain Corneel Siqueira, João Viera, José L. Ferreira Neto, Luiz Carlos Saraiva, Marciano M. Sales, Marcio H. Salgado, Moisés P. G. Vasconcelos, Rodrigo Galano, Soltan Mesquita, Vinicius Vieira Azevedo, Tasso |
author_role |
author |
author2 |
Shimbo, Julia Zanin Rosa, Marcos Reis Parente, Leandro L. Alencar, Ane A. Rudorff, Bernardo Friedrich Theodor Hasenack, Heinrich Matsumoto, Marcelo Ferreira, Laerte G. Souza Filho, Pedro Walfir Martins e Oliveira, Sergio W. de Rocha, Washington Fonseca, Antônio Victor Marques, Camila B. Diniz, Cesar G. Costa, Diego Pereira Monteiro, Dyeden Rosa, Eduardo R. Vélez Martin, Eduardo Weber, Eliseu Jose Lenti, Felipe Eduardo Brandão Paternost, Fernando F. Pareyn, Frans Germain Corneel Siqueira, João Viera, José L. Ferreira Neto, Luiz Carlos Saraiva, Marciano M. Sales, Marcio H. Salgado, Moisés P. G. Vasconcelos, Rodrigo Galano, Soltan Mesquita, Vinicius Vieira Azevedo, Tasso |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Souza Junior, Carlos Shimbo, Julia Zanin Rosa, Marcos Reis Parente, Leandro L. Alencar, Ane A. Rudorff, Bernardo Friedrich Theodor Hasenack, Heinrich Matsumoto, Marcelo Ferreira, Laerte G. Souza Filho, Pedro Walfir Martins e Oliveira, Sergio W. de Rocha, Washington Fonseca, Antônio Victor Marques, Camila B. Diniz, Cesar G. Costa, Diego Pereira Monteiro, Dyeden Rosa, Eduardo R. Vélez Martin, Eduardo Weber, Eliseu Jose Lenti, Felipe Eduardo Brandão Paternost, Fernando F. Pareyn, Frans Germain Corneel Siqueira, João Viera, José L. Ferreira Neto, Luiz Carlos Saraiva, Marciano M. Sales, Marcio H. Salgado, Moisés P. G. Vasconcelos, Rodrigo Galano, Soltan Mesquita, Vinicius Vieira Azevedo, Tasso |
dc.subject.por.fl_str_mv |
Uso da terra Solo Biomas Landsat Brasil |
topic |
Uso da terra Solo Biomas Landsat Brasil |
description |
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. |
publishDate |
2020 |
dc.date.accessioned.fl_str_mv |
2020-11-13T04:21:34Z |
dc.date.issued.fl_str_mv |
2020 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
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http://hdl.handle.net/10183/215029 |
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2072-4292 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001117848 |
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http://hdl.handle.net/10183/215029 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Remote Sensing. Basel. Vol. 12, n. 17 (2020), 27 p. |
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openAccess |
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