Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Ciência Florestal (Online) |
Texto Completo: | https://periodicos.ufsm.br/cienciaflorestal/article/view/34380 |
Resumo: | Since 1988, the Brazilian National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais - INPE) has been executing the annual inventory of forest cover loss in the Legal Amazon using satellite data under the Program for Deforestation Monitoring in the Brazilian Legal Amazon (PRODES). This survey comprises mapping more than four million squared kilometers and the produced information are employed by the Brazilian government to evaluate and establish public policies related to the control and counter deforestation. This data has been produced and published annually since 1988. However, its accuracy is not known. Therefore, this work objective is to develop a methodology to estimate the accuracy of the deforested areas mapped by PRODES for the year 2014 using stratified sampling of the deforestation patterns mapped in 50 by 50 Km cells. Mapping these patterns was accomplished by establishing and using a typology of deforestation patterns, landscape metrics and data mining techniques. Typical sample points of each deforestation pattern of were randomly drawn and analyzed visually by independent experts. This evaluation results established that the global accuracy level of the mapping under study is estimated to be 93%, with omission and commission indices estimates being 7% and 1.5%, respectively. Patterns such as fishbone, multidirectional and consolidated ones, which are considered the most complexes, present the lowest indexes of correctness, showing coherence and indicating that they should be mapped with more rigor. The presented results are consistent in a general way, indicating that the developed methodology can be applied to similar mappings. |
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Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal AmazonPadrões espaciais de desmatamento e a estimativa da exatidão dos mapas do PRODES para Amazônia Legal BrasileiraDeforestation mappingLand useRemote sensingWeb-GIS and mapping assessmentMapeamento de desmatamentoUso da terraSensoriamento remotoWeb-GIS e avaliação de mapeamentoSince 1988, the Brazilian National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais - INPE) has been executing the annual inventory of forest cover loss in the Legal Amazon using satellite data under the Program for Deforestation Monitoring in the Brazilian Legal Amazon (PRODES). This survey comprises mapping more than four million squared kilometers and the produced information are employed by the Brazilian government to evaluate and establish public policies related to the control and counter deforestation. This data has been produced and published annually since 1988. However, its accuracy is not known. Therefore, this work objective is to develop a methodology to estimate the accuracy of the deforested areas mapped by PRODES for the year 2014 using stratified sampling of the deforestation patterns mapped in 50 by 50 Km cells. Mapping these patterns was accomplished by establishing and using a typology of deforestation patterns, landscape metrics and data mining techniques. Typical sample points of each deforestation pattern of were randomly drawn and analyzed visually by independent experts. This evaluation results established that the global accuracy level of the mapping under study is estimated to be 93%, with omission and commission indices estimates being 7% and 1.5%, respectively. Patterns such as fishbone, multidirectional and consolidated ones, which are considered the most complexes, present the lowest indexes of correctness, showing coherence and indicating that they should be mapped with more rigor. The presented results are consistent in a general way, indicating that the developed methodology can be applied to similar mappings.O Instituto Nacional de Pesquisas Espaciais (INPE) opera desde 1988 o Projeto de Monitoramento do Desmatamento na Amazônia por Satélites (PRODES), cujo principal objetivo é fornecer taxa anual de desmatamento florestal da Amazônia Legal Brasileira utilizando imagens de satélite de sensoriamento remoto. Esse levantamento envolve o mapeamento de mais de quatro milhões de km2 e os resultados obtidos são utilizados pelo governo brasileiro no estabelecimento e acompanhamento das políticas públicas relativas ao controle e combate ao desmatamento. Este dado tem sido produzido e divulgado em base anual desde 1988, porém, uma avaliação sobre a qualidade dos dados nunca foi estabelecida. Assim, o objetivo deste trabalho foi desenvolver uma metodologia para estimar índices de exatidão do mapeamento das áreas desmatadas apontadas pelo PRODES para o ano de 2014, a partir de uma amostragem estratificada de padrões de desmatamento mapeados em células de 50 x 50 km. O mapeamento desses padrões foi realizado a partir do estabelecimento e uso de uma tipologia de padrões de desmatamento, métricas de paisagem e técnica de mineração de dados. Pontos amostrais representativos de cada padrão de desmatamento foram sorteados aleatoriamente e avaliados visualmente por especialistas independentes. Como resultado dessa avaliação foi possível estabelecer o nível exatidão global do mapeamento em questão, estimado em 93% e com índices de omissão e de inclusão estimados em 7% e 1,5%, respectivamente. Padrões como espinha de peixe, multidirecional e consolidado, considerados mais complexos, apresentaram menores índices de acerto, mostrando coerência e indicando que maior atenção deve ser dada ao seu mapeamento. Os resultados apresentados, de uma forma geral, se mostraram consistentes, indicando que a metodologia desenvolvida pode ser replicada em mapeamentos similares.Universidade Federal de Santa Maria2019-12-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/3438010.5902/1980509834380Ciência Florestal; Vol. 29 No. 4 (2019); 1763-1775Ciência Florestal; v. 29 n. 4 (2019); 1763-17751980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/34380/34380Copyright (c) 2019 Ciência Florestalinfo:eu-repo/semantics/openAccessMaurano, Luis Eduardo PinheiroEscada, Maria Isabel SobralRenno, Camilo Daleles2019-12-10T21:30:48Zoai:ojs.pkp.sfu.ca:article/34380Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2019-12-10T21:30:48Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon Padrões espaciais de desmatamento e a estimativa da exatidão dos mapas do PRODES para Amazônia Legal Brasileira |
title |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
spellingShingle |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon Maurano, Luis Eduardo Pinheiro Deforestation mapping Land use Remote sensing Web-GIS and mapping assessment Mapeamento de desmatamento Uso da terra Sensoriamento remoto Web-GIS e avaliação de mapeamento |
title_short |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
title_full |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
title_fullStr |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
title_full_unstemmed |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
title_sort |
Spatial deforestation patterns and the accuracy of deforestation mapping for the Brazilian Legal Amazon |
author |
Maurano, Luis Eduardo Pinheiro |
author_facet |
Maurano, Luis Eduardo Pinheiro Escada, Maria Isabel Sobral Renno, Camilo Daleles |
author_role |
author |
author2 |
Escada, Maria Isabel Sobral Renno, Camilo Daleles |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Maurano, Luis Eduardo Pinheiro Escada, Maria Isabel Sobral Renno, Camilo Daleles |
dc.subject.por.fl_str_mv |
Deforestation mapping Land use Remote sensing Web-GIS and mapping assessment Mapeamento de desmatamento Uso da terra Sensoriamento remoto Web-GIS e avaliação de mapeamento |
topic |
Deforestation mapping Land use Remote sensing Web-GIS and mapping assessment Mapeamento de desmatamento Uso da terra Sensoriamento remoto Web-GIS e avaliação de mapeamento |
description |
Since 1988, the Brazilian National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais - INPE) has been executing the annual inventory of forest cover loss in the Legal Amazon using satellite data under the Program for Deforestation Monitoring in the Brazilian Legal Amazon (PRODES). This survey comprises mapping more than four million squared kilometers and the produced information are employed by the Brazilian government to evaluate and establish public policies related to the control and counter deforestation. This data has been produced and published annually since 1988. However, its accuracy is not known. Therefore, this work objective is to develop a methodology to estimate the accuracy of the deforested areas mapped by PRODES for the year 2014 using stratified sampling of the deforestation patterns mapped in 50 by 50 Km cells. Mapping these patterns was accomplished by establishing and using a typology of deforestation patterns, landscape metrics and data mining techniques. Typical sample points of each deforestation pattern of were randomly drawn and analyzed visually by independent experts. This evaluation results established that the global accuracy level of the mapping under study is estimated to be 93%, with omission and commission indices estimates being 7% and 1.5%, respectively. Patterns such as fishbone, multidirectional and consolidated ones, which are considered the most complexes, present the lowest indexes of correctness, showing coherence and indicating that they should be mapped with more rigor. The presented results are consistent in a general way, indicating that the developed methodology can be applied to similar mappings. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/34380 10.5902/1980509834380 |
url |
https://periodicos.ufsm.br/cienciaflorestal/article/view/34380 |
identifier_str_mv |
10.5902/1980509834380 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/34380/34380 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 Ciência Florestal info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 Ciência Florestal |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência Florestal; Vol. 29 No. 4 (2019); 1763-1775 Ciência Florestal; v. 29 n. 4 (2019); 1763-1775 1980-5098 0103-9954 reponame:Ciência Florestal (Online) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Ciência Florestal (Online) |
collection |
Ciência Florestal (Online) |
repository.name.fl_str_mv |
Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br |
_version_ |
1799944133982289920 |