Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1038/s41598-021-01350-y http://hdl.handle.net/11449/222817 |
Resumo: | The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann–Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo. |
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Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approachThe guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann–Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo.State University of Mato Grosso (UNEMAT)Department of Geography State University of Mato Grosso (UNEMAT)Department of Crop Science Department of Agronomy Federal University of Mato Grosso Do Sul (UFMS)State University of São Paulo (UNESP)State University of São Paulo (UNESP)State University of Mato Grosso (UNEMAT)Universidade Federal de Mato Grosso do Sul (UFMS)Universidade Estadual Paulista (UNESP)Lourençoni, Thaisda Silva Junior, Carlos AntonioLima, MendelsonTeodoro, Paulo EduardoPelissari, Tatiane Deoti [UNESP]dos Santos, Regimar GarciaTeodoro, Larissa Pereira RibeiroLuz, Iago ManuelsonRossi, Fernando Saragosa [UNESP]2022-04-28T19:46:59Z2022-04-28T19:46:59Z2021-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41598-021-01350-yScientific Reports, v. 11, n. 1, 2021.2045-2322http://hdl.handle.net/11449/22281710.1038/s41598-021-01350-y2-s2.0-85118676179Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengScientific Reportsinfo:eu-repo/semantics/openAccess2022-04-28T19:46:59Zoai:repositorio.unesp.br:11449/222817Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:46:59Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
title |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
spellingShingle |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach Lourençoni, Thais |
title_short |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
title_full |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
title_fullStr |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
title_full_unstemmed |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
title_sort |
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach |
author |
Lourençoni, Thais |
author_facet |
Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti [UNESP] dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa [UNESP] |
author_role |
author |
author2 |
da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti [UNESP] dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa [UNESP] |
author2_role |
author author author author author author author author |
dc.contributor.none.fl_str_mv |
State University of Mato Grosso (UNEMAT) Universidade Federal de Mato Grosso do Sul (UFMS) Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti [UNESP] dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa [UNESP] |
description |
The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann–Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-01 2022-04-28T19:46:59Z 2022-04-28T19:46:59Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1038/s41598-021-01350-y Scientific Reports, v. 11, n. 1, 2021. 2045-2322 http://hdl.handle.net/11449/222817 10.1038/s41598-021-01350-y 2-s2.0-85118676179 |
url |
http://dx.doi.org/10.1038/s41598-021-01350-y http://hdl.handle.net/11449/222817 |
identifier_str_mv |
Scientific Reports, v. 11, n. 1, 2021. 2045-2322 10.1038/s41598-021-01350-y 2-s2.0-85118676179 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Scientific Reports |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1803047002227867648 |