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Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach

dc.contributor.authorLourençoni, Thais
dc.contributor.authorda Silva Junior, Carlos Antonio
dc.contributor.authorLima, Mendelson
dc.contributor.authorTeodoro, Paulo Eduardo
dc.contributor.authorPelissari, Tatiane Deoti [UNESP]
dc.contributor.authordos Santos, Regimar Garcia
dc.contributor.authorTeodoro, Larissa Pereira Ribeiro
dc.contributor.authorLuz, Iago Manuelson
dc.contributor.authorRossi, Fernando Saragosa [UNESP]
dc.contributor.institutionState University of Mato Grosso (UNEMAT)
dc.contributor.institutionUniversidade Federal de Mato Grosso do Sul (UFMS)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-28T19:46:59Z
dc.date.available2022-04-28T19:46:59Z
dc.date.issued2021-12-01
dc.description.abstractThe 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.en
dc.description.affiliationState University of Mato Grosso (UNEMAT)
dc.description.affiliationDepartment of Geography State University of Mato Grosso (UNEMAT)
dc.description.affiliationDepartment of Crop Science Department of Agronomy Federal University of Mato Grosso Do Sul (UFMS)
dc.description.affiliationState University of São Paulo (UNESP)
dc.description.affiliationUnespState University of São Paulo (UNESP)
dc.identifierhttp://dx.doi.org/10.1038/s41598-021-01350-y
dc.identifier.citationScientific Reports, v. 11, n. 1, 2021.
dc.identifier.doi10.1038/s41598-021-01350-y
dc.identifier.issn2045-2322
dc.identifier.scopus2-s2.0-85118676179
dc.identifier.urihttp://hdl.handle.net/11449/222817
dc.language.isoeng
dc.relation.ispartofScientific Reports
dc.sourceScopus
dc.titleAdvance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approachen
dc.typeArtigo
dspace.entity.typePublication

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