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Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576044/ https://www.ncbi.nlm.nih.gov/pubmed/34750464 http://dx.doi.org/10.1038/s41598-021-01350-y |
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author | Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa |
author_facet | Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa |
author_sort | Lourençoni, Thais |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8576044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85760442021-11-10 Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa Sci Rep Article 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. Nature Publishing Group UK 2021-11-08 /pmc/articles/PMC8576044/ /pubmed/34750464 http://dx.doi.org/10.1038/s41598-021-01350-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lourençoni, Thais da Silva Junior, Carlos Antonio Lima, Mendelson Teodoro, Paulo Eduardo Pelissari, Tatiane Deoti dos Santos, Regimar Garcia Teodoro, Larissa Pereira Ribeiro Luz, Iago Manuelson Rossi, Fernando Saragosa 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 |
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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576044/ https://www.ncbi.nlm.nih.gov/pubmed/34750464 http://dx.doi.org/10.1038/s41598-021-01350-y |
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