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

Thais Lourençoni,Fernando Saragosa Rossi,Paulo Eduardo Teodoro,Mendelson Lima,Larissa Pereira Ribeiro Teodoro,Iago Manuelson Luz,Tatiane Deoti Pelissari,Regimar Garcia Dos Santos,Carlos Antonio Da Silva Junior

doi:10.1038/s41598-021-01350-y

Abstract

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.

Highlights

The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques
All variables quantified with the ImazonGeo monitoring system presented a significant increase trend by the Mann–Kendall test, i.e., there is a trend for increased deforestation over the years evaluated as well as an increase in polygons
The results show that the deforested area in the Amazonia portion of the State of Mato Grosso between August 2008 to October 2019 has increased over the 12 years evaluated (Supplementary Table 1)

Summary

Introduction

The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. One of the ways to contain deforestation in the region were the agreements signed, such as the Soy Moratorium (SoyM) in the soybean sector, which foresees the non-commercialization of soybeans originating from deforested areas as from August 2008, and the Beef Conduct Adjustment Terms (TAC) in the livestock sector[14,15,16]. Despite these efforts, the forest is still being illegally deforested and replaced with pastures and soy[17].

Objectives

Methods

Results

Conclusion