Deforestation forecasts in the Legal Amazon using intervention models

Anderson Da Silva Costa,Larissa Steiner Chermont,Everaldo Barreiros De Souza,Marcelo Bentes Diniz,Debora Lisboa Correa Costa,Osmar Alves Lameira,Joaquim Carlos Barbosa Queiroz,Helyelson Paredes Moura

doi:10.33448/rsd-v10i4.13787

Anderson Da Silva Costa, Larissa Steiner Chermont + Show 6 more

Open Access

https://doi.org/10.33448/rsd-v10i4.13787

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Abstract

In this paper, it was used the Box-Jenkins methodology to assess the historical deforestation data generated by PRODES in the Brazilian Legal Amazon region from 1988 to 2018, in order to acquire deforestation forecasts. Considering that the model achieved an acceptable performance, forecasts were estimated for the next seven years (2019 to 2023). If there is no significant intervention in the series, deforestation rates are expected to remain ranging from 7,559.97 km2 to 7,730.88 km2, with a mean around 7,625.12 km2. In the case of an intervention, these quantities may vary from 10,429.28 km2 to 28,669.75 km2, with a mean near to 16,766.71 km2, indicating an increase of 119% on deforestation rates. In this sense, this article reinforces the need for maintenance and expansion of the environmental governance structure for the Brazilian Legal Amazon, according to what has happened in the last decade, especially based on the instruments of Command and Control related, for example, to expansion of Conservation Units, institution of the Rural Environmental Registry (CAR), inducing land regularization, improvement of the detection and monitoring system of burning and deforestation, such as PRODES and DETER, and also ostensive operations to combat illegal deforestation governmental institutions.

Highlights

The use of remote sensing techniques applied to forest cover monitoring is increasingly common (Ustin, et al, 1999)
If there is no significant intervention in the series, deforestation rates should be in the coming years (2019-2025) ranging from 7,559.97 km2 to 7,730.88 km2, with an average of 7625.12 km2 and 95% confidence intervals ranging from 2829.54 to 12641.31 km2
A study made by Sales & Souza (2011) well predicted deforestation sites from August 2010 to July 2012. The results of this prediction show that deforestation risk models can be an important tool for deforestation prevention in the Amazon, because they indicate the locations at risk with good accuracy. It is emphasized the importance of continued actions that allow a timely assessment of the evolution of deforestation in the Amazon, that can bring information to guide the development plans and policies in the region, with a view to promoting more sustainable use of the territory

Summary

Introduction

The use of remote sensing techniques applied to forest cover monitoring is increasingly common (Ustin, et al, 1999). One of the most frequently used techniques for monitoring forest cover in the Legal Amazon is the multi-temporal analysis of sensor observations (Foody, et al, 1996; Lucas, et al, 2002). This procedure allows us to evaluate the evolution of deforestation and to predict future scenarios. Deforestation is a complex phenomenon, there are techniques that develop probabilistic statistical models capable of estimating future values of a variable. Among these techniques stands out the Box-Jenkins methodology Box-Jenkins (1976). According to Abdel-aal and Al-Garni (1997), Box-Jenkins models have been widely used for modeling and forecasting in medical, environmental, financial and engineering applications

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