Deforestation, Remote Sensing, Bolsa Floresta Program

Deforestation control is essential to avoid the impacts of forest loss. Therefore, understanding the process of opening small areas in primary forest is essential for the development of more detailed models, so that they are more representative of the local context, more refined and can support the construction of public policies such as the Bolsa Floresta Program (PBF). In this context, remote sensing (SR) appears as a promising tool, providing sufficient spatial and temporal coverage for the monitoring of small forest openings in the Amazon region. The objective of this work was to identify and quantify deforestation in areas larger than 0.5 ha of primary forests before and after the implementation of: Bolsa Floresta Program (PBF) in the Sustainable Development Reserves (RDS) of Rio Negro and Puranga Conquista, in the state of Amazonas. For this purpose, the methodology consisted of using spectral indices of vegetation such as the Normalized Difference Moisture Index (NDMI) that is sensitive to moisture levels in the vegetation, and the implementation of the PBF as the initial temporal marker for each RDS with three subsequent periods. The mapping showed, in general, that there is a downward trend regarding the opening of new areas in primary forest. However, when compared to the official data, the methodology used in this study is more sensitive, presenting increases in deforestation per period with values ten times higher. The results show the efforts of local families to comply with the rules of zero deforestation of the PBF and, as a consequence, the more detailed data, using this methodology, are essential to understand the dynamics of deforestation in small areas.