No abstract

Conserving tropical forests is crucial for the environment and future of our climate. Tropical rainforests worldwide, including the Brazilian Legal Amazon (BLA), offer exceptional ecosystem services. However, the disturbances that have been occurring more frequently within them are endangering their key role in tackling climate change. An alternative approach for preserving the intact forests that remain in the BLA is the delimitation of Indigenous Lands (ILs), which can, additionally, ensure the well-being of the traditional peoples inhabiting there. An increase in deforestation rates of the BLA in recent years, due to the weakening of the Brazilian environmental policy, is not confined to unprotected areas but is also occurring within ILs. Under this scenario, mining, not allowed in ILs, is a growing threat in these protected areas. Thus, using the freely available MapBiomas dataset, we have quantified for the first time the total mining area within ILs of the BLA from 1985 to 2020. Such activity jumped from 7.45 km2 in 1985 to 102.16 km2 in 2020, an alarming increase of 1271%. Three ILs (Kayapó, Mundurukú, and Yanomami) concentrated 95% of the mining activity within ILs in 2020 and, therefore, they require closer monitoring. Most of the mining in ILs in 2020 (99.5%) was related to gold extraction. A total of 25 of the 31 ILs of the BLA where mining activity was detected in at least one of 36 years analyzed (~81% of them) had a statistically significant increasing trend according to the Mann–Kendall test at 5%. The datasets used or cited in this study (MapBiomas, PRODES, and DETER) enable the monitoring of the current status of ILs, and the identification of emerging trends related to illegal activities. Therefore, they are critical tools for legal authorities.

The objective of this work was to detect land use and land cover changes in the municipality of Rondon do Pará, in the Brazilian Legal Amazon, through the Geographic Object-based Image Analysis (GEOBIA), aiming to identify whether its inclusion in the list of priority municipalities for actions to prevent, monitor and control deforestation in the Amazon (Decree 6.321/2007), has inhibited this process. The methodological procedure involved the calculation of vegetation indices to highlight interest classes, the segmentation of the images into geo-objects and the classification using Support Vector Machine (SVM) algorithm. Also, we evaluated the relationship between annual rates of particulate material with a diameter of fewer than 2.5 micrometers (PM2.5) emitted from fires and deforestation in Rondon do Pará. The results show the reduction of deforestation rates but the conversion, in absolute values, of 984,47 km² of natural vegetation to anthropized areas along the 2006-2017 period, and the reduction of the average PM2.5 fire emissions from 31,107 tons year-1 between 2002 and 2007 to 10,394 ton year-1 in the post-inclusion period (2008-2019). This represents that the inclusion of Rondon do Pará in this list was beneficial, but the suppression of natural vegetation was not totally curbed, reinforcing that changes from environmental policies are gradual. Activities that do not use fire to suppress natural vegetation, such as selective logging, common in Rondon do Pará, had impact. This makes it necessary to intensify inspections and the development of sustainable actions in the region.

Elaborado por Maurício Amormino Júnior -CRB6/2422O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores.2019 Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais.

O monitoramento climático é um elemento essencial para predições nas mudanças de temperatura e a sua influência na segurança e saúde ambiental. No entanto, a esparsa densidade de estações meteorológicas limita a obtenção de dados confiáveis e dificulta as análises a respeito de variáveis e eventos climáticos, tornando necessário o uso de estimadores de dados para onde não há medições, como as interpolações. Por meio deste trabalho, objetivou-se avaliar qual método de interpolação representa melhor a variável climática de temperatura máxima no Estado da Bahia, com o uso de séries históricas de temperatura e um Modelo Digital de Elevação proveniente de dados da Shuttle Radar Topographic Mission - SRTM. Pode-se observar que os interpoladores geoestatísticos apresentaram melhor desempenho, especialmente a Cokrigagem, e que a utilização de sistemas de informações geográficas são ferramentas importantes para monitoramento da temperatura.