Assessing Forest Degradation Through Remote Sensing in the Brazilian Amazon: Implications and Perspectives for Sustainable Forest Management - Afonso Henrique Moraes Oliveira; Eraldo Aparecido Matricardi; Luiz Eduardo Oliveira e Cruz de Aragão; Iara Musse Felix; José Humberto Chaves; Mauro Mendonça Magliano; José Max Barbosa Oliveira-Junior; Thiago Almeida Vieira; Lizandra Elizeário dos Santos; Leonardo Pequeno Reis; Diogo Otávio Scália Pereira; Carlos Tadeu dos Santos Dias; et al. (Remote Sensing)
Forest degradation and forest disturbance are distinct yet often conflated concepts, complicating their definition and monitoring. Forest degradation involves interrupted succession and a severe reduction in forest services over time, caused by factors like fires, illegal selective logging, and edge effects. Forest disturbance, on the other hand, refers to abrupt, localized events, natural or anthropogenic, such as legal selective logging, tropical blowdowns, storms, or fires, without necessarily leading to long-term degradation. Despite the varying intensity and scale of forest degradation and disturbance, systematic studies distinguishing its types and classes are limited. This study reviews anthropogenic impacts on forests in the Brazilian Amazon, analyzing 80 scientific articles using remote sensing techniques and data. Most research focuses on the “arc of deforestation,” characterized by intense human activity, showcasing methodological advancements but also revealing gaps in monitoring less-studied regions like the central and western Amazon. The findings emphasize the need for advanced remote sensing tools to differentiate degradation types, particularly in sustainable forest management (SFM) contexts. Expanding research to underrepresented regions and refining methodologies are crucial for better understanding forest dynamics and improving conservation strategies. These efforts are essential to support effective forest management and informed policy development across the Amazon.