Methodological Approach for Assessing Impacts and Recovery of Selectively Logged Forests in Tropical Forests - Castillo, Guido Vicente Briceno; Freitas, Lucas Jose Mazzei de; Reategui-Betancourt, Jorge Luis; Santos, Renato Prado dos; Miguelo, Eder Pereira; Carvalho, Osmar Luiz Ferreira de; Matricardi, Eraldo Aparecido Trondoli (Environmental Management and Sustainable Development, 2024)
<span style="color: #000000; font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 10px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: #ffffff; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; display: inline !important; float: none;">Ecosystem structure and function depends on the local and regional species pools, climate, geology, and type and frequency of disturbances. Tropical rain forests have long been growing in relatively stable climatic conditions and little disturbances until recent decades, when large-scale of land conversion into croplands and forest impacts by selective logging activities and forest fires have been more frequently observed. Selective logging causes forest degradation, which requires a rigorous monitoring system to control and mitigate forest impacts and recovery. Overtime forest disturbances and recovery can be estimated by using vegetation indices derived from remotely sensed data that enable us to distinguish disturbed from undisturbed forests and estimate the degree of those disturbances. This study aimed to assess the suitability of the Modified Soil Adjusted Vegetation Index (MSAVI) to detect selectively logged forests and estimate the forest recovery structure in a study site in the state of Pará, Eastern Amazon region. We retrieved the MSAVI from Landsat imagery to assess forest impacts by selective logging before and after logging. The estimated MSAVI index before and after logging activities were significantly different and enabled us to distinguish forest recovery structures after selective logging in the study site. Our methodological approach can be used to monitor selective logging activities and support planning of Sustainable Forest Management in tropical regions.