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Abstract
Introduction: Costa Rica is committed to addressing environmental issues by involving a range of strategies and policies, with goals of sustainability and conservation. Nonetheless, addressing many challenges remains necessary, with the prominent issue of illegal activities, such as logging and land use change. Objective: To evaluate the direct detection capacity of tree cover losses caused by logging within the various land uses of the landscape, and their relationship with physical variables of the environment such as slope and proximity to the road network using remote sensing techniques. Methods: Tree cover losses were detected using time series analysis of the Normalized Difference Vegetation Index (NDVI) from Landsat and Sentinel images (S2) through the Breaks for Additive Season and Trend (BFAST) algorithm in The Golfo Dulce Forest Reserve (RFGD) and the Amistosa Biological Corridor (CBA). Selected sites where logging was detected were physically visited in the field and inspected using Unmanned Aerial Vehicles (UAVs). The results were analyzed through confusion matrices to determine the algorithms accuracy to detect illegal logging. Results: The study highlighted a significant relationship between NDVI change and logging activities on the ground. In areas with major NDVI changes (less than -500), the model accuracy was greater than 75 %. In addition, there is a significant relationship between logged areas and slope, and distance to roads. Conclusions: The proposed methodological approach allows identifying forest cover logging activities in space and time. It could be adopted and complement field operations to improve monitoring of illegal logging.
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