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Historical trends of degradation,loss,and recovery in the tropical forest reserves of Ghana

International Journal of Digital Earth 2022年第1期15卷 30-51页

作者： Michael C.Wimberly Francis K.Dwomoh Izaya Numata foster mensah Jacob Amoako Dawn M.Nekorchuk Andrea McMahon Department of Geography and Environmental Sustainability University of OklahomaNormanOKUSA Department of Geography and Geospatial Sciences South Dakota State UniversityBrookingsSDUSA Centre for Remote Sensing and Geographic Information Services University of GhanaAccraGhana The Forestry Commission of Ghana AccraGhana

The Upper Guinean Forest region of West Africa,a globally significant biodiversity hotspot,is among the driest and most human-impacted tropical *** used Landsat to study forest degradation,loss,and recovery in the forest reserves of Ghana from 2003 to *** canopy cover maps were generated using random forests and results were temporally segmented using the LandTrendr *** cover was predicted with a predicted-observed r2 of 0.76,mean absolute error of 12.8%,and mean error of 1.3%.Forest degradation,loss,and recovery were identified as transitions between closed(>60%cover),open(15–60%cover)and low tree cover(<15%cover)*** was relatively slow from 2003 to 2015,but there was more disturbance than recovery resulting in a gradual decline in closed canopy *** 2016,widespread fires associated with El Niño drought caused forest loss and degradation across more than 12%of the moist semi-deciduous and upland evergreen forest *** workflow was implemented in Google Earth Engine,allowing stakeholders to visualize the results and download *** about historical disturbances will help to prioritize locations for future studies and target forest protection and restoration activities aimed at increasing resilience.

关键词： Landsat random forests machine learning time series LandTrendr drought wildfire

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