Detection of Forest Tree Losses in Côte d’Ivoire Using Drone Aerial Images

The fight against deforestation and forest degradation is now a major challenge for the preservation of global ecosystems. remote sensing monitoring methods that are currently deployed not always adapted to Ivorian context because high cloud cover, diversity shaded crops, land clearing techniques. This study proposes drone-based approach assess intra-annual tree losses in Bossématié classified forest. method used based on detection analysis areas from time series aerial images acquired by drones November 2018 April 2019 five sites studied Based photogrammetric models photointerpretation, heights crown sizes were estimated. Then, detected variation during period. An distribution reveals maximum height was 65.06 m 64.07 with an average 34.29–37.00 34.63–36.88 2019. area, meanwhile, estimated be 152 m². With estimation accuracy about 97%, these structural data indicate minimum loss 107 trees corresponding area 2 ha across all surveyed shows considerable local biodiversity should involved implementation preservation, rehabilitation, deployment strategies operational system Côte d’Ivoire.