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

Abstract

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

How Can Drones Uncover Land Degradation Hotspots and Restoration Hopespots? An Integrated Approach in the Mount Elgon Region with Community Perceptions

“…The photogrammetry methodology was followed using Agisoft Metashape software (vr1.7.3) for processing drone images, including orthorectification and mosaicking [28]. The workflow included the alignment of aerial images to establish the camera positions and orientations, building a dense cloud to generate a 3D model, creating a mesh for orthomosaic generation, and applying texture to the 3D model [39,40].…”

“…Drones have been employed to monitor the impact of tourism on trails' conditions, vegetation structure, and disturbances in protected areas [27]. In addition, drone-based assessments have revealed significant intra-annual tree cover losses, such as a minimum loss of 107 trees within a span of 2 years in a classified forest [28]. It is worth noting that UAV operations can be influenced by windy and rainy conditions, carry a higher risk of crashing, and are limited in spatial coverage [25,29].…”

Lab-on-a-Drone: remote voltammetric analysis of lead in water with real-time data transmission

“…[8][9][10][11][12] Although increasingly accessible, the cost of most commercially-available UAV place them outside the reach of most low-income communities, where the contaminants are typically discharged. Many of these systems can evaluate chlorophyll levels, 13 estimate nutrition of plants, 14 detect deforestation, 15 compute urbanization 16 or even identify cracks in concrete structures. 17 In addition, these sophisticated UAV need greater ight stability, greater autonomy and the possibility of carrying loads, use multiple rotors like the hexacopter, 8,18 leading to substantial cost increases.…”

“…Aiming to increase their accessibility, low-cost adaptations have been recently reported in the literature. [13][14][15][16][17] For environmental applications, the main applications using UAV are related to measurements of turbidity, pH, alkalinity, ionic conductivity and chlorophyll, using multiparameter probes. [13][14][15][16][17] However, many of these measurements employ analytical methods with limited selectivity.…”

“…[13][14][15][16][17] For environmental applications, the main applications using UAV are related to measurements of turbidity, pH, alkalinity, ionic conductivity and chlorophyll, using multiparameter probes. [13][14][15][16][17] However, many of these measurements employ analytical methods with limited selectivity. 5,19 Thus, the miniaturization of additional instrumentation could open additional avenues to monitor specic contaminants.…”