Savanna is one of the main African ecosystems. The tree community in the savanna is a key element and provides many ecosystem services. Unmanned aerial vehicles (UAVs) combined with photogrammetric analysis are useful tools to produce accurate 3D maps, which, in turn, help describe the structure of the tree populations. The purpose of this study was to evaluate the use of commercial economical UAVs to assess tree characteristics in the savanna. A Dji Spark UAV was used to map 24 1-ha plots in northern Senegal. The images were processed using Pix4D software to produce a high-resolution canopy height model (CHM). A total of 239 trees were selected and their heights and crown areas were manually measured in the field. A strong correlation was found between UAV and field measurements with R² = 0.84 for height and R² = 0.93 for crown area. Based on tree canopy colours and tree morphologies measured by UAV, it was possible to predict tree species with an error rate of 20%, using a random forest classification. This study thus confirms the possibility of using low-cost UAVs to assess tree structures in the savanna not only for research on tree communities in savanna, but also by forestry agencies to inform stakeholders.

稀树草原是非洲主要的生态系统之一。稀树草原上的树木群落是关键要素，并提供许多生态系统服务。无人飞行器（UAV）与摄影测量分析相结合是生成准确的3D地图的有用工具，而3D地图又有助于描述树木种群的结构。这项研究的目的是评估使用商业经济型无人机来评估热带稀树草原的树木特征。Dji Spark无人机用于在塞内加尔北部绘制24个1公顷的地块。使用Pix4D软件对图像进行处理，以生成高分辨率的树冠高度模型（CHM）。总共选择了239棵树，并在野外手动测量了它们的高度和树冠面积。发现无人机与R ^2的实地测量之间存在很强的相关性 高度= 0.84， 顶部面积R ² = 0.93。基于无人机测量的树冠颜色和树形，可以使用随机森林分类来预测误差为20％的树种。因此，这项研究证实了使用低成本无人机评估大草原中树木结构的可能性，不仅可以用于研究大草原中的树木群落，还可以通过林业机构告知利益相关者。