Drone-Based Identification and Monitoring of Two Invasive Alien Plant Species in Open Sand Grasslands by Six RGB Vegetation Indices

Today, invasive alien species cause serious trouble for biodiversity and ecosystem services, which are essential human survival. In order to effectively manage species, it is important know their current distribution the dynamics of spread. Unmanned aerial vehicle (UAV) monitoring one best tools gathering this information from large areas. Vegetation indices multispectral camera images often used this, but RGB colour-based vegetation can provide a simpler less expensive solution. The goal was examine whether six suitable identifying plant in QGIS environment on UAV images. To we determined shoot area number common milkweed (Asclepias syriaca) inflorescence blanket flowers (Gaillardia pulchella) as two typical open sandy grasslands. According results, cover identified with TGI SSI indices. producers’ accuracy 76.38% (TGI) 67.02% (SSI), while user’s 75.42% 75.12% respectively. For flower, IF index proved be most index. spite gave low producer’s 43.74% 51.4%. methods were not determination flower number, due significant overestimation. With presented here, data populations processed simple, fast, cost-effective manner, ensure precise planning treatments nature conservation practitioners.