Using Uncrewed Aerial Vehicles for Identifying the Extent of Invasive Phragmites australis in Treatment Areas Enrolled in an Adaptive Management Program

Higher spatial and temporal resolutions of remote sensing data are likely to be useful for ecological monitoring efforts. There many different treatment approaches the introduced European genotype Phragmites australis, adaptive management principles being integrated in at least some long-term In this paper, we investigated how natural color a smaller set near-infrared (NIR) images collected with low-cost uncrewed aerial vehicles (UAVs) could help quantify aboveground effects efforts 20 sites enrolled Adaptive Management Framework (PAMF) spanning coastal Laurentian Great Lakes region. We used object-based image analysis field ground truth classify other cover types present each calculate percent Phragmites, including whether it was alive or dead, UAV images. The mean overall accuracy our 91.7% using four standardized classes (Live Dead Other Vegetation, Non-vegetation). Live class had user’s 90.3% producer’s 90.1%, 76.5% 85.2% (not all existed sites). These results show that UAV-based imaging classification can tool measure extent dead live series undergoing management. Overall, these indicate appears identifying sites.