A direct geolocation method for aerial imaging surveys of invasive plants

A software tool was developed to extract the positions of features identified in individual undistorted images acquired by unmanned aircraft systems (UAS), to support operations to locate and control invasive organisms in sensitive natural habitats. The tool determines a feature’s position based on selected pixels and metadata in the image. Accuracy tests were performed using test imagery obtained from different camera altitudes (30, 40 and 50 m above ground level) and orientations (0°, 15° and 30° from the vertical) for direct geolocation of features of interest. As an additional case study, the tool was integrated with a deep neural network (DNN) for simultaneous detection and geolocation of the invasive tree Miconia calvescens in natural landscapes on Hawaii Island. For vertical camera orientations, median horizontal position errors were below 5 m. Images from oblique camera views resulted in larger median errors, approaching 10 m. While numerous approaches have been used to improve locational accuracy of objects identified in aerial imagery, the presented tool can be applied directly to individual images collected with commercial off-the-shelf UAS and flight planning software, making it accessible for applications in natural resource management. Furthermore, the tool does not require accurate ground control points, so it is especially suitable for locating invasive plants in dynamic natural landscapes with extensive forest canopy.