Journal of Spectral Imaging, Volume 6 Article ID a6 (2017)
Peer reviewed Paper
Mapping of vegetation species and communities in sensitive ecosystems is essential for identification and management of anthropogenic impacts. Unmanned aerial vehicle (UAV)-hyperspectral systems are among the latest technologies in remote sensing that hold a potential for obtaining unprecedented quality of remote sensing data for vegetation mapping and health status monitoring applications. In this study, high-resolution (1–1.5 cm) spectral imaging data (15 bands) from a tunable spectrometer is used to map five species of vegetation in a complex upland swamp environment. The overall accuracy of classification was found to be 88.9% with a kappa coefficient of 0.83. Three classes (bare earth, sedgeland grass and black sheoak) have achieved higher accuracy (above 78%) and one class (bracken fern) has lower accuracy (58%). UAV-hyperspectral technology is, therefore, an effective tool to identify and map sensitive swamp vegetation. The technology can be potentially applied to determine the health status of the species.
Keywords: UAV, hyperspectral, sensitive species, upland swamps
Journal of Spectral Imaging
Volume 6 Article ID a6 (2017)
Publication: 2 November 2017
© 2017 The Authors
This work is licensed under a Creative Commons BY Licence.