The Use of an Unmanned Aerial Vehicle for Tree Phenotyping Studies

A strip of 20th-century landscape woodland planted alongside a 17th to mid-18th century ancient and semi-natural (ASNW) was investigated by applied aerial spectroscopy using an unmanned vehicle (UAV) with multispectral image camera (MSI). simple classification approach normalized difference spectral index (NDSI), derived principal component analysis (PCA), enabled the identification non-native trees within boundary. The tree species this boundary, classified NDSI, were further segmented machine learning segmentation method k-means clustering. This combined innovative has multiple in Phenotyping at canopy level UAV MSI, across 8052 m2, identified black pine (23%), Norway maple (19%), Scots (12%), sycamore (19%) as well native (oak silver birch, 27%). data corroborated field ground-level, over area 6785 that confirmed presence (26%), (30%), (10%), (14%) other 20%). benefits UAV, MSI camera, for monitoring boundaries next new housing development are demonstrated.