Mapping woodland species composition and structure using airborne spectral and LiDAR data

Tree and shrub species composition and vegetation structure are key components influencing the quality of woodland or forest habitat for a wide range of organisms. This paper investigates the unique thematic classes that can be derived using integrated airborne LiDAR and spectral data. The study area consists of a heterogeneous, semi‐natural broadleaf woodland on an ancient site and homogeneous broadleaf and conifer woodland on an adjoining plantation. A parcel‐based unsupervised classification approach was employed, using the first two Principal Components from 12 selected wavebands of HyMap data and a Digital Canopy Height Model extracted from LiDAR data. The resultant 52 data clusters were amalgamated into 10 distinct thematic classes that contain information on species composition and vegetation structure. The thematic classes are relevant to the National Vegetation Classification (NVC) scheme for woodlands and scrub of Great Britain. Furthermore, in distinguishing structural subdivisions within the s...