Abstract
Abstract. Anthropogenic climate change is already impacting native vegetation world-wide. Thus accurate mapping of current vegetation condition is necessary for benchmarking and conservation planning. We examine the potential for the mapping of native vegetation of forested ecosystems in south-western Australia using LiDAR data. Airborne LiDAR (distance between data points 1.2 m) and RGB imagery was acquired with a discrete 4-return Leica ALS 50-II system in April 2011 and vertical canopy profiles determined in Boyagin Nature Reserve. Elevation, slope and geomorphological descriptions of the terrain in combination with vertical canopy profiles based on presence/absence of returns within voxels were derived from the LiDAR data and processed at a spatial resolution of 4.0 meters. Based on these profiles, crown height and depth, ground cover, mean intensity of crown returns, presence of understory and number of vegetation layers were determined for each grid cell. Unsupervised classification revealed distinctive canopy profiles. Vegetation is strongly linked to geomorphology in this old landscape. Thus Kwongan shrubland occurs on the plateaus, Allocasuarina heugeliana woodland on the fringes of rock outcrops, Eucalyptus astringens and E. accedens woodland on breakaways and E. wandoo and Corymbia calophylla woodland in more fertile valley systems. The vegetation types present within distinctive spatial clusters were determined in two field visits. Vegetation types were mapped with an object-based image analysis approach at geomorphological, vegetation and tree scales using the geomorphology of the terrain and structural, textural and reflective characteristics of the canopy. All vertical profiles identified were present on each geomorphological unit. Tree species with a distinctive vertical profile such as Eucalyptus astringens and Allocasuarina heugeliana were defined and distinguished in combination with object-based geomorphological and spatial characteristics. Vegetation types were mapped accurately with a kappa coefficient of 0.80. We conclude that vertical profiles and geomorphology of the terrain derived from commercially available discrete return LiDAR systems provides a valuable means to benchmark the mapping of native vegetation in the forested ecosystems of south-western Australia.
Highlights
Regional mapping of vegetation is important for conservation planning and natural resource management (Wardell-Johnson and Williams 1996; Lawson and Wardell-Johnson 2006)
Boyagin has extensive areas with characteristic Kwongan communities dominated by Banksia nobilis, Eucalyptus drummondii and E. caesia and by Banksia attenuata and B. grandis (Dames and Moore 1985). 14 associations of woody plant communities were identified by Dames and Moore in their vegetation map of the area (Dames and Moore 1985)
Six PC images were required to capture 95%, and 9 PCs for 99% of the total variation in the layers as derived from the LiDAR dataset. This highlights the richness of LiDAR data
Summary
Regional mapping of vegetation is important for conservation planning and natural resource management (Wardell-Johnson and Williams 1996; Lawson and Wardell-Johnson 2006). Mapping the vegetation structure and biodiversity patterns in this global biodiversity hotspot is vitally important for benchmarking and conservation planning in the face of anthropogenic climate change. Vegetation mapping (type, condition, structure or floristic patterns) can be problematic in old and stable, but heterogeneous landscapes (Wardell-Johnson and Williams 1996; Mucina and Wardell-Johnson 2011), exemplified by much of south-western Australia. Complexity in vegetation mapping is amplified by disturbance, with temporal heterogeneity exacerbated in areas that include recent disturbance (e.g. fire)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
