ALIGNMENT OF HYPERSPECTRAL IMAGERY AND FULL-WAVEFORM LIDAR DATA FOR VISUALISATION AND CLASSIFICATION PURPOSES

• DOI: 10.5194/isprsarchives-xl-7-w3-1257-2015
• Publication Date: 2015-04-30T14:43:47Z
• Authors: M. Miltiadou; M. A. Warren; M. Grant; M. Brown
• Keywords: Polygon (computer graphics); Ranging

Abstract. The overarching aim of this paper is to enhance the visualisations and classifications airborne remote sensing data for forest surveys. A new open source tool presented aligning hyperspectral full-waveform LiDAR data. produces coloured polygon representations scanned areas aligned metrics from both datasets. Using provided by NERC ARSF, tree coverage maps are generated projected into polygons. 3D meshes show well-separated structures suitable direct rendering with commodity 3D-accelerated hardware allowing smooth visualisation. intensity profile each wave sample accumulated a discrete density volume building representation area. then polygonised using Marching Cubes algorithm. Further, three user-defined bands images mesh as RGB colours. Regarding data, previous work used extraction point clouds while introduces approach deriving information We generate multiple resolutions, including standard deviation width reflected waveform derived volume. Tree Bayesian probabilistic model due combination higher accuracy classification results expected.