Volume XXXIX-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 541-546, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B7-541-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 541-546, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B7-541-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

  05 Oct 2012

05 Oct 2012

THE BENEFITS OF TERRESTRIAL LASER SCANNING AND HYPERSPECTRAL DATA FUSION PRODUCTS

S. J. Buckley1, T. H. Kurz1, and D. Schneider2 S. J. Buckley et al.
  • 1Uni CIPR, Postboks 7810, N-5020 Bergen, Norway
  • 2Technische Universität Dresden, Institute of Photogrammetry and Remote Sensing, D-01062 Dresden, Germany

Keywords: Hyper spectral, lidar, fusion, visualization, analysis, texture, value-added, photo-realism

Abstract. Close range hyperspectral imaging is a developing method for the analysis and identification of material composition in many applications, such as in within the earth sciences. Using compact imaging devices in the field allows near-vertical topography to be imaged, thus bypassing the key limitations of viewing angle and resolution that preclude the use of airborne and spaceborne platforms. Terrestrial laser scanning allows 3D topography to be captured with high precision and spatial resolution. The combination of 3D geometry from laser scanning, and material properties from hyperspectral imaging allows new fusion products to be created, adding new information for solving application problems. This paper highlights the advantages of terrestrial lidar and hyperspectral integration, focussing on the qualitative and quantitative aspects, with examples from a geological field application. Accurate co-registration of the two data types is required. This allows 2D pixels to be linked to the 3D lidar geometry, giving increased quantitative analysis as classified material vectors are projected to 3D space for calculation of areas and examination of spatial relationships. User interpretation of hyperspectral results in a spatially-meaningful manner is facilitated using visual methods that combine the geometric and mineralogical products in a 3D environment. Point cloud classification and the use of photorealistic modelling enhance qualitative validation and interpretation, and allow image registration accuracy to be checked. A method for texture mapping of lidar meshes with multiple image textures, both conventional digital photos and hyperspectral results, is described. The integration of terrestrial laser scanning and hyperspectral imaging is a valuable means of providing new analysis methods, suitable for many applications requiring linked geometric and chemical information.