Fusion of imaging spectrometer LIDAR data using support vector machines for land cover classification

A combination of the two remote sensing systems, imaging spectrometry (IS) and Light Detection And Ranging (LiDAR), is well suited to map fuel types, especially within the complex wildland urban interface. LiDAR observations sample the spatial information dimension describing geometric surface properties. Imaging spectrometry on the other hand samples the spectral dimension, which is sensitive for discrimination of species and surface types. As a non-parametric classifier Support Vector Machines (SVM) are particularly well adapted to classify data of high dimensionality and from multiplesources as proposed in this work. The presented approach achieves an improved land cover mapping based on a single SVM classifier combining the spectral and spatial information dimensions provided by imaging spectrometry and LiDAR. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-77980 Published Version Originally published at: Koetz, Benjamin; Morsdorf, Felix; Curt, T; van der Linden, S; Borgniet, L; Odermatt, Daniel; Alleaume, S; Lampin, C; Jappiot, C; Allgöwer, Britta (2007). Fusion of imaging spectrometer LIDAR data using support vector machines for land cover classification. In: ISPRS Working Group VII/1 Workshop ISPMSRS’07: ”Physical Measurements and Signatures in Remote Sensing” , Davos (CH), 12 March 2007 14 March 2007, 297-301. FUSION OF IMAGING SPECTROMETER AND LIDAR DATA USING SUPPORT VECTOR MACHINES FOR LAND COVER CLASSIFICATION IN THE CONTEXT OF FOREST FIRE MANAGEMENT B. Koetz a,* , F. Morsdorf a , T. Curt b , S. van der Linden c , L. Borgniet b , D. Odermatt a , S. Alleaume b , C. Lampin b , M. Jappiot b and B. Allgöwer d a Remote Sensing Laboratories (RSL), Dept. of Geography, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland, Email: [email protected] b Cemagref, Aix-en-Provence, Mediterranean ecosystems and associated risks research unit, 3275 route de Cézanne-CS 40061-13182 Aix en Provence cedex 5, France c Geomatics Department, Humboldt-Universität zu Berlin, Unter den Linden 6, D-10099 Berlin, Germany d Geographic Information Systems, Dept. of Geography, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland Commission VII, WG 1