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Proceedings Paper

Lidar-based measurement of surface roughness features of single tree crowns
Author(s): Melanie Kolditz; Petra M. Krahwinkler; Jürgen Roßmann
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Paper Abstract

In remote sensing data, trees have a low interspecies variability and show a high variability within the tree species. Therefore, specific features that distinguish between unique properties of two tree species are required for a single tree based genera classification. To improve classification results, the suitability of seven surface roughness features, calculated on single tree crown regions, is studied. The algorithms developed to provide roughness parameters can be validated and prototyped in a Virtual Forest testbed. The features are extracted from a normalized digital surface model with a resolution of 0.4m per pixel. Within the test area of 340km2 more than 4000 single trees of eleven different species and additionally 200 buildings are available as reference data. Technical standards define several parameters to describe surface properties. These roughness features are evaluated in the context of single tree crowns. All of these features are based on the deviation of the height values of the tree crown to its mean height. As an additional feature the relationship between the crown's surface area and its occupied ground area is used. The evaluation results of these features regarding the discrimination of tree species on different levels - eleven single tree species, seven tree classes, deciduous and coniferous - and also towards discrimination of trees from buildings will be presented.

Paper Details

Date Published: 26 October 2011
PDF: 15 pages
Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII, 81800V (26 October 2011); doi: 10.1117/12.897568
Show Author Affiliations
Melanie Kolditz, RWTH Aachen Univ. (Germany)
Petra M. Krahwinkler, RWTH Aachen Univ. (Germany)
Jürgen Roßmann, RWTH Aachen Univ. (Germany)

Published in SPIE Proceedings Vol. 8180:
Image and Signal Processing for Remote Sensing XVII
Lorenzo Bruzzone, Editor(s)

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