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Opaque voxel-based tree models for virtual laser scanning in forestry applications

Weiser, Hannah; Winiwarter, Lukas; Anders, Katharina; Fassnacht, Fabian Ewald ORCID iD icon 1; Höfle, Bernhard
1 Institut für Geographie und Geoökologie (IFGG), Karlsruher Institut für Technologie (KIT)

Abstract:

Virtual laser scanning (VLS), the simulation of laser scanning in a computer environment, is a useful tool for field campaign planning, acquisition optimisation, and development and sensitivity analyses of algorithms in various disciplines including forestry research. One key to meaningful VLS is a suitable 3D representation of the objects of interest. For VLS of forests, the way trees are constructed influences both the performance and the realism of the simulations. In this contribution, we analyse how well VLS can reproduce scans of individual trees in a forest. Specifically, we examine how different voxel sizes used to create a virtual forest affect point cloud metrics (e.g., height percentiles) and tree metrics (e.g., tree height and crown base height) derived from simulated point clouds. The level of detail in the voxelisation is dependent on the voxel size, which influences the number of voxel cells of the model. A smaller voxel size (i.e., more voxels) increases the computational cost of laser scanning simulations but allows for more detail in the object representation. We present a method that decouples voxel grid resolution from final voxel cube size by scaling voxels to smaller cubes, whose surface area is proportional to estimated normalised local plant area density. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000137077
Veröffentlicht am 15.09.2021
Originalveröffentlichung
DOI: 10.1016/j.rse.2021.112641
Scopus
Zitationen: 18
Web of Science
Zitationen: 17
Dimensions
Zitationen: 20
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 0034-4257, 1879-0704
KITopen-ID: 1000137077
Erschienen in Remote Sensing of Environment
Verlag Elsevier
Band 265
Seiten Art.-Nr.: 112641
Nachgewiesen in Dimensions
Scopus
Web of Science
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