Texture-based landform segmentation of LiDAR imagery
journal contributionposted on 2023-05-16, 16:23 authored by Arko LucieerArko Lucieer, Stein, A
In this study, we implement and apply a region growing segmentation procedure based on texture to extract spatial landform objects from a light detection and ranging (LiDAR) digital surface model (DSM). The local binary pattern (LBP) operator, modeling texture, is integrated into a region growing segmentation algorithm to identify landform objects. We apply a multiscale LBP operator to describe texture at different scales. The paper is illustrated with a case study that involves segmentation of coastal landform objects using a LiDAR DSM of a coastal area in the UK. Landform objects can be identified with the combination of a multi-scale texture measure and a region growing segmentation. We show that meaningful coastal landform objects can be extracted with this algorithm. Uncertainty values provide useful information on transition zones or fuzzy boundaries between objects. (c) 2004 Elsevier B.V. All rights reserved.
Publication titleInternational Journal of Applied Earth Observation and Geoinformation
Department/SchoolSchool of Geography, Planning and Spatial Sciences
Place of publicationNetherlands