The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 171–178, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-171-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 171–178, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-171-2021

  28 Jun 2021

28 Jun 2021

A CONCEPT FOR THE SEGMENTATION OF INDIVIDUAL URBAN TREES FROM DENSE MLS POINT CLOUDS

P.-R. Hirt, L. Hoegner, and U. Stilla P.-R. Hirt et al.
  • Photogrammetry and Remote Sensing, Technical University of Munich, Munich 80333, Germany

Keywords: mobile laser scanning, point cloud, instance segmentation, voxel, tree segmentation, urban areas

Abstract. In our daily lives, trees can be seen as the tallest and most noticeable representatives of the plant kingdom. Especially in urban areas, the individual tree is of high significance and responsible for a manifold of positive effects on the environment and residents. In the context of urban tree registers and thus monitoring of urban vegetation, we propose a general concept for the segmentation of trees from 3D point clouds. Mobile Laser Scanning (MLS) is introduced as the preferred sensor. Based on an analysis of earlier work in this field, we gather arguments and methods in order to involve segmentation in the bigger frame of a tree register workflow, including detailed modeling and change detection. Our concept for segmentation is based on a voxel-structure. In a first step, region growing approaches are used for ground removal and rough segmentation. Later, graph-based optimization will separate neighboring trees. For now, only the general concept can be introduced—quantitative analysis and optimization of the steps will follow in future work.