351
Views
0
CrossRef citations to date
0
Altmetric
Articles

Extraction of topographic deformation based on the 3D information of individual trees

, &
Pages 8668-8682 | Received 20 Oct 2018, Accepted 01 Apr 2019, Published online: 22 May 2019
 

ABSTRACT

Terrestrial laser scanning (TLS) has been used widely in topographic deformation monitoring, and the issue of deformation information extraction from multi-temporal point cloud data has high importance. Here, a method is developed for the extraction of topographic deformation in a forested area based on the 3D spatial information of individual trees. Initially, ground points are removed by using a local topographic surface fitting method, then individual trees are segmented using the PTrees algorithm; finally, the motion of individual trees is computed with a combination of global and local rigid-body transformations. Experimental validation results show that the proposed method is reliable to within a 0.12° maximum tilt error and 8.7 mm maximum displacement error. In addition, some inferences were drawn based on the original topography and the topographic deformation monitoring results. For example, a mining work-face was located beyond the eastern part of the study area, and trees growing in the middle part of this region of interest may face a survival challenge.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant No. 51504239.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 689.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.