The impact of voxel size, forest type, and understory cover on visibility estimation in forests using terrestrial laser scanning

Xin Zong (Corresponding Author), Tiejun Wang, A.K. Skidmore, Marco Heurich

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Abstract

Visibility (or viewshed) analysis, a common function in geographical information systems, is used in a wide range of fields such as urban planning, landscape management, and ecological research. However, measuring fine-scale visibility within a forest environment is challenging due to the structural complexity of plant architecture. Here we propose a new method for estimating visibility in forests using terrestrial laser scanning (TLS). We compare the visibility in forest plots derived from TLS with that derived from the gold standard photography-based approach and show that there is good agreement between the visibility derived from TLS-based and photography-based approaches with R2 values ranging from 0.67 to 0.79 and RMSE values ranging from 12.45% to 17.29%. We further examine the potential impacts of voxel size, forest type, and understory cover on TLS-based estimation accuracy. Voxel size has a strong effect on visibility estimates, with the most accurate estimates obtained at a voxel size of 10 cm. In general, the TLS-based approach achieves higher estimation accuracy in deciduous forest plots than in coniferous and mixed forest plots. The understory has a significant effect on the estimates, with a lower accuracy for dense understory cover. Our results demonstrate that TLS technology can serve as an appropriate approach to rapidly estimate fine-scale visibility in forests. More importantly, TLS provides the opportunity to move beyond estimating visibility at single locations and from limited perspectives, to estimating visibility at any location and from any perspective within a scanned area, thereby greatly improving sampling efficiency.
Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalGIScience & remote sensing
DOIs
Publication statusE-pub ahead of print/First online - 16 Feb 2021

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-HYBRID
  • UT-Hybrid-D

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