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A new GIS-compatible methodology for visibility analysis in digital surface models of earth sites

As a GIS tool, visibility analysis is used in many areas to evaluate both visible and non-visible places. Visibility analysis builds on a digital surface model describing the terrain morphology, including the position and shapes of all objects that can sometimes act as visibility barriers. However,...

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Bibliographic Details
Published in:Di xue qian yuan. 2021-07, Vol.12 (4), p.101109, Article 101109
Main Authors: Ruzickova, Katerina, Ruzicka, Jan, Bitta, Jan
Format: Article
Language:English
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Summary:As a GIS tool, visibility analysis is used in many areas to evaluate both visible and non-visible places. Visibility analysis builds on a digital surface model describing the terrain morphology, including the position and shapes of all objects that can sometimes act as visibility barriers. However, some barriers, for example vegetation, may be permeable to a certain degree. Despite extensive research and use of visibility analysis in different areas, standard GIS tools do not take permeability into account. This article presents a new method to calculate visibility through partly permeable obstacles. The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation. Each iteration result represents 1% of vegetation permeability, which can thus range from 1% to 100% visibility behind vegetation obstacles. The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software. The incorporation of the proposed method in GIS software would facilitate work in many fields, such as architecture, archaeology, radio communication, and the military. [Display omitted] •A new method improves standard visibility analyse over the surface•The improvement is in counting with vegetation permeability•The method is based on a quasi-Monte Carlo simulation•The method is easy to implement in any GIS software•The method was tested on selected area and results are presented
ISSN:1674-9871
2588-9192
DOI:10.1016/j.gsf.2020.11.006