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Li, Z, An, J, Zhang, J, Shi, H, Gao, Y, Xue, J, Li, C and Mohi-ud-din, G (2024) Quantitative Evaluation of the View of the Landscape Using a Visibility Analysis Optimization Algorithm. Applied Sciences, 14 (6).
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Quantitative Evaluation of the View of the Landscape Using a Visibility Analysis Optimization Algorithm.pdf - Published Version Available under License Creative Commons Attribution. Download (5MB) | Preview |
Abstract
Visual evaluation of the landscape is an important way to judge landscape quality. In this study, by optimizing the vertical angle and relative slope parameters of a visibility analysis algorithm, we intuitively and quantitatively display visibility grid data on the landscape based on tourists’ viewpoints and realize the transformation from making calculations only for the visible area to quantitatively evaluating the quality of visually experiencing the landscape considering parallax. We consider a variety of landscape visual influence factors (visible area, landscape water system distribution, number of landscape resources) to construct an index system for evaluating landscape visual effects. Finally, a set of improved landscape visual evaluation methods is proposed by integrating the analytic hierarchy process (AHP) and an optimization algorithm into the visibility analysis. Validation of the case study of the ancient town Fenghuang shows that these methods can effectively distinguish good and bad landscape viewpoints in a scenic area and support planning and design decisions on the related spatial layout and viewing platform. This study provides a new perspective for developing a quantitative, intelligent digital landscape analysis system.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) G Geography. Anthropology. Recreation > G Geography (General) > G149 Travel. Voyages and travels (General) > G154.9 Travel and state. Tourism |
| Divisions: | Civil Engineering and Built Environment |
| Publisher: | MDPI |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 10 Jan 2025 14:49 |
| Last Modified: | 10 Jan 2025 14:49 |
| DOI or ID number: | 10.3390/app14062436 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/25244 |
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