Exploring Visualisation Methodology of Landscape Design on Rural Tourism in China
Author(s): |
Weijia Wang
Makoto Watanabe Kenta Ono Donghong Zhou |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 21 December 2021, n. 1, v. 12 |
Page(s): | 64 |
DOI: | 10.3390/buildings12010064 |
Abstract: |
Rural tourism has become a hot topic in China in the context of the nation’s rural revitalisation. Rural tourism allows tourists to experience local life and promotes local economic development. However, there is considerable controversy over the landscape design of ancient Chinese villages. Many problems, such as how to design and protect the landscape of these ancient villages and how to improve the tourist experience, are not resolved. For our research object, we selected the ancient Gaotiankeng Village in Kaihua County, Zhejiang Province. Using questionnaires, image interviews, and some user experience techniques such as mental maps, we collected user experience data by assessing design cases. The visualisation method presented a wide range of experience in the landscape and planning field. This study primarily used computer image processing, image entropy calculation, and colour mapping to process the data. A visualisation framework was defined to highlight the landscape aesthetics, landscape service, and tourists’ emotion. The results indicated the relationship of three elements. The objective of our study was to develop a method of landscape design and planning that can effectively enhance tourists’ experience and provide practical suggestions for rural landscapes and relatively better services. |
Copyright: | © 2021 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10657781 - Published on:
17/02/2022 - Last updated on:
01/06/2022