E3S Web Conf.
Volume 194, 20202020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|Number of page(s)||4|
|Section||Environmental Engineering, Ecological Environment and Urban Construction|
|Published online||15 October 2020|
Research on landscape planning of rural eco-tourism area based on network text analysis——Take the Longji Terrace Scenic Spot as an example
1 College of Tourism&Landscape Architecture, Guilin University of Technology, Guilin 541000, China
2 Institute of Guangxi Tourism Industry, Guilin 541000, China
At present, with the development of rural tourism in full swing, the protection and renewal of rural eco-tourism landscape has become an important part of rural landscape planning and construction in the new era. From the perspective of tourists’ perception, this paper takes Longji Terrace Scenic Spot in Guilin, Guangxi as an example, and uses ROST CM6 software analyzes tourists’ landscape perception and characteristics from high-frequency vocabulary, semantic network and other aspects. Based on this, it finds out the existing problems in the current landscape planning of rural eco-tourism area, and puts forward planning suggestions. The purpose is to provide reference for the rational planning and allocation of rural tourism landscape, to improve the quality of life of rural residents, and to promote the construction of beautiful villages. The results show that: (1) high-frequency words indicate that tourists focus on human landscape and natural landscape; (2) the semantic network matrix takes “landscape”, “Jiulong Wuhu”, “Longji Terrace”, “Jinkeng Dazhai” as the core; (3) tourists’ perception of the landscape of Longji Terrace Scenic Spot focuses on terrace scenery, ethnic customs and specialties, mountain climbing ways and other aspects; (4) tourists’ emotional evaluation of Longji Terrace Scenic Spot is mainly positive emotion, and relatively less negative emotion.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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