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Research on landscape planning of rural eco-tourism area based on network text analysis——Take the Longji Terrace Scenic Spot as an example

Authors :
Miao Yucong
Huang Yanling
Luo Shengfeng
Qin Yu
Source :
E3S Web of Conferences, Vol 194, p 05026 (2020)
Publication Year :
2020
Publisher :
EDP Sciences, 2020.

Abstract

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.

Subjects

Subjects :
Environmental sciences
GE1-350

Details

Language :
English, French
ISSN :
22671242
Volume :
194
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.6752d04d88814c1a8181c186baa18509
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202019405026