Reconsidering the Suitability Assessment Method for Glacier Tourism: A Case Study from Tibet, China

冰川 旅游 环境资源管理 德尔菲法 层次分析法 捐赠 资源(消歧) 可持续发展 生态旅游 地理 水资源管理 自然地理学 环境科学 计算机科学 生态学 运筹学 政治学 工程类 计算机网络 考古 人工智能 法学 生物
作者
Hu Yu,Li Xu,Limin Liu
出处
期刊:Journal of resources and ecology [BioOne (Institute of Geographic Scienes and Natural Resources Research, Chinese Academy of Sciences)]
卷期号:13 (4) 被引量:1
标识
DOI:10.5814/j.issn.1674-764x.2022.04.014
摘要

Glacier retreat is becoming more widespread and severe due to global warming, and improper exploitation of glacier resources by tourism activities accelerates the destruction of glacier landscapes. Therefore, establishing a set of quantitative assessment tools is critical for guiding the rational utilization of glacier tourism resources. This study selected regional tourism resources, the natural environment of glaciers, service support, and market demand factors to build a suitability assessment method for glacier tourism (SAMGT), and it used the Delphi and Analytic Hierarchy Process (AHP) to determine the index weights, and combined them with GIS analysis technology. The Tibet autonomous region was proposed in this study as a case to build the SAMGT and provide scientific support for the rational development, scientific management, and sustainable development of glacier tourism resources. With regard to influencing the suitability of glacier tourism resource development, the results indicate that the weights of glacier resource endowment, ecological vulnerability, and tourism resource combination were high whereas that of market demand-related factors was low. The glacier tourism resource development area in Tibet can be divided into suitable, relatively suitable, barely suitable, and unsuitable exploitation zones, accounting for 5.39%, 9.76%, 15.28%, and 69.57% of the total area, respectively. Five representative glaciers were selected to verify the validity or test the rationality of SAMGT and prove that the model is reasonable, innovative, and effective from the perspectives of multiple dimensions and the comprehensiveness of the selected indicators.
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