Author
Listed:
- Huang, Sheng
- Yi, Jiawei
- Du, Yunyan
- Liang, Fuyuan
- Xu, Rui
- Wang, Nan
- Qian, Jiale
- Tu, Wenna
- Luo, Peixian
- Xing, Andrew Z.F.
Abstract
The Qinghai-Tibet Plateau (QTP) is globally recognized as a prime tourism destination, renowned for its unique plateau landscapes and rich cultural heritage. Assessing the supply of cultural ecosystem services (CES) in this vast, data-scarce region holds paramount significance for local sustainable tourism development. However, limited research has addressed this issue. This study harnessed over 60,000 outdoor hiking trajectories from tourists and outdoor enthusiasts (2017–2020) to map both the current and potential CES provision across the QTP. Our findings show that only about 16 % of the plateau currently offers CES experiences for tourists. This supply is unevenly distributed, with 39 % of the tourist visits concentrated in the coniferous forest ecoregions of eastern QTP. Using robust random forest models and advanced AI techniques, we identify key biophysical factors—landscape diversity and water bodies—as well as socioeconomic predictors, such as proximity to hotels and roads, that influence CES availability. We estimate that an additional 4.8 % of the QTP’s area could offer high CES supply, contrasting with the current 1.2 % realized CES supply. These high-potential zones are promising candidates for new tourist attractions and could benefit from targeted infrastructure investment. Our study highlights the potential of tourist-contributed Volunteered Geographic Information (VGI) in assessing cultural services and informing tourism planning.
Suggested Citation
Huang, Sheng & Yi, Jiawei & Du, Yunyan & Liang, Fuyuan & Xu, Rui & Wang, Nan & Qian, Jiale & Tu, Wenna & Luo, Peixian & Xing, Andrew Z.F., 2025.
"Unveiling the potential supply of cultural ecosystem services on the Qinghai-Tibet Plateau: Insights from tourist hiking trajectories,"
Ecosystem Services, Elsevier, vol. 73(C).
Handle:
RePEc:eee:ecoser:v:73:y:2025:i:c:s2212041625000154
DOI: 10.1016/j.ecoser.2025.101711
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