Impact of climate change on hiking: quantitative evidence through big data mining

This study measures quantitatively the impact of climate change on hiking across 100 cities in China by analyzing tourist-generated big data with a hybrid method involving the generalized additive model and segmented regression model. The results indicate that temperature, relative humidity, and sunshine duration influence hiking participation nonlinearly, with threshold effects. Results from a simulation study show that hiking in over 90% of the cities studied will be affected negatively by climate change in the future. The hiking duration will drop by 7.17% to 7.39% in 2050 and 7.16% to 7.57% in 2080 under RCP 4.5. The situation is even worse under RCP 8.5. We encourage the use of this approach among nations or regions with such available data for further research.