| 摘要 |
Research on tourism climate comfort is undergoing a paradigm shift from classic static assessment to intelligent dynamic sensing. Early models such as temperature-humidity index and tourism climate index, established based on data of meteorological stations, laid the foundation for the discipline but were unable to meet the dynamic demands of climate change, spatial heterogeneity, and individual experience. Global climate change is reshaping the landscape of tourism comfort and driving the assessment to shift towards future risk prediction. Downscaling technology becomes the key to connecting global scenarios and local assessments. Remote sensing and Internet of Things technologies have constructed a "sky-ground" collaborative sensing network, achieving a revolution in data acquisition. Artificial intelligence and big data analysis serve as the intelligent core to drive research from description to prediction. The new paradigm has significant potential in improving assessment accuracy and timeliness, but also faces challenges such as data integration, model interpretability, interdisciplinary integration, and ethical privacy. In the future, it is needed to develop interpretable AI, construct climate digital twins, and promote full-chain coupling research. This transformation is not merely an upgrade of methods, but a fundamental shift in the study of philosophy from an "environment-centered" perspective to an "experience-centered" one, providing key scientific support for sustainable tourism. |
