| Summary: | Due to the influence of climate warming, the degradation of permafrost on the Qinghai-Tibet Plateau (QTP) has become evident. The formation of thermokarst hazards induced by the degradation of ice-rich permafrost has a significant impact on infrastructure construction and local ecology; therefore, it is necessary to assess its risk. In this study, a novel multiple thermokarst hazards risk assessment framework was proposed by combining stacking machine learning and potential environmental factors (vegetation factors, terrain factors, climate factors, and soil factors) to assess the risk of thermokarst hazards in the Yangtze River source region (YRSR). The results show the risk assessment (susceptibility) of thermokarst hazards in the YRSR from 2000 to 2016 at 500 m spatial resolution. This study divided the risk into 5 levels: very low (0.0-0.2), low (0.2-0.4), moderate (0.4-0.6), high (0.6-0.8), and very high (0.8-1.0)
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