摘要: Landslides pose a significant threat to both human society and environmental sustainability, yet, their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood. In this study, we projected global landslide susceptibility under four shared socioeconomic pathways (SSPs) from 2021 to 2100, utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) and static metrics. Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period (2001-2020), with the most significant increase of about 1% in the very far future (2081-2100) under the high emissions scenario (SSP5-8.5). Currently, approximately 13% of the world's land area is at very high risk of landslide, mainly in the Cordillera of the Americas and the Andes in South America, the Alps in Europe, the Ethiopian Highlands in Africa, the Himalayas in Asia, and the countries of East and South-East Asia. Notably, India is the country most adversely affected by climate change, particularly during 2081-2100 under SSP3-7.0, with approximately 590 million people-23 times the global average-living in areas categorized as having very high susceptibility.