【摘要】 正在兴起的大规模低轨卫星星座（简称星链）和人工智能技术为地理学研究范式变革提供了历史性机遇，推动地理学继定性地理、定量地理、数字地理之后迈入“星链智能地理”的新纪元。在“星链智能地理”的发展框架下，未来地理学研究可依托星链提供的高时空分辨率监测数据，在多尺度（特别是全球尺度）上精准捕捉地理要素的高时频动态变化；通过耦合物理模式和人工智能技术，可实现自然与人文要素相互作用复杂过程、系统状态和界面变化的模拟实验，深化对变量耦合、多过程级联效应及遥相关机理等地理学核心问题的认识。为推动“星链智能地理”发展，亟须打造依托星链的新一代数据采集共享平台，无缝绘制全球地理资源要素“动态一张图”；构建物理和AI耦合的地理模拟器，实现地理要素、图景变化及影响的智能模拟预估。更多还原

【Abstract】 The integration of large-scale Low Earth Orbit satellite constellations(hereinafter referred to as "LEO constellations") and artificial intelligence(AI) technology presents a historic opportunity for a paradigm shift in geography research, heralding a new era for geography to evolve from qualitative geography, quantitative geography, and digital geography into the "LEO constellation-AI-driven Geography". Under this framework, future geographic research can rely on the high spatio-temporal resolution monitoring data provided by LEO constellations to accurately capture the high-frequency dynamic changes of geographic elements at multiple scales, particularly at the global scale. By coupling physical models with AI, it becomes feasible to conduct simulation experiments on the complex interactions between natural and human elements, system states, and interface changes. This will facilitate a deeper understanding of core geographic issues such as variable coupling, multi-process cascading effects, and teleconnection mechanisms. To propel "LEO constellation-AI-driven Geography",there is an urgent need to establish a new-generation data acquisition and sharing platform relying on LEO constellation, seamlessly creating a "dynamic map" of global geographic resources and elements. Additionally, a geographic process simulator that couples physical models and AI needs to be developed to intelligently simulate and predict changes and impacts of geographic elements and landscapes.更多还原