遥感科学与技术领域十大前沿问题

Remote sensing is a fundamental tool for understanding the Earth system. The integration of spaceborne, airborne, tower-based, and ground-based multi-platform collaborative observations with emerging technologies, including artificial intelligence, big data, and digital twins, is reshaping remote sensing paradigms. Traditional approaches based on static, single-sphere, and morphological observations are evolving toward a comprehensive framework that integrates dynamic, cross-sphere process inversion and 3-D perspective detection, thereby accelerating the transformation of geoscience toward a data-driven and quantitatively analytical paradigm. This study distills 10 cutting-edge scientific issues arising from the ongoing transformation of remote sensing and groups them into three major categories. The first category focuses on theory and modeling, covering multidimensional radiative transfer mechanisms, remote sensing foundation models and intelligent agents, and penetrating remote sensing of polar ice sheets. It aims to establish a unified modeling framework that integrates physical mechanisms with artificial intelligence. The second category centers on observational technologies, including virtual constellation collaborative observation, multimodal real-time data processing, as well as natural disaster monitoring and early warning, with an emphasis on advancing multi-platform collaboration and intelligent processing. The third category addresses systematic applications, involving carbon – water – energy cycle regulation, habitable planet exploration, human – environment system integration, and climate change impact assessment, aiming to meet critical scientific research and societal demands. These three categories collectively underline three key development directions: the in-depth integration of remote sensing and artificial intelligence, the synergistic utilization of multi-source geospatial data, and the systematic upgrade of the“observation-to-decision” paradigm. Specifically, theoretical research prioritizes breakthroughs in fundamental mechanisms, technological research focuses on systematic engineering implementation, and applied research targets interdisciplinary practical deployment. Overall, remote sensing science is transitioning from conventional experience-driven approaches to a novel paradigm that integrates physical mechanism constraints and data-driven analytics, while evolving from static environmental monitoring touard dynamic prediction and intelligent decision-making. Future research efforts should prioritize interdisciplinary collaboration, open scientific platforms development, and international cooperation to address major global challenges, including climate change, natural disaster outbreaks, ecological degradation, and deep-space exploration.