Rapid assimilation and analysis of a suit of remote sensing data for predicting extreme events and their impact on ecological-human systems
Rapid assimilation and analysis of a suit of remote sensing data for predicting extreme events and their impact on ecological-human systems
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DOI：
10.2172/1769770
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发表时间：
2021-03
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影响因子：
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通讯作者：
N. Falco
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文献类型：
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作者：
N. Falco
科学挑战。正在进行和未来的遥感（RS）任务预计将提供前所未有的数据量。希望这些数据将提高我们对地球系统功能及其对极端气候事件响应的预测性理解。然而，这种“数据洪流”带来了几个挑战：（1）我们如何快速综合大量数据并识别生态系统的紧急行为，特别是在极端事件下； （2）如何将这些知识有效地纳入地球系统模型（ESM）并推进应用和理论研究？我们预计下一代 ESM 将与基于理论的 RS 系统深度集成。然而，我们认为，实现这一目标的最快速途径是开发一种基于理论/模型的启发式方法，基于 RS 的估计将通过人工智能功能更快地推进科学发现。这种方法将能够确定如何更快地同化和分析遥感数据。发展此类能力对于捕获生物圈和生态系统变化极端事件（例如风暴、干旱）和相关灾害（例如火灾、山体滑坡、洪水）的关键驱动因素并量化其对自然（生物多样性、环境）和人类（基础设施、能源、农业）系统的影响至关重要。
Science Challenge. Ongoing and future remote sensing (RS) missions are expected to provide an unprecedented amount of data. The hope is that these data will improve our predictive understanding of the Earth System functioning and its response to extreme climate events. This 'data flood', however, poses several challenges: (1) how can we quickly synthesize the volume of data and identify emergent behavior of the ecosystems, particularly under extreme events; and (2) how can this knowledge be effectively incorporated in Earth system models (ESMs) and advance both applied and theoretical research? We envision the next-generation of ESMs will be deeply integrated with theory-informed RSsystems. However, we argue, that the most rapid pathway to get there is to develop a heuristic method based on theory/model-informed RS-based estimation will more rapidly advance scientific discoveries via AI capabilities. Such an approach will be able to identify how to more rapidly assimilate and analyze RS data. Developing such capabilities will be critical in capturing the key drivers of biosphere and ecosystem change extreme events (e.g., storms, droughts) and associated hazards (e.g., fires, landslides, floods) and quantifying their impact on both natural (biodiversity, environment) and human (infrastructure, energy, agriculture) systems.