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On-Demand Earth System Data Cubes
April 23, 2024, 4:42 a.m. | David Montero, C\'esar Aybar, Chaonan Ji, Guido Kraemer, Maximilian S\"ochting, Khalil Teber, Miguel D. Mahecha
cs.LG updates on arXiv.org arxiv.org
Abstract: Advancements in Earth system science have seen a surge in diverse datasets. Earth System Data Cubes (ESDCs) have been introduced to efficiently handle this influx of high-dimensional data. ESDCs offer a structured, intuitive framework for data analysis, organising information within spatio-temporal grids. The structured nature of ESDCs unlocks significant opportunities for Artificial Intelligence (AI) applications. By providing well-organised data, ESDCs are ideally suited for a wide range of sophisticated AI-driven tasks. An automated framework for …
abstract analysis arxiv cs.cv cs.db cs.lg data data analysis datasets demand diverse earth framework information nature opportunities science temporal type
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