Coastal science has entered a new era of data-driven research, facilitated by satellite data and cloud computing. Despite its potential, the coastal community has yet to fully capitalize on these advancements due to a lack of tailored data, tools, and models. This paper demonstrates how cloud technology can advance coastal analytics at scale. We introduce GCTS, a novel foundational dataset comprising over 11 million coastal transects at 100-m resolution. Our experiments highlight the importance of cloud-optimized data formats, geospatial sorting, and metadata-driven data retrieval. By leveraging cloud technology, we achieve up to 700 times faster performance for tasks like coastal waterline mapping. A case study reveals that 33% of the world’s first kilometer of coast is below 5 m, with the entire analysis completed in a few hours. Our findings make a compelling case for the coastal community to start producing data, tools, and models suitable for scalable coastal analytics.

中文翻译：

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在行星范围内实现海岸分析


在卫星数据和云计算的推动下，沿海科学已经进入了数据驱动研究的新时代。尽管具有潜力，但由于缺乏量身定制的数据、工具和模型，沿海社区尚未充分利用这些进步。本白皮书演示了云技术如何大规模推进沿海分析。我们介绍了 GCTS，这是一个新颖的基础数据集，包含超过 1100 万条分辨率为 100 m 的沿海样带。我们的实验强调了云优化数据格式、地理空间排序和元数据驱动数据检索的重要性。通过利用云技术，我们在执行沿海水线测绘等任务时的性能提高了 700 倍。案例研究显示，世界上第一公里的海岸中有 33% 在 5 m 以下，整个分析在几个小时内完成。我们的研究结果为沿海社区开始生成适用于可扩展沿海分析的数据、工具和模型提供了令人信服的理由。