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In order to take advantage of the unprecedented opportunity to measure global inland surface water heights using new-generation spaceborne instruments like ICESat-2’s Advanced Topographic Laser Altimeter System (ATLAS), robust water body shape information is necessary to group photon returns into body transits for along-track processing and to define water edges. A code environment that is able to combine known water body extent from past studies with real-time satellite observations can allow for such results. Even a static water body mask representing the state of a previous time, when working in conjunction with dynamic width-finding software algorithms that take advantage of contemporary return analysis, offers the opportunity for analysis of water surface profiles that change between satellite overpasses. However, previously existing masks do not include all water body types, are of insufficient resolution, or are not native to a format that allows for precise buffering, scalability, and efficient file size. By merging diverse buffered data sets in a modular, updatable fashion, a new global inland water body masking approach is created that can work in conjunction with an operational retrieval algorithm to identify water bodies globally and process to their edges for ICESat-2 analysis or other scientific investigations.
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Stoll et al. (2026) studied this question.
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