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proceedings of the 2025 conference on big data from-KJ0125486ENN.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/112591 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/112591 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/112591 archive 2 disk0/00/02/12/82 2026-02-03 08:55:20 2026-02-03 08:55:20 2026-02-03 08:55:20 book_section show Ho Y.-F. Heisig J. Milenkovic M. 2387 Parente L. Simoes R. Hengl T. pub ASA NODES Current satellite LiDAR missions, such as GEDI and ICESat- 2, provide billions of points annually that are typically not cloud-optimized and require additional quality filtering before any further analysis. In this study, we present Open-LandMap GEDI (OLM-GEDI), a new open, cloud-optimized, and global GEDI point dataset, for which we establish a spatio-temporal structure to facilitate efficient access. We show random access to OLM-GEDI achieves 20 seconds and a minute for areas around 50-thousand and 3-million km2, respectively. The OLM-GEDI STAC catalog is further established, which can be readily loaded into a local or cloud computing environment, such as openEO. This open GEDI dataset can be beneficial to future studies to enhance their reproducibility and mitigate the complexity of handling large GEDI data volumes (∼ 120 TiB) and quality filters. 2025 Publications Office of the European Union 10.2760/2119408 3524 public Luxembourg 69-72 TRUE 978-9268319352 Proceedings of the 2025 conference on Big Data from Space (BiDS'25) Kempeneers P. Lumnitz S. Albani S. info:eu-repo/semantics/bookPart