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UID:pretalx-opengeohub-summer-school-2025-DAN9MN@pretalx.earthmonitor.org
DTSTART;TZID=Europe/Amsterdam:20250904T153000
DTEND;TZID=Europe/Amsterdam:20250904T170000
DESCRIPTION:Discrete Global Grid Systems (DGGS) have emerged as a transform
 ative approach to minimizing spatial distortions in geospatial data proces
 sing. Unlike traditional methods that merely name locations\, DGGS offer a
  highly efficient data structure capable of reducing storage requirements 
 by up to 33% compared to the current Sentinel-2 UTM tiling grid. The perfo
 rmance of operations on DGGS native data cubes is intrinsically linked to 
 the cell index\, which plays a crucial role in data management and retriev
 al.\n\nMost DGGS implementations utilize a hierarchical one-dimensional in
 dex to name and sort cells\, optimizing them for parent-child queries. Thi
 s structure is particularly beneficial for operations such as upscaling an
 d downscaling\, which are essential for integrating data with varying spat
 ial resolutions. However\, many real-world applications\, such as visualiz
 ation\, fluid dynamics\, and convolutions\, require efficient handling of 
 distant neighbor queries based on spatial distances. These applications of
 ten rely on bounding boxes or moving windows\, which are not optimally sup
 ported by traditional DGGS implementations.\n\nIn response to these challe
 nges\, we introduce DGGS.jl\, a Julia package specifically developed to cr
 eate and utilize DGGS native data cubes optimized for distant neighbor que
 ries. Our package employs the DGGRID Q2DI index to store data on a hexagon
 al ISEA4H grid\, enabling compact and efficient data cube arrays. We have 
 implemented methods to seamlessly convert raster data between geographic a
 nd Q2DI coordinates\, access neighbor disks around a given cell\, and visu
 alize these data on a global scale.\n\nTo demonstrate the practical applic
 ation of DGGS.jl\, we present a hands-on workshop of our Julia package DGG
 S.jl to convert traditional geographical data cubes into DGGS native data 
 cubes. Furthermore\, we show how to process those data cubes and how to ac
 cess neighbors and regions around given coordinates.
DTSTAMP:20260624T124959Z
LOCATION:Expert Room 2
SUMMARY:Less distorted analyses of satellite imagery using Discrete Global 
 Grid Systems in Julia - Daniel Loos\, Luís Moreira de Sousa
URL:https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DAN
 9MN/
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