Open-Earth-Monitor Global Workshop 2026

Discrete Global Grid Systems (DGGS) tessellate the earth’s surface into zones of equal area and very similar shape, minimizing spatial distortions in geospatial data processing. DGGS are not only used for geocoding but also offer a highly efficient data structure by eliminating tile overlap compared to traditional grids like UTM used in Sentinel-2 products. In addition, many real-world applications, such as visualization or convolutions, require efficient handling of higher-order neighbor queries based on spatial distances, motivating a multidimensional DGGS coordinate system. This leads into DGGS native data cubes, in which the data is stored in such a DGGS grid to improve the performance on such operations.
In response to these challenges, we introduce DGGS.jl (https://danlooo.github.io/DGGS.jl), a Julia package specifically developed to create and utilize DGGS native data cubes optimized for indirect neighbor queries. Our package employs the DGGRID Q2DI index to store data on a grid based on the Icosahedral Snyder Equal Area projection, enabling compact and efficient data cube arrays. We have implemented methods to seamlessly convert raster data between geographic and Q2DI coordinates, access neighbor disks around a given cell, and visualize these data on a global scale. In addition, we developed an XYZ tile server, allowing us to view DGGS native data cubes in QGIS and in the browser. Finally, we used DGGS.jl to create such a data cube of Europe from quarterly cloudless Sentinel-2 mosaics of the Copernicus Data Space Ecosystem.