Alexander Kmoch

The rapid growth of Earth observation (EO) data, from satellite missions such as the Copernicus Sentinel missions to Digital Twin Earth frameworks like Destination Earth, which integrate high-resolution atmospheric and oceanic simulation models with the ever-growing satellite rem…

With discrete global gridding systems gaining interest, and storage options starting to form, the next question is how we can approach GIS style operations on DGGS structured data. Come discuss or learn more.

Discrete Global Grid Systems (DGGS) are increasingly adopted as a unified spatial reference framework for organising and analysing multi-source geospatial data at global scale.

This presentation covers the development of a national data cube for Estonia, integrating remote sensing data and using open-source tools. It provides analysis-ready data for biodiversity and carbon research, overcoming technical hurdles.

This hands-on workshop walks through a full DGGS data pipeline. You'll use the FOSS tool DGGRID to index geospatial data and then publish it using pydggsapi, a new open-source server for the OGC API DGGS standard. Leave with a running web service on your laptop.

Uber H3 has revolutionized spatial indexing, but its cell sizes vary a lot. I will introduce IGEO7, an aperture 7 hexagonal equal-area DGGS with its hierarchical indexing system Z7.

Over the past few years, Discrete Global Grid Systems (DGGS) that subdivide the earth into (roughly) equally sized faces have seen a rise in popularity. However, their in-memory representation is different from traditional projection-based data, which is either comprised of evenly shaped rectangular grid (aka raster) or discrete geometries (aka vector), and thus requires specialized tooling.

1. Introduction Traditional maps use projections to represent geospatial data in a 2-dimensional plane. This is both very convenient and computationally efficient.

1. Introduction Traditional maps use projections to represent geospatial data in a 2-dimensional plane. This is both very convenient and computationally efficient.