Jean-Marc Delouis
Senior research engineer at CNRS, specialize in data analysis across astrophysics and oceanography. With extensive expertise in AI, scattering transform, and statistical modeling, I contribute to cutting-edge projects such as Planck’s SRoll algorithm and the development of the FOSCAT library on PyPi. I currently lead projects integrating deep learning and dimensionality reduction techniques for Earth and space science applications, including sea ice analysis, galaxy mapping and turbulence modeling.
Session
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. In particular, this includes libraries that can work on the numeric cell ids defined by the specific DGGS.
xdggs is a library that provides a unified interface for xarray that allows working with and visualizing a variety of DGGS-indexed data sets.