Guillaume Eynard-Bontemps
Software research engineer at CNES since 2016, I've worked in satellite ground segment development and related projects for about 20 years. I've specialized myself in big data processing, deploying and using Hadoop and Spark for scientific data processing first in 2012. I then joined the CNES computing center team and helped users develop processing chains at scale using Dask or Slurm. At this time, I became a member of Pangeo community and contributed to deploy Dask enabled Jupyterhub for huge geospatial data analysis. I'm working now in the Data Campus division at CNES, where I maintain a snow detection tool and I also try to help improving the Python ecosystem around satellite raster processing (Xarray related projects like EOReader) and visualization.
Session
This talk will present and demonstrate new Python and Jupyter ecosystems tools to analyse huge amount of satellite or more generally geospatial data. Our goal is to demonstrate that we are close to be able to propose a Google Earth Engine open alternative, that anyone may use and contribute to. It is thus aimed at developers or scientists in the geospatial data analysis field, and will be about technologies such as JupyterGIS, Xarray, Titiler and OpenEO. A full use case demonstration on Snow Detection will be showcased at the end of the talk.