At OpenGeoHub, Chris supports the development of European wide land cover maps. He will be involved in developing data layers through the application of machine learning techniques on satellite imagery, helping policymakers and businesses achieve scalable insights from remote sensing data.
Specific tasks include but are not limited to:
- Remote Sensing data preparation, import, pre-processing, spatial overlay, and visualization,
- Model building and fine-tuning of Ensemble Machine Learning,
- Running cross-validation and accuracy assessment using statistical frameworks,
- Parallelization, and back-end development,
- Installation and optimization of software (under Linux OS or similar),
After taking part in the Future Planet Studies bachelor program at the University of Amsterdam Chris has worked with various levels of government and businesses. He joined OpenGeoHub to contribute as a machine learning engineer and researcher uncovering valuable insights from remote sensing data and help to bring those insights to users.
- 2021–present: Geospatial researcher at OpenGeoHub Foundation,
- Dec. 2020 - Present: Contributor Green City Watch open-source collective,
- Jan. 2018 – Dec. 2020: Co-founder and Data Scientist at Green City Watch
- March. 2019 – June 2019: Developer blended learning at University of Amsterdam,
- Feb. 2018 – Feb. 2019: Trainee Data Science at Xomnia stationed at the Port of Rotterdam,
- Sep. 2017 – Feb. 2018: GIS-specialist at Geodan stationed at de Persgroep Printing,
― Rutger Bregman, Humankind: A Hopeful History