Machine Learning for Climate Change

AI for monitoring and forecasting

The use of machine learning methods in environmental and climate research has become more successful in recent years and thus offer interesting new solutions to tackle some of the most important problems in that area. We have strong expertise in building data infrastructures that can accommodate different data sources that then again can be used to train ML models that can be used for different services such as real-time notifications, predictions and simulations.


  1. Petry, Lisanne und Herold, Hendrik und Meinel, Gotthard und Meiers, Thomas und Müller, Inken und Kalusche, Elenav und Erbertseder, Thilo und Taubenböck, Hannes und Zaunseder, Elaine und Srinivasan, Vignesh und Osman, Ahmed Mohamed Magdi Mohamed und Weber, Beatrix und Jäger, Stefan und Mayer, Christian und Gengenbach, Christian (2020) Air Quality Monitoring and Data Management in Germany - Status Quo and Suggestions for Improvement. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIV-4, Seiten 37-43. 5th International Conference on Smart Data and Smart Cities, 30. Sept. - 2. Oct. 2020, Nice, France. DOI: 10.5194/isprs-archives-XLIV-4-W2-2020-37-2020 ISSN 1682-1750
  2. Petry, L., Meiers, T., Reuschenberg, D., Mirzavand Borujeni, S., Arndt, J., Odenthal, L., Erbertseder, T., Taubenböck, H., Müller, I., Kalusche, E., Weber, B., Kaeflein, J., Mayer, C., Meinel, G., Gengenbach, C., & Herold, H. (2021). Design and Results of an AI-Based Forecasting of Air Pollutants for Smart Cities. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, VIII-4/W1-2021, 89–96.