Studying global change with satellites
Our research focuses on the application and development of satellite data sets and derived products to observe, analyse, model and predict changes in vegetation and the related impacts on the carbon and water cycle in ecosystems. We use and develop data-driven methods such as time series analysis and machine learning as well as process-based environmental models and model-data integration techniques.
© M. Forkel
Research of the Environmental Remote Sensing Group
We develop and use satellite observations to obtain information about the interactions between the climate, ecosystems, and vegetation. We aim to better quantify and understand changes in global land ecosystems and their impacts on carbon and water cycling. Therefore, we develop methods to analyse satellite observations, to predict ecosystem dynamics from satellite observations with machine learning approaches, and use satellite observations to improve global vegetation models.
Research questions
- Microwave remote sensing: Which information on vegetation properties can be derived from microwave satellites?
- Data integration: How can optical and microwave satellite observations be combined to better characterise vegetation changes?
- Predictive Earth observation: How can satellite observations be used to predict ecosystem states and processes by using machine learning methods?
- Phenology and photosynthesis: How did the seasonality of vegetation change in the last decades? What are the impacts on photosynthesis and the global carbon cycle?
- Vegetation dynamics: How did the structure and composition of ecosystems change in the last decades?
- Fires and other disturbances: How can we comprehensively observe and model drivers, dynamics and impacts of ecosystem disturbances from satellite observations?
- Model evaluation and development: How can satellite data be used to improve dynamic global vegetation models?