Earth observation from satellites and other platforms (aircrafts, drones) is crucial for our understanding of System Earth and to monitor the processes at the Earth surface. Accurate information on deforestation in the Amazon and the Congo basins, melting of the ice sheets, occurring droughts as in the summer of 2018 in western Europe comes from remote sensing sensors. The first Earth Observation images were launched in the seventies so we have fascinating timeseries of almost 50 years available to study the dynamics of the Earth. We use images at continental, regional and local level.
Computer models are essential to simulate natural earth surface processes and to run scenarios of climate change and human impact. Our group developed our own spatio-temporal simulation language, PCRaster, to build models simulating hydrological processes, erosion and landslides models. Information to run these models comes from remote sensing images, field studies or laboratory experiments.
The numerical models simulate as best as possible the physical earth surface processes in space and time but will never perfectly the real-world processes outside. The models are however very useful tools to assess the effect of human-decision making and to understand the complexity and feedbacks of systems.