GAIA lab dans les médias: https://avisdexperts.ch/experts/gregoire_mariethoz
The main research interests of the research group reside in the development of stochastic methods that characterize the spatial and temporal variability inherent to natural systems, in particular related to the water cycle. We use numerical techniques using high-order, nonparametric statistics. These allow us to analyze complex datasets such as remote sensing data or the outputs of complex models (climate models or flow/transport models). The work pursued is at the frontier between Earth modeling and computer science, with a strong emphasis on stochastic models, training images and example-based modeling.
One contribution has been the development of numerical methods that offer improved possibilities to integrate different kinds of data, especially those using the semi-qualitative concept of a training image. These include algorithms to perform reconstructions and stochastic simulations, broadly known as MPS. Please check out the book on this topic.
The main keywords of our research themes are:
- Remote Sensing (Image processing, gap-filling, data fusion, statistical downscaling, pattern analysis, rainfall measurement and uncertainty quantification, climate change indicators).
- Geostatistics (Multiple-point geostatistics as well as variogram-based geostatistics, training images, model inference, spatial variability, texture synthesis, parallel computing).
- Hydrology (Spatio-temporal rainfall analysis, rainfall-runoff modeling, rainfall measurement, time series analysis, water resources management using Agent-Based Models).
- Hydrogeology (Aquifer heterogeneity, flow and transport modeling, inverse problems, pore-scale models, karst infiltration processes, groundwater usage optimization).