Information Theory provides the foundations of knowledge, communication, and inference, and is applied in geophysical contexts to infer process, feedback, and scale, to make use of Observatory Big Data, or to assess the performance of dynamical systems models.
This ongoing project applies these ideas in hydrological, ecological, and climatological contexts. We support the continued development of the GeoInfoTheory community of science.
Funding has been provided by NASA and NSF. The ProcessNetwork software is a community-developed MATLAB code that allows the calculation of information flows and the inference of processes using time-series data. The HydroBench software incorporates many ProcessNetwork features using Python scripts and functions.
Links to Resources
Sponsors and Funding
NASA #NNX06AF71H, and JPL SURP
National Science Foundation, 1241960, 1928406, 1928374
U.S. Geological Survey Powell Center for Analysis and Synthesis
Gordon and Betty Moore Foundation Data-Driven Discovery Investigator grant
Jupyter Meets the Earth project