Getting Started: Applications of Information Theory in the Earth Sciences

Getting Started / Saturday, December 2nd, 2017

Applications of Information Theory in the Earth Sciences

  • Why hydrological predictions should be evaluated using information theory, SV Weijs, G Schoups & N van de Giesen (2010) (
  • HydroZIP: How Hydrological Knowledge can Be Used to Improve Compression of Hydrological Data, SV Weijs, N van de Giesen & MB Parlange (2013) (
  • Datcu, M., Seidel, K. and Walessa, M. (1998) ‘Spatial information retrieval from remote-sensing images. I. Information theoretical perspective’, IEEE Transactions on Geoscience and Remote Sensing, 36(5), pp. 1431-1445.
  • Brunsell, “A multiscale information theory approach to assess spatial–temporal variability of daily precipitation.” Journal of Hydrology 385.1 (2010): 165-172.
  • Pechlivanidis, I. G., B. Jackson, H. Mcmillan and H. V. Gupta (2016): Robust informational entropy-based descriptors of flow in catchment hydrology. Hydrological Sciences Journal 61 (1), 1-18, 10.1080/02626667.2014.983516.
  • Ruddell, B. L. and Kumar, P. (2009) ‘Ecohydrologic process networks: 1. Identification’, Water Resources Research, 45(3), 10.1029/2008wr007279.
  • Majda & B. Gershgorin, “Quantifying uncertainty in climate change science through empirical information theory.” Proceedings of the National Academy of Sciences 107.34 (2010): 14958-14963.
  • Ruddell, N. Brundell. & P. Stoy, “Applying information theory in the geosciences to quantify process uncertainty, feedback, scale.” Eos, Transactions American Geophysical Union 94.5 (2013): 56-56.
  • Nearing, G. S., H. V. Gupta and W. T. Crow (2013): Information loss in approximately Bayesian estimation techniques: A comparison of generative and discriminative approaches to estimating agricultural productivity. Journal of Hydrology 507, 163-173,
  • Leung and G. North (1990): Information Theory and Climate Prediction. Journal of Climate, V 3, 1990.