Machine Learning Information Fusion in Earth Observation: A Comprehensive Review of Methods, Applications and Data Sources

no code implementations • 7 Dec 2020 • S. Salcedo-Sanz, P. Ghamisi, M. Piles, M. Werner, L. Cuadra, A. Moreno-Martínez, E. Izquierdo-Verdiguier, J. Muñoz-Marí, Amirhosein Mosavi, G. Camps-Valls

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation.

BIG-bench Machine Learning Earth Observation

Statistical Learning for End-to-End Simulations

no code implementations • 7 Dec 2020 • J. Vicent, J. Verrelst, J. P. Rivera-Caicedo, N. Sabater, J. Muñoz-Marí, G. Camps-Valls, J. Moreno

This work evaluates the accuracy and computation cost of interpolation and emulation methods to sample the input LUT variable space.

Earth Observation