Let's consider more general nonlinear approaches to study teleconnections of climate variables

no code implementations • 15 Dec 2022 • D. Bueso, M. Piles, G. Camps-Valls

We argue that this method is essentially a particular case of the method called rotated complex kernel principal component analysis (ROCK-PCA) introduced in (Bueso et al., 2019, 2020), where we proposed the same approach: first transform the data to the complex plane with the Hilbert transform and then apply the varimax rotation, with the only difference that the eigendecomposition is performed in the dual (kernel) Hilbert space.

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