Source

Applications¶

Surveys¶

All papers in this section look at applications in Earth observation e.g. parameter retrieval, time-scale modeling, remote sensing, and any data dealing with multi/hyperspectral imagery.

A Survey on Gaussian Processes for Earth-Observation Data Analysis - Camps-Valls et. al. (2016) | Paper

This survey introduces GPs in a fairly simple way and lists a few basic GP algorithms. It also goes over some applications such as parameter retrieval, emulation and feature ranking. It's a great overview of GPs in the field from standard GPs. The software recommendations are outdated. I suggest you check out the GPy library for all GP algorithms mentioned in the paper. Also the treatment of sparse GPs (especially Matrix-Vector-Multiplications (MVNs)) is very brief and underrated. See this for more information about large scale GPs.

Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth - Gewali et. al. (2019) | Paper

Physics-Aware¶

Physics-aware Gaussian processes in remote sensing - Camps-Valls et. al. (2018) | Paper