Crop Phenology Retrieval Through Gaussian Process Regression. - Santiago Belda; Luca Pipia; Eatidal Amin; Matías Salinero; Pablo Reyes; Jochem Verrelst (IGARSS, 2021)

Mapping Essential Vegetation Variables Over Europe Using Gaussian Process Regression and Sentinel-3 Data in Google Earth Engine. - Pablo Reyes-Muñoz; Luca Pipia; Matías Salinero-Delgado; Charlotte De Grave; José Estévez; Santiago Belda; Jochem Verrelst (IGARSS, 2021)

Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine. - Luca Pipia; Eatidal Amin; Santiago Belda; Matías Salinero-Delgado; Jochem Verrelst (Remote. Sens., 2021)

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine. - Pablo Reyes-Muñoz; Luca Pipia; Matías Salinero-Delgado; Santiago Belda; Katja Berger; José Estévez; Miguel Morata; Juan Pablo Rivera Caicedo; Jochem Verrelst (Remote. Sens., 2022)

Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression. - Matías Salinero-Delgado; José Estévez; Luca Pipia; Santiago Belda; Katja Berger; Vanessa Paredes Gómez; Jochem Verrelst (Remote. Sens., 2022)

Synergy of Sentinel-1 and Sentinel-2 Time Series for Cloud-Free Vegetation Water Content Mapping with Multi-Output Gaussian Processes. - Gabriel Caballero; Alejandro Pezzola; Cristina Winschel; Paolo Sanchez Angonova; Alejandra Casella; Luciano Orden; Matías Salinero-Delgado; Pablo Reyes-Muñoz; Katja Berger; Jesús Delegido; Jochem Verrelst (Remote. Sens., 2023)

Cloud-Free Global Maps of Essential Vegetation Traits Processed from the TOA Sentinel-3 Catalogue in Google Earth Engine. - Dávid D. Kovács; Pablo Reyes-Muñoz; Matías Salinero-Delgado; Viktor Ixion Mészáros; Katja Berger; Jochem Verrelst (Remote. Sens., 2023)