Multi-decadal temporal reconstruction of Sentinel-3 OLCI-based vegetation products with multi-output Gaussian process regression

Autor: Dávid D.Kovács, Pablo Reyes-Muñoz, Katja Berger, Viktor Ixion Mészáros, Gabriel Caballero, Jochem Verrelst

Publikováno v: Ecological Informatics, Vol 83, Iss , Pp 102816- (2024)

Operational Earth observation missions, like the Sentinel-3 (S3) satellites, aim to provide imagery for long-term environmental assessment to monitor and analyze vegetation changes and dynamics. However, the S3 archive is limited in temporal availabi

Externí odkaz: https://doaj.org/article/33f9c74bf3384519937ea4b946d36b4b

Cloud-Free Global Maps of Essential Vegetation Traits Processed from the TOA Sentinel-3 Catalogue in Google Earth Engine

Autor: Dávid D. Kovács, Pablo Reyes-Muñoz, Matías Salinero-Delgado, Viktor Ixion Mészáros, Katja Berger, Jochem Verrelst

Publikováno v: Remote Sensing, Vol 15, Iss 13, p 3404 (2023)

Global mapping of essential vegetation traits (EVTs) through data acquired by Earth-observing satellites provides a spatially explicit way to analyze the current vegetation states and dynamics of our planet. Although significant efforts have been mad

Externí odkaz: https://doaj.org/article/a68e70c7ef09430db9cb9669ffe0de54

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

Autor: Pablo Reyes-Muñoz, Luca Pipia, Matías Salinero-Delgado, Santiago Belda, Katja Berger, José Estévez, Miguel Morata, Juan Pablo Rivera-Caicedo, Jochem Verrelst

Publikováno v: Remote Sensing, Vol 14, Iss 6, p 1347 (2022)

Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3

Externí odkaz: https://doaj.org/article/e82611827de54fedadefc0953b2af57b

Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data

Autor: José Estévez, Matías Salinero-Delgado, Katja Berger, Luca Pipia, Juan Pablo Rivera-Caicedo, Matthias Wocher, Pablo Reyes-Muñoz, Giulia Tagliabue, Mirco Boschetti, Jochem Verrelst

Publikováno v: José Estévez, Matías Salinero-Delgado, Katja Berger, Luca Pipia, Juan Pablo Rivera-Caicedo, Matthias Wocher, Pablo Reyes-Muñoz, Giulia Tagliabue, Mirco Boschetti, Jochem Verrelst (2022). Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data. Remote Sensing of Environment, 273, 112958.
Remote Sensing of Environment

The unprecedented availability of optical satellite data in cloud-based computing platforms, such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval models from the local to the planetary scale. Hybrid retrieval mod

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::824150b7fb5e755b4f72a1c0da194ded
https://pubmed.ncbi.nlm.nih.gov/36081832

Monitoring vegetation traits over Europe using top-of-atmosphere Sentinel-3 data in Google Earth Engine

Autor: Pablo Reyes-Muñoz, Luca Pipia, Matias Salinero-Delgado, Katja Berger, Santiago Belda, Juan Pablo Rivera-Caicedo, Jochem Verrelst

Monitoring the terrestrial photosynthetic capacity is vital for understanding ecological processes and modelling the responses of vegetated ecosystems to diverse environmental changes. Among multiple instruments foreseen to collect data over global t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::683464a84e33cf20ff26d9874949077f
https://doi.org/10.5194/egusphere-egu22-5919