Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Peter Kettig"'
Autor:
Jérôme Colin, Olivier Hagolle, Lucas Landier, Sophie Coustance, Peter Kettig, Aimé Meygret, Julien Osman, Eric Vermote
Publikováno v:
Remote Sensing, Vol 15, Iss 10, p 2665 (2023)
The correction of atmospheric effects on optical remote sensing products is an essential component of Analysis Ready Data (ARD) production lines. The MAJA processor aims at providing accurate time series of surface reflectances over land for satellit
Externí odkaz:
https://doaj.org/article/7a75de0eb6564c378024b2024554b253
Autor:
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini, Christophe Fatras, Peter Kettig, Gwendoline Blanchet, Santiago Peña Luque, Simon Baillarin
Publikováno v:
Water Resources Research. 58
Autor:
Thomas Huang, Cedric David, Catalina Oadia, Joe T. Roberts, Sujay V. Kumar, Paul Stackhouse, David Borges, Simon Baillarin, Gwendoline Blanchet, Peter Kettig
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Autor:
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini, Christophe Fatras, Peter Kettig, Gwendoline Blanchet, Santiago Peña Luque, Simon Baillarin
Publikováno v:
IOP Conference Series: Earth and Environmental Science. 1136:012018
As the severity and occurrence of flood events tend to intensify with climate change, the need for flood forecasting capability increases. In this regard, the Flood Detection, Alert and rapid Mapping (FloodDAM) project, funded by Space for Climate Ob
Autor:
Christophe Taillan, Alphan Altinok, Gwendoline Blanchet, Romain Goeury, Nga T. Chung, Sophie Ricci, Simon Baillarin, Thanh-Huy Nguyen, Thomas S. Huang, Peter Kettig, Alix Roumagnac, Guillaume Valladeau
Publikováno v:
IGARSS
Floods are the most common natural disasters all over the world. The space climate observatory (SCO)-FloodDAM project aims at utilizing the capabilities of new observing strategies in order to better alert, detect and map flood events globally. Lever
Autor:
Eduardo Sanchez-Diaz, Peter Kettig, Romain Hugues, Simon Baillarin, Jean-Marc Delvit, Pierre Lassalle, Olivier Hagolle
Pixels covered by clouds in optical Earth Observation images are not usable for most applications. For this reason, only images delivered with reliable cloud masks are eligible for an automated or massive analysis. Current state of the art cloud dete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7eb283f65a4097a24b02e7725387bec5
https://doi.org/10.5194/egusphere-egu2020-9983
https://doi.org/10.5194/egusphere-egu2020-9983