From Observation to Information and Users: The Copernicus Marine Service Perspective

Autor: Pierre Yves Le Traon, Antonio Reppucci, Enrique Alvarez Fanjul, Lotfi Aouf, Arno Behrens, Maria Belmonte, Abderrahim Bentamy, Laurent Bertino, Vittorio Ernesto Brando, Matilde Brandt Kreiner, Mounir Benkiran, Thierry Carval, Stefania A. Ciliberti, Hervé Claustre, Emanuela Clementi, Giovanni Coppini, Gianpiero Cossarini, Marta De Alfonso Alonso-Muñoyerro, Anne Delamarche, Gerald Dibarboure, Frode Dinessen, Marie Drevillon, Yann Drillet, Yannice Faugere, Vicente Fernández, Andrew Fleming, M. Isabel Garcia-Hermosa, Marcos García Sotillo, Gilles Garric, Florent Gasparin, Cedric Giordan, Marion Gehlen, Marilaure L. Gregoire, Stephanie Guinehut, Mathieu Hamon, Chris Harris, Fabrice Hernandez, Jørgen B. Hinkler, Jacob Hoyer, Juha Karvonen, Susan Kay, Robert King, Thomas Lavergne, Benedicte Lemieux-Dudon, Leonardo Lima, Chongyuan Mao, Matthew J. Martin, Simona Masina, Angelique Melet, Bruno Buongiorno Nardelli, Glenn Nolan, Ananda Pascual, Jenny Pistoia, Atanas Palazov, Jean Francois Piolle, Marie Isabelle Pujol, Anne Christine Pequignet, Elisaveta Peneva, Begoña Pérez Gómez, Loic Petit de la Villeon, Nadia Pinardi, Andrea Pisano, Sylvie Pouliquen, Rebecca Reid, Elisabeth Remy, Rosalia Santoleri, John Siddorn, Jun She, Joanna Staneva, Ad Stoffelen, Marina Tonani, Luc Vandenbulcke, Karina von Schuckmann, Gianluca Volpe, Cecilie Wettre, Anna Zacharioudaki

Publikováno v: Frontiers in Marine Science, Vol 6 (2019)

The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical ocean and sea-ice state for the global ocean and the European regional seas. CMEMS serves a wide ran

Externí odkaz: https://doaj.org/article/c76e591722a9418bad7a104f22e3d970

Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme

Autor: Marko Mäkynen, Jari Haapala, Giuseppe Aulicino, Beena Balan-Sarojini, Magdalena Balmaseda, Alexandru Gegiuc, Fanny Girard-Ardhuin, Stefan Hendricks, Georg Heygster, Larysa Istomina, Lars Kaleschke, Juha Karvonen, Thomas Krumpen, Mikko Lensu, Michael Mayer, Flavio Parmiggiani, Robert Ricker, Eero Rinne, Amelie Schmitt, Markku Similä, Steffen Tietsche, Rasmus Tonboe, Peter Wadhams, Mai Winstrup, Hao Zuo

Publikováno v: Remote Sensing, Vol 12, Iss 7, p 1214 (2020)

The detection, monitoring, and forecasting of sea-ice conditions, including their extremes, is very important for ship navigation and offshore activities, and for monitoring of sea-ice processes and trends. We summarize here recent advances in the mo

Externí odkaz: https://doaj.org/article/eec7a484f68447368d950d4881091e6c

Bohai Sea Ice Parameter Estimation Based on Thermodynamic Ice Model and Earth Observation Data

Autor: Juha Karvonen, Lijian Shi, Bin Cheng, Markku Similä, Marko Mäkynen, Timo Vihma

Publikováno v: Remote Sensing, Vol 9, Iss 3, p 234 (2017)

We estimate two essential sea ice parameters—namely, sea ice concentration (SIC) and sea ice thickness (SIT)—for the Bohai Sea using a combination of a thermodynamic sea ice model and Earth observation (EO) data from synthetic aperture radar (SAR

Externí odkaz: https://doaj.org/article/96a03bb6446b4f848b5d843acb93fc0f

U-net with ResNet-34 backbone for dual-polarized C-band baltic sea-ice SAR segmentation

Autor: Juha Karvonen

Publikováno v: Annals of Glaciology, Pp 1-15

In this study, the U-net with ResNet-34, i.e. a residual neural network with 34 layers, backbone semantic segmentation network is applied to C-band sea-ice SAR imagery over the Baltic Sea. Sentinel-1 Extra Wide Swath mode HH/HV-polarized SAR data acq

Externí odkaz: https://doaj.org/article/7476279e0f94468c8d85a0e4908f68f4

Baltic Sea Ice Concentration Estimation From C-Band Dual-Polarized SAR Imagery by Image Segmentation and Convolutional Neural Networks

Autor: Juha Karvonen

Publikováno v: IEEE Transactions on Geoscience and Remote Sensing. 60:1-11

In this study application of convolutional neural networks (CNNs) preceded by synthetic aperture radar (SAR), image segmentation for sea ice concentration (SIC) estimation over the Baltic Sea from dual-polarized C-band SAR imagery is studied. Three a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1fc184d15174e65f18c38435f6513bb8
https://doi.org/10.1109/tgrs.2021.3097885