Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Wolfgang Dierking"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7393-7402 (2023)
In this article, we investigate the feasibility to align synthetic aperture radar (SAR) imagery based on a compensation for sea ice drift occurring between temporally shifted image acquisitions. The image alignment is a requirement for improving sea
Externí odkaz:
https://doaj.org/article/d990ecf804354dd09cc4cd06cec3292e
SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel‐1/AMSR‐2 for Sea Ice Classification
Autor:
Eduard Khachatrian, Wolfgang Dierking, Saloua Chlaily, Torbjørn Eltoft, Frode Dinessen, Nick Hughes, Andrea Marinoni
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 4, Pp n/a-n/a (2023)
Abstract The most common source of information about sea ice conditions is remote sensing data, especially images obtained from synthetic aperture radar (SAR) and passive microwave radiometers (PMR). Here we introduce an adaptive fusion scheme based
Externí odkaz:
https://doaj.org/article/8b0e28c0460f4b1ab9de4ff7308f4b45
Autor:
Carolina Gabarró, Nick Hughes, Jeremy Wilkinson, Laurent Bertino, Astrid Bracher, Thomas Diehl, Wolfgang Dierking, Veronica Gonzalez-Gambau, Thomas Lavergne, Teresa Madurell, Eirik Malnes, Penelope Mae Wagner
Publikováno v:
Frontiers in Remote Sensing, Vol 4 (2023)
We present a comprehensive review of the current status of remotely sensed and in situ sea ice, ocean, and land parameters acquired over the Arctic and Antarctic and identify current data gaps through comparison with the portfolio of products provide
Externí odkaz:
https://doaj.org/article/dc027fd6c64c46a289643fca73ac6200
Autor:
Eduard Khachatrian, Saloua Chlaily, Torbjorn Eltoft, Wolfgang Dierking, Frode Dinessen, Andrea Marinoni
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 9025-9037 (2021)
It is of considerable benefit to combine information obtained from different satellite sensors to achieve advanced and improved characterization of sea ice conditions. However, it is also true that not all the information is relevant. It may be redun
Externí odkaz:
https://doaj.org/article/87abbfc58a714a81b98853fe66e92844
Publikováno v:
Annals of Glaciology, Vol 61, Pp 260-270 (2020)
Automated classification of sea-ice types in Synthetic Aperture Radar (SAR) imagery is complicated by the class-dependent decrease of backscatter intensity with Incidence Angle (IA). In the log-domain, this decrease is approximately linear over the t
Externí odkaz:
https://doaj.org/article/157b0e2314ad4649aa5eeeaec4a1fa29
Publikováno v:
Annals of Glaciology, Vol 59, Pp 124-136 (2018)
The presence of leads with open water or thin ice is an important feature of the Arctic sea ice cover. Leads regulate the heat, gas and moisture fluxes between the ocean and atmosphere and are areas of high ice growth rates during periods of freezing
Externí odkaz:
https://doaj.org/article/930e03b3bb4947b29d38c5fa0e767e07
Autor:
Ferran Gibert, Jacqueline Boutin, Wolfgang Dierking, Alba Granados, Yan Li, Eduard Makhoul, Junmin Meng, Alexandre Supply, Ester Vendrell, Jean-Luc Vergely, Jin Wang, Jungang Yang, Kunsheng Xiang, Xiaobin Yin, Xi Zhang
Publikováno v:
Remote Sensing, Vol 13, Iss 14, p 2847 (2021)
This paper provides an overview of the Dragon 4 project dealing with operational monitoring of sea ice and sea surface salinity (SSS) and new product developments for altimetry data. To improve sea ice thickness retrieval, a new method was developed
Externí odkaz:
https://doaj.org/article/b8faa851b10b4ceebb447d67d99820bc
Publikováno v:
Remote Sensing, Vol 13, Iss 4, p 552 (2021)
Robust and reliable classification of sea ice types in synthetic aperture radar (SAR) images is needed for various operational and environmental applications. Previous studies have investigated the class-dependent decrease in SAR backscatter intensit
Externí odkaz:
https://doaj.org/article/4cf03685ef104ddaa60d77dc60e3c1a7
Publikováno v:
Remote Sensing, Vol 12, Iss 4, p 606 (2020)
Satellite remote sensing is an important tool for continuous monitoring of sea ice covered ocean regions and spatial and temporal variations of their geophysical characteristics [...]
Externí odkaz:
https://doaj.org/article/4d01bab02fd24031a55cf76163a642a5
Publikováno v:
Remote Sensing, Vol 11, Iss 13, p 1574 (2019)
We introduce the fully automatic design of a numerically optimized decision-tree algorithm and demonstrate its application to sea ice classification from SAR data. In the decision tree, an initial multi-class classification problem is split up into a
Externí odkaz:
https://doaj.org/article/9a1cd81af364485887c0ca70b43456d0