A. Regmi, M. E. Leinonen, A. Pärssinen and M. Berg, "Monitoring Sea Ice Thickness Using GNSS-Interferometric Reflectometry," in IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 2001405, doi: 10.1109/LGRS.2022.3198189
Monitoring sea ice thickness using GNSS-interferometric reflectometry
|Author:||Regmi, Ankit1; Leinonen, Marko E.1; Pärssinen, Aarno1;|
1Centre for Wireless Communications-Radio Technologies (CWC-RT), University of Oulu, 90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 5.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022082456062
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2022-08-24
This letter presents the analysis of frozen sea surface properties using low-cost and low-complexity terrestrial global navigation satellite system (GNSS) receivers. Monitoring sea ice thickness and the mean sea level (MSL) of the frozen sea are performed using the interference frequency obtained by the GNSS interference pattern (IP) technique. The height variations between the GNSS antenna and the sea surface evaluated using the IP of the direct and reflected carrier-to-noise density ratio (C/N0) are used to find the corresponding MSL. The GNSS-reflectometry (GNSS-R) derived MSL for open sea conditions agreed well with the mareograph data with a root-mean-squared error (RMSE) of 2.72 cm with an R-squared value of 0.9644. For frozen sea, a notable difference was observed between the measured MSL and ground-truth MSL values. This difference was caused by the combined thickness of snow and ice above the frozen sea surface, also known as the total freeboard. Assuming the conditions for hydrostatic equilibrium is satisfied, total freeboard was converted to ice thickness. The ice thickness values agreed well with the published ice charts by the Finnish Meteorological Institute (FMI). The main uncertainty in the extracted ice thickness was due to the thick snow accumulation and unknown snow properties.
IEEE geoscience and remote sensing letters
|Pages:||1 - 5|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Academy of Finland 6Genesis Flagship under Grant 346208 and in part by 5G VIIMA project funded by Business Finland under Grant 6381/31/2018.
|Academy of Finland Grant Number:||
346208 (Academy of Finland Funding decision)
© The Author(s) 2022. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.