Preliminary sea ice detection results from GNSS-R payload on board Chinese Jilin-1 Wideband-01B (J1-01B) satellite

As a novel remote-sensing method, the Global Navigation Satellite System-Reflectometry (GNSS-R) can utilize a large number of reflected GNSS opportunity signals for sea ice observation. The first analysis of spaceborne GNSS-R data from the Chinese Jilin-1 Wideband-01B (J1-01B) Satellite Mission is c...

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Bibliographic Details
Published in:IEEE Geoscience and Remote Sensing Letters
Main Authors: Zhang, Zhaoyi, Guo, Bofeng, Nan, Yang, Du, Hao, Li, Fenghui, Zhai, Jingsheng
Format: Article in Journal/Newspaper
Language:English
Published: Institute of Electrical and Electronics Engineers 2024
Subjects:
Online Access:http://hdl.handle.net/10261/357698
https://doi.org/10.1109/LGRS.2024.3368082
Description
Summary:As a novel remote-sensing method, the Global Navigation Satellite System-Reflectometry (GNSS-R) can utilize a large number of reflected GNSS opportunity signals for sea ice observation. The first analysis of spaceborne GNSS-R data from the Chinese Jilin-1 Wideband-01B (J1-01B) Satellite Mission is carried out. 72 days of delay-Doppler maps (DDMs) obtained from global positioning system-reflectometry (GPS-R) and BeiDou navigation satellite system-reflectometry (BDS-R) is utilized for sea ice detection. In addition to the traditional pixel number (pn) and power summation (PS) observables, a novel DDM observable, named “trailing edge diffusion (TED),” was proposed to quantify the significant differences observed in DDMs obtained from seawater and sea ice. By establishing corresponding DDM observable thresholds, sea ice can be distinguished from seawater. Compared to the ocean and sea ice satellite application facility (OSI SAF) global sea ice concentration (SIC) product, the agreement of GPS-R and BDS-R is more than 96% and 98%, respectively, in the Antarctic. Results show high accuracy in the sea ice detection field, which demonstrates the feasibility of J1-01B DDMs and the superior performance of GPS-R and BDS-R in detecting sea ice. This study provides a novel data source for the cost-effective, data-rich, and stable GNSS-R method in sea ice detection. Peer reviewed