JOURNAL ARTICLE

GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data

Jinsheng TuHaohan WeiRui ZhangLei YangJichao LvXiaoming LiShihai NiePeng LiYanxia WangNan Li

Year: 2021 Journal:   Remote Sensing Vol: 13 (21)Pages: 4311-4311   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

Global navigation satellite system interferometric reflectometry (GNSS-IR) represents an extra method to detect snow depth for climate research and water cycle managing. However, using a single frequency of GNSS-IR for snow depth retrieval is often found to be challenging when attempting to achieve a high spatial and temporal sensitivity. To evaluate both the capability of the GNSS-IR snow depth retrieved by the multi-GNSS system and multi-frequency from signal-to-noise ratio (SNR) data, the accuracy of snow depth retrieval by different frequency signals from the multi-GNSS system is analyzed, and a joint retrieval is carried out by combining the multi-GNSS system retrieval results. The SNR data of the global positioning system (GPS), global orbit navigation satellite system (GLONASS), Galileo satellite navigation system (Galileo), and BeiDou navigation satellite system (BDS) from the P387 station of the U.S. Plate Boundary Observatory (PBO) are analyzed. A Lomb–Scargle periodogram (LSP) spectrum analysis is used to compare the difference in reflector height between the snow-free and snow surfaces in order to retrieve the snow depth, which is compared with the PBO snow depth. First, the different frequency retrieval results of the multi-GNSS system are analyzed. Then, the retrieval accuracy of the different GNSS systems is analyzed through multi-frequency mean fusion. Finally, the joint retrieval accuracy of the multi-GNSS system is analyzed through mean fusion. The experimental shows that the retrieval results of different frequencies of the multi-GNSS system have a strong correlation with the PBO snow depth, and that the accuracy is better than 10 cm. The multi-frequency mean fusion of different GNSS systems can effectively improve the retrieval accuracy, which is better than 7 cm. The joint retrieval accuracy of the multi-GNSS system is further improved, with a correlation coefficient (R) between the retrieval snow depth and the PBO snow depth of 0.99, and the accuracy is better than 3 cm. Therefore, using multi-GNSS and multi-frequency data to retrieve the snow depth has a good accuracy and feasibility.

Keywords:
GNSS applications Remote sensing GLONASS Satellite system Snow Global Positioning System Computer science Environmental science Geodesy Geology Meteorology Geography Telecommunications

Metrics

13
Cited By
0.72
FWCI (Field Weighted Citation Impact)
32
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cryospheric studies and observations
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Soil Moisture and Remote Sensing
Physical Sciences →  Environmental Science →  Environmental Engineering
Climate change and permafrost
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

Related Documents

JOURNAL ARTICLE

GNSS-IR Snow Depth Retrieval Based on the PSO-NFP Method With Multi-GNSS Constellations

Xintai YuanYuan HuWei LiuJens Wickert

Journal:   IEEE Transactions on Geoscience and Remote Sensing Year: 2024 Vol: 62 Pages: 1-10
JOURNAL ARTICLE

Assessment of GNSS-IR performance using multi-GNSS and multi-frequency SNR data from smartphones

Cemali AltuntaşNursu Tunalıoğlu

Journal:   Journal of Geodesy and Geoinformation Year: 2024 Vol: 12 (1)Pages: 1-19
JOURNAL ARTICLE

Multi-mode Multi-frequency GNSS-IR Combination System for Sea Level Retrieval

Wenyue CHE, Xiaolei WANG, Xiufeng HE, Jin LIU

Journal:   DOAJ (DOAJ: Directory of Open Access Journals) Year: 2023
© 2026 ScienceGate Book Chapters — All rights reserved.