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

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...

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Autores principales:	Jinsheng Tu, Haohan Wei, Rui Zhang, Lei Yang, Jichao Lv, Xiaoming Li, Shihai Nie, Peng Li, Yanxia Wang, Nan Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	GNSS-IR snow depth signal-to-noise ratio multi-GNSS multi-frequency mean fusion Science Q
Acceso en línea:	https://doaj.org/article/d4ecc771efe9406ea5694cbf7507ee71
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spelling	oai:doaj.org-article:d4ecc771efe9406ea5694cbf7507ee712021-11-11T18:53:38ZGNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data10.3390/rs132143112072-4292https://doaj.org/article/d4ecc771efe9406ea5694cbf7507ee712021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4311https://doaj.org/toc/2072-4292Global 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.Jinsheng TuHaohan WeiRui ZhangLei YangJichao LvXiaoming LiShihai NiePeng LiYanxia WangNan LiMDPI AGarticleGNSS-IRsnow depthsignal-to-noise ratiomulti-GNSSmulti-frequencymean fusionScienceQENRemote Sensing, Vol 13, Iss 4311, p 4311 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	GNSS-IR snow depth signal-to-noise ratio multi-GNSS multi-frequency mean fusion Science Q
spellingShingle	GNSS-IR snow depth signal-to-noise ratio multi-GNSS multi-frequency mean fusion Science Q Jinsheng Tu Haohan Wei Rui Zhang Lei Yang Jichao Lv Xiaoming Li Shihai Nie Peng Li Yanxia Wang Nan Li GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
description	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.
format	article
author	Jinsheng Tu Haohan Wei Rui Zhang Lei Yang Jichao Lv Xiaoming Li Shihai Nie Peng Li Yanxia Wang Nan Li
author_facet	Jinsheng Tu Haohan Wei Rui Zhang Lei Yang Jichao Lv Xiaoming Li Shihai Nie Peng Li Yanxia Wang Nan Li
author_sort	Jinsheng Tu
title	GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
title_short	GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
title_full	GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
title_fullStr	GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
title_full_unstemmed	GNSS-IR Snow Depth Retrieval from Multi-GNSS and Multi-Frequency Data
title_sort	gnss-ir snow depth retrieval from multi-gnss and multi-frequency data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d4ecc771efe9406ea5694cbf7507ee71
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_version_	1718431731260850176

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

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