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Land surface characterization using BeiDou signal-to-noise ratio observations

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A Correction to this article was published on 14 October 2019

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Abstract

China’s BeiDou Navigation Satellite System (BDS) is providing new opportunities for GNSS reflectometry-related applications. We give the first and comprehensive description of the feasibility and potential of using BDS signal-to-noise ratio (SNR) data to characterize land surface in terms of the volumetric soil moisture (VSM), vegetation water content (VWC) and snow depth. BDS SNR-derived interferogram metrics (phase φ, amplitude A, and effective reflector height h) are investigated, and their correlations to the corresponding land surface parameters are established. Data collected from a geodetic-quality BDS/GPS compatible receiver for approximately 300-day period were used to validate the VSM retrieval. Results show that both BDS B1 and B2 frequencies can perform well to reflect the fluctuations of the VSM. Specifically, the B2-derived phase φ exhibits a slightly higher correlation with in situ VSM than that of B1 (R = 0.83 vs. R = 0.80), and the B2-derived amplitude A also exhibits a higher correlation with MODIS NDVI than that of B1 (R = 0.49 vs. R = 0.53); whilst for snow, the B1 and B2 results indicate qualitative agreement with concurrent in situ snow depth measurements. Furthermore, similar estimation performance can be obtained by comparing the results of BDS B1 and B2 against GPS L2C and L5. Therefore, BDS could be a new and powerful data source with comparable potential as GPS for effectively characterizing high-temporal resolution land surface.

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Change history

  • 14 October 2019

    In the original article publication, the affiliation of co-author Yang Hong was accidentally omitted from the manuscript. The missing affiliation is given.

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Acknowledgements

This study was jointly supported by the National Natural Science Foundation of China (NSFC) projects (Grant Nos. 41501360, 91437214, and 41401377), the Open Research Fund of Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Chinese Academy of Sciences (Grant No. TEL201503), and the Open Research Fund of State Key Laboratory of Hydroscience and Engineering, Tsinghua University (sklhse-2017-A-02).

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Authors and Affiliations

  1. Institute of Remote Sensing and GIS, Peking University, Beijing, China

    Ting Yang, Wei Wan, Xiuwan Chen & Yang Hong

  2. Conrad Blucher Institute for Surveying and Science, Texas A&M University-Corpus Christi, Corpus Christi, TX, USA

    Tianxing Chu

  3. State Key Laboratory of Plateau Ecology and Agricultural, Qinghai University, Xining, China

    Zhen Qiao, Jiahua Wei & Guangqian Wang

  4. Center of Meteorological Observation, China Meteorological Administration, Beijing, China

    Hong Liang

  5. Department of Hydraulic Engineering, Tsinghua University, Beijing, China

    Jiahua Wei, Guangqian Wang & Yang Hong

Authors
  1. Ting Yang
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  2. Wei Wan
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  3. Xiuwan Chen
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  4. Tianxing Chu
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  5. Zhen Qiao
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  6. Hong Liang
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  7. Jiahua Wei
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  8. Guangqian Wang
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  9. Yang Hong
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Correspondence to Wei Wan.

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Yang, T., Wan, W., Chen, X. et al. Land surface characterization using BeiDou signal-to-noise ratio observations. GPS Solut 23, 32 (2019). https://doi.org/10.1007/s10291-019-0824-4

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