GPS Solutions

, 23:32 | Cite as

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

  • Ting Yang
  • Wei WanEmail author
  • Xiuwan Chen
  • Tianxing Chu
  • Zhen Qiao
  • Hong Liang
  • Jiahua Wei
  • Guangqian Wang
  • Yang Hong
Original Article


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.


BeiDou Navigation Satellite System (BDS) Signal-to-noise ratio (SNR) Volumetric soil moisture (VSM) Vegetation water content (VWC) Snow depth 



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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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Ting Yang
    • 1
  • Wei Wan
    • 1
    Email author
  • Xiuwan Chen
    • 1
  • Tianxing Chu
    • 2
  • Zhen Qiao
    • 3
  • Hong Liang
    • 4
  • Jiahua Wei
    • 3
    • 5
  • Guangqian Wang
    • 3
    • 5
  • Yang Hong
    • 1
    • 5
  1. 1.Institute of Remote Sensing and GISPeking UniversityBeijingChina
  2. 2.Conrad Blucher Institute for Surveying and ScienceTexas A&M University-Corpus ChristiCorpus ChristiUSA
  3. 3.State Key Laboratory of Plateau Ecology and AgriculturalQinghai UniversityXiningChina
  4. 4.Center of Meteorological ObservationChina Meteorological AdministrationBeijingChina
  5. 5.Department of Hydraulic EngineeringTsinghua UniversityBeijingChina

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