Abstract
Snowfall is an important freshwater resource; manual monitoring and laser detection can monitor snow to a certain extent, but there is a lot of uncertainty in time and space. Traditional ground-based geodetic Global Navigation Satellite System (GNSS) receivers are more widely distributed, this article uses the advantages of BDS all-weather, real-time, high time resolution and high automation to monitor snow depth, taking the snow monitoring station in Altai City, Xinjiang as the research object, Firstly, explain the basic principles of BeiDou System-Multipath reflectometry (BDS-MR) snow depth detection, secondly, based on the data of the Altai station from January to March 2017, about 90 days, From the aspects of Beidou satellite type, the feasibility and detection accuracy of BDS-MR are studied by using the signal-to-noise ratio (SNR) of BDS, and compared with the measured snow depth data. The results show that: When the SNR of the IGSO and MEO satellites of BDS is used to invert the snow depth deviation to 0.021 m. It is proved that BDS-MR can be used for snow depth detection, which can better utilize the advantages of microwave remote sensing and promote the application of Beidou navigation system.
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Acknowledgments
We gratefully acknowledge the Northwest Institute of Ecology and Environmental Resources, Chinese Academy of Sciences and the Altay Meteorological Bureau for providing experimental data. This work was supported by China Desert Meteorological Science Research Foundation (Sqj2017002), National Science Foundation of China (41731066, 41674001, 41104019) and the Special Fund for Basic Scientific Research of Central Colleges (310826172202).
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Zhang, S., Zhang, C., Wang, L., Che, T., Li, H., Chen, X. (2019). BDS-MR for Snow Depth Monitoring in Altai. In: Sun, J., Yang, C., Yang, Y. (eds) China Satellite Navigation Conference (CSNC) 2019 Proceedings. CSNC 2019. Lecture Notes in Electrical Engineering, vol 562. Springer, Singapore. https://doi.org/10.1007/978-981-13-7751-8_3
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DOI: https://doi.org/10.1007/978-981-13-7751-8_3
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