Abstract
As a part of global fresh water resources, the change of snow storage has an important impact on the earth’s ecological environment, climate change and human development. Recently years, with the continuous development of Global Navigation Satellite System, GNSS Multipath Reflectometry technology has become one of the emerging means of snow depth measurement because of its all-weather, low cost, high spatial-temporal resolution and other advantages. Based on the study of the basic principle of snow depth measurement by GNSS-MR technology, this paper uses the observation data of p351 station in the PBO network of the United States to retrieve the local snow depth. And then the retrieved snow depth is compared with the measured snow depth of 490 station in the SNOTEL network of the United States. The results show that the correlation coefficient between the two is about 0.98, and the Root Mean Square Error is about 0.1 m, which has a good consistency. On this basis, this article analyzes GNSS-MR snow depth measurement error from three aspects: azimuth, elevation angle and snow depth, and finds that there is a certain quantitative relationship between the negative error generated by GNSS-MR snow depth measurement and the snow depth. Aiming at different error characteristics and error sources, the weakening methods are proposed and verified in practice, which provides a reference for the error correction of GNSS-MR technology in snow depth measurement and other environmental monitoring.
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Acknowledgements
The authors would like to thank the PBO H2O research team for providing experimental data, and the US Department of Agriculture (USDA) Natural Resources Conservation Service Organization (NRCS) for providing measured snow depth data.
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Li, Z., Chen, P., Zheng, N., Liu, H., Liu, L. (2020). Application Research and Error Analysis of GNSS-MR Technology in Snow Depth Measurement. In: Sun, J., Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC) 2020 Proceedings: Volume I. CSNC 2020. Lecture Notes in Electrical Engineering, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-15-3707-3_13
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DOI: https://doi.org/10.1007/978-981-15-3707-3_13
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