International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 249–254, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-249-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 249–254, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-249-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  07 Feb 2020

07 Feb 2020

PRELIMINARY STUDY ON WAVELET DENOISING METHOD FOR INVERSION OF SNOW DEPTH IN GNSS-MR

F. F. Li1, L. L. Liu1,2, L. K. Huang1,2, W. Zhou3, and S. Wang1,2 F. F. Li et al.
  • 1College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
  • 2Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China
  • 3Naval University of Engineering, Wuhan 430000, China

Keywords: GNSS - MR technology, Signal-to-noise-ratio, The wavelet analysis, Low altitude Angle, Snow depth inversion, Noise

Abstract. GNSS-MR technology inverts snow depth by using low-altitude SNR data. This information contains rich surface information. Due to the complex surface environment, the signal received by the receiver contains noise,during snow depth inversion, it is not possible to extract relatively "pure" snow information. Therefore, the wavelet denoising method is used to compare with the traditional polynomial. The results show that the snow depth RMSE of the polynomial inversion is 8cm and the error is 7cm. Wavelet denoising inversion The snow depth RMSE is 5cm and the error is 3cm. The experimental verification wavelet denoising method can better eliminate the systematic error and improve the inversion precision.