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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-3-W10-249-2020</article-id>
<title-group>
<article-title>PRELIMINARY STUDY ON WAVELET DENOISING METHOD FOR INVERSION OF SNOW DEPTH IN GNSS-MR</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>F. F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liu</surname>
<given-names>L. L.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Huang</surname>
<given-names>L. K.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhou</surname>
<given-names>W.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Naval University of Engineering, Wuhan 430000, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>07</day>
<month>02</month>
<year>2020</year>
</pub-date>
<volume>XLII-3/W10</volume>
<fpage>249</fpage>
<lpage>254</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2020 F. F. Li et al.</copyright-statement>
<copyright-year>2020</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-3-W10/249/2020/isprs-archives-XLII-3-W10-249-2020.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-3-W10/249/2020/isprs-archives-XLII-3-W10-249-2020.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-3-W10/249/2020/isprs-archives-XLII-3-W10-249-2020.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-3-W10/249/2020/isprs-archives-XLII-3-W10-249-2020.pdf</self-uri>
<abstract>
<p>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 &quot;pure&quot; 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.</p>
</abstract>
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