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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-XLIII-B3-2021-645-2021</article-id>
<title-group>
<article-title>AN INVERSION APPROACH FOR BIOCHEMICAL PARAMETERS OF VEGETATION BASED ON THE PROSPECT-5 MODEL</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xing</surname>
<given-names>X.</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>Zheng</surname>
<given-names>X.</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>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>National Geomatics Center of China, Beijing, 100830, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>29</day>
<month>06</month>
<year>2021</year>
</pub-date>
<volume>XLIII-B3-2021</volume>
<fpage>645</fpage>
<lpage>650</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2021 X. Xing et al.</copyright-statement>
<copyright-year>2021</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/XLIII-B3-2021/645/2021/isprs-archives-XLIII-B3-2021-645-2021.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIII-B3-2021/645/2021/isprs-archives-XLIII-B3-2021-645-2021.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIII-B3-2021/645/2021/isprs-archives-XLIII-B3-2021-645-2021.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIII-B3-2021/645/2021/isprs-archives-XLIII-B3-2021-645-2021.pdf</self-uri>
<abstract>
<p>Accurate inversion of vegetation biochemicals using the PROSPECT model mostly depends on a proper inversion approach, including a suitable optimizing algorithm, appropriate dependent variables, and different properties from spectra of reflectance (R) and transmittance (T). In this paper, we propose a special inversion method using PROSPECT-5 and then explore its effectiveness in inverting chlorophyll, carotenoids, equivalent water thickness, and dry matter per area data from the ANGERS database. The inversion strategy includes (i) an optimal algorithm with constrained bounds (fminsearchbnd) to replace the common function fminsearch, (ii) and four parameters are considered together and separately as dependent variables of models, (iii) Using properties from the spectra of R, T and combined R&amp;T to invert the above four biochemical parameters. The results show that fminsearchbnd can improve the model&apos;s R&lt;sup&gt;2&lt;/sup&gt; based on a field-measured database. Moreover, using the entire set of parameters together as the model inputs is more effective than using single parameters separately. T spectra are favoured for all parameter inversions in the model database while being inapplicable in the ANGERS database. These findings provide an appropriate inversion strategy for the PROSPECT-5 model in vegetation biochemical parameters analysis and suggest further research to develop an accurate inversion process for vegetation based on various physical models.</p>
</abstract>
<counts><page-count count="6"/></counts>
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