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<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-B3-2020-553-2020</article-id>
<title-group>
<article-title>A PHYSICAL INVERSION METHOD OF CANOPY FPAR FROM AIRBORNE LIDAR DATA AND GROUND MEASUREMENTS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yang</surname>
<given-names>X.</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>Xi</surname>
<given-names>X.</given-names>
<ext-link>https://orcid.org/0000-0001-6979-170X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>C.</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>Shi</surname>
<given-names>J.</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>Huang</surname>
<given-names>Y.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>University of Chinese Academy of Sciences, Beijing 100049, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>School of Tourism and Geographical Science, Yunnan Normal University, Kunming 650500 , China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Guangxi Zhuang Autonomous Region Institute of Natural Resources Remote Sensing Sensing, Nanning 530029 530029, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>21</day>
<month>08</month>
<year>2020</year>
</pub-date>
<volume>XLIII-B3-2020</volume>
<fpage>553</fpage>
<lpage>557</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2020 X. Yang 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/XLIII-B3-2020/553/2020/isprs-archives-XLIII-B3-2020-553-2020.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIII-B3-2020/553/2020/isprs-archives-XLIII-B3-2020-553-2020.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIII-B3-2020/553/2020/isprs-archives-XLIII-B3-2020-553-2020.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIII-B3-2020/553/2020/isprs-archives-XLIII-B3-2020-553-2020.pdf</self-uri>
<abstract>
<p>Fraction of absorbed Photosynthetically Active Radiation (FPAR) is one of the pivotal parameters in terrestrial ecosystem modelling and crop growth monitoring. Airborne LiDAR is an advanced active remote sensing technology which can acquire fine three-dimensional canopy structural information quickly and accurately. Although some previous studies have shown that LiDAR-derived metrics had strong relationships with canopy FPARs, these estimation models without physical meaning are hard to be extended to various vegetation canopies and different growth periods. This study proposed a physical FPAR inversion method based on airborne LiDAR data and field measurements. The method considered direct and diffuse radiations separately based on the SAIL model and energy budget balance principle. The canopy FPAR was inversed from the structural information provided by LiDAR point cloud data and the spectral information provided by ground measurements. The estimated FPAR was validated with the field-measured FPAR over 39 maize plots. Results showed that the proposed method had a good performance in estimating the total FPAR of maize canopy (&lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;&amp;thinsp;=&amp;thinsp;0.76, RMSE&amp;thinsp;=&amp;thinsp;0.062, &lt;i&gt;n&lt;/i&gt;&amp;thinsp;=&amp;thinsp;39). This study provides the potential to estimate the total, direct, and diffuse FPARs of vegetation canopy from airborne LiDAR data.</p>
</abstract>
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