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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/isprsarchives-XL-8-443-2014</article-id>
<title-group>
<article-title>Hyperspectral analysis of clay minerals</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Janaki Rama Suresh</surname>
<given-names>G.</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>Sreenivas</surname>
<given-names>K.</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>Sivasamy</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Soil &amp; Land Resources Assessment Division, National Remote Sensing Centre, Hyderabad, India</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Dept. of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore, India</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>11</month>
<year>2014</year>
</pub-date>
<volume>XL-8</volume>
<fpage>443</fpage>
<lpage>446</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2014 G. Janaki Rama Suresh et al.</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-8/443/2014/isprs-archives-XL-8-443-2014.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-8/443/2014/isprs-archives-XL-8-443-2014.pdf</self-uri>
<abstract>
<p>A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the
dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique
information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical
properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on
stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature
parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through
DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in
the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to
classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that
kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.</p>
</abstract>
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