<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>4881</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>620</pageFirst>
    <pageLast>620</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue>8</issue>
    <volume>8</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Remote Sensing Exploration of Nb-Ta-LREE-Enriched Carbonatite (Epembe/Namibia)</title>
    <parentTitle language="eng">Remote Sensing</parentTitle>
    <identifier type="issn">2072-4292</identifier>
    <identifier type="doi">10.3390/rs8080620</identifier>
    <enrichment key="opus.import.data">@articlezimmermann_remote_2016, title = Remote Sensing Exploration of Nb-Ta-LREE-Enriched Carbonatite (Epembe/Namibia), volume = 8, copyright = http://creativecommons.org/licenses/by/3.0/, issn = 2072-4292, url = https://www.mdpi.com/2072-4292/8/8/620, doi = 10.3390/rs8080620, abstract = On the example of the Epembe carbonatite-hosted Nb-Ta-LREE deposit, we demonstrate the use of hyperspectral reflectance data and geomorphic indicators for improving the accuracy of remote sensing exploration data of structurally-controlled critical raw material deposits. The results further show how exploration can benefit from a combination of expert knowledge and remotely-sensed relief, as well as imaging data. In the first stage, multi-source remote sensing data were used in lithological mapping based on Kohonen Self-Organizing Maps (SOM). We exemplify that morphological indices, such as Topographic Position Index (TPI), and spatial coordinates are crucial parameters to improve the accuracy of carbonate classification as much as 10%. The resulting lithological map shows the spatial distribution of the ridge forming carbonatite dyke, the fenitization zone, syenite plugs and mafic intrusions. In a second step, the internal zones of the carbonatite complex were identified using the Multi-Range Spectral Feature Fitting (MRSFF) algorithm and a specific decision tree. This approach allowed detecting potential enrichment zones characterized by an abundance of fluorapatite and pyroxene, as well as dolomite-carbonatite (beforsite). Cross-validation of the mineral map with field observations and radiometric data confirms the accuracy of the proposed method., language = en, number = 8, urldate = 2023-11-30, journal = Remote Sensing, author = Zimmermann, Robert and Brandmeier, Melanie and Andreani, Louis and Mhopjeni, Kombada and Gloaguen, Richard, month = aug, year = 2016, note = Number: 8 Publisher: Multidisciplinary Digital Publishing Institute, keywords = carbonatite, decision tree, geomorphology, HyMap, Namibia, REE, self-organizing maps, spectral feature fitting, SRTM, pages = 620, file = Full Text PDF:CUsershafermannZoterostorageMBMTK82QZimmermann et al. - 2016 - Remote Sensing Exploration of Nb-Ta-LREE-Enriched .pdf:application/pdf,</enrichment>
    <enrichment key="opus.import.dataHash">md5:8e36f8be3aa7c64889fc785e6c06541d</enrichment>
    <enrichment key="opus.import.date">2023-11-30T13:50:01+00:00</enrichment>
    <enrichment key="opus.import.file">/tmp/phpJELqDK</enrichment>
    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">65689309d2b193.47222270</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Robert Zimmermann</author>
    <author>Melanie Brandmeier</author>
    <author>Louis Andreani</author>
    <author>Kombada Mhopjeni</author>
    <author>Richard Gloaguen</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>carbonatite</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>decision tree</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>geomorphology</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>HyMap</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Namibia</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>REE</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>self-organizing maps</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>spectral feature fitting</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SRTM</value>
    </subject>
  </doc>
</export-example>
