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  <front>
    <journal-meta>
      <journal-title-group><journal-title>SET Proceedings</journal-title></journal-title-group>
      <issn pub-type="epub">2978-4387</issn>
      <publisher><publisher-name>Caravel Press</publisher-name></publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.65582/set.2017.133</article-id>
      <article-id pub-id-type="publisher-id">2017.133</article-id>
      <title-group><article-title>Identifying suitable locations for onshore wind turbines using a GIS-MCDA approach</article-title></title-group>
    <contrib-group>
      <contrib contrib-type="author" corresp="yes">
        <name><surname>Harper</surname><given-names>Michael</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>m.harper@soton.ac.uk</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Anderson</surname><given-names>Ben</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>James</surname><given-names>Patrick</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Bahaj</surname><given-names>AbuBakr</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
      </contrib>
      <aff id="aff1">Sustainable Energy Research Group, Faculty of Engineering and the Environment, University of Hampshire/Solent, Hampshire/Solent, UK</aff>
    </contrib-group>
      <pub-date publication-format="electronic" date-type="pub"><day>13</day><month>07</month><year>2017</year></pub-date>
      <volume>16</volume>
      <isbn publication-format="electronic">9791220022033</isbn>
      <fpage>1</fpage>
      <lpage>10</lpage>
      <self-uri xlink:href="https://caravelpress.com/proceedings/set/papers/2017.133"/>
      <history>
        <date date-type="received"><string-date>13 July 2017</string-date></date>
      </history>
      <permissions>
        <copyright-statement>© 2017 Copyright WSSET</copyright-statement>
        <copyright-year>2017</copyright-year>
      </permissions>
      <abstract><p>Onshore wind generation is one of the most cost-effective methods of renewable electricity generation. However, there is often difficulty in identifying suitable sites for development. To assist such systems, geospatial information systems are extensively used in identifying suitable sites for wind turbines: these models predominantly focus on the technical and legislative constraints, and have a limited understanding of the social issues surrounding development. As a result, there are concerns with the validity of these models in accurately determining suitable sites and fail to acknowledge the strong local opposition which some projects can experience. Building upon previous statistical analysis, this paper presents a geospatial multi-criteria decision analysis that integrates the technological, legislative, and social constraints to determine suitable sites for onshore wind turbine development. To the authors’ knowledge, this is the first study that aims to understand whether suitable sites are likely to receive planning permission and to integrate this into the decision-making process. The findings highlight the importance of considering the planning constraints within modelling and demonstrates the limitations in identifying suitable sites for development.</p></abstract>
      <kwd-group kwd-group-type="author">
        <kwd>Onshore Wind</kwd>
        <kwd>GIS</kwd>
        <kwd>MCDA</kwd>
      </kwd-group>
      <conference>
        <conf-date>17 to 20 July 2017</conf-date>
        <conf-name>16th International Conference on Sustainable Energy Technologies</conf-name>
        <conf-acronym>SET2017</conf-acronym>
        <conf-num>16</conf-num>
        <conf-loc>Bologna, Italy</conf-loc>
      </conference>
    </article-meta>
  </front>
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