{"id":1794,"date":"2019-11-04T17:30:47","date_gmt":"2019-11-04T23:30:47","guid":{"rendered":"https:\/\/wpsites.ucalgary.ca\/geovation\/?page_id=1794"},"modified":"2019-11-22T12:14:55","modified_gmt":"2019-11-22T18:14:55","slug":"research","status":"publish","type":"page","link":"https:\/\/wpsites.ucalgary.ca\/geovation\/research\/","title":{"rendered":"Research"},"content":{"rendered":"\n

Dr Hay\u2019s long-term research program is titled \u201cThe Remote Sensing of Urban Energy Efficiency.\u201d<\/em> It involves the use of high-resolution (25 cm-1m) Thermal Infrared (TIR) imagery, geographic object-based image analysis (GEOBIA), machine learning, GIS and geo-spatial analysis to accurately define urban energy efficiency from space.<\/p>\n\n\n\n

Problem<\/strong>: The world wastes more energy than it uses \u2013 every year, with billions of gigajoules of wasted heat energy escaping from millions of buildings in thousands of cities worldwide [1]. Although energy-efficiency (EE) programs exist worldwide, most only measure energy consumption \u2013 not waste energy [2]. This is because waste-energy is invisible to the human eye, and challenging to quantify \u2013 and it\u2019s difficult to measure, monitor, or manage something that we can\u2019t see. Yet, waste-energy is responsible for an estimated 50% of urban energy demand, but is missing<\/em> from urban energy efficiency equations. <\/p>\n\n\n\n

Solution<\/strong>: In order to solve these challenges, Dr Hay\u2019s long-term goal is to evaluate whether high-resolution airborne thermal infrared (TIR) imagery acquired by the Canadian made TABI-1800 (Thermal Airborne Broadband Imager) can be used to quantify, map and monitor urban energy efficiency over time, at the resolution of individual houses, and the scale of a large Canadian city with over 1 million residents. <\/p>\n\n\n\n

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Proposed Research Projects<\/h2>\n\n\n\n

This is an example of projects either underway, or potentially available for students to work on that involve high-resolution (25 cm-1m) TIR imagery, geographic object-based image analysis (GEOBIA), machine learning, GIS and geo-spatial analysis.<\/p>\n<\/div><\/div><\/div>\n\n\n\n

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TIR Derived Urban Energy Efficiency<\/h2>

Potential PhD Project<\/em><\/p>

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    <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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    The Role of Anisotropy on TIR Waste Heat<\/h2>

    Potential PhD Project<\/em><\/p>

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      <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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      Auto-Roof Extraction from TIR Imagery<\/h2>

      Potential MSc Project<\/em><\/p>

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        <\/ul><\/div><\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n
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        TIR Hot-Spot Stability over Time and Space<\/h2>

        Potential MSc Project<\/em><\/p>

        <\/p><\/div>

          <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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          Machine Learning to Generate 3D Results from 2D TIR Imagery<\/h2>

          Potential MSc Project<\/em><\/p>

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            <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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            Diagnostic Machine Learning of TIR Heat-Loss Patterns<\/h2>

            Potential MSc Project<\/em><\/p>

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              <\/ul><\/div><\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n
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              Thermal Hyper-spectral Assessment of Roof Materials with the TASI-600<\/h2>

              Potential MSc Project<\/p>

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                <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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                Defining Roof Materials with RGBi Imagery<\/h2>

                Potential MGIS Project<\/p>

                <\/p><\/div>

                  <\/ul><\/div><\/div>\n<\/div><\/div>\n\n\n\n
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                  Your
                  Research Project<\/h2>

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                    References<\/strong>:[<\/em>1<\/em><\/strong>] International Energy Agency. (2017). Energy Efficiency 2017. Retrieved from iea.org\/ publications\/ freepublications\/ publication\/ Energy_Efficiency_2017.pdf [<\/em>2<\/em><\/strong>] Hemachandran B., et al., 2018. Chapter 11. Urban Remote Sensing 2nd edition. (Editor Q. Weng). Taylor and Francis Catalogue ISBN: 978-1-138-05460-8. pp 235 \u2013 270.<\/em><\/p>\n<\/div><\/div>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

                    Dr Hay\u2019s long-term research program is titled \u201cThe Remote Sensing of Urban Energy Efficiency.\u201d It involves the use of high-resolution (25 cm-1m) Thermal Infrared (TIR) imagery, geographic object-based image analysis (GEOBIA), machine learning, GIS and geo-spatial analysis to accurately define urban energy efficiency from space. Problem: The world wastes more energy than …<\/p>\n","protected":false},"author":49,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"footnotes":""},"class_list":["post-1794","page","type-page","status-publish","hentry"],"featured_image_src":null,"featured_image_src_square":null,"_links":{"self":[{"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/pages\/1794","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/users\/49"}],"replies":[{"embeddable":true,"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/comments?post=1794"}],"version-history":[{"count":50,"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/pages\/1794\/revisions"}],"predecessor-version":[{"id":2243,"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/pages\/1794\/revisions\/2243"}],"wp:attachment":[{"href":"https:\/\/wpsites.ucalgary.ca\/geovation\/wp-json\/wp\/v2\/media?parent=1794"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}