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Evaluating the Operational Potential of LRV Signatures Derived from UAV Imagery in Performance Evaluation of Cool Roofs

Author

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  • Seong-Il Park

    (Department of Climate Change, Kyungpook National University, Daegu 41566, Korea)

  • Taek-Hyoung Ryu

    (Department of Geography, Kyungpook National University, Daegu 41566, Korea)

  • Ick-Chang Choi

    (Institute of Advanced Convergence Technology, Kyungpook National University, Daegu 41061, Korea)

  • Jung-Sup Um

    (Department of Geography, Kyungpook National University, Daegu 41566, Korea)

Abstract

It is quite difficult to find studies regarding area-wide data from UAV (Unmanned Aerial Vehicle) remote sensing in evaluating the energy saving performance of a cool roof. Acknowledging these constraints, we investigated whether LRV (Light Reflectance Value) signatures derived from UAV imagery could be used effectively as an indicator of area-wide heating and cooling load that distinctively appears according to rooftop color. The case study provides some quantitative tangible evidence for two distinct colors: A whitish color roof appears near the edge of the highest LRV (91.36) and with a low temperature (rooftop surface temperature: (38.03 °C), while a blackish color roof shows the lowest LRV (18.14) with a very high temperature (65.03 °C) where solar radiation is extensively absorbed. A strong negative association (Pearson correlation coefficient, r = −0.76) was observed between the LRV and surface temperature, implying that a higher LRV (e.g., a white color) plays a decisive role in lowering the surface temperature. This research can be used as a valuable reference introducing LRV in evaluating the thermal performance of rooftop color as rooftops satisfying the requirement of a cool roof (reflecting 75% or more of incoming solar energy) are identified based on area-wide objective evidence from UAV imagery.

Suggested Citation

  • Seong-Il Park & Taek-Hyoung Ryu & Ick-Chang Choi & Jung-Sup Um, 2019. "Evaluating the Operational Potential of LRV Signatures Derived from UAV Imagery in Performance Evaluation of Cool Roofs," Energies, MDPI, vol. 12(14), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2787-:d:250021
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    References listed on IDEAS

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    Cited by:

    1. Kirim Lee & Jihoon Seong & Youkyung Han & Won Hee Lee, 2020. "Evaluation of Applicability of Various Color Space Techniques of UAV Images for Evaluating Cool Roof Performance," Energies, MDPI, vol. 13(16), pages 1-12, August.

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