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Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward
DOI link for Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward
Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward book
Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward
DOI link for Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward
Developing Multiscale HEAT Scores from H-Res Airborne Thermal Infrared Imagery to Support Urban Energy Efficiency: Challenges Moving Forward book
ABSTRACT
HEAT Score metrics are developed as a part of the HEAT (Heat Energy Assessment Technologies) research project, initially developed as a public GeoWeb service (www.saveheat.co) designed to help residents improve their home energy efficiency, save on energy costs, and reduce greenhouse gas emissions. HEAT Scores are ranked numbers between 0 and 100 representing “low” and “high” waste heat escaping from houses, which allow for a meaningful comparison with all other mapped houses in a city. Waste heat represents expensive heated air (from space heating) that is leaving a home, instead of staying and keeping the house warm. HEAT Scores provide feedback to homeowners about their home’s waste heat, which may be considered as a measure of energy efficiency. This project is conducted on 9000+ houses in 12 communities in the southwest region of Calgary, Alberta, Canada. HEAT Scores are defined for each house using high-resolution thermal infrared (TIR) imagery obtained from the Thermal Airborne Broadband Imager (TABI-1800). This paper reports on the evolution of different methodologies used to develop TIR-based HEAT Scores along with their strengths and challenges. We then describe the multi-scale interface where HEAT Scores are visualized from a smooth interpolated HEAT map at the City/Pseudo-City level, to colored house polygons comprising Community levels, to individual house HEAT maps. Based on lessons learned, we then discuss requirements for future HEAT Scores.