Analysis of rooftop surface temperatures in an urban residential environment

The urban heat island (UHI) effect is an important worldwide problem caused by rapid urbanization. The mitigation efforts include using high albedo rooftops, green rooftops, and planting vegetation around the buildings. Rooftop properties such as albedo, color, material, slope, area, aspect, and height are factors that potentially contribute. Nearby landscaping is also important factors to be considered. To analyze rooftop parameters and outdoor landscaping, high spatial resolution satellite imagery, LIDAR (light detection and ranging) data and high resolution thermal imagery are necessary. Using data from the City of Tempe AZ, we digitized residential rooftop footprints and derived rooftop configuration parameters from airborne LIDAR data and QuickBird imagery (2.4 m resolution imagery). High resolution daytime and nighttime surface temperature data (7m) were derived from the MODIS/ASTER airborne simulator (MASTER). Ordinary least squares (OLS) regression was utilized to explore the relationships between residential building rooftops and rooftop surface temperature in Tempe. The results showed that daytime rooftop surface temperature was related to rooftop spectral attributes, slope, aspect, and surrounding trees. Night time temperature was only affected by rooftop spectral attributes and slope.