Identification and analysis of urban surface temperature patterns in Greater Athens, Greece, using MODIS imagery

Iphigenia Keramitsoglou, Chris T. Kiranoudis, Giulio Ceriola, Qihao Weng, Umamaheshwaran Rajasekar
2011 Remote Sensing of Environment  
Thermal infrared images are being acquired by satellites for more than two decades enabling studies of the human-induced Urban Heat Island (UHI) phenomenon. As a result, the requirement of the scientific community for fast and efficient methods for extracting and analyzing the thermal patterns from a vast volume of acquired data has emerged. The present paper proposes an innovative object-based image analysis procedure to extract thermal patterns for the quantitative analysis of
more » ... d Land Surface Temperature (LST) maps. The spatial and thermal attributes associated with these objects are then calculated and used for the analyses of the intensity, the position and the spatial extent of UHIs. A case study was conducted in the Greater Athens Area, Greece. More than 3000 LST images of the area acquired by MODIS sensor over a decade were analyzed. Three daytime hot-spots were identified and studied (Megara, Elefsina-Aspropyrgos and Mesogeia). They were all found to exhibit similar behavior, gradually increasing their maximum temperature during the summer season and reaching their maxima in mid-July. The hot-spots' thermal intensities compared to a suburban area were of 9-10°C and were found to be highly correlated to their areal extent. During the night-time, Athens center developed a typical UHI spatially coinciding with the dense urban fabric. The nighttime maximum LST peaked (on average) at the end of July, two weeks later than the daytime surface patterns. The mean spatial extent of UHI in Athens was 55.2 km 2 , whilst its mean intensity was 5.6°C. The proposed automatic extraction process can be customized for other cities and potentially used for comparison of LST patterns and UHI behavior between different cities.
doi:10.1016/j.rse.2011.06.014 fatcat:tghqehwo5jbknmjy64mogdw22m