The characteristics of urban land surfaces contribute to the urban heat island, and, in turn, can exacerbate the severity of heat wave impacts. However, the mechanisms and complex interactions in urban areas underlying land surface temperature are still being understood. Understanding these mechanisms is necessary to design strategies that mitigate land temperatures in our cities. Using the recently available night-time moderate-resolution thermal satellite imagery and employing advanced nonlinear statistical models, we seek to answer the question What is the influence and relative importance of urban characteristics on land surface temperature, during both the day and night? To answer this question, we analyze urban land surface temperature in four cities across the United States. We devise techniques for training and validating nonlinear statistical models on geostatistical data and use these models to assess the interdependent effects of urban characteristics on urban surface temperature. Our results suggest that vegetation and impervious surfaces are the most important urban characteristics associated with land surface temperature. While this may be expected, this is the first study to quantify this relationship for Landsat-resolution nighttime temperature estimates. Our results also demonstrate the potential for using nonlinear statistical analysis to investigate land surface temperature and its relationships with urban characteristics. Improved understanding of these relationships influencing both night and day land surface temperature will assist planners undertaking climate change adaptation and heat wave mitigation.
Logan, TM; Zaitchik, B; Guikema, S; Nisbet, A
Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature
Remote Sensing Of Environment