A new approach to the estimation of the nighttime land surface temperature

In the context of global warming, the urban heat island (UHI) has become more and more serious, aggravating the severity of heat waves impacts, which not only cause pollution and increase energy consumption, but also pose a threat to human life and health. Many studies have shown that urban surfaces are warmer by absorbing more solar radiation than non-urban areas during the day and stay warm at night, which makes a larger UHI effect at night. Considering that urban surface characteristics are one of the main factors leading to UHI effect, it is necessary to study urban land surface temperature. Due to the lack of high-resolution nighttime remote sensing data, most of the studies on nighttime land surface temperature uses weather station data or Modis remote sensing images with a resolution of 1km, which cannot present more detailed urban climate behaviors, and there are certain limitations to urban climate research. Therefore, this paper aims to find a new approach to solve the problems existing in the traditional method and develop a new model to obtain a more accurate and higher resolution nighttime LST. In this paper, Landsat 8 daytime images (with spatial resolution of 30 square meters per pixel) will be used to build a night cooling model by means of multiple regression analysis in order to obtain the nighttime LST, and compare the day and night models to study the impact of UHI effects. The case study is Madrid Municipality (604.45 km2, 3.3 million inhabitants).