# Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives
## Key Research Findings
### SUHI Variations among Cities and Their Drivers  
SUHI variations among cities had been a research focus since the beginning of the SUHI research when the satellite data were only available at a coarse spatial resolution [55; 57; 33]. However, local-scale SUHI studies soon dominated the SUHI literature and this has continued to the present with the advent of high-resolution satellite data like Landsat and ASTER. As a result, there were very few studies on large-scale SUHI variations before 2010. With advancing quality and quantity of remote sensing data (in particular MODIS data) as well as increased computing power, more researchers started to look at the SUHI phenomenon on a regional scale [114; 120; 139; 177; 178; 179], a national scale like China [121; 122; 126; 168; 169; 115; 16, 53], the United States [3; 52], and India [181; 182], a continental scale such as Europe [111; 5, 68; 111; 183], North America [125], and Asia [127], or a global scale [50; 184; 2, 4, 50]. These studies have greatly enhanced our knowledge on large-scale SUHI variations and their underlying potential drivers. The previous efforts indicated a great deal of spatiotemporal variability of SUHIs, especially during the daytime. SUHI intensity has been widely found to be the largest during the day in the summertime with the maximum urban-rural LST difference >10 Kelvin [127; 122; 123; 16, 52]. In general, the daytime SUHI was larger in humid-hot cities than in their cold-drier counterparts, and larger in the summer than in the winter [112; 112; 113; 16, 52]. In contrast, cooling effects have been found in some arid cities during the summer season [181; 52; 52] and a few mid-high latitudinal cities in the winter season [12; 6, 76]. Comparatively, SUHIs have been observed to be more pervasive at night regardless of the background climate and/or season [121; 6, 76; 181; 6, 76]. However, the mean SUHI intensity was mostly estimated to be lower at night than during the day, especially in the summer [12; 122; 12]. In addition, stronger nighttime SUHIs were often found in cold-drier cities than humid-hotter cities [112; 53; 76]. In addition, seasonal variations of SUHIs were clearly smaller at night than in the day [53], and the nighttime seasonal patterns remain controversial to date. For example,Peng et al. [76] suggested more intensive nighttime SUHI in the summertime than in the wintertime for 285 cities in China. [PERSON] et al. [6; 53] showed opposite trends for 32 major cities in China. SUHI distributions had been attributed to a variety of factors (Figure 5) and some of them are still highly disputed. The climate-vegetation background was found to be the main cause of the spatiotemporal variability of SUHI over large areas [6; 52; 53; 125]. Vegetation, which cooled the non-urban surface by evapotranspiration, was widely documented as a dominant factor in regulating the SUHI patterns during the summer [2; 4; 6; 50; 51; 139; 182; 185]. Overall, it contributed little to SUHI variations in the winter due to low vegetation activity for most cities in the season [4; 6]. However, it remains controversial whether vegetation contributes significantly to the SUHIs during summer nights [4; 6; 109; 186]. Background climatic factors such as precipitation [6; 178; 125; 178], temperature [6; 109; 111; 114; 178], wind speed [178], and solar irradiance [139] can significantly influence SUHIs since they can impact not only vegetation activity but also the energy balance of urban and rural areas [6; 125]. In fact, the climate was usually considered the ultimate factor that shapes the spatiotemporal patterns of SUHIs over large areas [6; 52; 53; 125]. Anthropogenic factors also contribute significantly to SUHI distributions. ISA, warming urban surface by trapping, storing, and emitting more heat, is positively correlated with SUHI in the summer and/or nighttime [2; 6; 177; 180; 183], and was shown to be the primary driver for urban heating effects at mid-latitudes to high-latitudes [50; 52]. For example, [PERSON] et al.