# Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives
## Key Research Findings
### SUHI Variations at a Local Scale and Their Drivers  
Increasing studies on local-scale SUHI variations constitute the major body of SUHI literature (Figure 3c). More than 300 papers have been published and nearly 60% of these studies have appeared within the last five years. These efforts in general can be grouped into three main categories based on their studied drivers: land cover/land use and changes, urban site characteristics (USCs), and landscape composition and configuration. The USC term originally stems from [PERSON] et al. [94] and is used here as a hypernym to summarize all kinds of quantitative descriptors helping to explain SUHI variations within cities. Land cover/land use and their changes are inarguably some of the most important factors influencing SUHIs. Built-up areas, vegetation, and water are central to explain the spatio-temporal characteristics of urban LST [30]. The presence of buildings and impervious surfaces usually result in an increase of LST [66; 95; 105; 106; 133; 134; 135], while the opposite is true for urban vegetation [66; 81; 94; 95; 102; 105; 108; 116; 136; 137; 138; 139; 140] and water bodies [103; 106; 141; 142; 143]. The impact of bare soil areas on SUHI is ambiguous, with a few studies reporting both positive [95] and negative [116] correlations with LST. Overall, land cover alone can be decisive regarding whether an urban area forms a SUHI or an urban heat sink [30; 144]. However, the sole consideration of land cover is sometimes not sufficient for explaining the LST variations within cities. Several studies indicate that land use is a better suited parameter since it takes into account human activities [145; 146]. For example, industrial areas are often found to be among the hottest places in urban environments due to the associated high heat emissions [62; 102]. Furthermore, the degree of correlation between the land cover and LST depends on the type of urban land use [94; 99; 101; 147; 148]. However, no matter which of the two variables is actually more important, research undoubtedly shows that land cover and land use can lead to not only urban-rural temperature gradients but also intra-urban temperature differences [30]. The intra-urban differences typically manifest themselves in the form of spatial clusters of hot and cold spots [149; 150], which, at times, can be even greater than the urban-rural temperature gradient [105]. Dynamics of land cover and land use over time are of equal importance in shaping the SUHI patterns. For example, urban growth can increase the SUHI extent and intensity [95; 149; 151; 152] by increasing proportions of built-up land and decreasing proportions of vegetated areas, especially in the earlier stages of urbanization [90] and/or regions undergoing rapid land cover and land use change [116]. Impacts of the three major urban land covers (built-up land, vegetated areas, and water bodies) have also been extensively studied by a wide variety of quantitative descriptors termed as USCs. The area covered by built-up land represents some of the main causes of SUHI formation [30]. Accordingly, a considerable amount of 2D indicators has been used to reflect the built-up land properties such as the ISA, the index-based built-up index (IBI), the normalized difference built-up index (NDBI), and the urbanization index (UI) [66; 94; 95; 99; 106; 133; 135; 138; 141; 143; 148]. The coverage, density, and materials of specific built-up land cover elements (e.g., buildings, roads, and parking lots) have also been related to SUHIs [94; 153; 154; 155; 82; 94; 156; 157]. Furthermore, 3D indicators such as the building heights and volumes, the frontal area index (FAI), the floor area ratio (FAR), and the sky view factor (SVF) are regularly used to represent the effects of urban morphology on SUHI [94; 102; 153; 156; 158; 159]. When comparing the linkage between 2D/3D USCs and SUHIs, it is worth noting that correlation statistics might be biased in favor of 2D USCs.