# Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives
## 7 Future Directions
### New Methods to Quantify SUHI Intensity  
As summarized in Sections 4 and 6.6, SUHI intensity may vary greatly due to differences in the selected urban/reference areas. A classification to distinguish between different urban surface components can help the selection of urban/reference areas to quantify SUHI. [PERSON] and [PERSON] [235] developed a new method of local climate zone (LCZ) to establish an urban landscape classification system. A LCZ refers to an area with uniform urban land use, morphology, material, and metabolism, and demonstrates a characteristic air temperature regime at screen height. This LCZ provides a reference system for the selection of urban/reference areas to calculate SUHI intensity. This method has been validated for the purposes of urban landscape classification in both surface and air UHI studies [249]. At present, LCZ maps have been widely developed in numerous cities ([[http://www.wudapt.org/cities](http://www.wudapt.org/cities)]([http://www.wudapt.org/cities](http://www.wudapt.org/cities))). However, the LCZ method requires a large number of input datasets including some that are not easy to obtain globally. Additionally, the derived SUHI intensity based on the LCZ map still only represents inter-zone temperature differences. There remains a large uncertainty associated with the selection of urban-rural reference zones [235].  
With the development of new urban datasets and spatial analysis methods, more universal methods have been proposed for the calculation of SUHI intensity, with the possibility to ease the challenges to delineate the extent of urban/reference context. For example, a consistent method has  
Figure 7: Global distribution of population density in 2015 [247] and the projected urban population growth in 2050 relative to 2015 in each country [17].  
been proposed to determine urban and reference areas, which defines the surrounding buffer as having the same size as the urban area, by using nighttime light or land cover data [3; 4; 6]. SUHI intensity was also quantified based on the relationship between LST and urban indicators, such as urban fraction and ISA [131; 250]. The relationship between SUHI and urban size can potentially be used to quantify SUHI intensity because SUHI intensity usually increases with the expansion of the urban extent [5]. [PERSON] and [PERSON] [251] investigated the relationship between the spatial trend of LST and the distance to the city center using a ring-based buffer approach. They found that the daytime LST can be modeled using an inverse S-shape function, whereas the night-time LST can be modeled using a quadratic function in Bangkok, Thailand. The fitted LST functions against the distance that provides a potential way to quantify SUHI intensity. Compared with the traditional methods, these new methods consider more urban information (e.g., urban land cover and expansion) and can better represent the overall characteristic of SUHI. The uncertainties due to the selection of urban/reference areas in previous methods can be mitigated to a large extent. Therefore, the SUHI intensity calculated using these new approaches can be more reliable and more comparable to one another.