Abstract
The surface urban heat island (SUHI) of urban agglomeration has always been an important topic in the studies of urban heat island, especially with the development of satellite-based land surface temperature (LST) products. However, most studies are limited to the perspective of a single city, ignoring the impact of urban agglomeration and the changes of LST at day and night on the reference LST (RLST) (e.g., rural areas). Consequently, this article proposed a novel method about SUHI intensity estimation for the multicenters (mcSUHII) of urban agglomeration in Guangdong-Hong Kong-Macao Greater Bay Area (GHMBay) using nighttime light (NTL) data (i.e., DMSP/OLS) obtained in October, 2010. The mcSUHII method considered the RLST of SUHII estimation based on multicenter structure, and was more flexible to adapt the impact of human activity intensity. The study showed that compared with other RLSTs, such as suburban and forest, mcSUHII mitigates the underestimation bias caused by ignoring the multicenter structure. Importantly, the change in SUHII for urban agglomerations is greater than for a single city. Moreover, it was illustrated that the variation of SUHII presented an obvious inverted U-shape along the gradient from the inland to the coastal cities. The highest SUHIIs in the delta cities at day and night are ~7.27 ± 1.71 °C and ~4.46 ± 1.42 °C, respectively. Additionally, NTL served as the dominator together with other factors that were capable of explaining more than 90% of the spatial variation in SUHII in GHMBay. Therefore, considering multicenters more in estimation of SUHII of urban agglomeration for the sustainable development.
Highlights
T HE urban heat island (UHI) effect is a significant microclimate effect, which refers to a phenomenon where the temperature of a city is higher than that of the surrounding area [1], [2]
The first is that surface UHI (SUHI) is replaced by land surface temperature (LST) [9], which mainly emphasizes the spatiotemporal variation of SUHI but ignores its intensity [8]
We incorporated the capacity of nighttime light (NTL) for human footprint into the multicenters pattern analysis of urban agglomeration
Summary
T HE urban heat island (UHI) effect is a significant microclimate effect, which refers to a phenomenon where the temperature of a city is higher than that of the surrounding area [1], [2]. Statistical models are very efficient in describing the spatial temperature on a continuous surface, such as Gaussian surface and kernel convolution model [10], [11], while they are affected by climate and clouds [8]. These problems of the aforementioned methods are avoided in the third method, which refers to LST difference between the urban and surrounding reference areas and had been widely used in most studies [3], [12], [13]
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