Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration

Abstract

Surface urban heat island (SUHI) in the context of urbanization has gained much attention in recent decades; however, the seasonal variations of SUHI and their drivers are still not well documented. In this study, the Beijing-Tianjin-Hebei (BTH) urban agglomeration, one of the most typical areas experiencing drastic urbanization in China, was selected to study the SUHI intensity (SUHII) based on remotely sensed land surface temperature (LST) data. Pure and unchanged urban and rural pixels from 2000 to 2010 were chosen to avoid non-concurrency between land cover data and LST data and to estimate daytime and nighttime thermal effects of urbanization. Different patterns of the seasonal variations were found in daytime and nighttime SUHIIs. Specifically, the daytime SUHII in summer (4 • C) was more evident than in other seasons while a cold island phenomenon was found in winter; the nighttime SUHII was always positive and higher than the daytime one in all the seasons except summer. Moreover, we found the highest daytime SUHII in August, which is the growing peak stage of summer maize, while nighttime SUHII showed a trough in the same month. Seasonal variations of daytime SUHII showed higher significant correlations with the seasonal variations of ∆LAI (leaf area index) (R 2 = 0.81, r = −0.90) compared with ∆albedo (R 2 = 0.61, r = −0.78) and background daytime LST (R 2 = 0.69, r = 0.83); moreover, agricultural practices (double-cropping system) played an important role in the seasonal variations of daytime SUHII. Seasonal variations of the nighttime SUHII did not show significant correlations with either of seasonal variations of ∆LAI, ∆albedo, and background nighttime LST, which implies different mechanisms in nighttime SUHII variation needing future studies.

Diversification of Land Surface Temperature Change under Urban Landscape Renewal: A Case Study in the Main City of Shenzhen, China

“…Although there is no doubt that the form and expansion of urban landscape directly increases the threats of UHIs, the quantitative spatiotemporal variations of land surface temperature (LST) under urban landscape transformation are diverse [3][4][5][6]. This diversification could be caused by differences in seasons, hours, climate zones, and urbanization types [7][8][9][10]. Thus, the relationship between landscape pattern and LST is not consistent among various research conditions.…”

Urbanisation-Induced Land Cover Temperature Dynamics for Sustainable Future Urban Heat Island Mitigation

“…Other Australian State capitals including Sydney, Melbourne and Adelaide are involved with the Urban Climates Project identifying effects of the UHI for integration into planning and design guidelines [63]. However, current global UHI methodologies frequently provide singular metropolitan temperature comparison values for cities, which are inappropriate for assessing land-cover temperature change relationships at the intra-urban scale [30,[52][53][54][55]. Such limitations in current UHI measurement approaches prevent effective UHI mitigation and future sustainable rezoning policy formulations required at the sub-metropolitan level, as defined by the State, Planning Commission and Local Government strategies [62].…”

“…Cross-sectional studies either ignore the temporal component of urbanisation on LST [49,50] or assume a consistent urban area over the study period [5,48,51]. Longitudinal studies classify land cover over multiple periods but often disregard valuable spatial information through comparison of global temperature indices (e.g., the Urban Heat Island Intensity (UHII)) across years and do not quantify changes in land cover that are associated with temperature change [30,[52][53][54][55]. Transformation of land during urbanisation encompasses a broad range of changes within metropolitan regions which are frequently excluded from temperature analysis, and this needs consideration to address the aforementioned limitations.…”

Does Quality Control Matter? A Revisit of Surface Urban Heat Island Intensity Estimated by Satellite-Derived Land Surface Temperature Products

“…By comparison, others achieved the temporal aggregation through weighting the clearsky LSTs by the QC flags (hereafter termed the unequally weighted aggregation (UWA) strategy) [Zhou et al, 2013;Gawuc and Struzewska, 2016]. This study estimated the weights of the UWA as the inverse-square of the retrieved LST error [Zhou et al, 2013].…”

“…Dealing with this, different preprocessings of the LST data were adapted in the temporal composition. Some studies disregarded that and directly use the average of the valid LSTs (Zhou et al, 2014); while others, additionally, performed a temporal aggregation of LSTs taking data quality into consideration, such as only using LSTs with good quality (Clinton,2013;Bechtel, 2015;Zhao et al, 2017), or adapting a weighted average method that the LST is weighted by the quality flags provided by the satellite products (i.e., MODIS LST QC flags (Wan, 2008)) (Zhou et al, 2013). Such different data selected methods in temporal aggregation, however, have been clarified to be able to affect the SUHII calculation even for the same city (Gawuc and Struzewska, 2016).…”