Abstract
Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.
Highlights
The urban heat island (UHI) effect occurs when urban areas have higher temperatures than surrounding rural areas [1], which can contribute to a series of environmental and socio-economic problems, e.g., increasing the frequency and persistence of heat waves [2,3], raising energy consumption [4], accelerating air pollution [5], and threatening public health [6]
When urban core areas and suburb/rural areas were zoned by the contour line of ISAKDE of 50% [28], the ratio of urban core areas increased from 1752 km2 in 2009 to 2075 km2 in 2017
This study explored land surface temperature (LST) and surface urban heat island intensity (SUHII) changes in response to impervious surface area (ISA) and forest cover variations based on remote sensing analysis for the case of Beijing
Summary
The urban heat island (UHI) effect occurs when urban areas have higher temperatures than surrounding rural areas [1], which can contribute to a series of environmental and socio-economic problems, e.g., increasing the frequency and persistence of heat waves [2,3], raising energy consumption [4], accelerating air pollution [5], and threatening public health [6]. A number of studies have focused on discovering the contributions of both the LULC composition and configuration to the land surface temperature (LST). The effects of the LULC configuration on LST variations have been confirmed, e.g., clustered impervious surfaces/vegetation cover act more strongly in elevating/lowering LST [13], and the rational use of connectivity from a landscape source–sink point of view can bring additional cooling effects [14]. The composition of LULC has been proven to be more important in influencing LST than the configuration based on macro-scale remote sensing observations, and the proportions of impervious surface (IS) and green spaces have been shown to have a dominant effect on LST spatial differentiation in different seasons [15,16,17,18,19,20,21]
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