Thermal Environment Effects of Built-Up Land Expansion in Shijiazhuang

Qin, Ling; Liu, Han; Shang, Gao; Yang, Huichao; Yan, Haiming

doi:10.3390/land11070968

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…Ecological spaces such as green areas and water bodies have a cooling effect in cities, known as the cool island effect. The study found that the intensity of the cool island effect increases with the increase in the proportion of ecological space area, like previous research findings [15,23,35,36]. However, this study goes beyond the previous research focus on a single land cover type in relation to the heat island problem and instead explores the long-term spatial pattern evolution of the three ecological spaces in Beijing and its impact on the dynamic distribution of surface heat environment from the perspective of land function.…”

Section: Discussionsupporting

confidence: 62%

“…However, the above-mentioned studies generally provide limited information on the response mechanisms between PLAND indices and LST for various types of spaces, and it is of special significance to analyze the impact of PLES expansions on the urban surface thermal environment based on grids [21,22]. For example, Chen et al proposed a 35% built-up PLAND index to split the thermal environment effect of the construction land expansion in Wu'an City by grid sampling statistics [22], and Qin et al derived a 55-60% PLAND index of the built-up land within the grid to split the thermal environment effect in Shijiazhuang City by a 990 m × 990 m grid analysis [23].…”

Section: Introductionmentioning

confidence: 99%

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Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

et al. 2023

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Rapid economic and social development has triggered competition for limited land space from different industries, accelerating the evolution of Beijing’s urban landscape types. The increase in impermeable surfaces and the decrease in ecological land have led to an increase in the impact on the urban thermal environment. Since previous studies have mainly focused on the impact of a single urban landscape on the urban thermal environment and lacked an exploration of the combined impact of multiple landscapes, this study applied standard deviation ellipses, Pearson correlation analysis, land surface temperature (LST) profile analysis, and hot spot analysis to comprehensively explore the influence of the evolving production–living–ecological space (PLES) pattern on LST. The results show that the average LST of various spaces continued to increase before 2009 and decreased slowly after 2009, with the highest average temperature being living space, followed by production space, and the lowest average temperature being ecological space for each year. The spatiotemporal shift path of the thermal environment is consistent with the shift trajectory of the living space center of gravity in Beijing; LST is positively correlated with living space (LS) and negatively correlated with production space (PS) and ecological space (ES). LST is positively correlated with LS and negatively correlated with PS and ES. Influenced by the change in bedding surface type, the longitudinal thermal profile curve of LST shows a general trend of “low at both ends and high in the middle”. With the change in land space type, LST fluctuates significantly, and the horizontal thermal profile curve shows a general trend of “first decreasing, followed by increasing and finally decreasing”. In addition, the hot spot analysis shows that the coverage area of very hot spots, hot spots, and warm spots increased by 0.72%, 1.13%, and 2.03%, respectively, in the past 30 years, and the main expansion direction is southeast, and very cold spots and cold spots are distributed in the northwest ecological space, and the area change first decreases and then increases.

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Section: Discussionsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

et al. 2023

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Spatial Pattern Impact of Impervious Surface Density on Urban Heat Island Effect: A Case Study in Xuzhou, China

Wang

Ding

Yang

2022

Land

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Impervious surfaces (IPS) are the major source of urban heat island effect (UHI), and the relationships between IPS and land surface temperature (LST) have been widely studied. However, the spatial impact of landscape patterns of patches with different IPS density (IPSD) on the thermal environment remains largely unexplored. Based on three Landsat 8 images of the Xuzhou built-up area obtained in May and the corresponding ground observations from 2014 to 2020, the IPSD and LST maps were inversed through a linear spectral mixture analysis and mono-window algorithm, respectively. The landscape patterns of the five IPSD levels were characterized by four landscape-level and five class-level metrics. Finally, the spatial correlation between all landscape metrics and LST were analyzed using bivariate Moran’s I. The results were as follows: (1) The findings revealed that for the landscape-level metrics, LST had significant positive spatial correlations with Shannon’s diversity index (SHDI), Shannon’s evenness index (SHEI), and patch density (PD), while showing a significant negative correlation with contagion index (CONTAG), indicating that increasing the types, even distribution degree, and density of patches, or decreasing the aggregation degree of the five IPSD levels will lead to the enhancement of the thermal environment. (2) Furthermore, the class-level metrics of each IPSD level, percentage of landscape (PLAND), largest patch index (LPI), landscape shape index (LSI), aggregation index (AI), and patch cohesion index (COHESION) showed significant correlations and LST, which signified that the spatial characteristics of patch proportion, predominance degree, shape complexity, aggregation degree, and natural connectivity degree of each IPSD level are important factors affecting UHI. In addition, the spatial correlations between LST and class-level metrics were significantly positive for IPSD levels 4 and 5 with an evidently higher Moran’s I value, indicating that landscape patterns of IPSD levels 4 and 5 were the key factors in UHI enhancement. Furthermore, the impact weights of each class-level metric of IPSD levels 4 and 5 on LST were also analyzed by applying the principal component analysis and the multivariate regression standardization coefficient. These results reveal the importance and impact mechanism of the IPSD spatial patterns on UHI evolution, which may provide a valuable reference for future urban planning and climate management. This study also suggests that regional UHI can be mitigated by reducing the area proportion, natural connectivity, and shape complexity of high-density impervious surfaces.

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Thermal Environment Effects of Built-Up Land Expansion in Shijiazhuang

Cited by 2 publications

References 21 publications

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

Spatial Pattern Impact of Impervious Surface Density on Urban Heat Island Effect: A Case Study in Xuzhou, China

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