Reconciling Debates on the Controls on Surface Urban Heat Island Intensity: Effects of Scale and Sampling

Author(s):  
Jiameng Lai ◽  
Wenfeng Zhan ◽  
Jinling Quan ◽  
Zihan Liu ◽  
Long Li ◽  
...  
2018 ◽  
Vol 56 (4) ◽  
pp. 576-604 ◽  
Author(s):  
Qihao Weng ◽  
Mohammad Karimi Firozjaei ◽  
Amir Sedighi ◽  
Majid Kiavarz ◽  
Seyed Kazem Alavipanah

2019 ◽  
Vol 46 (4) ◽  
pp. 2204-2212 ◽  
Author(s):  
Rui Yao ◽  
Lunche Wang ◽  
Xin Huang ◽  
Wei Gong ◽  
Xiangao Xia

Author(s):  
Tao Chen ◽  
Anchang Sun ◽  
Ruiqing Niu

Man-made materials now cover a dominant proportion of urban areas, and such conditions not only change the absorption of solar radiation, but also the allocation of the solar radiation and cause the surface urban heat island effect, which is considered a serious problem associated with the deterioration of urban environments. Although numerous studies have been performed on surface urban heat islands, only a few have focused on the effect of land cover changes on surface urban heat islands over a long time period. Using six Landsat image scenes of the Metropolitan Development Area of Wuhan, our experiment (1) applied a mapping method for normalized land surface temperatures with three land cover fractions, which were impervious surfaces, non-chlorophyllous vegetation and soil and vegetation fractions, and (2) performed a fitting analysis of fierce change areas in the surface urban heat island intensity based on a time trajectory. Thematic thermal maps were drawn to analyze the distribution of and variations in the surface urban heat island in the study area. A Multiple Endmember Spectral Mixture Analysis was used to extract the land cover fraction information. Then, six ternary triangle contour graphics were drawn based on the land surface temperature and land cover fraction information. A time trajectory was created to summarize the changing characteristics of the surface urban heat island intensity. A fitting analysis was conducted for areas showing fierce changes in the urban heat intensity. Our results revealed that impervious surfaces had the largest impacts on surface urban heat island intensity, followed by the non-chlorophyllous vegetation and soil fraction. Moreover, the results indicated that the vegetation fraction can alleviate the occurrence of surface urban heat islands. These results reveal the impact of the land cover fractions on surface urban heat islands. Urban expansion generates impervious artificial objects that replace pervious natural objects, which causes an increase in land surface temperature and results in a surface urban heat island.


2018 ◽  
Vol 624 ◽  
pp. 262-272 ◽  
Author(s):  
Huidong Li ◽  
Yuyu Zhou ◽  
Xiaoma Li ◽  
Lin Meng ◽  
Xun Wang ◽  
...  

2021 ◽  
Author(s):  
Yanhua Chen ◽  
Wendy Y. Chen ◽  
Raffaele Lafortezza

Abstract Context Surface urban heat island intensity (SUHII) is a classical measure, which is sensitive to the selection of pixels/measurements representative of urban and rural areas, and overlooks pixel-level SUHII variation and thermodynamics of heterogeneous urban landscape. Accounting inter-pixel landscape heterogeneity in SUHII would capture inter-pixel thermodynamics and reveal complicated micro-thermal situations, contribute to assessment of potential heat risks at micro-pixel scale. Objectives This study develops [[EQUATION]] using pixel-based sharpening enhancement method. It integrates a pixel’s LST magnitude that reflects a city’s thermal context with local SUHII considering landscape variations and cognate thermal interactions of neighboring pixels. Methods [[EQUATION]] is constructed using MODIS LST product for Guangzhou (south China) in the summer season of 2015 through cloud-based GEE platform. Its effectiveness is tested using a bivariate choropleth map and Gaussian density curve with stepwise increments of the thermal influence from neighboring pixels. Results We found that (1) local SUHII variations are sensitive to the spatial configuration of a center pixel’s land use and that of its neighbors; (2) [[EQUATION]] makes more pronounced those spots that are heat per se (with higher original LST), but also receive additional heat load from adjacent pixels due to land-use homogeneity; (3) the effectiveness of [[EQUATION]] could be demonstrated by Gaussian density curve. Conclusions This paper proposed a new SHUII indicator, [[EQUATION]] , which models inter-pixel spatial variation of SHUI and highlights how neighboring pixels’ homogenous/heterogeneous land-use and associated thermal properties could affect center pixels’ thermal characteristics via either reinforcement or mitigation of heat load.


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