scholarly journals Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Qiquan Yang ◽  
Xin Huang ◽  
Jiayi Li
Keyword(s):  
Urban Heat Islands ◽  
Landscape Patterns ◽  
Climatic Zones ◽  
Heat Islands ◽  
Urban Heat ◽  
The Relationship

scholarly journals Erratum: Zhao, H.; Zhang, H.; Miao, C.; Ye, X.; Min, M. Linking Heat Source–Sink Landscape Patterns with Analysis of Urban Heat Islands: Study on the Fast-Growing Zhengzhou City in Central China. Remote Sens. 2018, 10, 1268

2020 ◽  
Vol 12 (18) ◽  
pp. 2965
Author(s):  
Hongbo Zhao ◽  
Hao Zhang ◽  
Changhong Miao ◽  
Xinyue Ye ◽  
Min Min
Keyword(s):  
Heat Source ◽  
Urban Heat Islands ◽  
Landscape Patterns ◽  
Central China ◽  
Heat Islands ◽  
Fast Growing ◽  
Urban Heat ◽  
Source Sink

The authors wish to make the following corrections to this paper [...]

scholarly journals Quantifying the effect of waterways and green areas on the surface temperature

2017 ◽  
Vol 39 (1) ◽  
pp. 89 ◽  
Author(s):  
Elis Dener Lima Alves
Keyword(s):  
Surface Temperature ◽  
Temporal Variability ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Natural Area ◽  
Heat Islands ◽  
Green Areas ◽  
Urban Heat ◽  
Cooling Effects ◽  
The Relationship

The cooling effects of urban parks and green areas, which form the “Park Cool Island” (PCI) can help decrease the surface temperature and mitigate the effects of urban heat islands (UHI). Therefore, the objective of this research was to know the temporal variability of PCI intensity, as well as analyze the factors that determines it and propose an equation to predict the PCI intensity in Iporá, Goiás State, Brazil. To this purpose, the PCI intensity values were obtained using the Landsat-8 satellite (band 10), and then correlated with the NDVI and the LAI, in which proposes equations through multiple linear regression to estimate the PCI intensity. The results indicated that: 1) the greater the distance of the natural area, greater the surface temperature; 2) there is a great seasonality in PCI, in which the intensity of PCI is much higher in the spring (or close to it); 3) the relationship between NDVI and LAI variables, showed good coefficients of determination; 4) the equations for the buffer of 200 and 500 m, had low RMSE with high coefficients of determination (r2 = 0.924 and r2 = 0.957 respectively). 

scholarly journals Visualising a comparison of simulated urban heat islands: a case study of two Slovakian cities

2019 ◽  
Vol 1 ◽  
pp. 1-8 ◽  
Author(s):  
Ján Feranec ◽  
Juraj Holec ◽  
Pavel Šťastný ◽  
Daniel Szatmári ◽  
Monika Kopecká
Keyword(s):  
Urban Heat Islands ◽  
Heat Island ◽  
Urban Fabric ◽  
Temperature Changes ◽  
Heat Islands ◽  
Computer Animations ◽  
Urban Heat ◽  
The Relationship

<p><strong>Abstract.</strong> Temperature increases in cities affects inhabitants’ quality of life, justifying the extent of research focusing on identifying, analysing, and assessing the relationship between the density of urban fabric represented by land cover/land use (LC/LU) classes and manifestation of the urban heat island (UHI) phenomenon. This paper delimits LC/LU classes for the urban Bratislava (2,117&amp;thinsp;ha of class 12110 dominated in 2016) and Trnava (598 ha of class 12120 dominated in 2016). The greatest median air temperature over 33&amp;thinsp;&amp;deg;C (at 18:00) was derived with the MUKLIMO model for the class <i>Continuous urban fabric with the sealing degree &amp;gt;&amp;thinsp;80%</i> in Bratislava. The graphic outputs improve our perception and evaluation of the LC/LU and UHI relationship. The information potential of the graphical outputs may increase through use of computer animations to represent the temperature changes during day or the temperature changes among years.</p>

scholarly journals Linking Heat Source–Sink Landscape Patterns with Analysis of Urban Heat Islands: Study on the Fast-Growing Zhengzhou City in Central China

2018 ◽  
Vol 10 (8) ◽  
pp. 1268 ◽  
Author(s):  
Hongbo Zhao ◽  
Hao Zhang ◽  
Changhong Miao ◽  
Xinyue Ye ◽  
Min Min
Keyword(s):  
Heat Source ◽  
Land Surface ◽  
Urban Landscape ◽  
Urban Heat Islands ◽  
Landscape Patterns ◽  
Central China ◽  
Heat Sources ◽  
Heat Islands ◽  
Urban Heat ◽  
Source Sink

Globally, the urban heat island (UHI) effect is a major problem which leads to urban residents suffering from adverse urban ecological environments and serious health risks. Understanding the impacts of urban landscape features on the thermal environment has been an important focus across various fields of research. The purpose of this study is to analyze the impacts of urban heat source–sink landscape patterns on urban heat islands, using the fast-growing Zhengzhou City in central China as the case study. Landsat data (captured in 1996, 2006, and 2014), various geospatial approaches, and correlation analysis were applied to facilitate the analysis. Based on the contributions of the urban landscape to land surface temperature (LST), we empirically identified the heat sources and heat sinks. Then, the composition and configurations of heat source and sink landscapes were estimated by a series of spatial metrics at the landscape and class levels. The results showed that the overall mean land surface temperature (LST) in the study area increased by 2.72 °C from 1996 to 2014. This observed increasing trend in overall mean LST is consistent with the process of rapid urbanization in the study area, which was evidenced by the dramatic increase in impervious surfaces and the substantial loss in vegetation cover. Generally, as observed, landscape composition has a stronger influence on LST than does landscape configuration. For heat sources, the proportion, size, aggregation, and density of patches have positive effects on LST, while adjusting the spatial distribution and abundance of urban landscape are effective ways to control the UHI effects. In contrast, the percentage, size, density, and aggregation of heat sink patches have negative effects on LST. Additionally, the effects of increasing total patch edges and shape complexity should be considered when mitigating the UHI effect. These findings are beneficial for furthering our understanding of how urban landscape patterns affect UHI, and they can help optimize urban landscape patterns to alleviate the UHI effect and enhance sustainable development in the study area.

scholarly journals Distinct Influences of Urban Villages on Urban Heat Islands: A Case Study in the Pearl River Delta, China

2018 ◽  
Vol 15 (8) ◽  
pp. 1666 ◽  
Author(s):  
Wei Wu ◽  
Hongyan Ren ◽  
Ming Yu ◽  
Zhen Wang
Keyword(s):  
Land Use ◽  
Pearl River Delta ◽  
Object Oriented ◽  
Urban Heat Islands ◽  
Object Oriented Method ◽  
Heat Islands ◽  
Land Use Types ◽  
Core Areas ◽  
Urban Heat ◽  
The Relationship

Widely scattered urban villages (UVs) and increasingly serious urban heat islands (UHIs) are common urban problems in highly urbanized regions, especially in the developing countries. However, the influences of UVs on UHIs remain little understood. In this study, different methodologies are performed to retrieve land surface temperature (LST) from thermal bands and the nearest object-oriented method with spectral, texture, shape metrics using ZY-3 high-resolution satellite imagery, and road network data are used to extract UVs and other land-use types in the Guangzhou–Foshan (GF) core areas of Pearl River Delta (PRD). Moreover, the relationship between LST and land-use types is then analyzed on the multiple scales. The results show that five land-use types (vegetation, normal construction land (NCL), UVs, water, and unused land) extracted by the object-oriented method were qualified for subsequent analysis because of satisfactory overall accuracy (0.887) and the Kappa coefficient (0.863). In the GF core areas presenting the most outstanding UHI effect across the PRD region, about 60.5% of the total area is covered by the impervious surfaces, including NCL (50.4%) and UVs (10.1%). The average LST of UVs was 1.89–2.97 °C lower than that of NCL. According to the average contribution index of thermal effect and the Pearson’s correlation coefficients, UVs present a relatively lower contribution to UHI and a weaker warming effect than NCL, but possess a higher contribution to UHI and a stronger warming effect than other land-use types, resulting in some slightly lower LST-valleys in the UVs adjacent to the NCL and distinct LST-peaks of UVs close to vegetation and water on the surface temperature profile lines. This work increases our understanding of the relationship between increasingly serious UHIs and widely distributed UVs, and would be valuable for local authorities to monitor and improve urban environment in metropolitan regions.

Daytime and nighttime urban heat islands statistical models for Atlanta

2016 ◽  
Vol 44 (2) ◽  
pp. 308-327 ◽  
Author(s):  
Bumseok Chun ◽  
Subhrajit Guhathakurta
Keyword(s):  
Urban Design ◽  
Surface Characteristics ◽  
Urban Heat Islands ◽  
Dominant Factor ◽  
Relative Importance ◽  
Geospatial Information ◽  
Heat Islands ◽  
Urban Heat ◽  
2D And 3D ◽  
The Relationship

In this study, we empirically model the interactions between 2D and 3D geospatial information and both daytime and nighttime urban heat islands, and estimate the relative importance of various urban heat islands drivers. While previous studies have explored the relationship between the urban heat islands and 2D urban features, the interactions with 3D urban features and neighboring surface characteristics have not been adequately explored. This paper specifies the impacts of these urban features on the urban heat islands intensity during daytime and nighttime, which tend to be quite different. The empirical evidence from this study suggests that while vegetation is the dominant factor for urban heat islands intensity during daytime, the urban canyon has stronger impacts on the urban heat islands than vegetation at night. In addition, adjacent surfaces are more likely to influence nighttime surface temperatures. These results could be used to develop urban design solutions for mitigating the urban heat islands.

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