scholarly journals The impact of building height on urban thermal environment in summer: A case study of Chinese megacities

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0247786
Author(s):  
Meiya Wang ◽  
Hanqiu Xu
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Single Channel ◽  
Thermal Environment ◽  
Quantitative Relationship ◽  
Cooling Effect ◽  
Height Range ◽  
Building Height ◽  
High Rise ◽  
The Impact

The quantitative relationship between the spatial variation of building’s height and the associated land surface temperature (LST) change in six Chinese megacities is investigated in this paper. The six cities involved are Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, and Shenzhen. Based on both remote sensing and building footprint data, we retrieved the LST using a single-channel (SC) algorithm and evaluate the heating/cooling effect caused by building-height difference via correlation analysis. The results show that the spatial distribution of high-rise buildings is mainly concentrated in the center business districts, riverside zones, and newly built-up areas of the six megacities. In the urban area, the number and the floor-area ratio of high to super high-rise buildings (>24m) account for over 5% and 4.74%, respectively. Being highly urbanized cities, most of urban areas in the six megacities are associated with high LST. Ninety-nine percent of the city areas of Shanghai, Beijing, Chongqing, Guangzhou, Shenzhen, and Tianjin are covered by the LST in the range of 30.2~67.8°C, 34.8~50.4°C, 25.3~48.3°C, 29.9~47.2°C, 27.4~43.4°C, and 33.0~48.0°C, respectively. Building’s height and LST have a negative logarithmic correlation with the correlation coefficients ranging from -0.701 to -0.853. In the building’s height within range of 0~66m, the LST will decrease significantly with the increase of building’s height. This indicates that the increase of building’s height will bring a significant cooling effect in this height range. When the building’s height exceeds 66m, its effect on LST will be greatly weakened. This is due to the influence of building shadows, local wind disturbances, and the layout of buildings.

scholarly journals An Effect of Urban Forest on Urban Thermal Environment in Seoul, South Korea, Based on Landsat Imagery Analysis

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 630
Author(s):  
Peter Sang-Hoon Lee ◽  
Jincheol Park
Keyword(s):  
South Korea ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Forest ◽  
Thermal Environment ◽  
Urban Forests ◽  
Cooling Effect ◽  
Surrounding Areas

The urban heat island effect has posed negative impacts on urban areas with increased cooling energy demand followed by an altered thermal environment. While unusually high temperature in urban areas has been often attributed to complex urban settings, the function of urban forests has been considered as an effective heat mitigation strategy. To investigate the cooling effect of urban forests and their influence range, this study examined the spatiotemporal changes in land surface temperature (LST) of urban forests and surrounding areas by using Landsat imageries. LST, the size of the urban forest, its vegetation cover, and Normalized Difference Vegetation Index (NDVI) were investigated for 34 urban forests and their surrounding areas at a series of buffer areas in Seoul, South Korea. The mean LST of urban forests was lower than that of the overall city, and the threshold distance from urban forests for cooling effect was estimated to be roughly up to 300 m. The group of large-sized urban forests showed significantly lower mean LST than that of small-sized urban forests. The group of urban forests with higher NDVI showed lower mean LST than that of urban forests with lower mean NDVI in a consistent manner. A negative linear relationship was found between the LST and size of urban forest (r = −0.36 to −0.58), size of vegetation cover (r = −0.39 to −0.61), and NDVI (r = −0.42 to −0.93). Temporal changes in NDVI were examined separately on a specific site, Seoul Forest, that has experienced urban forest dynamics. LST of the site decreased as NDVI improved by a land-use change from a barren racetrack to a city park. It was considered that NDVI could be a reliable factor for estimating the cooling effect of urban forest compared to the size of the urban forest and/or vegetation cover.

scholarly journals Quantifying the Effects of Urban Form on Land Surface Temperature in Subtropical High-Density Urban Areas Using Machine Learning

2019 ◽  
Vol 11 (8) ◽  
pp. 959 ◽  
Author(s):  
Yanwei Sun ◽  
Chao Gao ◽  
Jialin Li ◽  
Run Wang ◽  
Jian Liu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Urban Areas ◽  
Thermal Environment ◽  
High Density ◽  
Cooling Effects ◽  
Urban Thermal Environment ◽  
The Impact

It is widely acknowledged that urban form significantly affects urban thermal environment, which is a key element to adapt and mitigate extreme high temperature weather in high-density urban areas. However, few studies have discussed the impact of physical urban form features on the land surface temperature (LST) from a perspective of comprehensive urban spatial structures. This study used the ordinary least-squares regression (OLS) and random forest regression (RF) to distinguish the relative contributions of urban form metrics on LST at three observation scales. Results of this study indicate that more than 90% of the LST variations were explained by selected urban form metrics using RF. Effects of the magnitude and direction of urban form metrics on LST varied with the changes of seasons and observation scales. Overall, building morphology and urban ecological infrastructure had dominant effects on LST variations in high-density urban centers. Urban green space and water bodies demonstrated stronger cooling effects, especially in summer. Building density (BD) exhibited significant positive effects on LST, whereas the floor area ratio (FAR) showed a negative influence on LST. The results can be applied to investigate and implement urban thermal environment mitigation planning for city managers and planners.

scholarly journals Effects of Spatial Pattern of Forest Vegetation on Urban Cooling in a Compact Megacity

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 282 ◽  
Author(s):  
Wen Zhou ◽  
Fuliang Cao ◽  
Guibin Wang
Keyword(s):  
Spatial Patterns ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Environment ◽  
Forest Vegetation ◽  
Cooling Effect ◽  
Vegetation Coverage ◽  
Adaptive Planning ◽  
Fixed Amount ◽  
Cooling Intensity

Urban forests can be an effective contributor to mitigate the urban heat island (UHI) effect. Understanding the factors that influence the cooling intensity of forest vegetation is essential for creating a more effective urban greenspace network to better counteract the urban warming. The aim of this study was to quantify the effects of spatial patterns of forest vegetation on urban cooling, in the Shanghai metropolitan area of China, using correlation analyses and regression models. Cooling intensity values were calculated based on the land surface temperature (LST) derived from remote sensing imagery and spatial patterns of forest vegetation were quantified by eight landscape metrics, using standard and moving-window approaches. The results suggested that 90 m × 90 m was the optimal spatial scale for studying the cooling effect of forest vegetation in Shanghai’s urban area. It also indicated that woodland performed better than grassland in urban cooling and the size, shape, and spatial distribution of woodland patches had significant impacts on the urban thermal environment. Specifically, the increase of size and the degree of compactness of the patch shape can effectively reduce the LST within the woodland. Areas with a higher percentage of vegetation coverage experienced a greater cooling effect. Moreover, when given a fixed amount of vegetation covers, aggregated distribution provided a stronger cooling effect than fragmented distribution and increasing overall shape complexity of woodlands can enhance the cooling effect on surrounding urban areas. This study provides insights for urban planners and landscape designers to create forest adaptive planning strategies to effectively alleviate the UHI effect.

scholarly journals The Influence of Sky View Factor on Daytime and Nighttime Urban Land Surface Temperature in Different Spatial-Temporal Scales: A Case Study of Beijing

2021 ◽  
Vol 13 (20) ◽  
pp. 4117
Author(s):  
Qiang Chen ◽  
Qianhao Cheng ◽  
Yunhao Chen ◽  
Kangning Li ◽  
Dandan Wang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Experimental Results ◽  
View Factor ◽  
Temporal Scales ◽  
Building Height ◽  
Sky View Factor ◽  
The Impact

Urban building morphology has a significant impact on the urban thermal environment (UTE). The sky view factor (SVF) is an important structure index of buildings and combines height and density attributes. These factors have impact on the land surface temperature (LST). Thus, it is crucial to analyze the relationship between SVF and LST in different spatial-temporal scales. Therefore, we tried to use a building vector database to calculate the SVF, and we used remote sensing thermal infrared band to retrieve LST. Then, we analyzed the influence between SVF and LST in different spatial and temporal scales, and we analyzed the seasonal variation, day–night variation, and the impact of building height and density of the SVF–LST relationship. We selected the core built-up area of Beijing as the study area and analyzed the SVF–LST relationship in four periods in 2018. The temporal experimental results indicated that LST is higher in the obscured areas than in the open areas at nighttime. In winter, the maximum mean LST is in the open areas. The spatial experimental results indicate that the SVF and LST relationship is different in the low SVF region, with 30 m and 90 m pixel scale in the daytime. This may be the shadow cooling effect around the buildings. In addition, we discussed the effects of building height and shading on the SVF–LST relationship, and the experimental results show that the average shading ratio is the largest at 0.38 in the mid-rise building area in winter.

scholarly journals Impacts of Building Features on the Cooling Effect of Vegetation in Community-Based MicroClimate: Recognition, Measurement and Simulation from a Case Study of Beijing

2020 ◽  
Vol 17 (23) ◽  
pp. 8915
Author(s):  
Wei Chen ◽  
Jianjun Zhang ◽  
Xuelian Shi ◽  
Shidong Liu
Keyword(s):  
Wind Speed ◽  
Human Health ◽  
Land Surface ◽  
Vegetation Index ◽  
Thermal Environment ◽  
Cooling Effect ◽  
Landsat 8 ◽  
Community Based ◽  
Building Density ◽  
The Impact

Due to the accumulation of heat, the urban environment and human health are threatened. Land surface cover has effects on the thermal environment; nevertheless, the effects of land surface features and spatial patterns remain poorly known in a community-based microclimate. This study quantified and verified the impacts of normalized difference vegetation index (NDVI) on land surface temperature (LST) (K, the slope of the trend line of a linear regression between NDVI and LST) in different building density by using building outline and Landsat 8 satellite imagery. Comparing the cooling effect and distribution of vegetation showed that the vegetative cover had a cooling effect on LST, characterized by synchronous change, and building density had a significant impact on the cooling effect of vegetation. Through identification and simulation, it was found that the key factor is the wind speed between the buildings because, in different building densities, the wind speed was different, and studies had shown that when the building density was between 0.35 and 0.50, the wind speed between buildings was higher, resulting in a better cooling effect of vegetation. This conclusion has important reference significance for urban planning and mitigating the impact of the thermal environment on human health.

scholarly journals The Changes of Heat Contribution Index in Urban Thermal Environment: A Case Study in Fuzhou

2021 ◽  
Vol 13 (17) ◽  
pp. 9638
Author(s):  
Yuan-Bin Cai ◽  
Ke Li ◽  
Yan-Hong Chen ◽  
Lei Wu ◽  
Wen-Bin Pan
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Environment ◽  
Temporal Distribution ◽  
Positive Contribution ◽  
Negative Contribution ◽  
Construction Land ◽  
The Impact

With the acceleration of global warming and urbanization, the problem of the thermal environment in urban areas has become increasingly prominent. In this paper, Fuzhou was selected to quantify the impact of land use cover change (LUCC) on land surface temperature (LST). The results showed that from 1993 to 2016, the land use/cover types of the study area changed greatly, especially the change of construction land, which led to an obvious change in the spatial pattern of LST. From 1993 to 2016, the spatial and temporal distribution of LST contributions in Fuzhou was uneven. The central urban area had a positive contribution to the rise of LST, while Minqing and Yongtai had a negative contribution. From the perspective of different land use/land cover types, forest or grass land, cultivated land, and water all made a negative contribution to the increase of surface temperature, while construction land made a positive contribution. Outcomes provided by the multi-distance spatial cluster analysis (Ripley’s K function) showed that there was a scale effect in the concentration and dispersion of LST; from 1993 to 2016, the concentration range of LST in the study area gradually expanded and the degree of concentration increased.

scholarly journals Detecting Urban Landscape Factors Controlling Seasonal Land Surface Temperatures: From the Perspective of Urban Function Zones

2021 ◽  
Author(s):  
Tong Li ◽  
Ying Xu ◽  
Lei Yao
Keyword(s):  
Landscape Structure ◽  
Land Surface ◽  
Urban Landscape ◽  
Landscape Planning ◽  
Thermal Environment ◽  
Metropolitan Region ◽  
Biophysical Parameters ◽  
Landscape Factors ◽  
Urban Function ◽  
The Impact

Abstract Understanding of the impact on the thermal effect by urbanization is of great significance for urban thermal regulation, it is essential to determine the relationship between the urban heat island (UHI) effect and the complexities of urban function and landscape structure. For this purpose, we conducted a case research in the metropolitan region of Beijing, China, and >5000 urban blocks assigned with different urban function zones (UFZs) were identified as the basic spatial analysis units. Seasonal land surface temperature (LST) retrieved from remote sensing data were used to represent the UHI characteristics of the study area, and surface biophysical parameters, building forms, and landscape pattern metrics were selected as the urban landscape factors. Then, the effects of urban function and landscape structure on the UHI effect were examined by spatial regression models. The results indicated that: (1) Significant spatio-temporal heterogeneity of LST were found in the study area, and there was obvious temperature gradient with “working-living-resting” UFZs; (2) All the types of urban landscape factors showed significant contribution to seasonal LST, and sorted by surface biophysical factors > building forms > landscape factors. However, their contributions varied in different seasons; (3) The major contribute factors showed a certain difference due to the variation of urban function and landscape complexity. This study expands understanding on the complex relationship among urban landscape, function, and thermal environment, which could benefit urban landscape planning for UHI alleviation.

scholarly journals SPATIOLTEMPORAL MODELING THE IMPACT OF SURFACE CHARACTERISTICS VARIATIONS ON LAND SURFACE TEMPERATURE VARIATIONS: A CASE STUDY OF SAMALGHAN VALLY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 401-405
Author(s):  
M. K. Firozjaei ◽  
M. Makki ◽  
J. Lentschke ◽  
M. Kiavarz ◽  
S. K. Alavipanah
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Incident Angle ◽  
Surface Characteristics ◽  
Slope Aspect ◽  
Biophysical Parameters ◽  
The Impact

Abstract. Spatiotemporal mapping and modeling of Land Surface Temperature (LST) variations and characterization of parameters affecting these variations are of great importance in various environmental studies. The aim of this study is a spatiotemporal modeling the impact of surface characteristics variations on LST variations for the studied area in Samalghan Valley. For this purpose, a set of satellite imagery and meteorological data measured at the synoptic station during 1988–2018, were used. First, single-channel algorithm, Tasseled Cap Transformation (TCT) and Biophysical Composition Index (BCI) were employed to estimate LST and surface biophysical parameters including brightness, greenness and wetness and BCI. Also, spatial modeling was used to modeling of terrain parameters including slope, aspect and local incident angle based on DEM. Finally, the principal component analysis (PCA) and the Partial Least Squares Regression (PLSR) were used to modeling and investigate the impact of surface characteristics variations on LST variations. The results indicated that surface characteristics vary significantly for case study in spatial and temporal dimensions. The correlation coefficient between the PC1 of LST and PC1s of brightness, greenness, wetness, BCI, DEM, and solar local incident angle were 0.65, −0.67, −0.56, 0.72, −0.43 and 0.53, respectively. Furthermore, the coefficient coefficient and RMSE between the observed LST variation and modelled LST variation based on PC1s of brightness, greenness, wetness, BCI, DEM, and local incident angle were 0.83 and 0.14, respectively. The results of study indicated the LST variation is a function of s terrain and surface biophysical parameters variations.

scholarly journals Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

2021 ◽  
Vol 10 (12) ◽  
pp. 809
Author(s):  
Jing Sun ◽  
Suwit Ongsomwang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Decomposition Analysis ◽  
Lulc Change ◽  
Main Components ◽  
The Impact

Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature.

scholarly journals RS and GIS Supported Urban LULC and UHI Change Simulation and Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Pei Liu ◽  
Shoujun Jia ◽  
Ruimei Han ◽  
Yuanping Liu ◽  
Xiaofeng Lu ◽  
...  
Keyword(s):  
Land Surface ◽  
Thermal Environment ◽  
Urban Expansion ◽  
Dynamic Change ◽  
Urban Sustainability ◽  
Remotely Sensed Data ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
High Level ◽  
The Impact

Rapid urbanization has become a major urban sustainability concern due to environmental impacts, such as the development of urban heat island (UHI) and the reduction of urban security states. To date, most research on urban sustainability development has focused on dynamic change monitoring or UHI state characterization, while there is little literature on UHI change analysis. In addition, there has been little research on the impact of land use and land cover changes (LULCCs) on UHI, especially simulates future trends of LULCCs, UHI change, and dynamic relationship of LULCCs and UHI. The purpose of this research is to design a remote sensing-based framework that investigates and analyzes how the LULCCs in the process of urbanization affected thermal environment. In order to assess and predict the impact of LULCCs on urban heat environment, multitemporal remotely sensed data from 1986 to 2016 were selected as source data, and Geographic Information System (GIS) methods such as the CA-Markov model were employed to construct the proposed framework. The results showed that (1) there has been a substantial strength of urban expansion during the 40-year study period, (2) the farthest distance urban center of gravity moves from north-northeast (NEE) to west-southwest (WSW) direction, (3) the dominate temperature was middle level, sub-high level, and high level in the research area, (4) there was a higher changing frequency and range from east to west, and (5) there was a significant negative correlation between land surface temperature and vegetation and significant positive correlation between temperature and human settlement.

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