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 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 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 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 Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China

2020 ◽  
Vol 12 (18) ◽  
pp. 3006
Author(s):  
Chaobin Yang ◽  
Fengqin Yan ◽  
Xuelei Lei ◽  
Xiuli Ding ◽  
Yue Zheng ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Snow Cover ◽  
Spatial Patterns ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Driving Factors ◽  
Seasonal Effects ◽  
Landsat 8 ◽  
Crop Species

Land surface temperature (LST) is a crucial parameter in surface urban heat island (SUHI) studies. A better understanding of the driving mechanisms, influencing variations in LST dynamics, is required for the sustainable development of a city. This study used Changchun, a city in northeast China, as an example, to investigate the seasonal effects of different dominant driving factors on the spatial patterns of LST. Twelve Landsat 8 images were used to retrieve monthly LST, to characterize the urban thermal environment, and spectral mixture analysis was employed to estimate the effect of the driving factors, and correlation and linear regression analyses were used to explore their relationships. Results indicate that, (1) the spatial pattern of LST has dramatic monthly and seasonal changes. August has the highest mean LST of 38.11 °C, whereas December has the lowest (−19.12 °C). The ranking of SUHI intensity is as follows: summer (4.89 °C) > winter with snow cover (1.94 °C) > spring (1.16 °C) > autumn (0.89 °C) > winter without snow cover (−1.24 °C). (2) The effects of driving factors also have seasonal variations. The proportion of impervious surface area (ISA) in summer (49.01%) is slightly lower than those in spring (56.64%) and autumn (50.85%). Almost half of the area is covered with snow (43.48%) in winter. (3) The dominant factors are quite different for different seasons. LST possesses a positive relationship with ISA for all seasons and has the highest Pearson coefficient for summer (r = 0.89). For winter, the effect of vegetation on LST is not obvious, and snow becomes the dominant driving factor. Despite its small area proportion, water has the strongest cooling effect from spring to autumn, and has a warming effect in winter. (4) Human activities, such as agricultural burning, harvest, and different choices of crop species, could also affect the spatial patterns of LST.

scholarly journals Analyzing the Spatial Heterogeneity of the Built Environment and Its Impact on the Urban Thermal Environment—Case Study of Downtown Shanghai

2021 ◽  
Vol 13 (20) ◽  
pp. 11302
Author(s):  
Jiejie Han ◽  
Xi Zhao ◽  
Hao Zhang ◽  
Yu Liu
Keyword(s):  
Built Environment ◽  
Spatial Heterogeneity ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Environment ◽  
Urban Expansion ◽  
Surface Heat ◽  
Positive Contribution ◽  
Heat Island ◽  
Island Effect

Ongoing urban expansion has accelerated the explosive growth of urban populations and has led to a dramatic increase in the impervious surface area within urban areas. This, in turn, has exacerbated the surface heat island effect within cities. However, the importance of the surface heat island effect within urban areas, scilicet the intra-SUHI effect, has attracted less concern. The aim of this study was to quantitatively explore the relationship between the spatial heterogeneity of a built environment and the intra-urban surface heat island (intra-SUHI) effect using the thermally sharpened land surface temperature (LST) and high-resolution land-use classification products. The results show that at the land parcel scale, the parcel-based relative intensity of intra-SUHI should be attributed to the land parcels featured with differential land developmental intensity. Furthermore, the partial least squares regression (PLSR) modeling quantified the relative importance of the spatial heterogeneity indices of the built environment that exhibit a negative contribution to decreasing the parcel-based intra-SUHI effect or a positive contribution to increasing the intra-SUHI effect. Finally, based on the findings of this study, some practical countermeasures towards mitigating the adverse intra-SUHI effect and improving urban climatic adaption are discussed.

scholarly journals Estimating the Cooling Effect of Pocket Green Space in High Density Urban Areas in Shanghai, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Caiyan Wu ◽  
Junxiang Li ◽  
Chunfang Wang ◽  
Conghe Song ◽  
Dagmar Haase ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
High Density ◽  
Landscape Patterns ◽  
Green Spaces ◽  
Cooling Effect ◽  
Cooling Efficiency ◽  
Landscape Features ◽  
Cooling Effects

Recently, pocket green spaces (PGS), i.e., small green spaces, have attracted growing attention for their various ecological and social services. As a crucial part of urban green spaces in high-density urban areas, PGS facilitates recreation and relaxation for neighborhoods and thus improves the livability of cities at the local scale. However, whether and how the PGS cools the urban heat island effect is still unclear. This research was performed in the highly developed areas of the city of Shanghai during hot summer daytime. We applied a set of cooling effect indicators to estimate the cooling extent, cooling intensity, and cooling efficiency of PGS. We further examined whether and how landscape features within and surrounding the PGS influence its cooling effects. The results showed that 90% of PGS are cooler than their surroundings. Among the landscape features, the land surface temperature of PGS logarithmically decreased with its area, and the maximum local cool island intensity and maximum cooling area logarithmically increased with the area of PGS. The vegetation types and their composition within the PGS also influenced their surface temperature and the cooling effect. The PGS dominated by tree-shrub-grass showed the highest cooling efficiency. The surrounding landscape patterns, especially the patch density and the landscape shape index, influence the cooling effect of PGS at both class and landscape levels. These findings add new knowledge on factors influencing the cooling effect of PGS, and provide the biophysical theoretical basis for developing nature-based cooling strategies for urban landscape designers and planners.

scholarly journals Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing

2021 ◽  
Vol 13 (8) ◽  
pp. 1526
Author(s):  
Yaoyao Zheng ◽  
Yao Li ◽  
Hao Hou ◽  
Yuji Murayama ◽  
Ruci Wang ◽  
...  
Keyword(s):  
Inner City ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landscape Patterns ◽  
Water Bodies ◽  
Cooling Effect ◽  
Landsat 8 ◽  
West Lake

The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands.

scholarly journals Outdoor Thermal Environments of Main Types of Urban Areas during Summer: A Field Study in Wuhan, China

2022 ◽  
Vol 14 (2) ◽  
pp. 952
Author(s):  
Kun Li ◽  
Xuefei Li ◽  
Keji Yao
Keyword(s):  
Temperature Difference ◽  
Urban Areas ◽  
Thermal Environment ◽  
Cooling Effect ◽  
Maximum Temperature ◽  
Water Evaporation ◽  
Heat Island ◽  
Maximum Temperature Difference ◽  
Thermal Environments ◽  
Island Effect

Under the influence of the urban heat island effect, the thermal environments of urban built-up areas are poor, leading to the loss of urban vitality and the extreme deterioration of thermal comfort. In this paper, the outdoor thermal environment in Wuhan’s main urban area is studied via the use of field measurements. From June to August in the years 2015 to 2017, 20 measurement points were selected for monitoring from 08:00 to 19:00 h, which were located in spaces such as residential areas, parklands, commercial streets, and college/university campuses. The measurements for the same types of land and different types of land use are analyzed. A comprehensive thermal environment index is used to quantitatively evaluate the overall situations of thermal environments. The results showed that the cooling effect of vegetation shading was stronger than the effect of water evaporation and the maximum temperature difference between the two cooling methods reached 6.1 °C. The cooling effect of the canopy shading of tall trees was stronger than the effect of grassland transpiration and the maximum temperature difference was 2.8 °C. The streets with higher aspect ratios might improve the ventilation, but the wind speeds remained low, which did not provide a strong cooling effect. This study helps urban planners understand the thermal environment of Wuhan or similar cities with hot summer and diversified urban areas, and puts forward suggestions to reduce the heat island effect from the aspect of building layout, green coverage, shading mode, and street aspect ratio, so as to establish sustainable cities that are climate adaptable and environmentally friendly.

ANALYSING STREET HERITAGE TREES SURFACE TEMPERATURE FOR UHI MITIGATION USING REMOTE SENSING AND GIS APPLICATION

2019 ◽  
Vol 6 (2) ◽  
pp. 77
Author(s):  
Nor Suhaida Yusof ◽  
Nur Huzeima Mohd Hussain ◽  
Noradila Rusli
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Urban Trees ◽  
Cooling Effect ◽  
Landsat 8 ◽  
Environmental Implications ◽  
Heritage Trees ◽  
Tree Characteristics

Urban Trees are important in reducing the heat by providing the shade and cooling effect to the urban environment. Every tree species provides different cooling effect depending on their tree characteristics. Evergreen species such as heritage tree are significant in reducing the surface temperature. In particular, heritage trees do have environmental implications which provide lots of benefits for the environment and human health. The aim of this paper is to analyse the heritage trees surface temperature in mitigating urban heat island (UHI) at Taiping Old Town. The research has conducted utilizing Landsat 8 OLI data and on-site data collection. This research integrated Geographic Information System (GIS) and remote sensing in data processing and SPSS for analysis. The result shows the low significant relationship of tree characteristics and Land Surface Temperature (LST) with (R²=0.17) indicates that external factors can reduce the cooling effect from heritage trees in reducing the surface temperature in the urban area. Moreover, there is also an analysis on the LST of land cover features together with the frequency of heritage trees.  The findings revealed that the higher frequency of heritage trees planted at the hard surface; the higher the ability to reduce the LST (about 5.3°C) in urban areas.

Application of Remote Sensing Technology in the Analysis of Thermal Environment in Dongying City

2013 ◽  
Vol 726-731 ◽  
pp. 4558-4561
Author(s):  
Hai Bo Yang ◽  
Li Ping Zhou ◽  
Run Fen Li
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Thermal Environment ◽  
Remote Sensing And Gis ◽  
Ecological Environment ◽  
Vegetation Coverage ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Dongying City ◽  
Urban Thermal Environment

Urban thermal environment, as an important reflection of urban ecological environment, is affected strongly by urban land change, especially the loss of green land. By using remote sensing and GIS, two terms of remote images of Dongying city are studied to disclose vegetation coverage and land surface temperature that can reflect urban thermal environment.

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