scholarly journals Spatio-Temporal Relationship between Land Cover and Land Surface Temperature in Urban Areas: A Case Study in Geneva and Paris

2020 ◽  
Vol 9 (10) ◽  
pp. 593
Author(s):  
Xu Ge ◽  
Dasaraden Mauree ◽  
Roberto Castello ◽  
Jean-Louis Scartezzini
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Large Scale ◽  
Health Management ◽  
Spatial Lag Model ◽  
Green Area ◽  
Cooling Effects ◽  
Grid Based

Currently, more than half of the world’s population lives in cities, which leads to major changes in land use and land surface temperature (LST). The associated urban heat island (UHI) effects have multiple impacts on energy consumption and human health. A better understanding of how different land covers affect LST is necessary for mitigating adverse impacts, and supporting urban planning and public health management. This study explores a distance-based, a grid-based and a point-based analysis to investigate the influence of impervious surfaces, green area and waterbodies on LST, from large (distance and grid based analysis with 400 m grids) to smaller (point based analysis with 30 m grids) scale in the two mid-latitude cities of Paris and Geneva. The results at large scale confirm that the highest LST was observed in the city centers. A significantly positive correlation was observed between LST and impervious surface density. An anticorrelation between LST and green area density was observed in Paris. The spatial lag model was used to explore the spatial correlation among LST, NDBI, NDVI and MNDWI on a smaller scale. Inverse correlations between LST and NDVI and MNDWI, respectively, were observed. We conclude that waterbodies display the greatest mitigation on LST and UHI effects both on the large and smaller scale. Green areas play an important role in cooling effects on the smaller scale. An increase of evenly distributed green area and waterbodies in urban areas is suggested to lower LST and mitigate UHI effects.

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 Mapping Land Surface Temperature Developments in Functional Urban Areas across Europe

2021 ◽  
Vol 13 (11) ◽  
pp. 2111
Author(s):  
Anna Hellings ◽  
Andreas Rienow
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Cooling Effects ◽  
Development Paths

Unsustainable development paths have reached critical levels in Europe. In recent years, in cities, urbanization has been contributing to the intensification of urban heat islands. To analyze the development of surface urban heat islands (SUHI) in Europe in the last few years, the present study combines the land surface temperature (LST) from MODIS with the urban classes of the CORINE land cover data within 617 functional urban areas (FUAs). Urban and industrial uses have significantly higher LST than green urban areas across all years (about 4 to 6 °C), as do agricultural areas within cities. Besides land cover, location also influences LST differences. While, e.g., Bolzano (Italy) shows particularly large LST differences (>6 °C) between the core and the commuting zone, this effect is hardly visible in Porto (Portugal) and Madrid (Spain) (<2.5 °C). Cities of moderate climates show increasing differences between a city and its commuting zones with rising LST (r = 0.68), i.e., less cooling effects at night.

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.

Further evidence of impacts of large-scale wind farms on land surface temperature

2012 ◽  
Vol 16 (8) ◽  
pp. 6432-6437 ◽  
Author(s):  
Jenell M. Walsh-Thomas ◽  
Guido Cervone ◽  
Peggy Agouris ◽  
Germana Manca
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Wind Farms

scholarly journals Quantification of Urban Heat Island-Induced Contribution to Advance in Spring Phenology: A Case Study in Hangzhou, China

2021 ◽  
Vol 13 (18) ◽  
pp. 3684
Author(s):  
Yingying Ji ◽  
Jiaxin Jin ◽  
Wenfeng Zhan ◽  
Fengsheng Guo ◽  
Tao Yan
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Heat Island ◽  
Spring Phenology ◽  
Urban Heat ◽  
The Difference

Plant phenology is one of the key regulators of ecosystem processes, which are sensitive to environmental change. The acceleration of urbanization in recent years has produced substantial impacts on vegetation phenology over urban areas, such as the local warming induced by the urban heat island effect. However, quantitative contributions of the difference of land surface temperature (LST) between urban and rural (ΔLST) and other factors to the difference of spring phenology (i.e., the start of growing season, SOS) between urban and rural (ΔSOS) were rarely reported. Therefore, the objective of this study is to explore impacts of urbanization on SOS and distinguish corresponding contributions. Using Hangzhou, a typical subtropical metropolis, as the study area, vegetation index-based phenology data (MCD12Q2 and MYD13Q1 EVI) and land surface temperature data (MYD11A2 LST) from 2006–2018 were adopted to analyze the urban–rural gradient in phenology characteristics through buffers. Furthermore, we exploratively quantified the contributions of the ΔLST to the ΔSOS based on a temperature contribution separation model. We found that there was a negative coupling between SOS and LST in over 90% of the vegetated areas in Hangzhou. At the sample-point scale, SOS was weakly, but significantly, negatively correlated with LST at the daytime (R2 = 0.2 and p < 0.01 in rural; R2 = 0.14 and p < 0.05 in urban) rather than that at nighttime. Besides, the ΔSOS dominated by the ΔLST contributed more than 70% of the total ΔSOS. We hope this study could help to deepen the understanding of responses of urban ecosystem to intensive human activities.

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 THE EFFECT OF GREEN SPACE ON THE LAND SURFACE TEMPERATURE IN HUE CITY

2018 ◽  
Vol 55 (4C) ◽  
pp. 129
Author(s):  
Nguyen Bac Giang
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Satellite Image ◽  
Urban Green Space ◽  
Landsat 8 ◽  
Urban Green ◽  
Study Results

This paper presents the analysis of the effect of urban green space types on land surface temperature in Hue city. Data are collected with temperature monitoring results from each green space type and the interpretation of surface temperature based on Landsat 8 satellite image data to determine temperatures at different times of the year. Results showed that there was a significant correlation between types of urban green space and the surface temperature. Types of green space with a large area and vegetation indexes have a greater effect on temperature than areas with a smaller green space do. Green space types including forest green space, dedicated green space and agriculture green space have the most effect on the surface temperature. The forest area has the greatest influence on the temperature with a temperature difference of more than 1.6 degrees Celsius at 9:00 in the daytime. Besides, the results extracted from satellite images also show that the area of urban green space going to be reduced makes a contribution to increase the surface temperature of urban areas. The study results have established foundation for planning the green spaces in climate change challenges in Hue City.

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