Spatio-Temporal Analysis of Urban Heat Island of Nantong City Based on TM/ETM+ Images

2012 ◽  
Vol 610-613 ◽  
pp. 3720-3723
Author(s):  
Feng Yun Gu ◽  
Xiao Feng Dong ◽  
Hong Quan Xie
Keyword(s):  
Urban Heat Island ◽  
Central City ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Area Ratio ◽  
Direct Result ◽  
Heat Island ◽  
Distribution Diagram ◽  
Urban Heat ◽  
Temperature Area

A direct result of the urban heat island's intensification of Nantong is the accelerated process of urbanization in recent years. In order to analyze spatial and temporal distribution of urban heat island of Nantong City, adiative transfer equation was used to inversion surface temperature of Nantong based on 2001 and 2005TM / ETM + remote sensing images. The results are divided into six grades and temperature level distribution diagram and temperature area ratio statistics were outputted. By the analysis of temperature rating maps and temperature area ratio statistics, it showed that the heat island effect mainly occure in the central city of Nantong from 2001 to 2005. The range of heat island increase and the intensity also increase. The heat island grows in the central urban and the intensity of heat island of other parts is from weak to strong.

scholarly journals Spatiotemporal Changes in the Built Environment Characteristics and Urban Heat Island Effect in a Medium-Sized City, Chiayi City, Taiwan

2020 ◽  
Vol 12 (1) ◽  
pp. 365 ◽  
Author(s):  
Jou-Man Huang ◽  
Heui-Yung Chang ◽  
Yu-Su Wang
Keyword(s):  
Population Density ◽  
Built Environment ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Area Ratio ◽  
Heat Island ◽  
Downtown Area ◽  
Green Area ◽  
Spatiotemporal Changes ◽  
Urban Heat

This study took Chiayi City—a tropical, medium-sized city—as an example to investigate the urban heat island (UHI) effect using mobile transects and built environment characteristics in 2018. The findings were compared to those from a study in 1999 to explore the spatiotemporal changes in the built environment characteristics and UHI phenomenon. The result for the UHI intensity (UHII) during the day was approximately 4.1 °C and at midnight was approximately 2.5 °C. Compared with the survey in 1999, the UHII during the day increased by approximately 1.3 °C, and the UHII at midnight decreased by approximately 1.2 °C. The trend of the spatial distribution of the increasing artificial area ratio (AAR) proved the importance of urban land use expansion on UHI. The results of the air temperature survey were incorporated with the nesting space in GIS to explore the role of built environment characteristics in UHI effects. The higher the population density (PD) and artificial area ratio (AAR) were, the closer the proximity was to the downtown area. The green area ratio (GAR) was less than 0.2 in the downtown area and increased closer to the rural areas. The built environment factors were analyzed in detail and correlated with the UHI effect. The air temperature in the daytime increased with the population density (PD) and artificial area ratio (AAR), but decreased with the green area ratio (GAR) (r = ±0.3–0.4). The result showed good agreement with previous studies.

scholarly journals The Urban Heat Island Analysis of Changsha-zhuzhou-xiangtan Urban Agglomeration Aased on Modis Data

2018 ◽  
Vol 53 ◽  
pp. 03045
Author(s):  
Jiao Yuan ◽  
Jingwen Li ◽  
Suxian Ye ◽  
Xiaoqiang Han ◽  
Yao Hu
Keyword(s):  
Urban Heat Island ◽  
Temperature Difference ◽  
Land Surface ◽  
Temporal Distribution ◽  
Maximum Temperature ◽  
Heat Island ◽  
Maximum Temperature Difference ◽  
High Temperature Area ◽  
Urban Heat ◽  
The Difference

Using a spatial resolution of MODIS land 1000m standard products, we can get the Land Surface Temperature.Researching for the Land Surface Temperature including spatial and temporal distribution characteristics influence factors.The results show that Spring,Summer and Autumn temperatures mainly concentrated in the central region,Winter temperature mainly concentrated in the South region.From 2001 to 2015,the maximum temperature difference is summer daytime and the difference is 17.58°C,the minimum temperature difference is autumn daytime and the difference is 11.3°C.According to the thermal field intensity distribution,compared 2005 with 2015,Urban Heat Island intensity gradually increased in 2015,the high temperature area increased and distributed more concentrated,and diffusion weakened from the city to the surrounding,the urban heat field is higher than the thermal field.That index by calculating the thermal landscape,account for a dominant position in the middle of heat distribution,and all types index in 2015 are higher than in 2005.

Spatial and temporal analysis of urban heat island using Landsat satellite images

2021 ◽  
Author(s):  
Atiyeh Amindin ◽  
Soheila Pouyan ◽  
Hamid Reza Pourghasemi ◽  
Saleh Yousefi ◽  
John P. Tiefenbacher
Keyword(s):  
Urban Heat Island ◽  
Satellite Images ◽  
Temporal Analysis ◽  
Heat Island ◽  
Spatial And Temporal Analysis ◽  
Urban Heat ◽  
Landsat Satellite

scholarly journals Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient

2021 ◽  
Vol 13 (7) ◽  
pp. 1396
Author(s):  
Darshana Athukorala ◽  
Yuji Murayama
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Gradient Analysis ◽  
Temporal Analysis ◽  
Heat Island ◽  
Island Effect ◽  
Greater Cairo ◽  
Urban Rural ◽  
Urban Heat ◽  
Spatio Temporal

An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves.

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