scholarly journals Spatio-temporal Features of Urban Heat Island and its Relationship with Land Use/Cover in Mountainous City: A Case Study in Chongqing

2018 ◽  
Author(s):  
Chunxia Liu ◽  
Yuechen Li
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Landscape ◽  
Remote Sensing Data ◽  
Rate Of Change ◽  
Heat Island ◽  
Spatial And Temporal Patterns ◽  
Temporal Features ◽  
Urban Heat ◽  
Spatio Temporal

The urban heat island (UHI) becomes more and more serious with the acceleration of urbanization. Many researchers have shown interest in studying the UHI by using remote sensing data. But these studies rarely examine the mountainous cities. The studies on UHI in mountainous cities often used empirical parameters to estimate the land surface temperature (LST), and lacked satellite-ground synchronous experiment to test the accuracy. This paper revised the parameters in mono-window algorithm used to retrieve the LST according to the characteristics of mountainous cities. This study examined the spatial and temporal patterns of the UHI intensity in Chongqing, a typical mountainous city, and its relationship with land cover from 2007 to 2011 based on the Landsat TM data and the improved method. The accuracy of the LST derivation increased by about 1°C compared to the traditional method. The high LST areas increased and extended from the downtown to suburban area each year, but the rate of change decreased. The UHI is dramatically impacted by the rivers. There is a good relationship between the urban sprawl and the UHI. The LST was reduced by about 1°C within a 300m distance from large urban fringe green spaces. The urban landscape parks had a strong effect relieving the UHI at a 100m distance. The LST was reduced by about 0.5°C. The study greatly improves the accuracy of LST derivation, and provides a reliable parameters for the UHI researched in mountainous city.

scholarly journals Evaluating the roles of green and built-up areas in reducing a surface urban heat island using remote sensing data

Urbani izziv ◽  
2019 ◽  
Vol 2 (30) ◽  
pp. 105-112
Author(s):  
Gordana Kaplan
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Heat Island ◽  
Negative Effects ◽  
Rapid Urbanization ◽  
Green Areas ◽  
Urban Heat ◽  
Surface Urban Heat Island

Rapid urbanization has several negative effects on both the environment and human health. Urbanization has also become an important contributor to global warming. One of these effects is the urban heat island (UHI), which is caused by human activities and defined as the temperature difference between urban and surrounding rural areas. With rapid urbanization in the past few decades, Skopje has experienced remarkable UHI effects. To investigate the roles of built-up and green areas in a surface UHI, this article uses satellite data from Landsat ETM+ to analyse the land surface temperature and high-resolution Planet Scope DOVE data to analyse built-up and green areas. For geostatistical analyses, seventeen randomly selected subareas in Skopje were used. The results show a significant correlation between the UHI and built-up areas, and strong correlation between green areas and areas not affected by the UHI, indicating that the UHI effect can be significantly weakened with additional green areas. One of the significant findings in the study is the ideal proportion of built-up (40%) and green areas (60%), where the UHI effect is weak, or in some cases prevented. For future studies, investigating other factors that may contribute to the UHI phenomenon is suggested.

Land Surface Temperature Estimation and Urban Heat Island Detection

2019 ◽  
pp. 1538-1560
Author(s):  
Abhisek Santra
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Global Climate ◽  
Theoretical Background ◽  
Heat Island ◽  
Temperature Estimation ◽  
Urban Heat ◽  
Spatio Temporal

Earth's land surface temperature is considered to be very important for modeling the environment. Following the trend of increasing global population, urban areas are expanding in spatio-temporal domain. In this way it is affecting the urban climate and subsequently the global climate. Thus, scientific understanding is required to conceive the knowledge about interaction between urban land use/land cover and the atmospheric conditions prevailing in that area. In this chapter the land surface temperature estimation and urban heat island detection are perceived from remote sensing perspective. The chapter in this context highlights three major aspects, viz. the theoretical background, description about some of the common thermal sensors and widely used algorithms to retrieve surface temperature from these satellite sensors.

scholarly journals Determining the Boundary and Probability of Surface Urban Heat Island Footprint Based on a Logistic Model

2019 ◽  
Vol 11 (11) ◽  
pp. 1368 ◽  
Author(s):  
Zhi Qiao ◽  
Chen Wu ◽  
Dongqi Zhao ◽  
Xinliang Xu ◽  
Jilin Yang ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Landscape Heterogeneity ◽  
Remote Sensing Data ◽  
Precise Determination ◽  
Heat Island ◽  
Rural Regions ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Moderate Resolution Imaging Spectroradiometer

Studies of the spatial extent of surface urban heat island (SUHI or UHISurf) effects require precise determination of the footprint (FP) boundary. Currently available methods overestimate or underestimate the SUHI FP boundary, and can even alter its morphology, due to theoretical limitations on the ability of their algorithms to accurately determine the impacts of the shape, topography, and landscape heterogeneity of the city. The key to determining the FP boundary is identifying background temperatures in reference rural regions. Due to the instability of remote sensing data, these background temperatures should be determined automatically rather than manually, to eliminate artificial bias. To address this need, we developed an algorithm that adequately represents the decay of land surface temperature (LST) from the urban center to surrounding rural regions, and automatically calculates thresholds for reference rural LSTs in all directions based on a logistic curve. In this study, we applied this algorithm with data from the Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS) 8-day level 3 (L3) LST global grid product to delineate precise SUHI FPs for the Beijing metropolitan area during the summers of 2004–2018 and determine the interannual and diurnal variations in FP boundaries and their relationship with SUHI intensity.

scholarly journals Transformation of Urban Surfaces and Heat Islands in Nanjing during 1984–2018

2020 ◽  
Vol 12 (16) ◽  
pp. 6521
Author(s):  
Yanxia Li ◽  
Xinkai Zhang ◽  
Sijie Zhu ◽  
Xiaoyu Wang ◽  
Yongdong Lu ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Heat Islands ◽  
Island Effect ◽  
Urban Heat ◽  
The Many

One of the many consequences of urbanization is the expansion of cities into rural areas, which leads to the transformation of lands from natural surfaces to developed surfaces. It is widely considered an established fact that urbanization generally increases the heat island effect. The objective of this study is to understand the pattern of urban surface transformation in the city of Nanjing since 1980 and to find, if any, the correlation between such transformation and the urban heat island effect. The supervised classification technique was used to analyze the remote sensing data obtained from Landsat to identify the different kinds of underlying surfaces. Land surface temperatures were calculated using a subset of Landsat data. The correlation between the transformation of underlying surfaces and the heat island effect was established through analytical and statistical approaches. The results clearly show that the proportion of developed surfaces has been steadily rising in Nanjing in the past 30 years and that the urban heat island effect is positively correlated with the expansion of hard pavement and the deterioration of green surfaces and water bodies considering the general trend.

Land Surface Temperature Estimation and Urban Heat Island Detection

2017 ◽  
pp. 16-45
Author(s):  
Abhisek Santra
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Global Climate ◽  
Theoretical Background ◽  
Heat Island ◽  
Temperature Estimation ◽  
Urban Heat ◽  
Spatio Temporal

Earth's land surface temperature is considered to be very important for modeling the environment. Following the trend of increasing global population, urban areas are expanding in spatio-temporal domain. In this way it is affecting the urban climate and subsequently the global climate. Thus, scientific understanding is required to conceive the knowledge about interaction between urban land use/land cover and the atmospheric conditions prevailing in that area. In this chapter the land surface temperature estimation and urban heat island detection are perceived from remote sensing perspective. The chapter in this context highlights three major aspects, viz. the theoretical background, description about some of the common thermal sensors and widely used algorithms to retrieve surface temperature from these satellite sensors.

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.

scholarly journals Spatio-Temporal Mechanism Underlying the Effect of Urban Heat Island on Cardiovascular Diseases

2020 ◽  
Author(s):  
Huanchun HUANG ◽  
Xin DENG ◽  
Hailin YANG ◽  
Xinhui ZHOU ◽  
Qi JIA
Keyword(s):  
Cardiovascular Diseases ◽  
Urban Heat Island ◽  
Land Surface ◽  
Central Area ◽  
Space Distribution ◽  
Heat Island ◽  
Point Distribution ◽  
Urban Heat ◽  
Spatio Temporal ◽  
High Level

Background: We explored the spatio-temporal characteristics of urban heat island (UHI) effect on cardiovascular diseases (CVDs). Methods: The land surface temperatures (LST) were retrieved from four Landsat remote-sensing images’ data, the temperature data from 95 meteorological stations, and analysis data on CVDs mortality. Based on these data, landscape pattern indexes were used to analyze the pattern-process-function and the mechanism. Results: During 1984–2017, the effects of UHI on CVDs increased, thereby increased the mortality by 28.8%. The affected areas gradually expand from the central area of the city and undergo three evolution stages; the highly affected areas are mainly distributed in central and southern regions, and patches increase in number. The areas and ratio of high-level patches also show an upward tendency, increasing dominance in the overall landscape. Patches of the overall landscape become more complicated in shape, whereas those of high-level ones become less complicated. Concentration degree of the overall landscape decreases gradually with the types of landscapes patches increasing, reaching a rather even space distribution. Conclusion: Increased temperatures exacerbated by UHI lead to increased CVD mortality. As cities expand, the effects of UHI on CVDs increase in terms of both intensity and areas, with the overall landscape in uneven distribution, high-level affected areas in point distribution, and low-level ones in large-area concentration.

Sign in / Sign up

Export Citation Format

Share Document