scholarly journals Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives

2018 ◽  
Vol 11 (1) ◽  
pp. 48 ◽  
Author(s):  
Decheng Zhou ◽  
Jingfeng Xiao ◽  
Stefania Bonafoni ◽  
Christian Berger ◽  
Kaveh Deilami ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Land Surface ◽  
Time Of Day ◽  
Thematic Mapper ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Annual Variations ◽  
Satellite Sensors ◽  
Urban Heat

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.

scholarly journals Effect of Land Cover Fractions on Changes in Surface Urban Heat Islands Using Landsat Time-Series Images

2019 ◽  
Vol 16 (6) ◽  
pp. 971 ◽  
Author(s):  
Tao Chen ◽  
Anchang Sun ◽  
Ruiqing Niu
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Impervious Surfaces ◽  
Heat Islands ◽  
Urban Heat ◽  
Surface Urban Heat Island

Man-made materials now cover a dominant proportion of urban areas, and such conditions not only change the absorption of solar radiation, but also the allocation of the solar radiation and cause the surface urban heat island effect, which is considered a serious problem associated with the deterioration of urban environments. Although numerous studies have been performed on surface urban heat islands, only a few have focused on the effect of land cover changes on surface urban heat islands over a long time period. Using six Landsat image scenes of the Metropolitan Development Area of Wuhan, our experiment (1) applied a mapping method for normalized land surface temperatures with three land cover fractions, which were impervious surfaces, non-chlorophyllous vegetation and soil and vegetation fractions, and (2) performed a fitting analysis of fierce change areas in the surface urban heat island intensity based on a time trajectory. Thematic thermal maps were drawn to analyze the distribution of and variations in the surface urban heat island in the study area. A Multiple Endmember Spectral Mixture Analysis was used to extract the land cover fraction information. Then, six ternary triangle contour graphics were drawn based on the land surface temperature and land cover fraction information. A time trajectory was created to summarize the changing characteristics of the surface urban heat island intensity. A fitting analysis was conducted for areas showing fierce changes in the urban heat intensity. Our results revealed that impervious surfaces had the largest impacts on surface urban heat island intensity, followed by the non-chlorophyllous vegetation and soil fraction. Moreover, the results indicated that the vegetation fraction can alleviate the occurrence of surface urban heat islands. These results reveal the impact of the land cover fractions on surface urban heat islands. Urban expansion generates impervious artificial objects that replace pervious natural objects, which causes an increase in land surface temperature and results in a surface urban heat island.

scholarly journals Combined Effects of the Surface Urban Heat Island with Landscape Composition and Configuration Based on Remote Sensing: A Case Study of Shanghai, China

2019 ◽  
Vol 11 (10) ◽  
pp. 2890 ◽  
Author(s):  
Hongyu Du ◽  
Jinquan Ai ◽  
Yongli Cai ◽  
Hong Jiang ◽  
Pudong Liu
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Land Surface ◽  
Surface Coverage ◽  
Agricultural Land ◽  
Thermal Environment ◽  
Landscape Patterns ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization leads to changes in surface coverage and landscape patterns. This results in urban heat island (UHI) effects and a series of negative ecological consequences. Considering this concern and taking Shanghai as an example, this paper concentrates on the effects of surface coverage and landscape patterns on urban land surface temperature (LST). The research is based on quantitative retrieval of remote sensing data with consideration of methods in multiple disciplines, including landscape ecology, geographic information systems, and statistical analysis. It concludes that, over time, the thermal environment of Shanghai is becoming critical. The average LST ranking of different surface coverage is as follows: Construction land (CL) > bare land (BL) > green land (GL) > agricultural land (AL) > water body (WB). LST varies significantly with the type of surface coverage. CL contributes the most to the UHI, while WB and GL have obvious mitigation effects on the UHI. The large area, low degree of landscape fragmentation, and complex outlines lead to low LST rankings for GL, WB, and AL and a high LST ranking for CL. The conclusions indicate that CL should be broken down by GL and WB into discrete pieces to effectively mitigate UHI effects. The research reveals UHI features and changes in Shanghai over the years and provides practical advice that can be used by urban planning authorities to mitigate UHI.

scholarly journals A study of urban heat island of Banda Aceh City, Indonesia based on land use/cover changes and land surface temperature

2019 ◽  
Vol 8 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Ashfa Achmad ◽  
Laina Hilma Sari ◽  
Ichwana Ramli
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Planning Process ◽  
Sustainable Urban Development ◽  
Heat Island ◽  
Urban Heat ◽  
Banda Aceh

This article described the spatial and temporal of land surface temperature (LST) patterns in Banda Aceh City, Indonesia, in the context of urban heat island (UHI) phenomenon. Landsat imaginary in 1998 and 2018 was used in this study, which represents the conditions before and after the tsunami. Geographic Information System (GIS) and Remote Sensing (RS) technique were used for data analysis. The 1998 and 2018 LUC maps were derived from remote sensing satellite images using a supervised classification method (maximum likelihood). Both LUC maps contained five categories, namely built-up area, vegetation, water body, vacant land, and wet land. The 1998 LUC map had a kappa coefficient 0.91, while the 2018 LUC map had 0.84. It was found that the built-up area increased by 100%, while the vegetation category fell 50%. The overall mean LST in the study area increased 5.90C between 1998 and 2018, with the highest mean increase in the built-up area category. The study recommends that LST should be taken into consideration in urban planning process to realize sustainable urban development. It also emphasizes the importance of optimizing the availability of green open space to reduce UHI effects and helps in improving the quality of the urban environment. 

scholarly journals Surface Urban Heat Island Assessment of a Cold Desert City: A Case Study over the Isfahan Metropolitan Area of Iran

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1368
Author(s):  
Alireza Karimi ◽  
Pir Mohammad ◽  
Sadaf Gachkar ◽  
Darya Gachkar ◽  
Antonio García-Martínez ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Metropolitan Area ◽  
Negative Correlation ◽  
Land Surface ◽  
Vegetation Index ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Cold Desert ◽  
Urban Heat ◽  
Surface Urban Heat Island

This study investigates the diurnal, seasonal, monthly and temporal variation of land surface temperature (LST) and surface urban heat island intensity (SUHII) over the Isfahan metropolitan area, Iran, during 2003–2019 using MODIS data. It also examines the driving factors of SUHII like cropland, built-up areas (BI), the urban–rural difference in enhanced vegetation index (ΔEVI), evapotranspiration (ΔET), and white sky albedo (ΔWSA). The results reveal the presence of urban cool islands during the daytime and urban heat islands at night. The maximum SUHII was observed at 22:30 pm, while the minimum was at 10:30 am. The summer months (June to September) show higher SUHII compared to the winter months (February to May). The daytime SUHII demonstrates a robust positive correlation with cropland and ΔWSA, and a negative correlation with ΔET, ΔEVI, and BI. The nighttime SUHII displays a negative correlation with ΔET and ΔEVI.

scholarly journals Research on the Spatial Effect of Urban Construction on Heat Island Effect in Shanghai Based on Remote Sensing Data

2019 ◽  
Author(s):  
Shuo Zhang ◽  
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Land Surface ◽  
Water Area ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Island Effect ◽  
Urban Construction ◽  
New Type ◽  
Urban Heat

Since the twentieth Century,global urbanization process is constantly accelerating,while the landscape pattern dominated by vegetation was gradually replaced by the landscape pattern dominated by artificial buildings.The change of climate and temperature caused by the expansion of urban construction land and the population aggregation,has aroused widespread concern.Under the background of national new type urbanization,improving the urban environment is the inevitable path to the new type urbanization. Urban heat island effect is the most prominent feature of human activities impact on temperature,and it has many effects on environment,economy,society,health and so on. Among the existing researches related to urban heat island effect,the influence of urbanization on it has not been paid enough attention.Therefore, the research on the effect of urban construction on the heat island effect is incompletable,and the method is limited to the quantitative analysis as the spatial analysis is insufficient. Based on the existing research,while under the background of urban planning major,taking Shanghai as a typical case, this paper concentrates on the urban heat island effect under the influence of Shanghai urban construction. First of all,this paper takes the Landsat-7 ETM+ remote sensing image data of Shanghai in 01/08/2000,28/07/2010 and 28/07/2016 as the basic research data.ENVI software is used to retrieve land surface temperature on the thermal infrared band.Then this paper divides the heat island effect level,analyses the spatiotemporal distribution of land surface temperature in different years in Shanghai,and summarizes the evolution characteristics of urban heat island effect, analyzing the spatial impact of urban construction related factors such as urban scale, spatial structure and land use. Analysis shows that city construction land expansion will aggravate the urban heat island effect.The increment of built construction in the city,the size of the resident population,as well as the population density have significant correlation with urban heat island effect,but the spatial distribution of population density and spatial distribution of heat island effect has no significant correlation.In various types of landuse,residential,industrial and mining,warehousing, commercial services,and transportation land can significantly aggravate the heat island effect, land types like green land, water area and farmland,etc can produce urban cold island effect in some individual area.At the same time,the location, area and shape of the green space and water area have an effect on the distance of reducing the heat island effect.

scholarly journals Identification of Urban Heat Islands &Its Relationship withVegetation Cover: A Case Study of Colombo & Gampaha Districts in Sri Lanka

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
G.M.T.S. Fernando
Keyword(s):  
High Temperature ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Urban Heat

Global Warming is a major environmental problem that all kind of organisms has been affected at present. Urban Heat Island (UHI) is one of primary impacts of Global Warming. UHI is a phenomenon that the temperature of urban area is higher than surrounding rural areas or suburban areas. This increasing trend of temperature in urban areas affects many environmental entities such as air quality, water resources, habitats behaviors and climate changes. The most remarkable incident that relate with UHI is the difference of thermal properties of the surfaces. Many countries experience the consequences of Urban Heat Islands in many aspects such as economic, health, social and environmental affects. Thus to mitigate such impacts of UHI, it is very important to identify the main reasons behind this. In this paper UHIs in Colombo, Gampaha Districts and the relationship between UHI and vegetation cover were analyzed based on Landsat 8, 30m resolution data. Land Surface Temperature was derived from Landsat thermal Infrared band through several equations of United State Geological Survay (USGS) guidelines using Arc GIS 10. Conversion of Digital Number (DN) values to Top of Atmosphere (TOA) Radiance, Conversion of TOA Radiance to Satellite Brightness temperature and final calculation of Land Surface Temperature considering land surface emissivity are the steps that had been done for the analysis. Vegetation cover was derived by using vegetation index with the Red and Near Infra Red bands. The result shows that the land high surface temperature directly relates with the urbanized regions where vegetation cover is very less. High temperature difference could be identified that cause to arise the urban heat island effects in Colombo & Gampaha districts. There is a strong linearly negative correlation with correlation coefficient value of -0.742 between land surface temperature and vegetation cover. 78.8 km2 (including water) of total area had been identified as NDVI value less than 0.1. And extent of high temperature area was 74.12 km2 where temperature more than 27oC at 10.22am. The area in temperature range of 25-27 was 464.95km2 and area in NDVI value range 0.1-0.2 was 333.04 km2. 1471.1 km2 was identified as NDVI value between 0.3-0.4 and the area at low temperature was 1529 km2where temperature less than 25oC. According to this results, high temperature at non-vegetated areas and low temperature at vegetated areas could be noted very clearly. This is probably due to the ecological function of vegetation that lay down the surface temperature from high evapotranspiration. Vegetated areas are mostly sensed with surface temperature.Thus research output can be useful for policy-makers and planners of development projects such as Western province Megapolis project as well as for general public to understand the urban heat island effects and importance of vegetation cover to mitigate such impacts.

scholarly journals Downscale MODIS Land Surface Temperature Based on Three Different Models to Analyze Surface Urban Heat Island: A Case Study of Hangzhou

2020 ◽  
Vol 12 (13) ◽  
pp. 2134 ◽  
Author(s):  
Rui Wang ◽  
Weijun Gao ◽  
Wangchongyu Peng
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Heat Island ◽  
Time Dimension ◽  
Urban Heat ◽  
Surface Urban Heat Island

Remote sensing technology plays an increasingly important role in land surface temperature (LST) research. However, various remote sensing data have spatial–temporal scales contradictions. In order to address this problem in LST research, the current study downscaled LST based on three different models (multiple linear regression (MLR), thermal sharpen (TsHARP) and random forest (RF)) from 1 km to 100 m to analyze surface urban heat island (SUHI) in daytime (10:30 a.m.) and nighttime (10:30 p.m.) of four seasons, based on Moderate Resolution Imaging Spectroradiometer (MODIS)/LST products and Landsat 8 Operational Land Imager (OLI). This research used an area (25 × 25 km) of Hangzhou with high spatial heterogeneity as the study area. R2 and RMSE were introduced to evaluate the conversion accuracy. Finally, we compared with similarly retrieved LST to verify the feasibility of the method. The results indicated the following. (1) The RF model was the most suitable to downscale MODIS/LST. The MLR model and the TsHARP model were not applicable for downscaling studies in highly heterogeneous regions. (2) From the time dimension, the prediction precision in summer and winter was clearly higher than that in spring and autumn, and that at night was generally higher than during the day. (3) The SUHI range at night was smaller than that during the day, and was mainly concentrated in the urban center. The SUHI of the research region was strongest in autumn and weakest in winter. (4) The validation results of the error distribution histogram indicated that the MODIS/LST downscaling method based on the RF model is feasible in highly heterogeneous regions.

scholarly journals Monitoring the Detailed Dynamics of Regional Thermal Environment in a Developing Urban Agglomeration

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1197 ◽  
Author(s):  
Yue Liu ◽  
Hui Li ◽  
Peng Gao ◽  
Cheng Zhong
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Thermal Environment ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Inner Cities ◽  
Urban Heat ◽  
Moderate Resolution Imaging Spectroradiometer

Many studies have revealed the characteristics and spatial-temporal dynamics of the thermal environment in specific cities or urban agglomerations (UA), as well as the associated determining factors. However, few studies focus on the changing relationships (the difference, distance, interaction, etc.) among inner cities’ heat islands in a UA, which represent not only the detailed dynamics of regional thermal environment (RTE), but also the changing competition and cooperation among cities in a developing UA. In this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products to map and analyze the detailed dynamics of the Beijing-Tianjin-Hebei (BTH) UA thermal environment. From 2001 to 2015, the mean surface urban heat island intensity (SUHII) of the BTH increased significantly, and the surface urban heat islands (SUHIs) in the southern BTH have rapidly increased, expanded and connected, eventually forming a large heat islands agglomeration. According to correlation analysis, urban sprawl probably led to the expansion and enhance of SUHIs in the south plain, while the forest has significantly alleviated urban heat island effect in northern mountains. The results expose the detailed evolution process of BTH thermal environment, and the changing relationships among the inner cities. In a developing UA, mitigation solutions (e.g., ecological corridors or controlling energy consumption) are in demand to stop the formation of a great heat region.

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