scholarly journals Comparative Study of Factors Contributing to Land Surface Temperature in High-Density Built Environments in Megacities Using Satellite Imagery

2021 ◽  
Vol 13 (24) ◽  
pp. 13706
Author(s):  
Frankie Fanjie Zeng ◽  
Jiajun Feng ◽  
Yuanzhi Zhang ◽  
Jin Yeu Tsou ◽  
Tengfei Xue ◽  
...  

In this study, the root sources contributing to the urban heat island (UHI) effect between megacities, such as Hong Kong and Shenzhen, were integrated and compared using satellite remote sensing data. Classification and multilayer perceptron regression tree (CARTMLP) algorithms were used to classify land use. The radiative transfer equation method was applied to retrieve the land surface temperatures (LSTs) in the study area. Multiple linear regression analysis was applied to determine the relationship between land-use types and UHIs. The experimental results show a large area of relatively high temperature dispersed within Shenzhen, and comparatively small areas highly centralized in Hong Kong, with the retrieved LST in Hong Kong lower than that in Shenzhen. In addition, the surface temperature of large complex buildings decorated with high-albedo materials in Hong Kong was higher than in Shenzhen (e.g., Hong Kong International Airport, 25.12 °C; Shenzhen Bao’an International Airport, 23.38 °C), with artificial heat being an important contributor to these differences. These results also imply that high-albedo materials are sufficient to alleviate high temperatures. These findings are integrated to propose an organic combination strategy for reducing UHI effects in urban areas in megacities worldwide, such as Hong Kong and Shenzhen in China.

2018 ◽  
Vol 55 (4C) ◽  
pp. 136
Author(s):  
Nguyen Huynh Anh Tuyet

Thermal remote sensing with its own concepts and potentials has presented a variety of applications in the atmosphere and land surface temperature (LST) variation detection. The objective of this study is to access the LST variation in the dry season of Binh Duong province for understanding the effect of land-use change on the microclimate conditions. The spectral radiation value was determined from gray-scale of thermal infrared images of Landsat 7 ETM+ and Landsat 8 OLI/TIRs, followed by the LST calculation. Results showed that the LST in dry season decreased approximately 1.5 °C over the past 15 years from 30.8 °C in the year 2002 to 29.3 °C in the year 2016, due to a large area of newly planted land of industrial trees changed into mature ones in 2016. The area, in which temperature increased corresponding to 16.6 % of the natural square, has developed rapidly with new industrial parks, urban areas, and vacant land areas. Therefore, the Government should have solutions to promote its positive side and mitigate its negative side by a suitable land-use structure in order to both develop the economic continuously and help to mitigate the climate change effects.


2019 ◽  
Vol 11 (19) ◽  
pp. 5492 ◽  
Author(s):  
Ullah ◽  
Tahir ◽  
Akbar ◽  
Hassan ◽  
Dewan ◽  
...  

Population growth and population inflow from other regions has caused urbanization which altered land use land cover (LULC) in the lower Himalayan regions of Pakistan. This LULC change increased the land surface temperature (LST) in the region. LULC and LST changes were assessed for the period of 1990–2017 using Landsat data and the support vector machine (SVM) method. A combined cellular automata and artificial neural network (CA-ANN) prediction model was used for simulation of LULC changes for the period of 2032 and 2047 using transition potential matrix obtained from the data years of 2002 and 2017. The accuracy of the CA-ANN model was validated using simulated and classified images of 2017 with correctness value of 70% using validation modules in QGIS. The thermal bands of Landsat images from the years 1990, 2002 and 2017 were used for LST derivation. LST acquired for this period was then modeled for 2032 and 2047 using urban indices (UI) and linear regression analysis. The SVM land cover classification results showed a 5.75% and 4.22% increase in built-up area and bare soil respectively, while vegetation declined by 9.88% during 1990–2017. The results of LST for LULC classes showed that the built-up area had the highest mean LST as compared to other classes. The future projection of LULC and LST showed that the built-up area may increase by 12.48% and 14.65% in 2032 and 2047, respectively, of the total LULC area which was ~11% in 2017. Similarly, the area with temperature above 30 °C could be 44.01% and 58.02% in 2032 and 2047, respectively, of the total study area which was 18.64% in 2017. This study identified major challenges for urban planners to mitigate the urban heat island (UHI) phenomenon. In order to address the UHI in the study area, an urban planner might focus on urban plantation and decentralization of urban areas.


2021 ◽  
Vol 10 (12) ◽  
pp. 809
Author(s):  
Jing Sun ◽  
Suwit Ongsomwang

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.


2018 ◽  
Vol 10 (3) ◽  
pp. 66-77
Author(s):  
Rosana Amaral Carrasco ◽  
Lucas Prado Osco ◽  
Rejane Ennes Cicerelli ◽  
Paulo Antônio Silva ◽  
Ana Paula Marques Ramos

Anthropogenic actions cause changes in the natural dynamics of the landscape, such as variations in climate and land use. Land Surface Temperature (LST) is one of the main physical parameters Recebido em: 27/08/2018Revisado em: 04/09/2018Aprovado em: 06/09/2018 67Colloquium Exactarum, v. 10, n.3,Jul-Set. 2018, p.66–77. DOI: 10.5747/ce.2018.v10.n3.e246of terrestrial surface processes. The importance of LST is increasingly recognized and there is a strong interest in developing methodologies for measuring LST using orbital platforms, such as the Landsat series. This work aims to verify if there was a change in the LST in the region of Pontal doParanapanema from the LST recorded by the Landsat series over the last 30 years. We adopted orbital images from Landsat5 TM and Landsat8 OLI satelliteto extract the LST value, and thenwe evaluated the LST variation at the studied area. A correlation was found between the LST variation and the type of land use and land cover. The urban areas, pasture, agriculture, vegetation and watercourses showed discrepancies in temperature when compared to each other. At Pontal, there were variations of 5 ° C of the average LST, between maximum and minimum temperatures. We concluded that temperature variations are associated with the dynamics of land use.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Diksha Rana ◽  
Maya Kumari ◽  
Rina Kumari

Urbanization is a human activity that changes the surface of the earth and degrades the surroundings of major cities all over the world. The problem is more acute in many developing cities with a high population and rapid economic growth. The present study focuses on the effect of land use/land cover (LULC) on the land surface temperature (LST) in Sonipat district, Haryana India. The LULC derived from multispectral satellite data of two periods, 2011 and 2021, indicated a significant increase in urban areas by (3%) and barren and fallow land by (7%), whereas crop land has decreased by (11%) and water bodies have remained the same, in comparison with 2011. The LST, derived from a thermal infrared sensor, showed an overall increase in LST by 5 °C from 2011 to 2021. The results also showed that there was a significant LST difference across the LULC units. Pearson’s correlation analysis results showed an inverse correlation between LST and NDVI across urban areas and other land use classes, whereas a positive correlation over water bodies were observed in the study area. Therefore, LST and its relationship with NDVI via LULC, is a key parameter to investigate the thermal glitches in an urban ecosystem. This can be adopted as a useful tool for analyzing the environmental influence on the ecological unit.


2019 ◽  
Vol 10 (3) ◽  
pp. 40-49
Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.


Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.


Author(s):  
F. Ike ◽  
I.C. Mbah ◽  
C.R. Otah ◽  
J. Babington ◽  
L. Chikwendu

The land surfaces of hot-humid tropical urban areas are exposed to significant levels of solar radiation. Increased heat gain adds to different land surface temperature profiles in cities, resulting in different thermal discomfort thresholds. Using multi-temporal (1986, 2001, and 2017) landsat data, this study examined the impact of land use change on urban temperature profiles in Umuahia, Nigeria. The findings revealed that over time, built-up regions grow in surface area and temperature at the expense of other land use. The transfer matrix, showed that approximately 59.88 percent of vegetation and 8.23 percent of bareland were respectively changed into built up during the course of 31 years. The highest annual mean temperature in built-up regions was 21.50°C in 1986, 22.20°C in 2001, and 26.01°C in 2017. Transect profiles across the landuses reveals that surface Temperature rises slowly around water/vegetation and quickly over built-up and bare land area. The study observed drastic changes in land cover with a corresponding increase in surface temperature for the period between 1986 and 2017 with consistent decrease in water bodies and bare land in the study area. Overall, the spatio-temporal distribution of surface temperature in densely built up areas was higher than the adjacent rural surroundings, which is evidence of Urban Heat Island. The impact of landuse change on urban surface temperature profiles could provide detailed data to planners and decision makers in evaluating thermal comfort levels and other risk considerations in the study area.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 762 ◽  
Author(s):  
Ahmed Ali Bindajam ◽  
Javed Mallick ◽  
Saeed AlQadhi ◽  
Chander Kumar Singh ◽  
Hoang Thi Hang

Land surface temperature (LST) can fully reflect the water–heat exchange cycle of the earth surface that is important for the study of environmental change. There is little research on LST in the semi-arid region of Abha-Khamis-Mushyet, which has a complex topography. The study used LST data, retrieved from ASTER data in semi-arid mountain areas and discussed its relationship with land use/land cover (LULC), topography and the normalized difference vegetation index (NDVI). The results showed that the LST was significantly influenced by altitude and corresponding LULC type. In the study area, during the summer season, extreme high-temperature zones were observed, possibly due to dense concrete surfaces. LST among different types of land use differed significantly, being the highest in exposed rocky areas and built-up land, and the lowest in dense vegetation. NDVI and LST spatial distributions showed opposite trends. The LST–NDVI feature space showed a unique ABC obtuse-angled triangle shape and showed an overall negative linear correlation. In brief, the LST could be retrieved well by the emissivity derived NDVI TES method, which relied on upwelling, downwelling, and transmittance. In addition, the LST of the semi-arid mountain areas was influenced by elevation, slope zenith angle, aspect and LULC, among which vegetation and elevation played a key role in the overall LST. This research provides a roadmap for land-use planning and environmental conservation in mountainous urban areas.


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