Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model
Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In...
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description | Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB) model was developed to uncover the effect of AHF on land surface temperature (LST) and surface anthropogenic heat island (SAHI) intensity. For this purpose, satellite imagery along with climatic and meteorological data from 1985 to 2019 were studied for six selected megacities: Los Angeles, Atlanta, Athens, Istanbul, Tehran, and Beijing. First, LST and the fraction of different surface covers were calculated by using a single-channel algorithm and a normalized spectral mixture analysis model, respectively. In the second step, impervious surface cover (ISC) and the urban main boundary area (UMBA) of each city were extracted based on the biophysical composite index and city clustering algorithm, respectively. In the third step, anthropogenic LST (ALST) was modeled using a triple-SEB model. In the fourth step, the ALST and UMBA were used together to model SAHI intensity at different dates. Finally, the relationship between the estimated ALST and ISC, as well as between SAHI and ISC, was examined. Results show that the average value of estimated ALST for the megacities increased from 2.02, 0.55, 0.61, 0.64, 0.58, and 0.72 to 2.99, 1.73, 1.66, 1.19, 2.32, and 2.76 °C, respectively. The coefficient of determination between the mean value of ISC and the estimated ALST for all megacities yielded 0.8, which was higher than that between ISC and satellite-derived LST. Moreover, the SAHI intensity for these megacities was found to have increased to 0.73, 0.92, 0.95, 0.98, 0.95 and 1.32 °C, respectively, which can be predicted by ISC with a coefficient of determination of 0.78, 0.79, 0.79, 0.73, 0.71 and 0.52, respectively. This suggests that the triple-SEB model proposed by this study allowed for independent modeling of AHF's influence on SUHI and a better determination of the effect of ISC on LST and SUHI intensity. This approach facilitated comparative analysis of LST and SAHI for a city at different times as well as SAHIs in different cities with different geographic and climate settings.
•A novel method based on triple-source energy balance model developed for LST•LST d |
doi_str_mv | 10.1016/j.rse.2020.111751 |
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•A novel method based on triple-source energy balance model developed for LST•LST due to anthropogenic heat flux used to model surface anthropogenic heat island•SAHI and the effect of ISC on SUHI in five global megacities were investigated.•Better determination and modeling of the effect of ISC on LST and SUHI intensity•New method for comparative analysis of LST and SAHI at different times and cities</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2020.111751</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Algorithms ; Anthropogenic factors ; Anthropogenic heat flux ; Clustering ; Comparative analysis ; Energy balance ; Energy consumption ; Heat ; Heat flux ; Heat islands ; Human influences ; Impervious surface coverage ; Islands ; Land surface temperature ; Land surface temperature due to anthropogenic heat flux ; Megacities ; Megacity ; Meteorological data ; Modelling ; Population growth ; Satellite imagery ; Surface anthropogenic heat island ; Surface energy ; Surface energy balance ; Surface properties ; Surface temperature ; Temperature effects ; Triple-source surface energy balance model ; Urban areas ; Urban heat islands</subject><ispartof>Remote sensing of environment, 2020-06, Vol.242, p.111751, Article 111751</ispartof><rights>2020 Elsevier Inc.</rights><rights>Copyright Elsevier BV Jun 1, 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c325t-414b261c55cba67283d92a10fecd74e6bde2cae3fa966d3f6df626eb6ba1f3873</citedby><cites>FETCH-LOGICAL-c325t-414b261c55cba67283d92a10fecd74e6bde2cae3fa966d3f6df626eb6ba1f3873</cites><orcidid>0000-0003-0391-6420 ; 0000-0002-3060-9162 ; 0000-0002-2498-0934 ; 0000-0003-0335-3795</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.rse.2020.111751$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27911,27912,45982</link.rule.ids></links><search><creatorcontrib>Firozjaei, Mohammad Karimi</creatorcontrib><creatorcontrib>Weng, Qihao</creatorcontrib><creatorcontrib>Zhao, Chunhong</creatorcontrib><creatorcontrib>Kiavarz, Majid</creatorcontrib><creatorcontrib>Lu, Linlin</creatorcontrib><creatorcontrib>Alavipanah, Seyed Kazem</creatorcontrib><title>Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model</title><title>Remote sensing of environment</title><description>Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB) model was developed to uncover the effect of AHF on land surface temperature (LST) and surface anthropogenic heat island (SAHI) intensity. For this purpose, satellite imagery along with climatic and meteorological data from 1985 to 2019 were studied for six selected megacities: Los Angeles, Atlanta, Athens, Istanbul, Tehran, and Beijing. First, LST and the fraction of different surface covers were calculated by using a single-channel algorithm and a normalized spectral mixture analysis model, respectively. In the second step, impervious surface cover (ISC) and the urban main boundary area (UMBA) of each city were extracted based on the biophysical composite index and city clustering algorithm, respectively. In the third step, anthropogenic LST (ALST) was modeled using a triple-SEB model. In the fourth step, the ALST and UMBA were used together to model SAHI intensity at different dates. Finally, the relationship between the estimated ALST and ISC, as well as between SAHI and ISC, was examined. Results show that the average value of estimated ALST for the megacities increased from 2.02, 0.55, 0.61, 0.64, 0.58, and 0.72 to 2.99, 1.73, 1.66, 1.19, 2.32, and 2.76 °C, respectively. The coefficient of determination between the mean value of ISC and the estimated ALST for all megacities yielded 0.8, which was higher than that between ISC and satellite-derived LST. Moreover, the SAHI intensity for these megacities was found to have increased to 0.73, 0.92, 0.95, 0.98, 0.95 and 1.32 °C, respectively, which can be predicted by ISC with a coefficient of determination of 0.78, 0.79, 0.79, 0.73, 0.71 and 0.52, respectively. This suggests that the triple-SEB model proposed by this study allowed for independent modeling of AHF's influence on SUHI and a better determination of the effect of ISC on LST and SUHI intensity. This approach facilitated comparative analysis of LST and SAHI for a city at different times as well as SAHIs in different cities with different geographic and climate settings.
•A novel method based on triple-source energy balance model developed for LST•LST due to anthropogenic heat flux used to model surface anthropogenic heat island•SAHI and the effect of ISC on SUHI in five global megacities were investigated.•Better determination and modeling of the effect of ISC on LST and SUHI intensity•New method for comparative analysis of LST and SAHI at different times and cities</description><subject>Algorithms</subject><subject>Anthropogenic factors</subject><subject>Anthropogenic heat flux</subject><subject>Clustering</subject><subject>Comparative analysis</subject><subject>Energy balance</subject><subject>Energy consumption</subject><subject>Heat</subject><subject>Heat flux</subject><subject>Heat islands</subject><subject>Human influences</subject><subject>Impervious surface coverage</subject><subject>Islands</subject><subject>Land surface temperature</subject><subject>Land surface temperature due to anthropogenic heat flux</subject><subject>Megacities</subject><subject>Megacity</subject><subject>Meteorological data</subject><subject>Modelling</subject><subject>Population growth</subject><subject>Satellite imagery</subject><subject>Surface anthropogenic heat island</subject><subject>Surface energy</subject><subject>Surface energy balance</subject><subject>Surface properties</subject><subject>Surface temperature</subject><subject>Temperature effects</subject><subject>Triple-source surface energy balance model</subject><subject>Urban areas</subject><subject>Urban heat islands</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9UMtOwzAQtBBIlMIHcLPEOcV2HDuBU1XxkipxAM6WY29aR21SvCmif4-r9MxpNauZ2dkh5JazGWdc3beziDATTCTMuS74GZnwUlcZ00yekwljucykKPQluUJsGeNFqfmEHD72sbEOqO2Gdex3_Qq64Oga7EADbmznkYaOYvilW1hZF4YA-EDnHbWIgLiFbqC1RfC0Tzs6xLDbQIb9PiZTPJlDB3F1SLxkmOC297C5JheN3SDcnOaUfD0_fS5es-X7y9tivsxcLoohk1zWQnFXFK62Sosy95WwnDXgvJagag_CWcgbWynl80b5RgkFtaotb_JS51NyN_ruYv-9BxxMm8J16aQRUjJZVlrnicVHlos9YoTG7GLY2ngwnJljw6Y1qWFzbNiMDSfN46iBFP8nQDToAqQHfYjgBuP78I_6DzvfhdY</recordid><startdate>20200601</startdate><enddate>20200601</enddate><creator>Firozjaei, Mohammad Karimi</creator><creator>Weng, Qihao</creator><creator>Zhao, Chunhong</creator><creator>Kiavarz, Majid</creator><creator>Lu, Linlin</creator><creator>Alavipanah, Seyed Kazem</creator><general>Elsevier Inc</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TG</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0003-0391-6420</orcidid><orcidid>https://orcid.org/0000-0002-3060-9162</orcidid><orcidid>https://orcid.org/0000-0002-2498-0934</orcidid><orcidid>https://orcid.org/0000-0003-0335-3795</orcidid></search><sort><creationdate>20200601</creationdate><title>Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model</title><author>Firozjaei, Mohammad Karimi ; Weng, Qihao ; Zhao, Chunhong ; Kiavarz, Majid ; Lu, Linlin ; Alavipanah, Seyed Kazem</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c325t-414b261c55cba67283d92a10fecd74e6bde2cae3fa966d3f6df626eb6ba1f3873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Anthropogenic factors</topic><topic>Anthropogenic heat flux</topic><topic>Clustering</topic><topic>Comparative analysis</topic><topic>Energy balance</topic><topic>Energy consumption</topic><topic>Heat</topic><topic>Heat flux</topic><topic>Heat islands</topic><topic>Human influences</topic><topic>Impervious surface coverage</topic><topic>Islands</topic><topic>Land surface temperature</topic><topic>Land surface temperature due to anthropogenic heat flux</topic><topic>Megacities</topic><topic>Megacity</topic><topic>Meteorological data</topic><topic>Modelling</topic><topic>Population growth</topic><topic>Satellite imagery</topic><topic>Surface anthropogenic heat island</topic><topic>Surface energy</topic><topic>Surface energy balance</topic><topic>Surface properties</topic><topic>Surface temperature</topic><topic>Temperature effects</topic><topic>Triple-source surface energy balance model</topic><topic>Urban areas</topic><topic>Urban heat islands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Firozjaei, Mohammad Karimi</creatorcontrib><creatorcontrib>Weng, Qihao</creatorcontrib><creatorcontrib>Zhao, Chunhong</creatorcontrib><creatorcontrib>Kiavarz, Majid</creatorcontrib><creatorcontrib>Lu, Linlin</creatorcontrib><creatorcontrib>Alavipanah, Seyed Kazem</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Firozjaei, Mohammad Karimi</au><au>Weng, Qihao</au><au>Zhao, Chunhong</au><au>Kiavarz, Majid</au><au>Lu, Linlin</au><au>Alavipanah, Seyed Kazem</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model</atitle><jtitle>Remote sensing of environment</jtitle><date>2020-06-01</date><risdate>2020</risdate><volume>242</volume><spage>111751</spage><pages>111751-</pages><artnum>111751</artnum><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB) model was developed to uncover the effect of AHF on land surface temperature (LST) and surface anthropogenic heat island (SAHI) intensity. For this purpose, satellite imagery along with climatic and meteorological data from 1985 to 2019 were studied for six selected megacities: Los Angeles, Atlanta, Athens, Istanbul, Tehran, and Beijing. First, LST and the fraction of different surface covers were calculated by using a single-channel algorithm and a normalized spectral mixture analysis model, respectively. In the second step, impervious surface cover (ISC) and the urban main boundary area (UMBA) of each city were extracted based on the biophysical composite index and city clustering algorithm, respectively. In the third step, anthropogenic LST (ALST) was modeled using a triple-SEB model. In the fourth step, the ALST and UMBA were used together to model SAHI intensity at different dates. Finally, the relationship between the estimated ALST and ISC, as well as between SAHI and ISC, was examined. Results show that the average value of estimated ALST for the megacities increased from 2.02, 0.55, 0.61, 0.64, 0.58, and 0.72 to 2.99, 1.73, 1.66, 1.19, 2.32, and 2.76 °C, respectively. The coefficient of determination between the mean value of ISC and the estimated ALST for all megacities yielded 0.8, which was higher than that between ISC and satellite-derived LST. Moreover, the SAHI intensity for these megacities was found to have increased to 0.73, 0.92, 0.95, 0.98, 0.95 and 1.32 °C, respectively, which can be predicted by ISC with a coefficient of determination of 0.78, 0.79, 0.79, 0.73, 0.71 and 0.52, respectively. This suggests that the triple-SEB model proposed by this study allowed for independent modeling of AHF's influence on SUHI and a better determination of the effect of ISC on LST and SUHI intensity. This approach facilitated comparative analysis of LST and SAHI for a city at different times as well as SAHIs in different cities with different geographic and climate settings.
•A novel method based on triple-source energy balance model developed for LST•LST due to anthropogenic heat flux used to model surface anthropogenic heat island•SAHI and the effect of ISC on SUHI in five global megacities were investigated.•Better determination and modeling of the effect of ISC on LST and SUHI intensity•New method for comparative analysis of LST and SAHI at different times and cities</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2020.111751</doi><orcidid>https://orcid.org/0000-0003-0391-6420</orcidid><orcidid>https://orcid.org/0000-0002-3060-9162</orcidid><orcidid>https://orcid.org/0000-0002-2498-0934</orcidid><orcidid>https://orcid.org/0000-0003-0335-3795</orcidid></addata></record> |
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subjects | Algorithms Anthropogenic factors Anthropogenic heat flux Clustering Comparative analysis Energy balance Energy consumption Heat Heat flux Heat islands Human influences Impervious surface coverage Islands Land surface temperature Land surface temperature due to anthropogenic heat flux Megacities Megacity Meteorological data Modelling Population growth Satellite imagery Surface anthropogenic heat island Surface energy Surface energy balance Surface properties Surface temperature Temperature effects Triple-source surface energy balance model Urban areas Urban heat islands |
title | Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model |
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