{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T10:40:58Z","timestamp":1776163258703,"version":"3.50.1"},"reference-count":95,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,7]],"date-time":"2021-11-07T00:00:00Z","timestamp":1636243200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mapping and monitoring the spatio-temporal variations of the Surface Urban Heat Island (SUHI) and thermal comfort of metropolitan areas are vital to obtaining the necessary information about the environmental conditions and promoting sustainable cities. As the most populated city of Iran, Tehran has experienced considerable population growth and Land Cover\/Land Use (LULC) changes in the last decades, which resulted in several adverse environmental issues. In this study, 68 Landsat-5 and Landsat-8 images, collected from the Google Earth Engine (GEE), were employed to map and monitor the spatio-temporal variations of LULC, SUHI, and thermal comfort of Tehran between 1989 and 2019. In this regard, planar fitting and Gaussian Surface Model (GSM) approaches were employed to map SUHIs and derive the relevant statistical values. Likewise, the thermal comfort of the city was investigated by the Urban Thermal Field Variance Index (UTFVI). The results indicated that the SUHI intensities have generally increased throughout the city by an average value of about 2.02 \u00b0C in the past three decades. The most common reasons for this unfavorable increase were the loss of vegetation cover (i.e., 34.72%) and massive urban expansions (i.e., 53.33%). Additionally, the intra-annual investigations in 2019 revealed that summer and winter, with respectively 8.28 \u00b0C and 4.37 \u00b0C, had the highest and lowest SUHI magnitudes. Furthermore, the decadal UTFVI maps revealed notable thermal comfort degradation of Tehran, by which in 2019, approximately 52.35% of the city was identified as the region with the worst environmental condition, of which 59.94% was related to human residents. Additionally, the relationships between various air pollutants and SUHI intensities were appraised, suggesting positive relationships (i.e., ranging between 0.23 and 0.43) that can be used for establishing possible two-way mitigations strategies. This study provided analyses of spatio-temporal monitoring of SUHI and UTFVI throughout Tehran that urban managers and policymakers can consider for adaption and sustainable development.<\/jats:p>","DOI":"10.3390\/rs13214469","type":"journal-article","created":{"date-parts":[[2021,11,7]],"date-time":"2021-11-07T20:42:54Z","timestamp":1636317774000},"page":"4469","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Spatial and Temporal Analysis of Surface Urban Heat Island and Thermal Comfort Using Landsat Satellite Images between 1989 and 2019: A Case Study in Tehran"],"prefix":"10.3390","volume":"13","author":[{"given":"Faezeh","family":"Najafzadeh","sequence":"first","affiliation":[{"name":"Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3329-5063","authenticated-orcid":false,"given":"Ali","family":"Mohammadzadeh","sequence":"additional","affiliation":[{"name":"Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8406-683X","authenticated-orcid":false,"given":"Arsalan","family":"Ghorbanian","sequence":"additional","affiliation":[{"name":"Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0961-9497","authenticated-orcid":false,"given":"Sadegh","family":"Jamali","sequence":"additional","affiliation":[{"name":"Department of Technology and Society, Faculty of Engineering, Lund University, P.O. Box 118, 221 00 Lund, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1080\/2150704X.2017.1312025","article-title":"Derivation of the characteristics of the Surface Urban Heat Island in the Greater Toronto area using thermal infrared remote sensing","volume":"8","author":"Ye","year":"2017","journal-title":"Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101518","DOI":"10.1016\/j.scs.2019.101518","article-title":"Spatial patterns and driving factors of surface urban heat island intensity: A comparative study for two agriculture-dominated regions in China and the USA","volume":"48","author":"Li","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.jenvman.2017.10.002","article-title":"Analysis and modelling of surface Urban Heat Island in 20 Canadian cities under climate and land-cover change","volume":"206","author":"Gaur","year":"2018","journal-title":"J. Environ. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"54023","DOI":"10.1088\/1748-9326\/11\/5\/054023","article-title":"Urban heat island impacts on plant phenology: Intra-urban variability and response to land cover","volume":"11","author":"Zipper","year":"2016","journal-title":"Environ. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1111\/j.1752-1688.2004.tb01612.x","article-title":"Predicting influences of urban development on thermal habitat in a warm water stream","volume":"40","author":"Krause","year":"2004","journal-title":"JAWRA J. Am. Water Resour. Assoc."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1016\/j.uclim.2017.12.001","article-title":"A modeling study of the sensitivity of urban heat islands to precipitation at climate scales","volume":"24","author":"Gu","year":"2018","journal-title":"Urban Clim."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.scitotenv.2018.04.254","article-title":"Interaction between urban heat island and urban pollution island during summer in Berlin","volume":"636","author":"Li","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1175\/JAMC-D-17-0243.1","article-title":"Use of cool roofs and vegetation to mitigate urban heat and improve human thermal stress in Melbourne, Australia","volume":"57","author":"Jacobs","year":"2018","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.enbuild.2014.09.052","article-title":"On the impact of urban heat island and global warming on the power demand and electricity consumption of buildings\u2014A review","volume":"98","author":"Santamouris","year":"2015","journal-title":"Energy Build."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1080\/10962247.2017.1325417","article-title":"Urban heat island (UHI) influence on secondary pollutant formation in a tropical humid environment","volume":"67","author":"Swamy","year":"2017","journal-title":"J. Air Waste Manag. Assoc."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sarif, M., Rimal, B., and Stork, N.E. (2020). Assessment of Changes in Land Use\/Land Cover and Land Surface Temperatures and Their Impact on Surface Urban Heat Island Phenomena in the Kathmandu Valley (1988\u20132018). ISPRS Int. J. Geo Inf., 9.","DOI":"10.3390\/ijgi9120726"},{"key":"ref_12","unstructured":"(2018). 2018 Revision of World Urbanization Prospects, UN DESA."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.isprsjprs.2017.09.008","article-title":"Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987\u20132015)","volume":"133","author":"Estoque","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"30808","DOI":"10.1007\/s11356-019-06273-w","article-title":"Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China","volume":"26","author":"Gui","year":"2019","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"102861","DOI":"10.1016\/j.scs.2021.102861","article-title":"Urban Heat Island associated with Land Use\/Land Cover and climate variations in Melbourne, Australia","volume":"69","author":"Harmay","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"102926","DOI":"10.1016\/j.scs.2021.102926","article-title":"Surface urban heat island intensity in five major cities of Bangladesh: Patterns, drivers and trends","volume":"71","author":"Dewan","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8820338","DOI":"10.1155\/2020\/8820338","article-title":"Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China","volume":"2020","author":"Han","year":"2020","journal-title":"Complexity"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2003.11.005","article-title":"Estimation of land surface temperature\u2013vegetation abundance relationship for urban heat island studies","volume":"89","author":"Weng","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.ecolind.2018.03.052","article-title":"Monitoring and forecasting heat island intensity through multi-temporal image analysis and cellular automata-Markov chain modelling: A case of Babol city, Iran","volume":"91","author":"Firozjaei","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., and Sobrino, J.A. (2019). Satellite remote sensing of surface urban heat islands: Progress, challenges, and perspectives. Remote Sens., 11.","DOI":"10.3390\/rs11010048"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1080\/15481603.2018.1548080","article-title":"Statistical analysis of surface urban heat island intensity variations: A case study of Babol city, Iran","volume":"56","author":"Weng","year":"2019","journal-title":"GIScience Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1080\/15481603.2020.1843869","article-title":"Use of Local Climate Zones to investigate surface urban heat islands in Texas","volume":"57","author":"Zhao","year":"2020","journal-title":"GIScience Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1080\/22797254.2018.1474494","article-title":"Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy","volume":"51","author":"Guha","year":"2018","journal-title":"Eur. J. Remote Sens."},{"key":"ref_24","first-page":"23","article-title":"Ecological evaluation of urban heat island in Chicago City, USA","volume":"4","author":"Alfraihat","year":"2016","journal-title":"J. Atmos. Pollut."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"102542","DOI":"10.1016\/j.scs.2020.102542","article-title":"Prediction of seasonal urban thermal field variance index using machine learning algorithms in Cumilla, Bangladesh","volume":"64","author":"Kafy","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.scs.2017.02.018","article-title":"Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate","volume":"32","author":"Singh","year":"2017","journal-title":"Sustain. Cities Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.scs.2016.03.009","article-title":"Assessment of urban heat island based on the relationship between land surface temperature and land use\/land cover in Tehran","volume":"23","author":"Bokaie","year":"2016","journal-title":"Sustain. Cities Soc."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Rousta, I., Sarif, M.O., Gupta, R.D., Olafsson, H., Ranagalage, M., Murayama, Y., Zhang, H., and Mushore, T.D. (2018). Spatiotemporal analysis of land use\/land cover and its effects on surface urban heat island using Landsat data: A case study of Metropolitan City Tehran (1988\u20132018). Sustainability, 10.","DOI":"10.3390\/su10124433"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"120529","DOI":"10.1016\/j.jclepro.2020.120529","article-title":"Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature","volume":"257","author":"Liu","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"101846","DOI":"10.1016\/j.scs.2019.101846","article-title":"Assessment of urbanisation and urban heat island intensities using landsat imageries during 2000\u20132018 over a sub-tropical Indian City","volume":"52","author":"Sultana","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1016\/j.scs.2018.12.005","article-title":"Evaluating the spatial distribution and the intensity of urban heat island using remote sensing, case study of Isfahan city in Iran","volume":"45","author":"Nasrabadi","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_32","first-page":"104","article-title":"The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data","volume":"64","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"7400","DOI":"10.1080\/01431161.2020.1759841","article-title":"Modelling the intensity of surface urban heat island and predicting the emerging patterns: Landsat multi-temporal images and Tehran as case study","volume":"41","author":"Hamzeh","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1007\/s12524-019-00966-y","article-title":"The effect of rapid population growth on urban expansion and destruction of green space in Tehran from 1972 to 2017","volume":"47","author":"Sharifi","year":"2019","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"101448","DOI":"10.1016\/j.scs.2019.101448","article-title":"Mitigating the urban heat island in a residential area in Tehran: Investigating the role of vegetation, materials, and orientation of buildings","volume":"46","author":"Farhadi","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.atmosres.2019.03.038","article-title":"Assessment of the urban heat island in the city of Tehran using reliability methods","volume":"225","author":"Jahangir","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1080\/12265934.2018.1548942","article-title":"Seasonal monitoring of urban heat island using multi-temporal Landsat and MODIS images in Tehran","volume":"23","author":"Bokaie","year":"2019","journal-title":"Int. J. Urban Sci."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Haashemi, S., Weng, Q., Darvishi, A., and Alavipanah, S.K. (2016). Seasonal variations of the surface urban heat island in a semi-arid city. Remote Sens., 8.","DOI":"10.3390\/rs8040352"},{"key":"ref_39","first-page":"1","article-title":"Analysis of Spatial-Temporal Structure of the Urban Heat Island in Tehran through Remote Sensing and Geographical Information System","volume":"1","author":"Sadeghinia","year":"2013","journal-title":"J. Geogr. Environ. Hazards"},{"key":"ref_40","first-page":"113","article-title":"Investigation of changes in surface urban heat-island (SUHI) in day and night using multi-temporal MODIS sensor data products (Case Study: Tehran metropolitan)","volume":"19","author":"AlaviPanah","year":"2019","journal-title":"J. Appl. Res. Geogr. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2463","DOI":"10.1007\/s00704-018-2735-7","article-title":"Spatiotemporal characteristics of urban land surface temperature and UHI formation: A case study of Tehran, Iran","volume":"137","author":"Moghbel","year":"2019","journal-title":"Theor. Appl. Climatol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Shi, H., Xian, G., Auch, R., Gallo, K., and Zhou, Q. (2021). Urban Heat Island and Its Regional Impacts Using Remotely Sensed Thermal Data\u2014A Review of Recent Developments and Methodology. Land, 10.","DOI":"10.3390\/land10080867"},{"key":"ref_43","first-page":"127","article-title":"Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: Using time-series of Landsat TM\/ETM+ data","volume":"19","author":"Li","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1016\/j.apr.2020.06.029","article-title":"Aerosol climatology and determination of different types over the semi-arid urban area of Tehran, Iran: Application of multi-platform remote sensing satellite data","volume":"11","author":"Sabetghadam","year":"2020","journal-title":"Atmos. Pollut. Res."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Zhong, C., Chen, C., Liu, Y., Gao, P., and Li, H. (2019). A Specific Study on the Impacts of PM2.5 on Urban Heat Islands with Detailed In Situ Data and Satellite Images. Sustainability, 11.","DOI":"10.3390\/su11247075"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"100542","DOI":"10.1016\/j.uclim.2019.100542","article-title":"Trade-off between urban heat island mitigation and air quality in urban valleys","volume":"31","author":"Henao","year":"2020","journal-title":"Urban Clim."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2724","DOI":"10.1016\/j.scitotenv.2008.12.002","article-title":"Air quality influenced by urban heat island coupled with synoptic weather patterns","volume":"407","author":"Lai","year":"2009","journal-title":"Sci. Total Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"123615","DOI":"10.1016\/j.jhazmat.2020.123615","article-title":"Exploring the relationship between particulate matter, CO, SO2, NO2, O3 and urban heat island in Seoul, Korea","volume":"403","author":"Ngarambe","year":"2021","journal-title":"J. Hazard. Mater."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1080\/15481603.2020.1736857","article-title":"Modeling the spatial variation of urban land surface temperature in relation to environmental and anthropogenic factors: A case study of Tehran, Iran","volume":"57","author":"Weng","year":"2020","journal-title":"GIScience Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.apr.2019.11.015","article-title":"Air pollution trends in Tehran and their anthropogenic drivers","volume":"11","author":"Torbatian","year":"2020","journal-title":"Atmos. Pollut. Res."},{"key":"ref_51","first-page":"754","article-title":"The link between urbanization and climatic factors: A concept on formation of urban heat island","volume":"6","author":"Shahmohamadi","year":"2010","journal-title":"WSEAS Trans. Environ. Dev."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.landusepol.2017.11.023","article-title":"Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran","volume":"71","author":"Tayyebi","year":"2018","journal-title":"Land Use Policy"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5326","DOI":"10.1109\/JSTARS.2020.3021052","article-title":"Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review","volume":"13","author":"Amani","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.rse.2017.03.026","article-title":"Cloud detection algorithm comparison and validation for operational Landsat data products","volume":"194","author":"Foga","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1080\/01431169308904400","article-title":"On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces","volume":"14","author":"Owe","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Kuenzer, C., and Dech, S. (2013). Thermal Infrared Remote Sensing: Sensors, Methods, Applications, Springer Science & Business Media.","DOI":"10.1007\/978-94-007-6639-6"},{"key":"ref_58","first-page":"737","article-title":"Generalizing El Nino effects upon Maasai livestock using hierarchical clusters of vegetation patterns","volume":"66","author":"Boone","year":"2000","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_60","first-page":"352","article-title":"A kernel functions analysis for support vector machines for land cover classification","volume":"11","author":"Kavzoglu","year":"2009","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.isprsjprs.2020.07.013","article-title":"Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples","volume":"167","author":"Ghorbanian","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Dissanayake, D., Morimoto, T., Murayama, Y., and Ranagalage, M. (2019). Impact of landscape structure on the variation of land surface temperature in sub-saharan region: A case study of Addis Ababa using Landsat data (1986\u20132016). Sustainability, 11.","DOI":"10.3390\/su11082257"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.rse.2016.09.007","article-title":"Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning","volume":"186","author":"Coutts","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1007\/s00704-017-2197-3","article-title":"Assessment of surface urban heat island across China\u2019s three main urban agglomerations","volume":"133","author":"Liu","year":"2018","journal-title":"Theor. Appl. Climatol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"3175","DOI":"10.1016\/j.rse.2011.07.003","article-title":"Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures","volume":"115","author":"Schwarz","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.scitotenv.2017.11.360","article-title":"A new method to quantify surface urban heat island intensity","volume":"624","author":"Li","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.rse.2014.03.037","article-title":"Multi-temporal trajectory of the urban heat island centroid in Beijing, China based on a Gaussian volume model","volume":"149","author":"Quan","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.rse.2014.05.005","article-title":"Spatial and temporal trends of the surface and air heat island over Milan using MODIS data","volume":"150","author":"Anniballe","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2595","DOI":"10.1080\/01431160110115023","article-title":"A remote sensing study of the urban heat island of Houston, Texas","volume":"23","author":"Streutker","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"82","DOI":"10.3390\/a8020082","article-title":"A stable Gaussian fitting procedure for the parameterization of remote sensed thermal images","volume":"8","author":"Anniballe","year":"2015","journal-title":"Algorithms"},{"key":"ref_71","first-page":"789","article-title":"Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect","volume":"10","author":"Zhang","year":"2006","journal-title":"J. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"101899","DOI":"10.1016\/j.scs.2019.101899","article-title":"Re-visitation of the thermal environment evaluation index standard effective temperature (SET*) based on the two-node model","volume":"53","author":"Du","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1007\/s00484-011-0454-1","article-title":"Deriving the operational procedure for the Universal Thermal Climate Index (UTCI)","volume":"56","author":"Fiala","year":"2012","journal-title":"Int. J. Biometeorol."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Matzarakis, A., and Amelung, B. (2008). Physiological equivalent temperature as indicator for impacts of climate change on thermal comfort of humans. Seasonal Forecasts, Climatic Change and Human Health, Springer.","DOI":"10.1007\/978-1-4020-6877-5_10"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"101432","DOI":"10.1016\/j.scs.2019.101432","article-title":"The spatio-temporal trends of urban growth and surface urban heat islands over two decades in the Semarang Metropolitan Region","volume":"46","author":"Sejati","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.ufug.2017.11.008","article-title":"Variations in land surface temperature and cooling efficiency of green space in rapid urbanization: The case of Fuzhou city, China","volume":"29","author":"Yu","year":"2018","journal-title":"Urban For. Urban Green."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Singh, N., Singh, S., and Mall, R.K. (2020). Urban ecology and human health: Implications of urban heat island, air pollution and climate change nexus. Urban Ecology, Elsevier.","DOI":"10.1016\/B978-0-12-820730-7.00017-3"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"141727","DOI":"10.1016\/j.scitotenv.2020.141727","article-title":"On the linkage between urban heat island and urban pollution island: Three-decade literature review towards a conceptual framework","volume":"751","author":"Ulpiani","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1038\/s41598-019-56578-6","article-title":"Temporal variations of ambient air pollutants and meteorological influences on their concentrations in Tehran during 2012\u20132017","volume":"10","author":"Yousefian","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1186\/s12940-016-0100-9","article-title":"Attribution of mortality to the urban heat island during heatwaves in the West Midlands, UK","volume":"15","author":"Heaviside","year":"2016","journal-title":"Environ. Health"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s00484-009-0256-x","article-title":"The urban heat island and its impact on heat waves and human health in Shanghai","volume":"54","author":"Tan","year":"2010","journal-title":"Int. J. Biometeorol."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.rse.2015.12.040","article-title":"A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery","volume":"175","author":"Fu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"105816","DOI":"10.1016\/j.ecolind.2019.105816","article-title":"Modelling surface heat island intensity according to differences of biophysical characteristics: A case study of Amol city, Iran","volume":"109","author":"Firozjaei","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10584-016-1596-2","article-title":"Modelling the potential of green and blue infrastructure to reduce urban heat load in the city of Vienna","volume":"135","author":"Koch","year":"2016","journal-title":"Clim. Chang."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"64004","DOI":"10.1088\/1748-9326\/11\/6\/064004","article-title":"Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: Evaluation with a regional climate model","volume":"11","author":"Sharma","year":"2016","journal-title":"Environ. Res. Lett."},{"key":"ref_86","first-page":"30","article-title":"Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures","volume":"67","author":"Deilami","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"294","DOI":"10.4236\/ajcc.2017.62015","article-title":"Seasonal variation of urban heat island and its impact on air-quality using SAFAR observations at Delhi, India","volume":"6","author":"Aslam","year":"2017","journal-title":"Am. J. Clim. Chang."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1016\/j.scitotenv.2018.03.050","article-title":"Temporal and spatial variation relationship and influence factors on surface urban heat island and ozone pollution in the Yangtze River Delta, China","volume":"631","author":"Wang","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"12509","DOI":"10.1038\/ncomms12509","article-title":"Urban heat islands in China enhanced by haze pollution","volume":"7","author":"Cao","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"93","DOI":"10.3389\/frsc.2021.705185","article-title":"Nature-based solutions for co-mitigation of air pollution and urban heat in Indian cities","volume":"3","author":"Menon","year":"2021","journal-title":"Front. Sustain. Cities"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s11252-008-0054-y","article-title":"Estimates of air pollution mitigation with green plants and green roofs using the UFORE model","volume":"11","author":"Currie","year":"2008","journal-title":"Urban Ecosyst."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"7266","DOI":"10.1016\/j.atmosenv.2008.07.003","article-title":"Quantifying air pollution removal by green roofs in Chicago","volume":"42","author":"Yang","year":"2008","journal-title":"Atmos. Environ."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.atmosenv.2015.10.094","article-title":"Secondary effects of urban heat island mitigation measures on air quality","volume":"125","author":"Fallmann","year":"2016","journal-title":"Atmos. Environ."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"8991","DOI":"10.1073\/pnas.1703560114","article-title":"Air-quality implications of widespread adoption of cool roofs on ozone and particulate matter in southern California","volume":"114","author":"Epstein","year":"2017","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_95","first-page":"1","article-title":"Monitoring mangrove forests: Are we taking full advantage of technology?","volume":"63","author":"Joyce","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4469\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:27:04Z","timestamp":1760167624000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4469"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,7]]},"references-count":95,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214469"],"URL":"https:\/\/doi.org\/10.3390\/rs13214469","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,7]]}}}