{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T09:55:04Z","timestamp":1769248504367,"version":"3.49.0"},"reference-count":131,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T00:00:00Z","timestamp":1643068800000},"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>In our current global warming climate, the growth of record-breaking heat waves (HWs) is expected to increase in its frequency and intensity. Consequently, the considerably growing and agglomerated world\u2019s urban population becomes more exposed to serious heat-related health risks. In this context, the study of Surface Urban Heat Island (SUHI) intensity during HWs is of substantial importance due to the potential vulnerability urbanized areas might have to HWs in comparison to their surrounding rural areas. This article discusses Land Surface Temperatures (LST) reached during the extreme HW over Western North America during the boreal summer of 2021 using Thermal InfraRed (TIR) imagery acquired from TIR Sensor (TIRS) (30 m spatial resolution) onboard Landsat-8 platform and Moderate Resolution Imaging Spectroradiometer (MODIS) (1 km spatial resolution) onboard Terra\/Aqua platforms. We provide an early assessment of maximum LSTs reached over the affected areas, as well as impacts in terms of SUHI over the main cities and towns. MODIS series of LST from 2000 to 2021 over urbanized areas presented the highest recorded LST values in late June 2021, with maximum values around 50 \u00b0C for some cities. High spatial resolution LSTs (Landsat-8) were used to map SUHI intensity as well as to assess the impact of SUHI on thermal comfort conditions at intraurban space by means of a thermal environmental quality indicator, the Urban Field Thermal Variance Index (UFTVI). The same high resolution LSTs were used to verify the existence of clusters and employ a Local Indicator of Spatial Association (LISA) to quantify its degree of strength. We identified the spatial distribution of heat patterns within the intraurban space as well as described its behavior across the thermal landscape by fitting a polynomial regression model. We also qualitatively analyze the relationship between both UFTVI and LST clusters with different land cover types. Findings indicate that average daytime SUHI intensity for the studied cities was typically within 1 to 5 \u00b0C, with some exceptional values surpassing 7 \u00b0C and 9 \u00b0C. During night, the SUHI intensity was reduced to variations within 1\u20133 \u00b0C, with a maximum value of +4 \u00b0C. The extreme LSTs recorded indicate no significant influence of HW on SUHI intensity. SUHI intensity maps of the intraurban space evidence hotspots of much higher values located at densely built-up areas, while urban green spaces and dense vegetation show lower values. In the same manner, UTFVI has shown \u201cno\u201d SUHI for densely vegetated regions, water bodies, and low-dense built-up areas with intertwined dense vegetation, while the \u201cstrongest\u201d SUHI was observed for non-vegetated dense built-up areas with low albedo material such as concrete and pavement. LST was evidenced as a good marker for assessing the influence of HWs on SUHI and recognizing potential thermal environmental consequences of SUHI intensity. This finding highlights that remote-sensing based LST is particularly suitable as an indicator in the analysis of SUHI intensity patterns during HWs at different spatial resolutions. LST used as an indicator for analyzing and detecting extreme temperature events and its consequences seems to be a promising means for rapid and accurate monitoring and mapping.<\/jats:p>","DOI":"10.3390\/rs14030561","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T21:07:11Z","timestamp":1643144831000},"page":"561","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["The Extreme Heat Wave over Western North America in 2021: An Assessment by Means of Land Surface Temperature"],"prefix":"10.3390","volume":"14","author":[{"given":"Gabriel I.","family":"Cotlier","sequence":"first","affiliation":[{"name":"Haifa Center for Theoretical Physics and Astrophysics (HCTPA), Data Science Research Center (DSRC), University of Haifa, Haifa 3498838, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7562-4895","authenticated-orcid":false,"given":"Juan Carlos","family":"Jimenez","sequence":"additional","affiliation":[{"name":"Global Change Unit (CGU), Image Processing Laboratory (IPL), University of Valencia, 46980 Paterna, Valencia, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1175\/1520-0450(2001)040<0762:OTDOAH>2.0.CO;2","article-title":"On the definition of a heat wave","volume":"40","author":"Robinson","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6284","DOI":"10.1002\/2015JD024659","article-title":"Land surface and atmospheric conditions associated with heat waves over the Chickasaw Nation in the South Central United States","volume":"121","author":"Lee","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1097\/EDE.0000000000000165","article-title":"Global variation in the effects of ambient temperature on mortality: A systematic evaluation","volume":"25","author":"Guo","year":"2014","journal-title":"Epidemiology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1175\/JAMC-D-13-0130.1","article-title":"The Impact of Recent Heat Waves on Human Health in California","volume":"53","author":"Guirguis","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1016\/j.jclepro.2017.10.069","article-title":"Assessment of the economic impacts of heat waves: A case study of Nanjing, China","volume":"171","author":"Xia","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Castillo, F., Wehner, M., and Stone, D.A. (2021). The Impact of Heat Waves on Agricultural Labor Productivity and Output. Extreme Events and Climate Change: A Multidisciplanary Approach, John Wiley & Sons, Inc.. [1st ed.].","DOI":"10.1002\/9781119413738.ch2"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"024022","DOI":"10.1088\/1748-9326\/ab6398","article-title":"Increasing occurrence of heat waves in the terrestrial Arctic","volume":"15","author":"Dobricic","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/978-3-030-71330-0_7","article-title":"Climate-Induced Global Forest Shifts due to Heatwave-Drought","volume":"241","author":"Lloret","year":"2021","journal-title":"Ecol. Stud."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e2020GL087091","DOI":"10.1029\/2020GL087091","article-title":"Atmospheric Aridity and Apparent Soil Moisture Drought in European Forest During Heat Waves","volume":"47","author":"Lansu","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"105276","DOI":"10.1016\/j.envint.2019.105276","article-title":"Heatwaves, droughts, and fires: Exploring compound and cascading dry hazards at the pan-European scale","volume":"134","author":"Sutanto","year":"2020","journal-title":"Environ. Int."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1007\/s00704-020-03443-6","article-title":"Climate change driven changes of vegetation fires in the Czech Republic","volume":"143","author":"Mozny","year":"2020","journal-title":"Theor. Appl. Climatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.rse.2010.08.024","article-title":"Heat waves measured with MODIS land surface temperature data predict changes in avian community structure","volume":"115","author":"Albright","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1038\/nature01286","article-title":"A globally coherent fingerprint of climate change impacts across natural systems","volume":"421","author":"Parmesan","year":"2003","journal-title":"Nature"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1007\/978-3-030-71330-0_12","article-title":"Marine Heatwave Drives Collapse of Kelp Forests in Western Australia","volume":"241","author":"Wernberg","year":"2021","journal-title":"Ecol. Stud."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1038\/nclimate1452","article-title":"A decade of weather extremes","volume":"2","author":"Coumou","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/s00704-015-1718-1","article-title":"Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models","volume":"128","author":"Guo","year":"2016","journal-title":"Theor. Appl. Climatol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"105458","DOI":"10.1016\/j.atmosres.2021.105458","article-title":"Identifying the dominant driving factors of heat waves in the North China Plain","volume":"252","author":"Wu","year":"2021","journal-title":"Atmos. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"114022","DOI":"10.1088\/1748-9326\/10\/11\/114022","article-title":"Cool city mornings by urban heat","volume":"10","author":"Theeuwes","year":"2015","journal-title":"Environ. Res. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1016\/0004-6981(73)90140-6","article-title":"City Size and the Urban Heat Island","volume":"7","author":"Oke","year":"1973","journal-title":"Atmos. Environ."},{"key":"ref_20","first-page":"1","article-title":"The Energetic Basis of the Urban Heat Island","volume":"108","author":"Oke","year":"1982","journal-title":"Q. J. R. Met. Soc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/S0038-092X(00)00095-5","article-title":"On the impact of urban climate on the energy consumption of buildings","volume":"70","author":"Santamouris","year":"2001","journal-title":"Sol. Energy"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0169-2046(99)00075-4","article-title":"Spatial distribution and microscale characteristics of the urban heat island in Tel-Aviv, Israel","volume":"48","author":"Saaroni","year":"2000","journal-title":"Landsc. Urban Plan."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/s00704-008-0017-5","article-title":"Quantifying the influence of land-use and surface characteristics on spatial variability in the urban heat island","volume":"95","author":"Hart","year":"2009","journal-title":"Theor. Appl. Climatol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"10973","DOI":"10.1038\/s41598-017-11407-6","article-title":"Synergies between Urban Heat Island and Heat Waves in Athens (Greece), during an extremely hot summer (2012)","volume":"7","author":"Founda","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"108138","DOI":"10.1016\/j.buildenv.2021.108138","article-title":"Impacts of land use\/ land cover types on interactions between urban heat island effects and heat waves","volume":"204","author":"Zou","year":"2021","journal-title":"Build. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"034003","DOI":"10.1088\/1748-9326\/aa9f73","article-title":"Interactions between urban heat islands and heat waves","volume":"13","author":"Zhao","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"109102","DOI":"10.1016\/j.envres.2019.109102","article-title":"Urban-rural moisture contrast: Regulator of the urban heat island and heatwaves\u2019 synergy over a mediterranean city","volume":"182","author":"Pyrgou","year":"2020","journal-title":"Environ. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"104021","DOI":"10.1088\/1748-9326\/ac25bb","article-title":"Scale-dependent response of the urban heat island to the European heatwave of 2018","volume":"16","author":"Shreevastava","year":"2021","journal-title":"Environ. Res. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kong, J., Zhao, Y., Carmeliet, J., and Lei, C. (2021). Urban Heat Island and Its Interaction with Heatwaves: A Review of Studies on Mesoscale. Sustainability, 13.","DOI":"10.3390\/su131910923"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1634","DOI":"10.1029\/2018GL081004","article-title":"Warming Trends in Summer Heatwaves","volume":"46","author":"Chapman","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_31","first-page":"29","article-title":"Seasonal analysis of cold and heat waves in Serbia during the period 1949\u20132012","volume":"120","year":"2014","journal-title":"Theor. Appl. Climatol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"W04510","DOI":"10.1029\/2011WR011357","article-title":"Relative efficiency of land surface energy balance components","volume":"48","author":"Bateni","year":"2012","journal-title":"Water Resour. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"6763","DOI":"10.1038\/s41467-021-26768-w","article-title":"The role of urban trees in reducing land surface temperatures in European cities","volume":"12","author":"Schwaab","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_35","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_36","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1007\/s00024-013-0685-7","article-title":"Land Surface Temperature Patterns in the Urban Agglomeration of Krakow (Poland) Derived from Landsat-7\/ETM+ Data","volume":"171","author":"Walawender","year":"2013","journal-title":"Pure Appl. Geophys."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Oke, T.R., Mills, G., Christen, A., and Voogt, J.A. (2017). Urban Climates, Cambridge University Press.","DOI":"10.1017\/9781139016476"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100541","DOI":"10.1016\/j.uclim.2019.100541","article-title":"Is the Urban Heat Island intensity relevant for heat mitigation studies?","volume":"31","author":"Martilli","year":"2020","journal-title":"Urban Clim."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1007\/s10980-012-9731-6","article-title":"Spatial pattern of greenspace affects land surface temperature: Evidence from the heavily urbanized Beijing metropolitan area, China","volume":"27","author":"Li","year":"2012","journal-title":"Landsc. Ecol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.landurbplan.2013.02.005","article-title":"Relationship between land surface temperature and spatial pattern of greenspace: What are the effects of spatial resolution?","volume":"114","author":"Li","year":"2013","journal-title":"Landsc. Urban Plan."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.landurbplan.2011.03.009","article-title":"Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes","volume":"102","author":"Zhou","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"44479","DOI":"10.1007\/s11356-021-13594-2","article-title":"Directionally and spatially varying relationship between land surface temperature and land-use pattern considering wind direction: A case study in central China","volume":"28","author":"Li","year":"2021","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"105314","DOI":"10.1016\/j.landusepol.2021.105314","article-title":"Effect of urban growth pattern on land surface temperature in China: A multi-scale landscape analysis of 338 cities","volume":"103","author":"Rao","year":"2021","journal-title":"Land Use Policy"},{"key":"ref_44","first-page":"100636","article-title":"Land surface temperature and vegetation cover changes and their relationships in Taiwan from 2000 to 2020","volume":"24","author":"Abdulmana","year":"2021","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1007\/s12517-021-07433-4","article-title":"Investigating effects of land use and land cover patterns on land surface temperature using landscape metrics in the city of Tehran, Iran","volume":"14","author":"Effati","year":"2021","journal-title":"Arab. J. Geosci."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Yu, Z., Zhang, J., Yang, G., and Schlaberg, J. (2021). Reverse Thinking: A New Method from the Graph Perspective for Evaluating and Mitigating Regional Surface Heat Islands. Remote Sens., 13.","DOI":"10.3390\/rs13061127"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Forman, R.T.T. (1995). Land Mosaics: The Ecology of Landscapes and Regions, Cambridge University Press.","DOI":"10.1017\/9781107050327"},{"key":"ref_48","unstructured":"Turner, M.G., Gardner, R.H., and O\u2019Neill, R.V. (2001). Landscape Ecology in Teory and Practice, Springer."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.agee.2003.09.011","article-title":"Land cover change and landscape fragmentation\u2014Comparing the utility of continuous and discrete analyses for a western Honduras region","volume":"101","author":"Southworth","year":"2004","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2223","DOI":"10.1080\/014311698214983","article-title":"Local spatial autocorrelation characteristics of remotely sensed imagery assessed with the Getis statistic","volume":"19","author":"Wulder","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Fan, C., and Wang, Z. (2020). Spatiotemporal Characterization of Land Cover Impacts on Urban Warming: A Spatial Autocorrelation Approach. Remote Sens., 12.","DOI":"10.3390\/rs12101631"},{"key":"ref_52","first-page":"100239","article-title":"Using Moran\u2019s I and GIS to study the spatial pattern of land surface temperature in relation to land use\/cover around a thermal power plant in Singrauli district, Madhya Pradesh, India","volume":"15","author":"Kumari","year":"2019","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"102100","DOI":"10.1016\/j.scs.2020.102100","article-title":"Impact of urban and industrial features on land surface temperature: Evidences from satellite thermal indices","volume":"56","author":"Portela","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.landurbplan.2016.05.001","article-title":"Quantifying land surface temperature change from LISA clusters: An alternative approach to identifying urban land use transformation","volume":"153","author":"Biswas","year":"2016","journal-title":"Landsc. Urban Plan."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1007\/s11769-019-1055-x","article-title":"Examining the Relationship Between Spatial Configurations of Urban Impervious Surfaces and Land Surface Temperature","volume":"29","author":"Wu","year":"2019","journal-title":"Chin. Geogr. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.landurbplan.2010.03.008","article-title":"Quantifying the cool island intensity of urban parks using ASTER and IKONOS data","volume":"96","author":"Cao","year":"2010","journal-title":"Landsc. Urban Plan."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"119","DOI":"10.18848\/2325-1077\/CGP\/v09i01\/55081","article-title":"The Impacts of Green Areas on Mitigating Urban Heat Island Effect","volume":"9","author":"Shishegar","year":"2014","journal-title":"Int. J. Environ. Sustain."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"868","DOI":"10.3390\/f4040868","article-title":"Estimation of the Relationship between Urban Park Characteristics and Park Cool Island Intensity by Remote Sensing Data and Field Measurement","volume":"4","author":"Ren","year":"2013","journal-title":"Forests"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3039","DOI":"10.1080\/014311697217198","article-title":"Airborne video thermal radiometry as a tool for monitoring microscale structures of the urban heat island","volume":"18","author":"Saaroni","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S0378-7788(99)00018-3","article-title":"Vegetation as a climatic component in the design of an urban street An empirical model for predicting the cooling effect of urban green","volume":"31","author":"Hoffman","year":"2000","journal-title":"Energy Build."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1002\/joc.1869","article-title":"Microclimate modelling of street tree species effects within the varied urban morphology in the Mediterranean city of Tel Aviv","volume":"30","author":"Potchter","year":"2010","journal-title":"Israel. Int. J. Climatol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1002\/joc.2177","article-title":"The influence of trees and grass on outdoor thermal comfort in a hot-arid environment","volume":"31","author":"Pearlmutter","year":"2011","journal-title":"Int. J. Climatol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecolind.2019.04.069","article-title":"Modeling thermal comfort in different condition of mind using satellite images: An Ordered Weighted Averaging approach and a case study","volume":"104","author":"Mijani","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"105798","DOI":"10.1016\/j.ecolind.2019.105798","article-title":"The seasonal and annual impacts of landscape patterns on the urban thermal comfort using Landsat","volume":"110","author":"Feng","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_65","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_66","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.3390\/rs3071535","article-title":"Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong","volume":"3","author":"Liu","year":"2011","journal-title":"Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"100107","DOI":"10.1016\/j.envc.2021.100107","article-title":"Assessment of urban thermal field variance index and defining the relationship between land cover and surface temperature in Chattogram city: A remote sensing and statistical approach","volume":"4","author":"Naim","year":"2021","journal-title":"Environ. Chall."},{"key":"ref_68","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_69","doi-asserted-by":"crossref","first-page":"100192","DOI":"10.1016\/j.envc.2021.100192","article-title":"Assessing and predicting land use\/land cover, land surface temperature and urban thermal field variance index using Landsat imagery for Dhaka Metropolitan area","volume":"4","author":"Faisal","year":"2021","journal-title":"Environ. Chall."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1927852","DOI":"10.1080\/20964129.2021.1927852","article-title":"Dynamic seasonal analysis on LST-NDVI relationship and ecological health of Raipur City, India","volume":"7","author":"Guha","year":"2021","journal-title":"Ecosyst. Health Sustain."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Nguyen, T., Lin, T.-H., and Chan, H.-P. (2019). The Environmental Effects of Urban Development in Hanoi, Vietna from Satellite and Meteorological Observations from 1999\u20132016. Sustainability, 11.","DOI":"10.3390\/su11061768"},{"key":"ref_72","first-page":"34","article-title":"Assessment with satellite data of the urban heat island effects in Asian mega cities","volume":"8","author":"Hung","year":"2006","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_73","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_74","doi-asserted-by":"crossref","first-page":"2051","DOI":"10.1175\/JAMC-D-13-02.1","article-title":"Synergistic Interactions between Urban Heat Islands and Heat Waves: The Impact in Cities Is Larger than the Sum of Its Parts","volume":"52","author":"Li","year":"2013","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1175\/JAMC-D-17-0093.1","article-title":"Thermal Anomalies Detect Critical Global Land Surface Changes","volume":"57","author":"Mildrexler","year":"2018","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"6931","DOI":"10.1038\/s41598-020-63701-5","article-title":"Driving forces of land surface temperature anomalous changes in North America in 2002\u20132018","volume":"10","author":"Yan","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"104046","DOI":"10.1016\/j.landurbplan.2021.104046","article-title":"Small vegetated patches greatly reduce urban surface temperature during a summer heatwave in Adelaide, Australia","volume":"209","author":"Ossola","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1002\/joc.2222","article-title":"Satellite monitoring of summer heat waves in the Paris metropolitan area","volume":"31","author":"Dousset","year":"2010","journal-title":"Int. J. Climatol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s00704-008-0088-3","article-title":"The urban heat island of Bucharest during the extreme high temperatures of July 2007","volume":"97","author":"Cheval","year":"2009","journal-title":"Theor. Appl. Climatol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1002\/joc.2261","article-title":"Derivation of Birmingham\u2019s summer surface urban heat island from MODIS satellite images","volume":"32","author":"Tomlinson","year":"2012","journal-title":"Int. J. Climatol."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.jastp.2019.02.001","article-title":"Spatio-temporal variations in urban heat island and its interaction with heat wave","volume":"185","author":"Rizvi","year":"2019","journal-title":"J. Atmos. Sol.-Terr. Phys."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1007\/s11069-009-9406-z","article-title":"Atlanta\u2019s urban heat island under extreme heat conditions and potential mitigation strategies","volume":"52","author":"Zhou","year":"2010","journal-title":"Nat. Hazards"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1002\/joc.1280","article-title":"Europe\u2019s 2003 heat wave: A satellite view of impacts and land\u2013atmosphere feedbacks","volume":"26","author":"Zaitchik","year":"2006","journal-title":"Int. J. Climatol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1016\/j.scitotenv.2016.06.119","article-title":"Heat waves and urban heat islands in Europe: A review of relevant drivers","volume":"569\u2013570","author":"Ward","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Oliveira, A., Lopes, A., Correia, E., Niza, S., and Soares, A. (2021). Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal. Atmosphere, 12.","DOI":"10.3390\/atmos12030292"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"064003","DOI":"10.1088\/1748-9326\/aabd6c","article-title":"Reduced Urban Heat Island intensity under warmer conditions","volume":"13","author":"Scott","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"100747","DOI":"10.1016\/j.uclim.2020.100747","article-title":"Is Urban Heat Island intensity higher during hot spells and heat waves (Dijon, France, 2014\u20132019)?","volume":"35","author":"Richard","year":"2021","journal-title":"Urban Clim."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"031001","DOI":"10.1088\/2515-7620\/ab121d","article-title":"Decline in surface urban heat island intensity in India during heatwaves","volume":"1","author":"Kumar","year":"2019","journal-title":"Environ. Res. Commun."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"105134","DOI":"10.1016\/j.atmosres.2020.105134","article-title":"Interaction between heat wave and urban heat island: A case study in a tropical coastal city, Singapore","volume":"247","author":"Chew","year":"2021","journal-title":"Atmos. Res."},{"key":"ref_90","unstructured":"Sjoukje, Y.P., Kew, S.F., van Oldenborgh, G.J., Anslow, F.S., Seneviratne, S.I., Vautard, R., Coumou, D., Ebi, K.L., Arrighi, J., and Singh, R. (2021, September 03). Rapid Attribution Analysis of the Extraordinary Heatwave on the Pacific Coast of the US and Canada June 2021. World Weather Attribution., Available online: https:\/\/www.worldweatherattribution.org\/wp-content\/uploads\/NW-US-extreme-heat-2021-scientific-report-WWA.pdf."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., and Sobrino, J. (2018). Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives. Remote Sens., 11.","DOI":"10.3390\/rs11010048"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"180214","DOI":"10.1038\/sdata.2018.214","article-title":"Present and future K\u00f6ppen-Geiger climate classification maps at 1-km resolution","volume":"5","author":"Beck","year":"2018","journal-title":"Sci. Data"},{"key":"ref_93","unstructured":"(2021, September 08). Available online: https:\/\/www.census.gov\/geographies\/mapping-files\/time-series\/geo\/carto-boundary-file.2017.html."},{"key":"ref_94","unstructured":"(2021, September 08). Available online: https:\/\/www12.statcan.gc.ca\/census-recensement\/2011\/geo\/bound-limit\/bound-limit-2016-eng.cfm."},{"key":"ref_95","unstructured":"(2021, September 08). Available online: https:\/\/lpdaac.usgs.gov\/products\/mod11a2v006\/."},{"key":"ref_96","unstructured":"(2021, November 11). Available online: https:\/\/lpdaac.usgs.gov\/products\/mod09gav006\/."},{"key":"ref_97","unstructured":"(2021, September 08). Available online: https:\/\/earthexplorer.usgs.gov."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2014.02.001","article-title":"Landsat-8: Science and product vision for terrestrial global change research","volume":"145","author":"Roy","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of Normalized Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"13763","DOI":"10.3390\/s150613763","article-title":"Classification of Potential Water Bodies Using Landsat 8 OLI and a Combination of Two Boosted Random Forest Classifiers","volume":"15","author":"Ko","year":"2015","journal-title":"Sensors"},{"key":"ref_101","unstructured":"USGS (United States Geological Survey) (2020). Landsat 8 Collection 2 (C2) Level 2 Science Product (L2SP) Guide."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Sobrino, J.A., and Irakulis, I. (2020). A Methodology for Comparing the Surface Urban Heat Island in Selected Urban Agglomerations Around the World from Sentinel-3 SLSTR Data. Remote Sens., 12.","DOI":"10.3390\/rs12122052"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1068\/a121073","article-title":"Algorithm 9: Simulation of Autocorrelation for Aggregate Data","volume":"12","author":"Goodchild","year":"1980","journal-title":"Environ. Plan. A Econ. Space"},{"key":"ref_104","unstructured":"Goodchild, M.F. (1986). Spatial Autocorrelation, Geo Books. CATMOG 47."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Shekhar, S., Xiong, H., and Zhou, X. (2017). Geary\u2019s, C. Encyclopedia of GIS, Springer.","DOI":"10.1007\/978-3-319-17885-1"},{"key":"ref_106","doi-asserted-by":"crossref","unstructured":"Bivand, R., Pebesma, E., and Gomez-Rubio, V. (2013). Applied Spatial Data Analysis with R, Springer. [2nd ed.].","DOI":"10.1007\/978-1-4614-7618-4"},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1007\/s11749-018-0599-x","article-title":"Comparing implementations of global and local indicators of spatial association","volume":"27","author":"Bivand","year":"2018","journal-title":"Test"},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","article-title":"Local indicators of spatial association: LISA","volume":"27","author":"Anselin","year":"1995","journal-title":"Geogr. Anal."},{"key":"ref_109","unstructured":"(2021, September 08). How Do I Use a Scale Factor with Landsat Level-2 Science Products? USGS Mapping, Remote Sensing and Geospatial Data, Available online: https:\/\/www.usgs.gov\/faqs\/how-do-i-use-a-scale-factor-landsat-level-2-science-products?qt-news_science_products=0#qt-news_science_products."},{"key":"ref_110","unstructured":"QGIS Development Team (2021, August 09). QGIS Version 3.18. Geographic Information System. Open-Source Geospatial Foundation Project., Available online: https:\/\/www.qgis.org\/en\/site\/."},{"key":"ref_111","unstructured":"MathWorks (2021). MATLAB ver. 2021b Computer Program, The MathWorks Inc.. Available online: https:\/\/www.mathworks.com\/."},{"key":"ref_112","unstructured":"R Core Team (2021). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https:\/\/www.R-project.org\/."},{"key":"ref_113","unstructured":"Bivand, R. (2021, August 09). Spdep: Spatial Dependence: Weighting Schemes, Statistics and Models. R Package Version 1.1-11. Available online: http:\/\/CRAN.R-project.org\/package=spdep."},{"key":"ref_114","unstructured":"Hijmans, R.J., and Van Etten, J. (2021, August 09). Raster: Geographic Analysis and Modeling with Raster Data. R Package Version 3.5-2. Available online: http:\/\/CRAN.R-project.org\/package=raster."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v084.i06","article-title":"tmap: Thematic Maps in R","volume":"84","author":"Tennekes","year":"2018","journal-title":"J. Stat. Softw."},{"key":"ref_116","unstructured":"(2021, September 08). Available online: https:\/\/gis.ncdc.noaa.gov\/maps\/ncei\/summaries\/daily."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"9245","DOI":"10.1038\/s41598-020-66168-6","article-title":"Spatial relationship between land-use\/land-cover change and land surface temperature in the Dongting Lake area, China","volume":"10","author":"Tan","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"10451","DOI":"10.1038\/s41598-020-67423-6","article-title":"Correlation analysis of land surface temperature and topographic elements in Hangzhou, China","volume":"10","author":"Peng","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_119","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_120","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1175\/BAMS-D-11-00019.1","article-title":"Local climate zones for urban temperature studies","volume":"93","author":"Stewart","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_121","doi-asserted-by":"crossref","unstructured":"Bonafoni, S., and Keeratikasikorn, C. (2018). Land surface temperature and urban density: Multiyear modeling and relationship analysis using MODIS and Landsat data. Remote Sens., 10.","DOI":"10.3390\/rs10091471"},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"3177","DOI":"10.1080\/01431161.2012.716548","article-title":"Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing","volume":"34","author":"Sobrino","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1109\/JSTARS.2020.2981285","article-title":"A Novel SUHI Referenced Estimation Method for Multicenters Urban Agglomeration using DMSP\/OLS Nighttime Light Data","volume":"13","author":"Li","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.scitotenv.2018.04.105","article-title":"Spatial-temporal change of land surface temperature across 285 cities in China: An urban-rural contrast perspective","volume":"635","author":"Peng","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.rse.2009.10.008","article-title":"Remote sensing of the urban heat island effect across biomes in the continental USA","volume":"114","author":"Imhoff","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.rse.2014.05.017","article-title":"Surface urban heat island in China\u2019s 32 major cities: Spatial patterns and drivers","volume":"152","author":"Zhou","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A Computer Movie Simulating Urban Growth in the Detroit Region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_128","doi-asserted-by":"crossref","unstructured":"Shekhar, S., and Xiong, H. (2008). Autocorrelation, Spatial. Encyclopedia of GIS, Springer.","DOI":"10.1007\/978-0-387-35973-1_1236"},{"key":"ref_129","doi-asserted-by":"crossref","unstructured":"Wiens, J.A., and Moss, M.R. (2005). The gradient concept of landscape structure [Chapter 12]. Issues and Perspectives in Landscape Ecology, Cambridge University Press.","DOI":"10.1017\/CBO9780511614415"},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.landurbplan.2013.10.002","article-title":"A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation","volume":"121","author":"Fan","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/s10980-008-9215-x","article-title":"On the accuracy of landscape pattern analysis using remote sensing data","volume":"23","author":"Shao","year":"2008","journal-title":"Landsc. Ecol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/561\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:07:18Z","timestamp":1760134038000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/561"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,25]]},"references-count":131,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030561"],"URL":"https:\/\/doi.org\/10.3390\/rs14030561","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,25]]}}}