{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T21:15:32Z","timestamp":1781298932820,"version":"3.54.1"},"reference-count":68,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42077433 and 71874196"],"award-info":[{"award-number":["42077433 and 71874196"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China","award":["No.21XNH037"],"award-info":[{"award-number":["No.21XNH037"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The spatially heterogeneous nature and geographical scale of surface urban heat island (SUHI) driving mechanisms remain largely unknown, as most previous studies have focused solely on their global performance and impact strength. This paper analyzes diurnal and nocturnal SUHIs in China based on the multiscale geographically weighted regression (MGWR) model for 2005, 2010, 2015, and 2018. Compared to results obtained using the ordinary least square (OLS) model, the MGWR model has a lower corrected Akaike information criterion value and significantly improves the model\u2019s coefficient of determination (OLS: 0.087\u20130.666, MGWR: 0.616\u20130.894). The normalized difference vegetation index (NDVI) and nighttime light (NTL) are the most critical drivers of daytime and nighttime SUHIs, respectively. In terms of model bandwidth, population and \u0394fine particulate matter are typically global variables, while \u0394NDVI, intercept (i.e., spatial context), and NTL are local variables. The nighttime coefficient of \u0394NDVI is significantly negative in the more economically developed southern coastal region, while it is significantly positive in northwestern China. Our study not only improves the understanding of the complex drivers of SUHIs from a multiscale perspective but also provides a basis for urban heat island mitigation by more precisely identifying the heterogeneity of drivers.<\/jats:p>","DOI":"10.3390\/rs13214428","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T21:57:49Z","timestamp":1635976669000},"page":"4428","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Identifying Surface Urban Heat Island Drivers and Their Spatial Heterogeneity in China\u2019s 281 Cities: An Empirical Study Based on Multiscale Geographically Weighted Regression"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4073-7264","authenticated-orcid":false,"given":"Lu","family":"Niu","sequence":"first","affiliation":[{"name":"School of Public Administration and Policy, Renmin University of China, Beijing 100872, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengfeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Public Administration and Policy, Renmin University of China, Beijing 100872, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhong","family":"Peng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0635-8498","authenticated-orcid":false,"given":"Yingzi","family":"Liang","sequence":"additional","affiliation":[{"name":"College of Management and Economics, Tianjin University, Tianjin 300072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yazhen","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8803-7056","authenticated-orcid":false,"given":"Jing","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Chemical and Biochemical Engineering, Iowa Technology Institute, Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronglin","family":"Tang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9540","DOI":"10.1073\/pnas.0400357101","article-title":"Evidence for a significant urbanization effect on climate in China","volume":"101","author":"Zhou","year":"2004","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1038\/nature01675","article-title":"Impact of urbanization and land-use change on climate","volume":"423","author":"Kalnay","year":"2003","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.landurbplan.2009.05.001","article-title":"Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization","volume":"92","author":"Deng","year":"2009","journal-title":"Landsc. Urban Plan."},{"key":"ref_4","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_5","first-page":"1","article-title":"Climate of London deduced from meteorological observation","volume":"1","author":"Howard","year":"1833","journal-title":"Harvey Darton"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.enbuild.2011.12.019","article-title":"London\u2019s urban heat island: Impact on current and future energy consumption in office buildings","volume":"47","author":"Kolokotroni","year":"2012","journal-title":"Energy Build."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/j.apenergy.2005.06.001","article-title":"Impacts of city-block-scale countermeasures against urban heat-island phenomena upon a building\u2019s energy-consumption for air-conditioning","volume":"83","author":"Kikegawa","year":"2006","journal-title":"Appl. Energy"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"110636","DOI":"10.1016\/j.enbuild.2020.110636","article-title":"The Leeds urban heat island and its implications for energy use and thermal comfort","volume":"235","author":"Parker","year":"2021","journal-title":"Energy Build."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.1016\/j.atmosenv.2005.11.037","article-title":"Impact of urban heat island on regional atmospheric pollution","volume":"40","author":"Sarrat","year":"2006","journal-title":"Atmos. Environ."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.landurbplan.2016.11.004","article-title":"Effects of settlement size, urban heat island and habitat type on urban plant biodiversity","volume":"159","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10613","DOI":"10.1002\/ece3.7872","article-title":"Shielded environments reduce stress in alien Asteraceae species during hot and dry summers along urban-to-rural gradients","volume":"11","author":"Lembrechts","year":"2021","journal-title":"Ecol. Evol."},{"key":"ref_13","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_14","doi-asserted-by":"crossref","unstructured":"Goggins, W.B., Chan, E.Y., Ng, E., Ren, C., and Chen, L. (2012). Effect modification of the association between short-term meteorological factors and mortality by urban heat islands in Hong Kong. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0038551"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"110584","DOI":"10.1016\/j.envres.2020.110584","article-title":"Localized synergies between heat waves and urban heat islands: Implications on human thermal comfort and urban heat management","volume":"193","author":"He","year":"2021","journal-title":"Environ. Res."},{"key":"ref_16","first-page":"1","article-title":"The energetic basis of the urban heat island","volume":"108","author":"Oke","year":"1982","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_17","unstructured":"Stewart, I., and Mills, G. (2021). The Urban Heat Island: A Guidebook, Elsevier."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.rse.2013.03.008","article-title":"MODIS detected surface urban heat islands and sinks: Global locations and controls","volume":"134","author":"Clinton","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.rse.2018.08.021","article-title":"Identification of typical diurnal patterns for clear-sky climatology of surface urban heat islands","volume":"217","author":"Lai","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1080\/02723646.2000.10642711","article-title":"Dynamics and controls of the near-surface heat island of Vancouver, British Columbia","volume":"21","author":"Runnalls","year":"2000","journal-title":"Phys. Geogr."},{"key":"ref_21","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_22","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_23","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_24","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1109\/LGRS.2009.2023825","article-title":"Evaluation of the surface temperature variation with surface settings on the urban heat island in Seoul, Korea, using Landsat-7 ETM+ and SPOT","volume":"6","author":"Bhang","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"109285","DOI":"10.1016\/j.jenvman.2019.109285","article-title":"Physical and non-physical factors driving urban heat island: Case of Bangkok Metropolitan Administration, Thailand","volume":"248","author":"Khamchiangta","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_26","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_27","doi-asserted-by":"crossref","first-page":"31","DOI":"10.2528\/PIERC20020403","article-title":"A Review of Remotely Sensed Surface Urban Heat Islands from the Fresh Perspective of Comparisons Among Different Regions (Invited Review)","volume":"102","author":"Li","year":"2020","journal-title":"Prog. Electromagn. Res. C"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1021\/es2030438","article-title":"Surface Urban Heat Island Across 419 Global Big Cities","volume":"46","author":"Peng","year":"2012","journal-title":"Environ. Sci. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1038\/nature13462","article-title":"Strong contributions of local background climate to urban heat islands","volume":"511","author":"Zhao","year":"2014","journal-title":"Nature"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/s41586-019-1512-9","article-title":"Magnitude of urban heat islands largely explained by climate and population","volume":"573","author":"Manoli","year":"2019","journal-title":"Nature"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Priyankara, P., Ranagalage, M., Dissanayake, D., Morimoto, T., and Murayama, Y. (2019). Spatial process of surface urban heat island in rapidly growing Seoul metropolitan area for sustainable urban planning using Landsat data (1996\u20132017). Climate, 7.","DOI":"10.3390\/cli7090110"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1111\/j.1538-4632.1972.tb00455.x","article-title":"Geographical variances","volume":"4","author":"Moellering","year":"1972","journal-title":"Geogr. Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1111\/j.1467-8306.2004.00428.x","article-title":"Who governs, at what scale and at what price? Geography, environmental governance, and the commodification of nature","volume":"94","author":"Liverman","year":"2004","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_34","first-page":"1247","article-title":"Multiscale geographically weighted regression (MGWR)","volume":"107","author":"Fotheringham","year":"2017","journal-title":"Ann. Am. Assoc. Geogr."},{"key":"ref_35","first-page":"1","article-title":"Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China","volume":"7","author":"Yang","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.rse.2016.02.010","article-title":"Remotely sensed assessment of urbanization effects on vegetation phenology in China\u2019s 32 major cities","volume":"176","author":"Zhou","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1016\/j.jclepro.2018.10.178","article-title":"Understanding the variability of urban heat islands from local background climate and urbanization","volume":"208","author":"Sun","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Niu, L., Tang, R., Jiang, Y., and Zhou, X. (2020). Spatiotemporal patterns and drivers of the surface urban heat island in 36 major cities in China: A comparison of two different methods for delineating rural areas. Sustainability, 12.","DOI":"10.3390\/su12020478"},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"102425","DOI":"10.1016\/j.scs.2020.102425","article-title":"Socioeconomic drivers of urban heat island effect: Empirical evidence from major Chinese cities","volume":"63","author":"Li","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"108051","DOI":"10.1016\/j.buildenv.2021.108051","article-title":"Simulating and mitigating extreme urban heat island effects in a factory area based on machine learning","volume":"202","author":"Liu","year":"2021","journal-title":"Build. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-018-0113-z","article-title":"Investigating important urban characteristics in the formation of urban heat islands: A machine learning approach","volume":"5","author":"Yoo","year":"2018","journal-title":"J. Big Data"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.scitotenv.2019.03.100","article-title":"Spatial-temporal variations of surface urban heat island intensity induced by different definitions of rural extents in China","volume":"669","author":"Li","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s00704-011-0517-6","article-title":"Local regression models for spatial interpolation of urban heat island\u2014An example from Wroc\u0142aw, SW Poland","volume":"108","author":"Szymanowski","year":"2012","journal-title":"Theor. Appl. Climatol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Zhao, C., Jensen, J., Weng, Q., and Weaver, R. (2018). A geographically weighted regression analysis of the underlying factors related to the surface urban heat island phenomenon. Remote Sens., 10.","DOI":"10.3390\/rs10091428"},{"key":"ref_46","first-page":"102131","article-title":"Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities","volume":"90","author":"Li","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_47","first-page":"1602","article-title":"Scale, Context, and Heterogeneity: A Spatial Analytical Perspective on the 2016 US Presidential Election","volume":"111","author":"Li","year":"2021","journal-title":"Ann. Am. Assoc. Geogr."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.ecocom.2009.02.002","article-title":"Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area, China","volume":"6","author":"Li","year":"2009","journal-title":"Ecol. Complex."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.ecolind.2018.08.059","article-title":"Spatial-temporal pattern of, and driving forces for, urban heat island in China","volume":"96","author":"Peng","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Niu, L., Peng, Z., Tang, R., and Zhang, Z. (2021, January 11\u201316). Development of a long-term dataset of China surface urban heat island for policy making: Spatio-temporal characteristics. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9554127"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.rse.2006.06.026","article-title":"New refinements and validation of the MODIS land-surface temperature\/emissivity products","volume":"112","author":"Wan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_52","unstructured":"Bontemps, S., Defourny, P., Radoux, J., Van Bogaert, E., Lamarche, C., Achard, F., Mayaux, P., Boettcher, M., Brockmann, C., and Kirches, G. (2013, January 9\u201313). Consistent global land cover maps for climate modelling communities: Current achievements of the ESA\u2019s land cover CCI. Proceedings of the ESA Living Planet Symposium, Edinburgh, UK."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2006.06.018","article-title":"Land-cover change detection using multi-temporal MODIS NDVI data","volume":"105","author":"Lunetta","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.5194\/essd-11-1931-2019","article-title":"1 km monthly temperature and precipitation dataset for China from 1901 to 2017","volume":"11","author":"Peng","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"3273","DOI":"10.5194\/acp-20-3273-2020","article-title":"Improved 1 km resolution PM2.5 estimates across China using enhanced space\u2013time extremely randomized trees","volume":"20","author":"Wei","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"112136","DOI":"10.1016\/j.rse.2020.112136","article-title":"Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: Spatiotemporal variations and policy implications","volume":"252","author":"Wei","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41597-020-0510-y","article-title":"A harmonized global nighttime light dataset 1992\u20132018","volume":"7","author":"Li","year":"2020","journal-title":"Sci. Data"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.rse.2005.11.016","article-title":"Remote sensing image-based analysis of the relationship between urban heat island and land use\/cover changes","volume":"104","author":"Chen","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_59","first-page":"163","article-title":"Multi-temporal NDVI and surface temperature analysis for Urban Heat Island inbuilt surrounding of sub-humid region: A case study of two geographical regions","volume":"10","author":"Rani","year":"2018","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"e2019GL084288","DOI":"10.1029\/2019GL084288","article-title":"PM2.5 pollution modulates wintertime urban heat island intensity in the Beijing-Tianjin-Hebei Megalopolis, China","volume":"47","author":"Yang","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.scitotenv.2011.10.043","article-title":"A study of urban heat island and its association with particulate matter during winter months over Delhi","volume":"414","author":"Pandey","year":"2012","journal-title":"Sci. Total Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"5439","DOI":"10.5194\/acp-17-5439-2017","article-title":"Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China","volume":"17","author":"Zhong","year":"2017","journal-title":"Atmos. Chem. Phys."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"103873","DOI":"10.1016\/j.landurbplan.2020.103873","article-title":"How to effectively mitigate urban heat island effect? A perspective of waterbody patch size threshold","volume":"202","author":"Peng","year":"2020","journal-title":"Landsc. Urban Plann."},{"key":"ref_64","first-page":"269","article-title":"A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability","volume":"74","author":"Chakraborty","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.isprsjprs.2020.07.021","article-title":"A spatially explicit surface urban heat island database for the United States: Characterization, uncertainties, and possible applications","volume":"168","author":"Chakraborty","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"119932","DOI":"10.1016\/j.energy.2021.119932","article-title":"Industrial electricity consumption and economic growth: A spatio-temporal analysis across prefecture-level cities in China from 1999 to 2014","volume":"222","author":"Cui","year":"2021","journal-title":"Energy"},{"key":"ref_67","unstructured":"Fotheringham, A.S., Brunsdon, C., and Charlton, M. (2003). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, John Wiley & Sons."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"e2020AV000303","DOI":"10.1029\/2020AV000303","article-title":"Urban forests as main regulator of the evaporative cooling effect in cities","volume":"2","author":"Paschalis","year":"2021","journal-title":"AGU Adv."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4428\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:25:26Z","timestamp":1760167526000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4428"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,3]]},"references-count":68,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214428"],"URL":"https:\/\/doi.org\/10.3390\/rs13214428","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,3]]}}}