{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T21:51:42Z","timestamp":1775857902843,"version":"3.50.1"},"reference-count":92,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T00:00:00Z","timestamp":1579219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japan Society for the Promotion of Science (JSPS),Grant-in-Aid for Scientific Research (B)","award":["18H00763"],"award-info":[{"award-number":["18H00763"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite-derived land surface temperature (LST) reveals the variations and impacts on the terrestrial thermal environment on a broad spatial scale. The drastic growth of urbanization-induced impervious surfaces and the urban population has generated a remarkably increasing influence on the urban thermal environment in China. This research was aimed to investigate land surface temperature (LST) intensity response to urban land cover\/use by examining the thermal impact on urban settings in ten Chinese megacities (i.e., Beijing, Dongguan, Guangzhou, Hangzhou, Harbin, Nanjing, Shenyang, Suzhou, Tianjin, and Wuhan). Surface urban heat island (SUHI) footprints were scrutinized and compared by magnitude and extent. The causal mechanism among land cover composition (LCC), population, and SUHI was also identified. Spatial patterns of the thermal environments were identical to those of land cover\/use. In addition, most impervious surface materials (greater than 81%) were labeled as heat sources, on the other hand, water and vegetation were functioned as heat sinks. More than 85% of heat budgets in Beijing and Guangzhou were generated from impervious surfaces. SUHI for all megacities showed spatially gradient decays between urban and surrounding rural areas; further, temperature peaks are not always dominant in the urban core, despite extremely dense impervious surfaces. The composition ratio of land cover (LCC%) negatively correlates with SUHI intensity (SUHII), whereas the population positively associates with SUHII. For all targeted megacities, land cover composition and population account for more than 63.9% of SUHI formation using geographically weighted regression. The findings can help optimize land cover\/use to relieve pressure from rapid urbanization, maintain urban ecological balance, and meet the demands of sustainable urban growth.<\/jats:p>","DOI":"10.3390\/rs12020307","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T07:39:02Z","timestamp":1579246742000},"page":"307","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Impacts of Land Cover\/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7779-6970","authenticated-orcid":false,"given":"Fei","family":"Liu","sequence":"first","affiliation":[{"name":"Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinmin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4397-6882","authenticated-orcid":false,"given":"Yuji","family":"Murayama","sequence":"additional","affiliation":[{"name":"Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6203-5933","authenticated-orcid":false,"given":"Takehiro","family":"Morimoto","sequence":"additional","affiliation":[{"name":"Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,17]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division, (UN DESA) (2015). World Population Prospects: The 2015 Revision, UN DESA."},{"key":"ref_2","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_3","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.rser.2013.05.057","article-title":"The city and urban heat islands: A review of strategies to mitigate adverse effects","volume":"25","author":"Gago","year":"2013","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_4","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_5","unstructured":"United Nations Development Programme (UNDP) (2016). Sustainable Urbanization Strategy, UNDP."},{"key":"ref_6","first-page":"433","article-title":"Sustainable development goals and inclusive development","volume":"16","author":"Gupta","year":"2016","journal-title":"Int. Environ. Agreem. Polit. Law Econ."},{"key":"ref_7","unstructured":"(2019, August 27). United Nations (UN).Transforming Our World: The 2030 Agenda for Sustainable Development. Available online: https:\/\/sustainabledevelopment.un.org\/post2015\/transformingourworld."},{"key":"ref_8","unstructured":"(2019, July 03). National Bureau of Statistics (NBS) of China, Available online: http:\/\/www.stats.gov.cn\/english\/."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1007\/s11434-012-5568-2","article-title":"Spatiotemporal dynamics of impervious surface areas across China during the early 21st century","volume":"58","author":"Kuang","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s11442-014-1082-6","article-title":"Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s","volume":"24","author":"Liu","year":"2014","journal-title":"J. Geogr. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2033","DOI":"10.3390\/rs4072033","article-title":"The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou, South China","volume":"4","author":"Xiong","year":"2012","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.scitotenv.2018.02.074","article-title":"Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China","volume":"628","author":"Zhou","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.cosust.2010.12.010","article-title":"Impacts and mitigation of climate change on Chinese cities","volume":"3","author":"Liu","year":"2011","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"3670","DOI":"10.3390\/rs70403670","article-title":"Spatiotemporal variation in surface urban heat island intensity and associated determinants across major Chinese cities","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1016\/j.scitotenv.2017.07.217","article-title":"Temporal trends of surface urban heat islands and associated determinants in major Chinese cities","volume":"609","author":"Yao","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_17","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_18","first-page":"2","article-title":"The footprint of urban heat island effect in China","volume":"5","author":"Zhou","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/BF02918748","article-title":"Impact of land use changes on surface warming in China","volume":"22","author":"Zhang","year":"2005","journal-title":"Adv. Atmos. Sci."},{"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":"377","DOI":"10.1177\/2399808317716935","article-title":"Spatially varying relationships between surface urban heat islands and driving factors across cities in China","volume":"46","author":"Huang","year":"2019","journal-title":"Environ. Plan. B Urban Anal. City Sci."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2017.01.001","article-title":"Characterizing the relationship between land use land cover change and land surface temperature","volume":"124","author":"Tran","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.jenvman.2018.05.024","article-title":"Interannual variations in surface urban heat island intensity and associated drivers in China","volume":"222","author":"Yao","year":"2018","journal-title":"J. Environ. Manag."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chen, W., Zhang, Y., Pengwang, C., and Gao, W. (2017). Evaluation of urbanization dynamics and its impacts on surface heat islands: A case study of Beijing, China. Remote Sens., 9.","DOI":"10.3390\/rs9050453"},{"key":"ref_26","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_27","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.scs.2017.01.017","article-title":"Comparison of urban heat island and urban reflection in Nanjing City of China","volume":"31","author":"Xu","year":"2017","journal-title":"Sustain. Cities Soc."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"084993","DOI":"10.1117\/1.JRS.8.084993","article-title":"Impact of land cover and population density on land surface temperature: Case study in Wuhan, China","volume":"8","author":"Li","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.scs.2017.05.005","article-title":"An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables","volume":"32","author":"Zhang","year":"2017","journal-title":"Sustain. Cities Soc."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.apgeog.2013.07.021","article-title":"Analysis of land use\/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China","volume":"44","author":"Zhang","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Deilami, K., Kamruzzaman, M., and Hayes, J.F. (2016). Correlation or causality between land cover patterns and the urban heat island effect? Evidence from Brisbane, Australia. Remote Sens., 8.","DOI":"10.3390\/rs8090716"},{"key":"ref_32","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_33","doi-asserted-by":"crossref","unstructured":"Luo, X., and Peng, Y. (2016). Scale effects of the relationships between urban heat islands and impact factors based on a geographically-weighted regression model. Remote Sens., 8.","DOI":"10.3390\/rs8090760"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.scitotenv.2017.01.191","article-title":"Linking potential heat source and sink to urban heat island: Heterogeneous effects of landscape pattern on land surface temperature","volume":"586","author":"Li","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Li, F., Sun, W., Yang, G., and Weng, Q. (2019). Investigating spatiotemporal patterns of surface urban heat islands in the Hangzhou Metropolitan Area, China, 2000\u20132015. Remote Sens., 11.","DOI":"10.3390\/rs11131553"},{"key":"ref_36","unstructured":"Naughton, B.J. (2006). The Chinese Economy: Transitions and Growth, MIT Press."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1007\/s11434-015-0864-2","article-title":"Modulation of the urban heat island by the tourism during the Chinese New Year holiday: A case study in Sanya City, Hainan Province of China","volume":"60","author":"Zhang","year":"2015","journal-title":"Sci. Bull."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zhang, X., Wang, D., Hao, H., Zhang, F., and Hu, Y. (2017). Effects of land use\/cover changes and urban forest configuration on urban heat islands in a loess hilly region: Case study based on Yan\u2019an City, China. Int. J. Environ. Res. Public Health, 14.","DOI":"10.3390\/ijerph14080840"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1080\/13504509.2010.490333","article-title":"Spatiotemporal changes of the urban heat island of a coastal city in the context of urbanisation","volume":"17","author":"Zhao","year":"2010","journal-title":"Int. J. Sustain. Dev. World Ecol."},{"key":"ref_40","unstructured":"The National Development and Reform Comimission (NDRC) (2019, September 20). China\u2019s National Climate Change Program (June 2007), Available online: http:\/\/www.china-un.org\/eng\/gyzg\/t626117.htm."},{"key":"ref_41","unstructured":"Williams, L. (2019, September 20). China\u2019s Climate Change Policies: Actors and Drivers. Available online: https:\/\/www.lowyinstitute.org\/publications\/chinas-climate-change-policies-actors-and-drivers."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.scitotenv.2016.07.012","article-title":"Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta Urban Agglomeration","volume":"571","author":"Du","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_43","first-page":"2","article-title":"Landsat evaluation of land cover composition and its impacts on urban thermal environment: A case study on the fast-growing Shanghai Metropolitan Area from 2000 to 2015","volume":"S3","author":"Liu","year":"2018","journal-title":"Geoinfor Geostat Overv."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.landurbplan.2018.07.007","article-title":"Six fundamental aspects for conceptualizing multidimensional urban form: A spatial mapping perspective","volume":"179","author":"Wentz","year":"2018","journal-title":"Landsc. Urban Plan."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"170001","DOI":"10.1038\/sdata.2017.1","article-title":"High resolution global gridded data for use in population studies","volume":"4","author":"Lloyd","year":"2017","journal-title":"Sci. Data"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Stevens, F.R., Gaughan, A.E., Linard, C., and Tatem, A.J. (2015). Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0107042"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1038\/sdata.2017.4","article-title":"WorldPop, open data for spatial demography","volume":"4","author":"Tatem","year":"2017","journal-title":"Sci. Data"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Phiri, D., and Morgenroth, J. (2017). Developments in Landsat land cover classification methods: A review. Remote Sens., 9.","DOI":"10.3390\/rs9090967"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/01431160600746456","article-title":"A survey of image classification methods and techniques for improving classification performance","volume":"28","author":"Lu","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s10980-013-9950-5","article-title":"Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures","volume":"29","author":"Zhou","year":"2014","journal-title":"Landsc. Ecol."},{"key":"ref_51","unstructured":"Laben, C.A., and Brower, B.V. (2000). Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pan-Sharpening. (No. 6,011,875), U.S. Patent."},{"key":"ref_52","first-page":"12","article-title":"Performance analyzing of high resolution pan-sharpening techniques: Increasing image quality for classification using supervised kernel support vector machine","volume":"3","author":"Yuhendra","year":"2011","journal-title":"Res. J. Inf. Technol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Anderson, J.R. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data.","DOI":"10.3133\/pp964"},{"key":"ref_54","first-page":"419","article-title":"Accuracy assessment of satellite derived land-cover data: A review","volume":"60","author":"Janssen","year":"1994","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Galve, J.M., S\u00e1nchez, J.M., Coll, C., and Villodre, J. (2018). A new single-band pixel-by-pixel atmospheric correction method to improve the accuracy in remote sensing estimates of LST. application to Landsat 7-ETM+. Remote Sens., 10.","DOI":"10.3390\/rs10060826"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"83","DOI":"10.3390\/rs3010083","article-title":"Satellite-observed urbanization characters in Shanghai, China: Aerosols, urban heat island effect, and land-atmosphere interactions","volume":"3","author":"Jin","year":"2011","journal-title":"Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2490","DOI":"10.1109\/36.964986","article-title":"Atmospheric correction of Landsat ETM+ land surface imagery\u2014Part I: Methods","volume":"39","author":"Liang","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","unstructured":"McCarville, D., Buenemann, M., Bleiweiss, M., and Barsi, J. (2011, January 1\u20135). Atmospheric correction of Landsat thermal infrared data: A calculator based on North American Regional Reanalysis (NARR) data. Proceedings of the American Society for Photogrammetry and Remote Sensing Conference, Milwaukee, WI, USA."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Tardy, B., Rivalland, V., Huc, M., Hagolle, O., Marcq, S., and Boulet, G. (2016). A software tool for atmospheric correction and surface temperature estimation of Landsat infrared thermal data. Remote Sens., 8.","DOI":"10.3390\/rs8090696"},{"key":"ref_60","first-page":"58820E","article-title":"Validation of a web-based atmospheric correction tool for single thermal band instruments","volume":"5882","author":"Barsi","year":"2005","journal-title":"Earth Obs. Syst. X"},{"key":"ref_61","unstructured":"Barsi, A.J., Barker, L.J., and Schott, R.J. (2003, January 21\u201325). An atmospheric correction parameter calculator for a single thermal band earth-sensing instrument. Proceedings of the 2003 IEEE International Geoscience and Remote Sensing Symposium (IEEE Cat. No. 03CH37477), IGARSS, Toulouse, France."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"9782686","DOI":"10.1155\/2016\/9782686","article-title":"Surface heat island in Shanghai and its relationship with urban development from 1989 to 2013","volume":"2016","author":"Chen","year":"2016","journal-title":"Adv. Meteorol."},{"key":"ref_63","first-page":"899","article-title":"Review of methods for land surface temperature derived from thermal infrared remotely sensed data","volume":"20","author":"Li","year":"2016","journal-title":"J. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.accre.2015.07.001","article-title":"Influence of urbanization on the thermal environment of meteorological station: Satellite-observed evidence","volume":"6","author":"Shi","year":"2015","journal-title":"Adv. Clim. Chang. Res."},{"key":"ref_65","unstructured":"Ahn, S., and Fessler, J.A. (2019, October 10). Standard Errors of Mean, Variance, and Standard Deviation Estimators. Available online: https:\/\/web.eecs.umich.edu\/~fessler\/papers\/lists\/files\/tr\/stderr.pdf."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1007\/s12665-009-0096-3","article-title":"An ERDAS image processing method for retrieving LST and describing urban heat evolution: A case study in the Pearl River Delta Region in South China","volume":"59","author":"Sun","year":"2009","journal-title":"Environ. Earth Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.landusepol.2015.05.017","article-title":"Intensity and spatial pattern of urban land changes in the megacities of Southeast Asia","volume":"48","author":"Estoque","year":"2015","journal-title":"Land Use Policy"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Dissanayake, D.M.S.L.B., 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_69","doi-asserted-by":"crossref","unstructured":"Dissanayake, D., Morimoto, T., Murayama, Y., Ranagalage, M., and Handayani, H.H. (2018). Impact of urban surface characteristics and socio-economic variables on the spatial variation of land surface temperature in Lagos City, Nigeria. Sustainability, 11.","DOI":"10.3390\/su11010025"},{"key":"ref_70","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_71","first-page":"276","article-title":"Remote sensing of the urban heat island and its changes in Xiamen City of SE China","volume":"16","author":"Xu","year":"2004","journal-title":"J. Environ. Sci."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Xiao, H., Kopeck\u00e1, M., Guo, S., Guan, Y., Cai, D., Zhang, C., Zhang, X., and Yao, W. (2018). Responses of urban land surface temperature on land cover: A comparative study of Vienna and Madrid. Sustainability, 10.","DOI":"10.3390\/su10020260"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Simwanda, M., Ranagalage, M., Estoque, R.C., and Murayama, Y. (2019). Spatial analysis of surface urban heat islands in four rapidly growing African cities. Remote Sens., 11.","DOI":"10.3390\/rs11141645"},{"key":"ref_74","first-page":"597","article-title":"Impact of land use on urban land surface temperature: A case study of Dongguan, Guangdong Province","volume":"26","author":"Liu","year":"2006","journal-title":"Sci. Geogr. Sin."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/s10666-014-9426-2","article-title":"The effect of urban expansion on urban surface temperature in Shenyang, China: An analysis with Landsat imagery","volume":"20","author":"Lu","year":"2015","journal-title":"Environ. Model. Assess."},{"key":"ref_76","first-page":"761","article-title":"Pearl River Delta land cover change on surface temperature effects","volume":"60","author":"Qian","year":"2005","journal-title":"Acta Geogr. Sin."},{"key":"ref_77","first-page":"68","article-title":"A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States","volume":"10","author":"Weng","year":"2008","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_78","unstructured":"Wilks, D.S. (2011). Statistical Methods in the Atmospheric Sciences, Academic Press."},{"key":"ref_79","first-page":"186","article-title":"The data model concept in statistical mapping","volume":"7","author":"Jenks","year":"1967","journal-title":"Int. Yearb. Cartogr."},{"key":"ref_80","first-page":"645","article-title":"Relationship between urban heat island phenomenon and land use\/land cover changes in Jakarta\u2014Indonesia","volume":"3","author":"Tursilowati","year":"2012","journal-title":"J. Emerg. Trends Eng. Appl. Sci."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s10708-007-9104-x","article-title":"Potential for global mapping of development via a nightsat mission","volume":"69","author":"Elvidge","year":"2007","journal-title":"GeoJournal"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1016\/j.jenvman.2017.03.095","article-title":"The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete","volume":"197","author":"Mohajerani","year":"2017","journal-title":"J. Environ. Manag."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Taha, H., Sailor, D., and Municipal, S. (1992). High-Albedo Materials for Reducing Building Cooling Energy Use.","DOI":"10.2172\/7000986"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.ufug.2015.11.013","article-title":"The role of green roofs in mitigating Urban Heat Island effects in the metropolitan area of Adelaide, South Australia","volume":"15","author":"Razzaghmanesh","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"2846","DOI":"10.1175\/2008JAMC1830.1","article-title":"On the use of cool materials as a heat island mitigation strategy","volume":"47","author":"Synnefa","year":"2008","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1002\/2017EF000569","article-title":"Albedo, land cover, and daytime surface temperature variation across an urbanized landscape","volume":"5","author":"Trlica","year":"2017","journal-title":"Earth\u2019s Futur."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.landurbplan.2014.04.018","article-title":"Effects of spatial pattern of greenspace on urban cooling in a large metropolitan area of eastern China","volume":"128","author":"Kong","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1016\/j.scitotenv.2017.01.158","article-title":"Utilising green and bluespace to mitigate urban heat island intensity","volume":"584\u2013585","author":"Gunawardena","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_89","first-page":"326","article-title":"The impact of urban green spaces on climate and air quality in cities","volume":"2","author":"Szaras","year":"2014","journal-title":"Geogr. Locality Stud."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.landurbplan.2016.10.001","article-title":"Simulating the cooling effects of water spray systems in urban landscapes: A computational fluid dynamics study in Rotterdam, The Netherlands","volume":"159","author":"Montazeri","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.compenvurbsys.2013.12.002","article-title":"Using street based metrics to characterize urban typologies","volume":"44","author":"Hermosilla","year":"2014","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/j.compenvurbsys.2011.05.008","article-title":"Derivation of the functional relations between fractal dimension of and shape indices of urban form","volume":"35","author":"Chen","year":"2011","journal-title":"Comput. Environ. Urban Syst."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/2\/307\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:20:01Z","timestamp":1760361601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/2\/307"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,17]]},"references-count":92,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2020,1]]}},"alternative-id":["rs12020307"],"URL":"https:\/\/doi.org\/10.3390\/rs12020307","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,17]]}}}