Spatiotemporal analysis of urban heat island intensification in the city of Minneapolis-St. Paul and Chicago metropolitan areas using Landsat data from 1984 to 2016

Reference

• Akbari H, Pomerantz M, Taha H. 2001. Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar Energy. 70(3):295–310.
   Web of Science ®Google Scholar
• Alcoforado MJ, Andrade H. 2006. Nocturnal urban heat island in Lisbon (Portugal): main features and modelling attempts. Theor Appl Climatol. 84(1-3):151–159.
   Web of Science ®Google Scholar
• Amiri R, Weng Q, Alimohammadi A, Alavipanah SK. 2009. Spatial–temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sens Environ. 113(12):2606–2617.
   Web of Science ®Google Scholar
• Andersson-Sköld Y, Klingberg J, Gunnarsson B, Cullinane K, Gustafsson I, Hedblom M, Knez I, Lindberg F, Ode Sang Å, Pleijel H, et al. 2018. A framework for assessing urban greenery’s effects and valuing its ecosystem services. J Environ Manage. 205:274–285.
   PubMed Web of Science ®Google Scholar
• Angel J. Climate of Illinois narrative (climate of Chicago) - Description, Illinois State Climatologist Office, Illinois State Water Survey, University of IIIinois Urbana-Champaign. https://www.isws.illinois.edu/statecli/General/chicago-climate-narrative.htm
   Google Scholar
• Artis DA, Carnahan WH. 1982. Survey of emissivity variability in thermography of urban areas. Remote Sens Environ. 12(4):313–329.
   Web of Science ®Google Scholar
• Baker LA, Brazel AT, Westerhoff P. 2004. Environmental consequences of rapid urbanization in warm, arid lands: case study of Phoenix, Arizona (USA). WIT Trans Ecol Environ. 72.
   Google Scholar
• Barsi JA, Lee K, Kvaran G, Markham BL, Pedelty JA. 2014. The spectral response of the Landsat-8 operational land imager. Remote Sens. 6(10):10232–10251.
   Web of Science ®Google Scholar
• Becker F, Li Z-L. 1990. Towards a local split window method over land surfaces. Int J Remote Sens. 11(3):369–393.
   Web of Science ®Google Scholar
• Bhargava A, Lakmini S, Bhargava S. 2017. Urban heat island effect: it’s relevance in urban planning. J Biodivers Endanger Species. 5:187.
   Google Scholar
• Bottyán Z, Unger J. 2003. A multiple linear statistical model for estimating the mean maximum urban heat island. Theor Appl Climatol. 75(3):233–243.
   Web of Science ®Google Scholar
• Brown MJ, Ivey A, McPherson TN, Boswell D, Pardyjak ER. 2004. A study of the Oklahoma City urban heat island using ground measurements and remote sensing. Preprints, Fifth Symposium on the Urban Environment, Vancouver, BC, Canada, American Meteor Society, 2.5A. https://ams.confex.com/ams/pdfpapers/80316.pdf.
   Google Scholar
• Cao L, Li P, Zhang L, Chen T. 2008. Remote sensing image-based analysis of the relationship between urban heat island and vegetation fraction. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing.
   Google Scholar
• Chander G, Markham B. 2003. Revised Landsat-5 tm radiometric calibration procedures and postcalibration dynamic ranges. IEEE Trans Geosci Remote Sens. 41(11):2674–2677.
   Web of Science ®Google Scholar
• Chen J, Chen YH, He CY, Shi PJ. 2001. Sub-pixel model for vegetation fraction estimation based on land cover classification. J Remote Sens Beijing. 5:422–426.
   Google Scholar
• Chen XL, Zhao HM, Li PX, Yin ZY. 2006. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens. Environ. 104:133–146.
   Web of Science ®Google Scholar
• Chen YH, Wang J, Li XB. 2002. A study on urban thermal field in summer based on satellite remote sensing. Remote Sens Land Resour. 4:55–59.
   Google Scholar
• Cheng J, Liang S, Jindi W, Li X. 2010. A stepwise refining algorithm of temperature and emissivity separation for hyperspectral thermal infrared data. IEEE Trans Geosci Remote Sens. 48:1588–1597.
   Web of Science ®Google Scholar
• Declet-Barreto J, Brazel AJ, Martin CA, Chow WT, Harlan SL. 2013. Creating the park cool island in an inner-city neighborhood: heat mitigation strategy for Phoenix, AZ. Urban Ecosyst. 16(3):617–635.
   Web of Science ®Google Scholar
• Dousset B. 1989. AVHRR-derived cloudiness and surface temperature patterns over the Los Angeles area and their relationships to land use. 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium. IGARSS'89; July 10–14; Vancouver, Canada: IEEE; p. 2132–2137.
   Google Scholar
• Effat HA, Taha LG, Mansour KF. 2014. Change detection of land over and urban heat islands using multi-temporal landsat images, application in Tanta City, Egypt. Open J Rem Sens Position. 1(2). doi:10.15764/RSP.2014.02001..
   Google Scholar
• Ellicott E, Vermote E, Petitcolin F, J, Hook S. 2009. Validation of a new parametric model for atmospheric correction of thermal infrared data. IEEE Trans Geosci Remote Sens. 47(1):295–311.
   Web of Science ®Google Scholar
• Erickson LE. 2017. Reducing greenhouse gas emissions and improving air quality: two global challenges. Environ Prog Sustain Energy. 36(4):982–988.
   PubMed Web of Science ®Google Scholar
• Finn MP, Reed MD, Yamamoto KH. 2012. A straight forward guide for processing radiance and reflectance for EO-1 ALI, Landsat 5 TM, Landsat 7 ETM and ASTER. http://cegis.usgs.gov/soil_moisture/pdf/A%20Straight %20Forward%20guide%20for%20Processing%20Radiance%20and%20Reflectance_V_24Jul12.pdf.
   Google Scholar
• Gallo KP, Adegoke JO, Owen TW, Elvidge CD. 2002. Satellite-based detection of global urban heat-island temperature influence. J Geophys Res. 107(D24):4776. 2002.
   Web of Science ®Google Scholar
• Gallo KP, Owen TW. 1998. Assessment of urban heat islands: a multi‐sensor perspective for the Dallas‐Ft. worth, USA region. Geocarto Int. 13(4):35–41.
   Google Scholar
• Gillespie A, Rokugawa S, Matsunaga T, Cothern JS, Hook S, Kahle AB. 1998. A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Trans Geosci Remote Sens. 36(4):1113–1126.
   Web of Science ®Google Scholar
• Green Roofs for Healthy Cities. 2016. San Francisco poised to be the first major U.S. city to pass requirements for green roofs on new buildings. http://www.marketwired.com/press-release/san-francisco-poised-be-first-major-us-city-pass-requirements-green-roofs-on-new-buildings-2159098.htm.
   Google Scholar
• Grover A, Singh RB. 2015. Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): a comparative study of Delhi and Mumbai. Environments. 2(4):125–138.
   Google Scholar
• Guhathakurta S, Gober P. 2007. The impact of the Phoenix urban heat island on residential water use. J Am Plan Assoc. 73(3):317–329.
   Web of Science ®Google Scholar
• Gullickson R. 2017. U.S. metro economies (PDF). IHS global insight; [accessed February 1]. https://www.munibondsforamerica.org/cms/wp-content/uploads/2013/06/Metro-Economies_Job-Impact-to-Municipal-Bonds_June-2013-1.pdf
   Google Scholar
• Howard L. 1833. The climate of London, Vol. 2. London (UK): London Harvey and Dorton; p. 1818–1820.
   Google Scholar
• IPCC. 2013. Summary for policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, and Midgley PM, editors. Climate change 2013: the physical science basis. Contribution of Working Group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge (UK): Cambridge University Press. p. 29.
   Google Scholar
• Jiménez‐Muñoz JC, Sobrino JA. 2003. A generalized single-channel method for retrieving land surface temperature from remote sensing data. J Geophys Res Atmos. 108:22.
   Web of Science ®Google Scholar
• Jiménez-Muñoz JC, Sobrino JA, Gillespie A, Sabol D, Gustafson WT. 2006. Improved land surface emissivities over agricultural areas using ASTER NDVI. Remote Sens Environ. 103(4):474–487.
   Web of Science ®Google Scholar
• Jiménez-Muñoz JC, Sobrino JA, Plaza A, Guanter L, Moreno J, Martínez P. 2009. Comparison between fractional vegetation cover retrievals from vegetation indices and spectral mixture analysis: case study of PROBA/CHRIS data over an agricultural area. Sensors. 9(2):768–793.
   PubMed Web of Science ®Google Scholar
• Jones KL, Poole GC, Meyer JL, Bumback W, Kramer EA. 2006. Quantifying expected ecological response to natural resource legislation: a case study of riparian buffers, aquatic habitat, and trout populations. Ecol Soc. 11(2):15.
   Web of Science ®Google Scholar
• Julien Y, Sobrino JA, Mattar C, Ruescas AB, Jiménez-Muñoz JC, Sòria G, Hidalgo V, Atitar M, Franch B, Cuenca J. 2011. Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001. Int J Remote Sens. 32(7):2057–2068.
   Web of Science ®Google Scholar
• Kahn B. 2014. Seventeen U.S. cities on track for hottest year | climate central. http://www.climatecentral.org/news/us-cities-hottest-year-18496
   Google Scholar
• Kant Y, Bharath BD, Mallick J, Atzberger C, Kerle N. 2009. Satellite-based analysis of the role of land use/land cover and vegetation density on surface temperature regime of Delhi, India. J Indian Soc Remote Sens. 37(2):201–214.
   Web of Science ®Google Scholar
• Karl T, Diaz H, Kukla G. 1988. Urbanization: its detection and effect in the United States climate record. J Clim. 1(11):1099–1123.
   Web of Science ®Google Scholar
• Kawashima S. 1994. Relation between vegetation, surface temperature, and surface composition in the Tokyo region during winter. Remote Sens Environ. 50(1):52–60.
   Web of Science ®Google Scholar
• Kendall I, Sabri H, Michell B. 2016. Green roofs effects on urban environments. https://www.epa.gov/green-infrastructure/reduce-urban-heat-island-effect.
   Google Scholar
• Ketterer C, Matzarakis A. 2015. Comparison of different methods for the assessment of the urban heat island in Stuttgart, Germany. Int J Biometeorol. 59(9):1299–1309.
   PubMed Web of Science ®Google Scholar
• Kim J-P, Guldmann J-M. 2014. Land-use planning and the urban heat island. Land-use planning and the urban heat island. Environ Plan B Plan Des. 41(6):1077–1099.
   Google Scholar
• Köhler M, Schmidt M, Grimme FW, Laar M, Lúcia V, Tavares S. 2002. Green roofs in temperate climates and in the hot‐humid tropics – far beyond the aesthetics. Environ Manage Health. 13(4):382–391.
   Google Scholar
• Kuang W, Chi W, Lu D, Dou Y. 2014. A comparative analysis of megacity expansions in China and the US: patterns, rates and driving forces. Landsc Urban Plan. 132:121–135.
   Web of Science ®Google Scholar
• Kuang W, Liu Y, Dou Y, Chi W, Chen G, Gao C, Yang T, Liu J, Zhang R. 2015. What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China. Landsc Ecol. 30(2):357–373.
   Web of Science ®Google Scholar
• Landsat 8 data users handbook | landsat missions. https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/LSDS-1574_L8_Data_Users_Handbook_v4.pdf
   Google Scholar
• Landsberg HE. 1981. Landsat 7 (L7) data users handbook, Vol. 2014. New York (NY): The Urban Climate Academic Press; p. 154.
   Google Scholar
• Laureti F, Martinelli L, Battisti A. 2018. Assessment and mitigation strategies to counteract overheating in urban historical areas in Rome. Climate. 6:18.
   Web of Science ®Google Scholar
• Lee ACK, Jordan HC, Horsley J. 2015. Value of urban green spaces in promoting healthy living and wellbeing: prospects for planning. Risk Manage Healthc Policy. 8:131–137.
   PubMed Web of Science ®Google Scholar
• Li F, Jackson TJ, Kustas WP, Schmugge TJ, French AN, Cosh MH, Bindlish R. 2004. Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX. Remote Sens Environ. 92:521–534.
   Web of Science ®Google Scholar
• Li Z-L, Wu H, Wang N, Qiu S, Sobrino JA, Wan Z, Tang B-H, Yan G. 2013. Land surface emissivity retrieval from satellite data. Int J Remote Sens. 34(9-10):3084–3127.
   Web of Science ®Google Scholar
• Lin P, Lau SSY, Qin H, Gou Z. 2017. Effects of urban planning indicators on urban heat island: a case study of pocket parks in high-rise high-density environment. Landsc Urban Plan. 168:48–60.
   Web of Science ®Google Scholar
• Liu L, Zhang Y. 2011. Urban heat island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sens. 3(7):1535–1552.
   Web of Science ®Google Scholar
• Lo CP, Quattrochi DA. 2003. Land-use and land-cover change, urban heat island phenomenon, and health implications. Photogramm Eng Remote Sens. 69:1053–1063.
   Web of Science ®Google Scholar
• Lu Y, Feng X, Xiao P, Shen C, Sun J. 2009. Urban heat island in summer of Nanjing based on TM data. 2009 Joint Urban Remote Sensing Event; May 20–22; Shanghai (China): IEEE; p. 1–5.
   Google Scholar
• Lynn BH, Carlson TN, Rosenzweig C, Goldberg R, Druyan L, Cox J, Gaffin S, Parshall L, Civerolo K. 2009. A modification to the NOAH LSM to simulate heat mitigation strategies in the New York City metropolitan area. J Appl Meteor Climatol. 48(2):199–216.
   Web of Science ®Google Scholar
• Ma Y, Kuang Y, Huang N. 2010. Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM + imagery. Int J Appl Earth Observ Geoinf. 12(2):110–118.
   Web of Science ®Google Scholar
• Mallick J, Kant Y, Bharath BD. 2008. Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J Ind Geophys Union. 12:131–140.
   Google Scholar
• Mallick J, Singh CK, Shashtri S, Rahman A, Mukherjee S. 2012. Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city. Int J Appl Earth Observ Geoinf. 19:348–358.
   Web of Science ®Google Scholar
• Masiello G, Serio C, De Feis I, Amoroso M, Venafra S, Trigo IF, Watts P. 2013. Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances. Atmos Meas Tech. 6(12):3613–3634.
   Web of Science ®Google Scholar
• Masiello G, Serio C, Venafra S, Liuzzi G, Göttsche F, F. Trigo I, Watts P. 2015. Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: a validation and intercomparison study. Atmos Meas Tech. 8(7):2981–2997.
   Web of Science ®Google Scholar
• Melillo JM, Richmond T, Yohe GW, editors. 2014. Climate change impacts in the United States: the third national climate assessment. U.S. global change research program, Vol. 841.
   Google Scholar
• Meng X, Cheng J, Liang S. 2017. Estimating land surface temperature from Feng Yun- 3C/MERSI data using a new land surface emissivity scheme. Remote Sens. 9(12):1247.
   Web of Science ®Google Scholar
• Millstein DE, Fischer ML. 2014. Reflective ‘cool’ roofs under aerosol-burdened skies: radiative benefits across selected Indian cities. Environ Res Lett. 9(10):104014.
   Web of Science ®Google Scholar
• Minneapolis/St. Paul Climate Page - Minnesota DNR - MN Department of Natural Resources. https://www.dnr.state.mn.us/climate/twin_cities/listings.html
   Google Scholar
• Ningrum W. 2018. Urban heat island towards urban climate. IOP Conf Ser Earth Environ Sci. 118:012048.
   Google Scholar
• Nowak DJ, Hoehn REI, Bodine AR, Crane DE, Dwyer JF, Bonnewell V, Watson G. 2013. Urban trees and forests of the Chicago region (No. NRS-RB-84). Newtown Square (PA): U.S. Department of Agriculture, Forest Service, Northern Research Station.
   Google Scholar
• Oke TR. 1973. City size and the urban heat island. Atmos Environ. 7(8):769–779.
   Web of Science ®Google Scholar
• Oke TR. 1982. The energetic basis of the urban heat island. Q J R Meteorol Soc. 108:1–24.
   Web of Science ®Google Scholar
• Peng S, Piao S, Ciais P, Friedlingstein P, Ottle C, Bréon F-M, Nan H, Zhou L, Myneni RB. 2012. Surface urban heat island across 419 global big cities. Environ. Sci. Technol. 46(2): 696–703. doi: 10.1021/es2030438
   Google Scholar
• Qin Z, Karnieli A, Berliner P. 2001. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Int J Remote Sens. 22(18):3719–3746.
   Web of Science ®Google Scholar
• Redon EC, Lemonsu A, Masson V, Morille B, Musy M. 2017. Implementation of street trees within the solar radiative exchange parameterization of TEB in SURFEX v8.0. Geosci Model Dev. 10(1):385–411.
   Web of Science ®Google Scholar
• Rehan RM. 2016. Cool city as a sustainable example of heat island management case study of the coolest city in the world. HBRC J. 12(2):191–204.
   Google Scholar
• Ritchie H, Roser M. 2018. Urbanization - our world in data; [accessed 2019 Jul 9]. https://ourworldindata.org/urbanization
   Google Scholar
• Rouse J, Jr, Haas RH, Schell JA, Deering DW. 1974. Monitoring vegetation systems in the Great Plains with ERTS. In Remote Sensing Center Texas A&M University, College Station, TX, 9.
   Google Scholar
• Roy DP, Kovalskyy V, Zhang HK, Vermote EF, Yan L, Kumar SS, Egorov A. 2016. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens Environ. 185:57–70.
   PubMed Web of Science ®Google Scholar
• Runnalls KE, Oke TR. 2000. Dynamics and controls of the near-surface heat island of Vancouver, British Columbia. Phys Geogr. 21(4):283–304.
   Web of Science ®Google Scholar
• Scott D, Hall CM, Gössling S. 2016. A review of the IPCC fifth assessment and implications for tourism sector climate resilience and decarbonization. J Sustain Tourism. 24:8–30.
   Web of Science ®Google Scholar
• Senanayake IP, Welivitiya WDDP, Nadeeka PM. 2013. Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using Landsat-7 ETM + data. Urban Clim. 5:19–35.
   Google Scholar
• Sharma R, Joshi PK. 2013. Monitoring urban landscape dynamics over Delhi (India) using remote sensing (1998–2011) inputs. J Indian Soc Remote Sens. 41(3):641–650.
   Web of Science ®Google Scholar
• Singh RB, Grover A. 2014. Remote sensing of urban microclimate with special reference to urban heat island using Landsat thermal data. Geogr Pol. 87(4):555–568.
   Google Scholar
• Snyder WC, Wan Z, Zhang Y, Feng YZ. 1998. Classification-based emissivity for land surface temperature measurement from space. Int J Remote Sens. 19(14):2753–2774.
   Web of Science ®Google Scholar
• Sobrino JA, Jiménez-Muñoz JC, Paolini L. 2004. Land surface temperature retrieval from LANDSAT TM 5. Remote Sens Environ. 90(4):434–440.
   Web of Science ®Google Scholar
• Somers KA, Bernhardt ES, Grace JB, Hassett BA, Sudduth EB, Wang S, Urban DL. 2013. Streams in the urban heat island: spatial and temporal variability in temperature. Freshw Sci. 32(1):309–326.
   Web of Science ®Google Scholar
• Stone B. 2007. Urban and rural temperature trends in proximity to large U.S. cities. Int J Climatol. 2007(27):1801.
   Web of Science ®Google Scholar
• Streutker DR. 2002. A remote sensing study of the urban heat island of Houston, Texas. Int J Remote Sens. 23(13):2595–2608.
   Web of Science ®Google Scholar
• Streutker DR. 2003. Satellite-measured growth of the urban heat island of Houston, Texas. Remote Sens Environ. 85(3):282–289.
   Web of Science ®Google Scholar
• Szymanowski M, Kryza M. 2012. Local regression models for spatial interpolation of urban heat island—an example from Wrocław, SW Poland. Theor Appl Climatol. 108(1-2):53–71.
   Web of Science ®Google Scholar
• Tang B-H, Shao K, Li Z-L, Wu H, Tang R. 2015. An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data. Int J Remote Sens. 36(19-20):4864–4878. United States Geological Survey (USGS). 2016; [accessed 12 Dec 2016]. www.earthexplorer.usgs.gov.
   Google Scholar
• University of Minnesota. 2015. New urban heat island study shows surprising variation in air temperatures across Twin Cities | University of Minnesota Twin Cities. Environment Science. https://twin-cities.umn.edu/news-events/new-Urban-heat-island-study-shows-surprising-variation-air-temperatures-across-twin-0.
   Google Scholar
• US EPA, OAR. 2014a. Reduce Urban Heat Island Effect. US EPA. https://www.epa.gov/green-infrastructure/reduce-urban-heat-island-effect.
   Google Scholar
• US EPA, OAR. 2014b. Using green roofs to reduce heat islands. US EPA. https://www.epa.gov/heat-islands/using-green-roofs-reduce-heat-islands.
   Google Scholar
• US EPA, OAR. 2014c. Using trees and vegetation to reduce heat islands. US EPA. https://www.epa.gov/heat-islands/using-trees-and-vegetation-reduce-heat-islands.
   Google Scholar
• US EPA, OAR. 2014d. Reduce Heat Island Risks. US EPA. https://www.epa.gov/heat-islands/reduce-heat-island-risks.
   Google Scholar
• Valor E, Caselles V. 1996. Mapping land surface emissivity from NDVI: application to European, African, and South American areas. Remote Sens Environ. 57(3):167–184.
   Web of Science ®Google Scholar
• Valsson S, Bharat A. 2009. Urban heat island: cause for microclimate variations. Architecture-Time Space & People :2–25.
   Google Scholar
• Van de Griend AA, Owe M. 2003. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Int J Remote Sens. 14(6):1119–1131.
   Web of Science ®Google Scholar
• Vargas-Hernández JG, Pallagst K, Zdunek-Wielgołaska J. 2018. Urban green spaces as a component of an ecosystem. In: J. Marques, editor, Handbook of engaged sustainability. Cham: Springer International Publishing; p. 1–32.
   Google Scholar
• Villanueva-Solis J. 2017. Urban heat island mitigation and urban planning: the case of the Mexicali, B. C. Mexico. Am J Clim Change. 06(01):22.
   Google Scholar
• Voogt JA, Oke TR. 2003. Thermal remote sensing of urban climates. Remote Sens Environ. 86(3):370–384.
   Web of Science ®Google Scholar
• Wan Z, Dozier J. 1996. A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote Sens. 34:892–905.
   Web of Science ®Google Scholar
• Wang F, Qin Z, Song C, Tu L, Karnieli A, Zhao S. 2015. An improved mono-window algorithm for land surface temperature retrieval from Landsat 8 thermal infrared sensor data. Remote Sens. 7(4):4268.
   Web of Science ®Google Scholar
• Weng Q. 2009. Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS J Photogramm Remote Sens. 64(4):335–344.
   Web of Science ®Google Scholar
• Weng Q, Lu D, Schubring J. 2004. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ. 89(4):467–483.
   Web of Science ®Google Scholar
• Xue J, Su B. 2017. Significant remote sensing vegetation indices: a review of developments and applications. J Sensors. 2017(2017):17.
   Web of Science ®Google Scholar
• Yang Q, Huang X, Li J. 2017. Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China. Sci Rep. 7(1):9337.
   PubMed Web of Science ®Google Scholar
• Yu Y, L, Privette J, Privette A. 2008. Evaluation of split-window land surface temperature algorithms for generating climate data records. IEEE Trans Geosci Remote Sens. 46(1):179–192.
   Web of Science ®Google Scholar
• Yuan F, Bauer ME. 2007. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sens Environ. 106(3):375–386.
   Web of Science ®Google Scholar
• Zhang J, Wang Y. 2008. Study of the relationships between the spatial extent of surface urban heat islands and urban characteristic factors based on Landsat ETM + data. Sensors. 8(11):7453–7468.
   PubMed Web of Science ®Google Scholar
• Zhang XX, Wu PF, Chen B. 2010. Relationship between vegetation greenness and urban heat island effect in Beijing City of China. Proced Environ Sci. 2:1438–1450.
   Google Scholar
• Zhang Y, Yiyun C, Qing D, Jiang P. 2012. Study on urban heat island effect based on normalized difference vegetated index: a case study of Wuhan City. Proced Environ Sci. 13:574–581.
   Google Scholar
• Zipper S, Schatz JD, Kucharik CJ, Loheide SP. 2017. Urban heat island-induced increases in evapotranspirative demand. Geophys Res Lett. 44(2):873.
   Web of Science ®Google Scholar