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What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China

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Abstract

Context

Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development.

Objective

The purpose of this study was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer.

Methods

The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes.

Results

Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within the urban area, the mean LST of urban impervious surfaces was about 6–12 °C higher than that of the urban green space. LSTs of built-up areas were on average 3–6 °C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index.

Conclusions

Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. To alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.

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References

  • Alberti M (2009) Advances in urban ecology: integrating humans and ecological processes in urban ecosystems. Springer, New York

    Google Scholar 

  • Asaeda T, Ca VT, Wake A (1996) Heat storage of pavement and its effects on the lower atmosphere. Atmos Environ 30(3):413–427

    Article  CAS  Google Scholar 

  • Becker F, Li ZL (1995) Surface temperature and emissivity at various scales: definition, measurements and related problems. Remote Sens Rev 12:225–253

    Article  Google Scholar 

  • Buyantuyev A, Wu JG (2010) Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landscape Ecol 25(1):17–33

    Article  Google Scholar 

  • Carnahan WH, Larson RC (1990) An analysis of an urban heat sink. Remote Sens Environ 33:65–71

    Article  Google Scholar 

  • Chen SB, Pan LQ (1997) Effects of urbanization on the annual mean temperature of Beijing. Acta Geogr Sin 52(1):27–36 (in Chinese)

    Google Scholar 

  • Connors JP, Galletti CS, Chow W (2013) Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona. Landscape Ecol 28(2):271–283

    Article  Google Scholar 

  • Dale A, Jeffrey C (1999) Thermal infrared remote sensing for analysis of landscape ecological processes: methods and applications. Landscape Ecol 14:577–598

    Article  Google Scholar 

  • Doulos L, Santamouris M, Livada I (2004) Passive cooling of outdoor urban spaces: the role of materials. Sol Energy 77(2):231–249

    Article  CAS  Google Scholar 

  • Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu JG, Bai XM, Briggs JM (2008) Global change and the ecology of cities. Science 319(5864):756–760

    Article  CAS  PubMed  Google Scholar 

  • Hafner J, Kidder SQ (1999) Urban heat island effect modeling in conjunction with satellite-derived surface/soil parameters. J Appl Meteorol 38(4):448–465

    Article  Google Scholar 

  • Hawkins TW, Brazel AJ, Stefanov WL, Bigler W, Saffell EM (2004) The role of rural variability in urban heat island determination for Phoenix, Arizona. J Appl Meteorol 43(3):476–486

    Article  Google Scholar 

  • Humes KS, Kustas WP, Moran MS, Nichols WD, Weltz MA (1994) Variability of emissivity and surface temperature over a sparsely vegetated surface. Water Resour Res 30(5):1299–1310

    Article  Google Scholar 

  • Ji CP, Liu WD, Xuan CY (2006) Impact of urban growth on the heat island in Beijing. Chin J Geophys-ch 49(1):69–77 (in Chinese)

    Google Scholar 

  • Kuang WH (2011) Simulating dynamic urban expansion at regional scale in Beijing–Tianjin–Tangshan metropolitan area. J Geogr Sci 21(2):317–330

    Article  Google Scholar 

  • Kuang WH (2012a) Evaluating impervious surface growth and its impacts on water environment in Beijing–Tianjin–Tangshan metropolitan area. J Geogr Sci 22(3):535–547

    Article  Google Scholar 

  • Kuang WH (2012b) Spatio-temporal patterns of intra-urban land use change in Beijing, China between 1984 and 2008. Chin Geogr Sci 22(2):210–220

    Article  Google Scholar 

  • Kuang WH, Liu JY, Zhang ZX, Lu DS, Xiang B (2013) Spatiotemporal dynamics of impervious surface areas across China during the early 21st century. Chin Sci Bull 58(14):1691–1701

    Article  Google Scholar 

  • Kuang WH, Chi WF, Lu DS, Dou YY (2014) A comparative analysis of megacity expansions in China and the U.S.: patterns, rates and driving forces. Landsc Urban Plan 132:121–135

    Article  Google Scholar 

  • Labed J, Stoll MP (1991) Spatial variability of land surface emissivity in the thermal infrared band: spectral signature and effective surface temperature. Remote Sens Environ 38(1):1–17

    Article  Google Scholar 

  • Li JX, Song CH, Cao L, Zhu FG, Meng XL, Wu JG (2011) Impacts of landscape structure on surface urban heat islands: a case study of Shanghai, China. Remote Sens Environ 115:3249–3263

    Article  Google Scholar 

  • Li XM, Zhou WQ, Ouyang ZY, Xu WH, Zheng H (2012) Spatial pattern of green space affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China. Landscape Ecol 27(6):887–898

    Article  Google Scholar 

  • Li ZL, Tang BH, Wu H, Ren HZ, Yan GJ, Wan ZM, Trigo IF, Sobrino JA (2013) Satellite-derived land surface temperature: current status and perspectives. Remote Sens Environ 131:14–37

    Article  Google Scholar 

  • Lin XC, Yu SQ (2005) Interdecadal changes of temperature in the Beijing region and its heat island effect. Chin J Geophys-ch 48:47–54

    Article  Google Scholar 

  • Liu JY, Zhang ZX, Xu XL, Kuang WH, Zhou WC, Zhang SW, Li RD, Yan CZ, Yu DS, Wu SX, Nan J (2010) Spatial patterns and driving forces of land use change in China during the early 21st century. J Geogr Sci 20:483–494

    Article  Google Scholar 

  • Liu WY, Gong AD, Zhou J, Zhan WF (2011) Investigation on relationships between urban building materials and land surface temperature through a multi-resource remote sensing approach. Remote Sens Inf 4:46–53

    Google Scholar 

  • Liu SM, Xu ZW, Zhu ZL, Jia ZZ, Zhu MJ (2013) Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. J Hydrol 487:24–38

    Article  Google Scholar 

  • Mao KB, Qin ZH, Shi J, Gong P (2005) A practical split-window algorithm for retrieving land surface temperature from MODIS data. Int J Remote Sens 26(15):3181–3204

    Article  Google Scholar 

  • Meyn SK, Oke TR (2009) Heat fluxes through roofs and their relevance to estimates of urban heat storage. Energy Buildings 41(7):745–752

    Article  Google Scholar 

  • Oke TR (1982) The energetic basis of the urban heat island. Q J Roy Meteor Soc 108:1–24

    Google Scholar 

  • Oke TR (1984) Methods in urban climatology. In: Kirchhofer W, Ohmura A, Wanner H (eds) Applied climatology, Zürcher Geogr. Schriften 14:19–29

  • Oke TR (1995) The heat island of the urban boundary layer: characteristics, causes and effects. In: Cermak JE, Davenport AG, Plate EJ et al (eds) Wind climate in cities: Proceedings of the NATO Advanced Study Institute, Waldbronn, Germany, July 5–16, 1993. Nato Science Series E, vol 277. Kluwer Academic Publishers, Dordrecht, pp 81–107

  • Oke TR (2004) Initial guidance to obtain representative meteorological observations at urban sites. Instruments and Observing Methods Report No 81. World Meteorological Organization, Geneva

  • O’Neill RV, Krummel JR, Gardner RH, Sugihara G, Jackson B, DeAngelis DL, Milne BT, Turner MG, Zygmunt B, Christensen SW, Dale VH, Graham RL (1988) Indices of landscape pattern. Landscape Ecol 1:153–162

    Article  Google Scholar 

  • Ouyang Z, Xiao RB, Schienke EW, Li WF, Wang X, Miao H, Zheng H (2007) Chapter 27: Beijing urban spatial distribution and resulting impacts on heat islands. In: Hong K, Nakagoshi N, Fu BJ et al (eds) Landscape ecological applications in man-influenced areas: linking man and nature systems. Springer, New York, pp 459–478

    Chapter  Google Scholar 

  • Pickett STA, Cadenasso ML, Grove JM, Boone CG, Groffman PM, Irwin E, Kaushal SS, Marshall V, McGrath BP, Nilon CH, Pouyat RV, Szlavecz K, Troy A, Warren P (2011) Urban ecological systems: scientific foundations and a decade of progress. J Environ Manag 92:331–362

    Article  CAS  Google Scholar 

  • Qin ZH, Li WJ, Xu B, Chen ZX, Liu J (2004) The estimation of land surface emissivity for Landsat TM6. Remote Sens Land Resour 3:28–32 (in Chinese)

    Google Scholar 

  • Rosenzweig C, Solecki WD, Parshall L, Chopping M, Pope G, Goldberg R (2005) Characterizing the urban heat island in current and future climates in New Jersey. Global Environ Change B 6:51–62

    Google Scholar 

  • Streutker DR (2003) Satellite-measured growth of the urban heat island of Houston, Texas. Remote Sens Environ 85:282–289

    Article  Google Scholar 

  • Twine TE, Kustas WP, Norman JM, Cook DR, Houser PR, Meyers TP, Prueger JH, Starks PJ, Wesely ML (2000) Correcting eddy-covariance flux underestimates over grassland. Agric For Meteorol 103:279–300

    Article  Google Scholar 

  • Voogt JA, Oke TR (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86:370–384

    Article  Google Scholar 

  • Wan ZM, Zhang YL, Zhang QC, Li ZL (2002) Validation of the land-surface temperature products retrieved from Terra moderate resolution imaging spectroradiometer data. Remote Sens Environ 83:163–180

    Article  Google Scholar 

  • Wang Y, Hu F (2006) Variations of the urban heat island in summer of the recent 10 years over Beijing and its environment effect. Chin J Geophys-ch 49(1):61–68

    Google Scholar 

  • Wang X, Bian LG, Lu CG (2003) A study of characteristic parameters of atmospheric boundary layer over Beijing in urban and suburban area in Autumn. Clim Environ Res 8(4):475–484

    Google Scholar 

  • Wang XX, Hu DS, Zhu QJ (2011) Comparison of infrared radiative temperatures from two scales on different land surfaces. J Guangxi Norm Univ 29(2):1–4 (in Chinese)

    Google Scholar 

  • Webb EK, Pearman GI, Leuning R (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J Roy Meteorol Soc 106:85–100

    Article  Google Scholar 

  • Weng QH, Lu DS, Schubring J (2004) Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ 89(4):467–483

    Article  Google Scholar 

  • Weng Q, Hu X, Quattrochi DA, Liu H (2013) Assessing intra-urban surface energy fluxes using remotely sensed ASTER imagery and routine meteorological data: a case study in Indianapolis, U.S.A. IEEE J Sel Top Appl 99:1–12

    Google Scholar 

  • Wu JG (2010) Urban sustainability: an inevitable goal of landscape research. Landscape Ecol 25:1–4

    Article  Google Scholar 

  • Wu JG (2013) Landscape sustainability science: ecosystem services and human well-being in changing landscape. Landscape Ecol 28:999–1023

    Article  Google Scholar 

  • Wu JG (2014) Urban ecology and sustainability: the state-of-the-science and future directions. Landsc Urban Plan. doi:10.1016/j.landurbplan.2014.01.018

  • Wu JG, David JL (2002) A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecol Model 153(1):7–26

    Article  Google Scholar 

  • Xiao RB, Ouyang ZY, Zheng H, Li WF, Schienke EW, Wang XK (2007) Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing. China. J Environ Sci 19(2):250–256

    Article  Google Scholar 

  • Xiao RB, Weng QH, Ouyang ZY, Li WF, Schienke EW, Zhang ZM (2008) Land surface temperature variation and major actors in Beijing, China. Photogramm Eng Rem Sens 74(4):451–461

    Article  Google Scholar 

  • Xu YY, Liu SH, Hu F (2009) Influence of Beijing urbanization on the characteristics of atmospheric boundary layer. J Atmos Sci-ch 3(4):859–867

    Google Scholar 

  • Yang P, Liu WD, Hou W (2011) The trend and inter-decadal evolution of extreme temperature events in Beijing area. J Catastrophology 26(1):60–64

    CAS  Google Scholar 

  • Yu SQ, Bian LG, Lin XC (2005) Changes in the spatial scale of Beijing UHI and urban development. Sci China Ser D 48(II):116–127

    Google Scholar 

  • Zhang C, Tian HQ, Pan SF, Liu ML, Lockaby G, Schilling EB, Stanturf J (2008) Effects of forest regrowth and urbanization on ecosystem carbon storage in a rural-urban gradient in the Southeastern United States. Ecosystems 11:1211–1222

    Article  CAS  Google Scholar 

  • Zhang C, Wu JG, Grimm BN, McHale M, Buyantuyev A (2013) A hierarchical patch mosaic ecosystem model for urban landscapes: model development and evaluation. Ecol Model 250:81–100

    Article  Google Scholar 

  • Zheng G, Lu M, Zhang T, Liu G, Ke C (2010) The impact of difference of land surface emissivity on the land surface temperature retrieval of Jinan City. J ShanDong JianZhu Univ 25(5):519–523 (in Chinese)

    Google Scholar 

  • Zhou J, Li J, Zhang LX (2009) Validation of algorithms for retrieving land surface temperature based on MODIS data: a case study in the upper reaches of Heihe River. J Glaciol Geocryol 31(2):239–246

    Google Scholar 

  • Zhou W, Huang G, Cadenasso ML (2011a) Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landsc Urban Plan 102:54–63

    Article  Google Scholar 

  • Zhou W, Qian Y, Li X, Li W, Han L (2011b) 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. Landscape Ecol 29(1):153–167

    Article  Google Scholar 

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Acknowledgments

We thank the National Natural Science Foundation of China (41371408), the National Basic Research Program of China (2014CB954302; 2010CB950900), and National Key Technology R&D Program (2012BAJ15B02) for financial support. We also thank Dr. Shaomin Liu of Beijing Normal University for providing the radiation and energy fluxes data from the Daxing Station, and Dr. Jianguo Wu for constructive comments/suggestions for this paper.

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Authors and Affiliations

  1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Wenhui Kuang, Yue Liu, Wenfeng Chi, Tianrong Yang, Jiyuan Liu & Renhua Zhang

  2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China

    Yinyin Dou

  3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China

    Wenfeng Chi

  4. Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA

    Guangsheng Chen

  5. Southwest University of Science and Technology, Mianyang, 621010, China

    Chengfeng Gao

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  1. Wenhui Kuang
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Correspondence to Wenhui Kuang.

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Kuang, W., Liu, Y., Dou, Y. et al. What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China. Landscape Ecol 30, 357–373 (2015). https://doi.org/10.1007/s10980-014-0128-6

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