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Frontiers of Earth Science

, Volume 13, Issue 2, pp 290–302 | Cite as

The relationships between urban-rural temperature difference and vegetation in eight cities of the Great Plains

  • Yaoping Cui
  • Xiangming XiaoEmail author
  • Russell B. Doughty
  • Yaochen Qin
  • Sujie Liu
  • Nan Li
  • Guosong Zhao
  • Jinwei DongEmail author
Research Article
  • 37 Downloads

Abstract

Interpreting the relationship between urban heat island (UHI) and urban vegetation is a basis for understanding the impacts of underlying surfaces on UHI. The calculation of UHI intensity (UHII) requires observations from paired stations in both urban and rural areas. Due to the limited number of paired meteorological stations, many studies have used remotely sensed land surface temperature, but these time-series land surface temperature data are often heavily affected by cloud cover and other factors. These factors, together with the algorithm for inversion of land surface temperature, lead to accuracy problems in detecting the UHII, especially in cities with weak UHII. Based on meteorological observations from the Oklahoma Mesonet, a world-class network, we quantified the UHII and trends in eight cities of the Great Plains, USA, where data from at least one pair of urban and rural meteorological stations were available. We examined the changes and variability in urban temperature, UHII, vegetation condition (as measured by enhanced vegetation index, EVI), and evapotranspiration (ET). We found that both UHI and urban cold islands (UCI) occurred among the eight cities during 2000–2014 (as measured by impervious surface area). Unlike what is generally considered, UHII in only three cities significantly decreased as EVI and ET increased (p<0.1), indicating that the UHI or UCI cannot be completely explained simply from the perspective of the underlying surface. Increased vegetative cover (signaled by EVI) can increase ET, and thereby effectively mitigate the UHI. Each study station clearly showed that the underlying surface or vegetation affects urban-rural temperature, and that these factors should be considered during analysis of the UHI effect over time.

Keywords

urbanization evapotranspiration urban cold island background climate air temperature 

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Notes

Acknowledgements

We thank Oklahoma Mesonet, which is designed and implemented by scientists at the University of Oklahoma (OU) and at Oklahoma State University (OSU), for providing the meteorological data for the entire state of Oklahoma.We thank Multi-Resolution Land Characteristics (MRLC) consortium for providing the percent developed imperviousness data layer. We thank NASA EOSDIS LP DAAC and the Numerical Terradynamic Simulation Group for providing the MODIS EVI and ET datasets. This study is supported in part by research grants from the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19040301), the National Science Foundation EPSCoR program of American (IIA-1301789), the National Natural Science Foundation of China (Grant Nos. 41671425 and 41401504), HENU-CPGIS Collaborative Fund (JOF201701), the Key Research Program of Frontier Sciences by the Chinese Academy of Sciences (QYZDB-SSW-DQC005), and the “Thousand Youth Talents Plan.”

References

  1. Argüeso D, Evans J P, Fita L, Bormann K J (2014). Temperature response to future urbanization and climate change. Clim Dyn, 42(7–8): 2183–2199Google Scholar
  2. Bang C, Sabo J L, Faeth S H (2010). Reduced wind speed improves plant growth in a desert city. PLoS One, 5(6): e11061Google Scholar
  3. Basara J B, Basara H G, Illston B G, Crawford K C (2010). The impact of the urban heat island during an intense heat wave in Oklahoma City. Adv Meteorol, 2010: 1–10Google Scholar
  4. Bokaie M, Zarkesh M K, Arasteh P D, Hosseini A (2016). Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use/Land Cover in Tehran. Sustainable Cities and Society, 23: 94–104Google Scholar
  5. Brock F V, Crawford K C, Elliott R L, Cuperus G W, Stadler S J, Johnson H L, Eilts M D (1995). The Oklahoma Mesonet: a technical overview. J Atmos Ocean Technol, 12(1): 5–19Google Scholar
  6. Brohan P, Kennedy J J, Harris I, Tett S F, Jones P D (2006). Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. J Geophys Res Atmos, 111(D12D12106): D12106Google Scholar
  7. Chandler T J (1976). Urban climatology and its relevance to urban design. WMO Tech, Note 149, WMO, GenevaGoogle Scholar
  8. Churkina G (2016). The role of urbanization in the global carbon cycle. Frontiers in Ecology and Evolution, 3, doi: 10.3389/fevo.2015.00144Google Scholar
  9. Clinton N, Gong P (2013). MODIS detected surface urban heat islands and sinks: global locations and controls. Remote Sens Environ, 134: 294–304Google Scholar
  10. Cui Y, Jiu J, Zhang X, Hu Y, Wang J (2012a). Modeling urban heat energy balance and temperature differences of different underlying surfaces. Geogr Res, 31(7): 1257–1268Google Scholar
  11. Cui Y, Liu J, Hu Y, Wang J, Kuang W (2012b). Modeling the radiation balance of different urban underlying surfaces. Chin Sci Bull, 57(9): 1046–1054Google Scholar
  12. Cui Y, Liu J, Zhang X, Qin Y, Dong J (2015). Modeling urban sprawl effects on regional warming in Beijing-Tianjing-Tangshan urban agglomeration. Acta Ecol Sin, 35(4): 993–1003Google Scholar
  13. Cui Y, Xiao X, Zhang Y, Dong J, Qin Y, Doughty R, Zhang G, Wang J, Wu X, Qin Y, Zhou S, Joiner J, Moore B III (2017). Temporal consistency between gross primary production and solar-induced chlorophyll fluorescence in the ten most populous megacity areas over years. Sci Rep, 7(1): 14963Google Scholar
  14. Cui Y, Xu X, Dong J, Qin Y (2016). Influence of urbanization factors on surface urban heat island intensity: a comparison of countries at different developmental phases. Sustainability, 8(8): 706Google Scholar
  15. Dong J, Xiao X, Wagle P, Zhang G, Zhou Y, Jin C, Torn M S, Meyers T P, Suyker A E, Wang J, Yan H, Biradar C, Moore B III (2015). Comparison of four EVI-based models for estimating gross primary production of maize and soybean croplands and tallgrass prairie under severe drought. Remote Sens Environ, 162: 154–168Google Scholar
  16. Eliasson I (1996). Urban nocturnal temperatures, street geometry and land use. Atmos Environ, 30(3): 379–392Google Scholar
  17. Fang J, Zhu J, Yue C, Wang S, Zheng T (2018). Carbon Emissions from China and the World. Beijing: Science PressGoogle Scholar
  18. Golubiewski N E (2006). Urbanization increases grassland carbon pools: effects of landscaping in Colorado’s front range. Ecol Appl, 16(2): 555–571Google Scholar
  19. Grimm N B, Faeth S H, Golubiewski N E, Redman C L, Wu J, Bai X, Briggs J M (2008). Global change and the ecology of cities. Science, 319(5864): 756–760Google Scholar
  20. Guo G, Wu Z, Xiao R, Chen Y, Liu X, Zhang X (2015). Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landsc Urban Plan, 135: 1–10Google Scholar
  21. Haashemi S, Weng Q, Darvishi A, Alavipanah S K (2016). Seasonal variations of the surface urban heat island in a semi-arid city. Remote Sens, 8(4): 352Google Scholar
  22. Heusinkveld B G, Steeneveld G J, van Hove L W A, Jacobs C M J, Holtslag A A M (2014). Spatial variability of the Rotterdam urban heat island as influenced by urban land use. J Geophys Res Atmos, 119(2): 677–692Google Scholar
  23. Hu L, Brunsell N A (2013). The impact of temporal aggregation of land surface temperature data for surface urban heat island (SUHI) monitoring. Remote Sens Environ, 134: 162–174Google Scholar
  24. Hu X, Zhou W, Qian Y, Yu W (2017). Urban expansion and local landcover change both significantly contribute to urban warming, but their relative importance changes over time. Landsc Ecol, 32(4): 763–780Google Scholar
  25. Hutyra L R, Duren R, Gurney K R, Grimm N, Kort E A, Larson E, Shrestha G (2014). Urbanization and the carbon cycle: current capabilities and research outlook from the natural sciences perspective. Earths Futur, 2(10): 473–495Google Scholar
  26. Imhoff M L, Bounoua L, DeFries R, Lawrence W T, Stutzer D, Tucker C J, Ricketts T (2004). The consequences of urban land transformation on net primary productivity in the United States. Remote Sens Environ, 89(4): 434–443Google Scholar
  27. ImhoffM L, Zhang P,Wolfe R E, Bounoua L (2010). Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens Environ, 114(3): 504–513Google Scholar
  28. Jenerette G D, Harlan S L, Buyantuev A, Stefanov W L, Declet-Barreto J, Ruddell B L, Myint SW, Kaplan S, Li X (2016). Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ, USA. Landsc Ecol, 31(4): 745–760Google Scholar
  29. Jones P, Lister D, Li Q (2008). Urbanization effects in large-scale temperature records, with an emphasis on China. J Geophys Res Atmos, 113(D16): D16122Google Scholar
  30. Kalnay E, Cai M (2003). Impact of urbanization and land-use change on climate. Nature, 423(6939): 528–531Google Scholar
  31. Kamarianakis Y, Li X, Turner B L II, Brazel A J (2017). On the effects of landscape configuration on summer diurnal temperatures in urban residential areas: application in Phoenix, AZ. Front Earth Sci, https://doi.org/10.1007/s11707-017-0678-4Google Scholar
  32. Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006). World map of the Köppen-Geiger climate classification updated. Meteorol Z, 15(3): 259–263Google Scholar
  33. Kusaka H, Kimura F (2004). Coupling a single-layer urban canopy model with a simple atmospheric model: impact on urban heat island simulation for an idealized case. J Meteorol Soc Jpn, 82(1): 67–80Google Scholar
  34. Li J, Song C, Cao L, Zhu F, Meng X,Wu J (2011). Impacts of landscape structure on surface urban heat islands: a case study of Shanghai, China. Remote Sens Environ, 115(12): 3249–3263Google Scholar
  35. Li X, Zhou Y, Asrar G R, Imhoff M, Li X (2017). The surface urban heat island response to urban expansion: a panel analysis for the conterminous united states. Sci Total Environ, 605–606: 426–435Google Scholar
  36. Lietzke B, Vogt R (2013). Variability of CO2 concentrations and fluxes in and above an urban street canyon. Atmos Environ, 74: 60–72Google Scholar
  37. Liu K, Gu X, Yu T, Gao Z, Gao W, Liu C (2011). Relationships between urban heat island effect and land use and land cover change around urban weather stations. Climatic and Environmental Research, 16(6): 707–716 (in Chinese)Google Scholar
  38. Liu K, Su H, Li X, Wang W, Yang L, Liang H (2016). Quantifying spatial–temporal pattern of urban heat island in Beijing: an improved assessment using land surface temperature (LST) time series observations from LANDSAT, MODIS, and Chinese new satellite GaoFen-1. IEEE J Sel Top Appl Earth Obs Remote Sens, 9(5): 2028–2042Google Scholar
  39. Liu Z, He C, Zhou Y, Wu J (2014). How much of the world’s land has been urbanized, really? A hierarchical framework for avoiding confusion. Landsc Ecol, 29(5): 763–771Google Scholar
  40. Luo X, 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(9): 760Google Scholar
  41. Lynn B H, Carlson T N, 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 Meteorol Climatol, 48(2): 199–216Google Scholar
  42. Mao W, Wang X, Cai J, Zhu M (2016). Multi-dimensional histogrambased information capacity analysis of urban heat island effect using Landsat 8 data. Remote Sens Lett, 7(10): 925–934Google Scholar
  43. McPherson R A, Fiebrich C A, Crawford K C, Kilby J R, Grimsley D L, Martinez J E, Basara J B, Illston B G, Morris D A, Kloesel K A, Melvin A D, Shrivastava H, Wolfinbarger J M, Bostic J P, Demko D B, Elliott R L, Stadler S J, Carlson J D, Sutherland A J (2007). Statewide monitoring of the mesoscale environment: a technical update on the Oklahoma Mesonet. J Atmos Ocean Technol, 24(3): 301–321Google Scholar
  44. Mildrexler D J, Zhao M, Running S W (2011). A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests. J Geophys Res Biogeosci, 116(G03025)Google Scholar
  45. Mu Q, Heinsch F A, Zhao M, Running S W (2007). Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sens Environ, 111(4): 519–536Google Scholar
  46. Oke T R (1973). City size and the urban heat island. Atmos Environ, 7 (8): 769–779Google Scholar
  47. Oke T R (2004). Initial guidance to obtain representative meteorological observations at urban sites. IOM Rep. 81, WMO/TD-No. 1250, 1–47. [Available online at http://www.wmo.ch/pages/prog/www/IMOP/publications/IOM-81/IOM-81-UrbanMetObs.pdf]Google Scholar
  48. Parker D E (2010). Urban heat island effects on estimates of observed climate change. Wiley Interdiscip Rev Clim Chang, 1(1): 123–133Google Scholar
  49. Peng S, Piao S, Ciais P, Friedlingstein P, Ottle C, Bréon F M, Nan H, Zhou L, Myneni R B (2012). Surface urban heat island across 419 global big cities. Environ Sci Technol, 46(2): 696–703Google Scholar
  50. Peterson T C (2003). Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found. J Clim, 16(18): 2941–2959Google Scholar
  51. Piao S, Sitch S, Ciais P, Friedlingstein P, Peylin P,Wang X, Ahlström A, Anav A, Canadell J G, Cong N, Huntingford C, Jung M, Levis S, Levy P E, Li J, Lin X, LomasMR, LuM, Luo Y, Ma Y, Myneni R B, Poulter B, Sun Z Z, Wang T, Viovy N, Zaehle S, Zeng N (2013). Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Glob Change Biol, 19(7): 2117–2132Google Scholar
  52. Price J C (1979). Assessment of the urban heat island effect through the use of satellite data. Mon Weather Rev, 107(11): 1554–1557Google Scholar
  53. Qian Y, Zhou W, Li W, Han L (2015). Understanding the dynamic of greenspace in the urbanized area of Beijing based on high resolution satellite images. Urban Forestry & Urban Greening, 14(1): 39–47Google Scholar
  54. Qiu G, Li H, Zhang Q, Chen W, Liang X, Li X (2013). Effects of evapotranspiration on mitigation of urban temperature by vegetation and urban agriculture. J Integr Agric, 12(8): 1307–1315Google Scholar
  55. Ren G, Zhou Y, Chu Z, Zhou J, Zhang A, Guo J, Liu X (2008). Urbanization effects on observed surface air temperature trends in North China. J Clim, 21(6): 1333–1348Google Scholar
  56. Roman K K, O’Brien T, Alvey J B, Woo O (2016). Simulating the effects of cool roof and PCM (phase change materials) based roof to mitigate UHI (urban heat island) in prominent US cities. Energy, 96: 103–117Google Scholar
  57. Schmid H, Cleugh H, Grimmond C, Oke T (1991). Spatial variability of energy fluxes in suburban terrain. Boundary-Layer Meteorol, 54(3): 249–276Google Scholar
  58. Steeneveld G, Koopmans S, Heusinkveld B, Van Hove L, Holtslag A (2011). Quantifying urban heat island effects and human comfort for cities of variable size and urban morphology in the Netherlands. J Geophys Res Atmos, 116(D20): D20129Google Scholar
  59. Stewart I D (2011). A systematic review and scientific critique of methodology in modern urban heat island literature. Int J Climatol, 31(2): 200–217Google Scholar
  60. Stewart I D, Oke T R (2012). Local climate zones for urban temperature studies. Bull Am Meteorol Soc, 93(12): 1879–1900Google Scholar
  61. Walker J, de Beurs K, Henebry G (2015). Land surface phenology along urban to rural gradients in the US Great Plains. Remote Sens Environ, 165: 42–52Google Scholar
  62. Wan Z (2008). New refinements and validation of the MODIS landsurface temperature/emissivity products. Remote Sens Environ, 112 (1): 59–74Google Scholar
  63. Watts M, Schultz S, Bailey T, Ast E, Russell B, Morris E, Vines K, S L (2015). Climate action in megacities 3.0: Networking works, there is no global solution without local action. London: C40 Cities Climate Leadership GroupGoogle Scholar
  64. 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): 467–483Google Scholar
  65. Wong N H, Chen Y, Ong C L, Sia A (2003). Investigation of thermal benefits of rooftop garden in the tropical environment. Build Environ, 38(2): 261–270Google Scholar
  66. Yang X, Li Y, Luo Z, Chan P W (2017). The urban cool island phenomenon in a high- rise high- density city and its mechanisms. Int J Climatol, 37(2): 890–904Google Scholar
  67. Yao R, Wang L, Huang X, Niu Y, Chen Y, Niu Z (2018). The influence of different data and method on estimating the surface urban heat island intensity. Ecol Indic, 89: 45–55Google Scholar
  68. Zhang X, Friedl M A, Schaaf C B, Strahler A H (2004a). Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data. Glob Change Biol, 10(7): 1133–1145Google Scholar
  69. Zhang X, Friedl M A, Schaaf C B, Strahler A H, Schneider A (2004b). The footprint of urban climates on vegetation phenology. Geophys Res Lett, 31(12): L12209Google Scholar
  70. Zhao G, Dong J, Cui Y, Liu J, Zhai J, He T, Zhou Y, Xiao X (2018). Evapotranspiration-dominated biogeophysical warming effect of urbanization in the Beijing-Tianjin-Hebei region, China. Clim Dyn, https://doi.org/10.1007/s00382-018-4189-0Google Scholar
  71. Zhao L, Lee X, Smith R B, Oleson K (2014). Strong contributions of local background climate to urban heat islands. Nature, 511(7508): 216–219Google Scholar
  72. Zhao S, Liu S, Zhou D (2016). Prevalent vegetation growth enhancement in urban environment. Proc Natl Acad Sci USA, 113(22): 6313–6318Google Scholar
  73. Zhou B, Rybski D, Kropp J (2013). On the statistics of urban heat island intensity. Geophys Res Lett, 40(20): 5486–5491Google Scholar
  74. Zhou D, Zhang L, Hao L, Sun G, Liu Y, Zhu C (2016). Spatiotemporal trends of urban heat island effect along the urban development intensity gradient in China. Sci Total Environ, 544: 617–626Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yaoping Cui
    • 1
    • 2
  • Xiangming Xiao
    • 2
    • 3
    Email author
  • Russell B. Doughty
    • 2
  • Yaochen Qin
    • 1
  • Sujie Liu
    • 1
  • Nan Li
    • 1
  • Guosong Zhao
    • 4
  • Jinwei Dong
    • 4
    Email author
  1. 1.Laboratory of Geospatial Technology for the Middle and Lower Yellow River RegionsHenan UniversityKaifengChina
  2. 2.Department of Microbiology and Plant Biology, Center for Spatial AnalysisUniversity of OklahomaNormanUSA
  3. 3.Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity ScienceFudan UniversityShanghaiChina
  4. 4.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

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