Environmental Earth Sciences

, Volume 73, Issue 12, pp 8387–8404 | Cite as

Improved monitoring of urbanization processes in China for regional climate impact assessment

  • Yonghong Hu
  • Gensuo Jia
  • Christine Pohl
  • Qiang Feng
  • Yuting He
  • Hao Gao
  • Ronghan Xu
  • John van Genderen
  • Jinming Feng
Original Article


Regional climate is influenced by land surface processes through energy exchange between land and atmosphere at various scales. The performance of climate model simulation is largely influenced by land cover parameterization, especially over areas that experience rapid change of land surface characterization. Accurate land cover datasets suited for climate modeling are urgently needed to improve model parameterization for better simulation. In this study, fused urban land cover datasets have been developed by combining multi-source urban land cover products based on cross-comparison and detailed validation from medium resolution images during recent decades. Fractional cover values at different spatial scales were aggregated from integrated land cover datasets to derive improved estimates of the urban extent of big cities in China. Urbanization in China as captured by the new dataset can be divided into steadily and rapidly increasing periods with the urban area increasing by 2.5 and 6.7 % per year, respectively. Rapid urbanization mostly happens in the urban fringe, especially in eastern China, with mass conversion of cropland and woodland to urban land. An improvement in climate model simulation could be achieved using the fused data applied in climate modeling for examining the impact of rapid urbanization on the regional climate.


Climate change Urbanization Land cover Remote sensing Feature fusion 



This research was supported by CAS Strategic Priority Research Program (XDA05090200) and the National Basic Research Program of China (2009 CB723904). We thank Dr. Deming Zhao, Dr. Liang Chen, and Mr. Jun Wang for their comments during the application tests for the climate models.


  1. Akiwowo A, Eftekhari M (2013) Feature-based detection using Bayesian data fusion. Int J Image Data Fusion 4:308–323CrossRefGoogle Scholar
  2. Arunprakash M, Giridharan L, Krishnamurthy RR, Jayaprakash M (2014) Impact of urbanization in groundwater of south Chennai city, Tamil Nadu, India. Environ Earth Sci 71:947–957CrossRefGoogle Scholar
  3. Bartholomé E, Belward AS (2005) GLC2000: a new approach to global land cover mapping from earth observation data. Int J Remote Sens 26:1959–1977CrossRefGoogle Scholar
  4. Brook A, Ben-Dor E, Richter R (2011) Modelling and monitoring urban built environment via multi-source integrated and fused remote sensing data. Int J Image Data Fusion 4:2–32CrossRefGoogle Scholar
  5. Bukovsky MS, Karoly DJ (2009) Precipitation simulations using WRF as a nested regional climate model. J Appl Meteorol Climatol 48:2152–2159CrossRefGoogle Scholar
  6. Cheon J-Y, Ham B-S, Lee J-Y, Park Y, Lee K-K (2014) Soil temperatures in four metropolitan cities of Korea from 1960 to 2010: implications for climate change and urban heat. Environ Earth Sci 71:5215–5230CrossRefGoogle Scholar
  7. Choi H (2013) Parameterization of high resolution vegetation characteristics using remote sensing products for the Nakdong River Watershed, Korea. Remote Sens 5:473–490CrossRefGoogle Scholar
  8. Clapham WB Jr (2003) Continuum-based classification of remotely sensed imagery to describe urban sprawl on a watershed scale. Remote Sens of Environ 86:322–340CrossRefGoogle Scholar
  9. Crutzen P (2004) New directions: the growing urban heat and pollution ‘island’ effect-impact on chemistry and climate. Atmos Environ 38:3539–3540CrossRefGoogle Scholar
  10. Dahiya S, Garg PK, Jat MK (2013) A comparative study of various pixel-based image fusion techniques as applied to an urban environment. Int J Image Data Fusion 4:197–213CrossRefGoogle Scholar
  11. Danko DM (1991) The digital chart of the world project. In: Proceedings ACSM-ASPRS annual convention, Baltimore 2, pp 83–93Google Scholar
  12. Dickinson RE, Henderson-Sellers A, Kennedy PJ (1993) Biosphere–atmosphere transfer scheme (BATS) Version 1e as coupled to the NCAR Community climate model. Technical note 198. NCAR. Accessed 03 Aug 2014
  13. Dong SC, Samsonov S, Yin HW, Ye SJ, Cao YR (2014) Time-series analysis of subsidence associated with rapid urbanization in Shanghai, China measured with SBAS InSAR method. Environ Earth Sci 72:677–691CrossRefGoogle Scholar
  14. Dudhia J, Gill D, Manning K, Wang W, Bruyere C (2005) PSU/NCAR mesoscale modeling. System tutorial class notes and user’s guide—MM5 modeling system version 3. Accessed 03 Aug 2014
  15. Eva HD, Belward AS, De Miranda EE et al (2004) A land cover map of South America. Glob Change Biol 10:731–744CrossRefGoogle Scholar
  16. Ezber Y, Lutfi Sen O, Kindap T, Karaca M (2007) Climatic effects of urbanization in Istanbul: a statistical and modeling analysis. Int J Climatol 27:667–679CrossRefGoogle Scholar
  17. Feddema JJ, Oleson KW, Bonan GB, Mearns LO, Buja LE, Meehl GA, Washington WM (2005) The importance of land-cover change in simulating future climates. Sci. 310:1674–1678CrossRefGoogle Scholar
  18. Friedl MA, McIver DK, Hodges JCF et al (2002) Global land cover mapping from MODIS: algorithms and early results. Remote Sens Environ 83:287–302CrossRefGoogle Scholar
  19. Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X (2010) MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens of Environ 114:168–182CrossRefGoogle Scholar
  20. Gao H, Jia G (2013) Assessing disagreement and tolerance of misclassification of satellite-derived land cover products used in WRF model applications. Adv Atmos Sci 30:125–141CrossRefGoogle Scholar
  21. Gibbard S, Caldeira K, Bala G, Phillips TJ, Wicket M (2005) Climate effects of global land cover change. Geophy Res Lett 32:1–4CrossRefGoogle Scholar
  22. Grawe D, Thompson HL, Salmond JA, Cai X-M, Schlünzen KH (2013) Modelling the impact of urbanisation on regional climate in the Greater London area. Int J Climatol 33:2388–2401CrossRefGoogle Scholar
  23. Grossman-Clarke S, Zehnder JA, Stefanov WL, Liu Y, Zoldak MA (2005) Urban modifications in a mesoscale meteorological model and the effects on near-surface variables in an arid metropolitan region. J Appl Meteorol 44:1281–1297CrossRefGoogle Scholar
  24. Guo Y-R, Chen S (1994) Terrain and land use for the fifth-generation Penn State/NCAR Mesoscale Modeling System (MM5): Program TERRAIN. Technical Note 213, NCAR. Accessed 03 Aug 2014
  25. Hagemann S, Botzet M, Duemenil L, Machenhauer B (1999) Derivation of global GCM boundary conditions from 1 km land use satellite data. MPI Report No. 289. Max Planck Institute for Meteorology. Accessed 03 Aug 2014
  26. Hansen MC, Reed B (2000) A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products. Int J Remote Sens 21:1365–1373CrossRefGoogle Scholar
  27. Hansen MC, Defries RS, Townshend JRG, Sohlberg R (2000) Global land cover classification at 1 km spatial resolution using a classification tree approach. Int J Remote Sens 21:1331–1364CrossRefGoogle Scholar
  28. Henderson M, Yeh ET, Gong P, Elvidge C, Baugh K (2003) Validation of urban boundaries derived from global night-time satellite imagery. Int J Remote Sens 24:595–610CrossRefGoogle Scholar
  29. Hou MT, Hu YH, He YT (2014) Modifications in vegetation cover and surface albedo during rapid urbanization: a case study from South China. Environ Earth Sci 72:1659–1666CrossRefGoogle Scholar
  30. Im ES, Coppola E, Giorgi F, Bi X (2009) Validation of a high-resolution regional climate model for the Alpine region and effects of a subgrid-scale topography and land use representation. J Clim 23:1854–1873CrossRefGoogle Scholar
  31. Khan AS, Khan SD, Kakar DM (2013) Land subsidence and declining water resources in Quetta Valley, Pakistan. Environ Earth Sci 70:2719–2727CrossRefGoogle Scholar
  32. 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 Ser. II 82:67–80CrossRefGoogle Scholar
  33. Lamptey BL, Barron EJ, Pollard D (2005) Impacts of agriculture and urbanization on the climate of the Northeastern United States. Glob Planet Change 49:203–221CrossRefGoogle Scholar
  34. Liu J, Liu M, Tian H, Zhuang D, Zhang Z, Zhang W, Tang X, Deng X (2005) Spatial and temporal patterns of China’s cropland during 1990–2000: an analysis based on Landsat TM data. Remote Sens Environ 98:442–456CrossRefGoogle Scholar
  35. Loveland TR, Reed BC, Brown JF, Ohlen DO, Zhu Z, Yang L, Merchant JW (2000) Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int J Remote Sens 21:1303–1330CrossRefGoogle Scholar
  36. Lu X, Chow K-C, Yao T, Lau AKH, Fung JCH (2010) Effects of urbanization on the land sea breeze circulation over the Pearl River Delta region in winter. Int J Climatol 30:1089–1104Google Scholar
  37. Masson V (2006) Urban surface modeling and the meso-scale impact of cities. Theor Appl Climatol 84:35–45CrossRefGoogle Scholar
  38. Nepstad DC, Stickler CM, Filho BS, Merry F (2008) Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point. Philos Trans R Soc B: Biol Sci 363:1737–1746CrossRefGoogle Scholar
  39. Nobre CA, Sellers PJ, Shukla J (1991) Amazonian deforestation and regional climate change. J Clim 4:957–988CrossRefGoogle Scholar
  40. Oleson KW, Bonan GB, Feddema J, Vertenstein M, Grimmond CSB (2008) An urban parameterization for a global climate model. Part I: formulation and evaluation for two cities. J Appl Meteorol Climatol 47:1038–1060CrossRefGoogle Scholar
  41. Pielke RA (2005) Land use and climate change. Sci 310:1625–1626Google Scholar
  42. Pielke RA, Pitman A, Niyogi D et al (2011) Land use/land cover changes and climate: modeling analysis and observational evidence. Wiley Interdis Rev: Clima Change 2:828–850Google Scholar
  43. Pitman AJ, De Noblet-Ducoudré N, Cruz FT et al (2009) Uncertainties in climate responses to past land cover change: first results from the LUCID intercomparison study. Geophys Res Lett 36:L14814. doi: 10.1029/2009GL039076 CrossRefGoogle Scholar
  44. Pitman AJ, Avila FB, Abramowitz G, Wang YP, Phipps SJ, De Noblet-Ducoudre N (2011) Importance of background climate in determining impact of land-cover change on regional climate. Nat Clim Change 1:472–475CrossRefGoogle Scholar
  45. Pohl C, Van Genderen J (2013) Remote sensing image fusion: an update in the context of Digital Earth. Int J Digital Earth 7:158–172CrossRefGoogle Scholar
  46. Python (2014) Open source programming language. Accessed 03 Aug 2014
  47. 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 21:1333–1348CrossRefGoogle Scholar
  48. Schneider A, Friedl MA, Potere D (2009) A new map of global urban extent from MODIS satellite data. Environ Res Lett 4:1–11CrossRefGoogle Scholar
  49. Sellers PJ, Mintz Y, Sud YC, Dalcher A, Simple A (1986) Biosphere model (SIB) for use within general circulation models. J Atmos Sci 43:505–531CrossRefGoogle Scholar
  50. Seto KC, Reenberg A, Boone CG et al (2012) Urban land teleconnections and sustainability. Proc Natl Acad Sci USA 109:7687–7692CrossRefGoogle Scholar
  51. Shao H, Song J, Ma H (2013) Sensitivity of the East Asian summer monsoon circulation and precipitation to an idealized large-scale urban expansion. J Meteorol Soc Jpn 9:163–177CrossRefGoogle Scholar
  52. Skamarock WC, Klemp JB, Dudhia J et al (2008) A description of the advanced research WRF Version 3. NCAR Technical Note 475, National Centre for Atmospheric Research, Mesoscale and Microscale Meteorology Division, Boulda, Colorado, USA. Accessed 03 Aug 2014
  53. Small C, Elvidge CD, Balk D, Montgomery M (2011) Spatial scaling of stable night lights. Remote Sens Environ 115:269–280CrossRefGoogle Scholar
  54. Strahler A, Muchoney D, Borak J, Friedl M, Gopal S, Lambin E, Moody A (1999) MODIS Land Cover Product Algorithm Theoretical Basis Document (ATBD) Version 5.0. Center for Remote Sensing. Boston University, Boston MA, USA. Accessed 03 Aug 2014
  55. Wade TG, Wickham JD, Zacarelli N, Riitters KH (2009) A multi-scale method of mapping urban influence. Environ Model Softw 24:1252–1256CrossRefGoogle Scholar
  56. Wang G, Shen Y, Zhang J, Wang S, Mao W (2010) The effects of human activities on oasis climate and hydrologic environment in the Aksu River Basin, Xinjiang, China. Environ Earth Sci 59:1759–1769CrossRefGoogle Scholar
  57. Wang J, Feng J, Yan Z, Hu Y, Jia G (2012) Nested high-resolution modeling of the impact of urbanization on regional climate in three vast urban agglomerations in China. J Geophys Res: Atmos 117:D21103Google Scholar
  58. Zhang J (2010) Multi-source remote sensing data fusion: status and trends. Int J Image and Data Fusion 1:5–24CrossRefGoogle Scholar
  59. Zhang Q, Seto KC (2011) Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data. Remote Sens Environ 115:2320–2329CrossRefGoogle Scholar
  60. Zhang D-L, Shou Y-X, Dickerson RR (2009) Upstream urbanization exacerbates urban heat island effects. Geophys Res Lett 36:L24401CrossRefGoogle Scholar
  61. Zhang N, Gao Z, Wang X, Chen Y (2010) Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China. Theor Appl Climatol 102:331–342CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Yonghong Hu
    • 1
  • Gensuo Jia
    • 2
  • Christine Pohl
    • 3
  • Qiang Feng
    • 1
  • Yuting He
    • 2
  • Hao Gao
    • 4
  • Ronghan Xu
    • 2
  • John van Genderen
    • 5
  • Jinming Feng
    • 2
  1. 1.Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  2. 2.Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  3. 3.Institute of Geospatial Science and TechnologyUniversiti Teknologi MalaysiaJohor BahruMalaysia
  4. 4.National Satellite Meteorological CenterChina Meteorological AdministrationBeijingChina
  5. 5.Geospatial Information Science Research CentreFaculty of Engineering, Universiti Putra MalaysiaSerdangMalaysia

Personalised recommendations