Quantitative Measurement of Urban Expansion and Its Driving Factors in Qingdao: An Empirical Analysis Based on County Unit Data

  • 1 Institute of Geographic Sciences and National Resources Research, CAS, Beijing 100101, China;
    2 University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2014-07-14

  Revised date: 2014-12-31

  Online published: 2015-05-22

Supported by

The Ministry of Land and Resources of Public Welfare Scientific Research (No. 201411014-2).


Qingdao is one of the essential growth poles in the process of new-type urbanization in Shandong Province. The study on the relationship between urban expansion and driving factors in this area is representative. This paper examined urban expansion from the perspective of non-urban to urban conversion, detailing an empirical investigation into the spatiotemporal variations and impact factors of urban expansion in Qingdao. By using the Urban Expansion Intensity Index (UEII) and Urban Expansion Differentiation Index (UEII), the spatial and temporal difference of urban expansion in the Municipal District, Jiaozhou County, Jimo County, Pingdu County, Jiaonan County and Laixi County were calculated on a county unit data set for the period 1990 to 2008. A GIS and logistical regression models were applied for discussing the results of various factors in land use change. Results indicated that the elevation and slope factors showed negative effects to urban expansion. Distance to the city center and to road both also conferred negative effects. The population density and GDP were vital and positive factors of urban conversion. Neighborhood factors showed consistently positive effects. The magnitude of factors was various in different counties. A better understanding of the factors influencing land use change could support land use management and planning decisions.

Cite this article

LI Qiuying, FANG Chuanglin, LI Guangdong, REN Zhoupeng . Quantitative Measurement of Urban Expansion and Its Driving Factors in Qingdao: An Empirical Analysis Based on County Unit Data[J]. Journal of Resources and Ecology, 2015 , 6(3) : 172 -179 . DOI: 10.5814/j.issn.1674-764x.2015.03.006


Chen J, Gong P, He C Y, et al. 2002. Assessment of the urban development plan of Beijing by using a CA-based urban growth model. Photogrammetric Engineering and Remote Sensing, 68(10): 1063-1071.
Crk T, M Uriarte, F Corsi, et al. 2009. Forest recovery in a tropical landscape: what is the relative importance of biophysical, socioeconomic, and landscape variables? Landscape Ecology, 24(5): 629-642.
Deng X Z and Bai X M 2014. Sustainable urbanization in western China. Environment, 56(3): 12-24.
Deng X Z, Huang J K, Lin Y Z, et al. 2013. Interactions between climate, socioeconomics, and land dynamics in Qinghai Province, China: A LUCD model-based numerical experiment. Advances in Meteorology, (Special Issue):1-9.
Deng X Z, Su H B and Zhan J Y 2008. Integration of multiple data sources to simulate the Dynamics of Land Systems. Sensors, 8(2): 620-634.
Deng X Z, Yin F, Lin Y Z, et al. 2012. Equilibrium analyses on structural changes of land uses in Jiangxi Province. Journal of Food Agriculture & Environment, 10(1): 846-852.
Dubovyk O, R Sliuzas and J Flacke. 2011. Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey. ISPRS Journal of Photogrammetry and Remote Sensing, 66(2): 235-246.
Franklin J, H M Regan and A D Syphard. 2014. Linking spatially explicit species distribution and population models to plan for the persistence of plant species under global change. Environmental Conservation, 41(2): 97-109.
Getis A and D A Griffith. 2002. Comparative spatial filtering in regression analysis. Geographical Analysis, 34(2): 130-140.
Huang B, Zhang L and Wu B 2009. Spatiotemporal analysis of rural-urban land conversion. International Journal of Geographical Information Science, 23(3): 379-398.
Jones S and C Somper. 2014. The role of green infrastructure in climate change adaptation in London. Geographical Journal, 180(2): 191-196.
Li X and A G O Yeh. 2001. Calibration of cellular automata by using neural networks for the simulation of complex urban systems. Environment and Planning A, 33(8): 1445-1462.
Li X, Zhou W and Ouyang Z. 2013. Forty years of urban expansion in Beijing: What is the relative importance of physical, socioeconomic, and neighborhood factors? Applied Geography, 38: 1-10.
Lichstein J W, T R Simons, S A Shriner, et al. 2002. Spatial autocorrelation and autoregressive models in ecology. Ecological Monographs, 72(3): 445-463.
Long Y, Gu Y and Han H. 2012. Spatiotemporal heterogeneity of urban planning implementation effectiveness: Evidence from five urban master plans of Beijing. Landscape and Urban Planning, 108(2-4): 103-111.
McKinney M L. 2006. Urbanization as a major cause of biotic homogenization. Biological Conservation, 127(3): 247-260.
McKinney M L. 2008. Effects of urbanization on species richness: A review of plants and animals. Urban Ecosystems, 11(2): 161-176.
McMahon S M and J M Diez. 2007. Scales of association: Hierarchical linear models and the measurement of ecological systems. Ecology Letters, 10(6): 437-452.
Munroe D K, J Southworth and C M Tucker. 2004. Modeling spatially and temporally complex land-cover change: The case of western Honduras. Professional Geographer, 56(4): 544-559.
Nations U 2012. World Urbanization Prospects, the 2011 Revision. N Q, M S S Ahamad, W M A W Hussin, et al. 2014. Markov CA, multi regression, and multiple decision making for modeling historical changes in Kirkuk City, Iraq. Journal of the Indian Society of Remote Sensing, 42(1): 165-178.
Wu B, Huang B and Fung T 2009. Projection of land use change patterns using Kernel logistic regression. Photogrammetric Engineering and Remote Sensing, 75(8): 971-979.
Wu J G, Shen W J, Sun W Z, et al. 2002. Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecology, 17(8): 761-782.
Wu K Y and Zhang H. 2012. Land use dynamics, built-up land expansion patterns, and driving forces analysis of the fast-growing Hangzhou metropolitan area, eastern China (1978-2008). Applied Geography, 34: 137-145.
Zhan J Y, Huang J, Zhao T, et al. 2013. Modeling the impacts of urbanization on regional climate change: A case study in the Beijing-Tianjin-Tangshan Metropolitan Area. Advances in Meteorology, (Special Issue):1-8.