Based on the night light data, urban area data, and economic data of Wuhan Urban Agglomeration from 2009 to 2015, we use spatial correlation dimension, spatial self-correlation analysis and weighted standard deviation ellipse to identify the general characteristics and dynamic evolution characteristics of urban spatial pattern and economic disparity pattern. The research results prove that: between 2009 and 2013, Wuhan Urban Agglomeration expanded gradually from northwest to southeast and presented the dynamic evolution features of “along the river and the road”. The spatial structure is obvious, forming the pattern of “core-periphery”. The development of Wuhan Urban Agglomeration has obvious imbalance in economic geography space, presenting the development tendency of “One prominent, stronger in the west and weaker in the east”. The contract within Wuhan Urban Agglomeration is gradually decreased. Wuhan city and its surrounding areas have stronger economic growth strength as well as the cities along The Yangtze River. However, the relative development rate of Wuhan city area is still far higher than other cities and counties.
References
[1]
Wu, J.S., Liu, H., Peng, J., et al. (2014) Hierarchical Structure and Spatial Pattern of China’s Urban System: Evidence from DMSP/OLS Nightlight Data. Acta Geographica Sinica, 69, 760-770.
[2]
Shang, Z.Y. and Zhang, X.L. (2009) Urban System Spatial Structure and ITS Fractal Characteristic of the Yangtze Delta. Economic Geography, 29, 913-928.
[3]
Liu, L.P. and Mu, G.S. (2011) Analysis of the Structure and Spatial Relation of Zhongyuan City Agglomeration. Areal Research and Development, 30, 165-168.
[4]
Small, C., Pozzi, F. and Elvidge, C.D. (2005) Spatial Analysis of Global Urban Extent from DMSP-OLS Night Lights. Remote Sensing of Environment, 96, 277-291. https://doi.org/10.1016/j.rse.2005.02.002
[5]
Li, Z., Qiang, L., Jin, C., et al. (2007) Characteristics Analysis of Urban Land Expansion in China in 1990s Using DMSP/OLS Data. Acta Scientiarum Naturalium Universitatis Sunyatseni, 3, 98-102.
[6]
Lu, D., Tian, H., Zhou, G. and Ge, H. (2008) Regional Mapping of Human Settlements in Southeastern China with Multisensor Remote Sensed Data. Remote Sensing of Environment, 112, 3668-3679. https://doi.org/10.1016/j.rse.2008.05.009
[7]
Cao, X., Chen, J., Imura, H. and Higashi, O. (2009) A SVM-Based Method to Extract Urban Areas from DMSP-OLS and SPOT VGT Data. Remote Sensing of Environment, 113, 2205-2209. https://doi.org/10.1016/j.rse.2009.06.001
[8]
Elvidge, C.D., Baugh, K.E., Kihn, E.A., et al. (1997) Relation between Satellite Observed Visible-Near Infrared Emissions, Population, Economic Activity and Electric Power Consumption. International Journal of Remote Sensing, 18, 1373-1379. https://doi.org/10.1080/014311697218485
[9]
Elvidge, C.D., Imhoff, M.L., Baugh, K.E., et al. (2001) Night-Time Lights of the World: 1994-1995. ISPRS Journal of Photogrammetry and Remote Sensing, 56, 81-99. https://doi.org/10.1016/S0924-2716(01)00040-5
[10]
He, C., Shi, P., Li, J., et al. (2006) Spatial Restruction of Urbanization in Chinese Mainland in 1990s Using DMSP/OLS Night Light Data and Statistical Data. Chinese Science Bulletin, 51, 856-861. https://doi.org/10.1007/s11434-006-2006-3
[11]
Raupach, M., Rayner, P. and Paget, M. (2009) Regional Variations in Spatial Structure of Nightlights, Population Density and Fossil-Fuel CO2 Emissions. Energy Policy, 38, 4756-4764. https://doi.org/10.1016/j.enpol.2009.08.021
[12]
Chalkias, C., Petrakis, M., Psiloglou, B. and Lianou, M. (2006) Modelling of Light Pollution in Suburban Areas Using Remotely Sensed Imagery and GIS. Journal of Environmental Management, 79, 57-63. https://doi.org/10.1016/j.jenvman.2005.05.015
[13]
Wang, Y.Y., Xu, D. and Zhu, X.G. (2010) The Spatio-Temporal Characteristics of Urban and Town Construction Land Expansion in Jiangsu Province from DMSP-OLS Nighttime Images. Modern Urban Research, No. 2, 67-73.
[14]
Liao, B., Wei, K.X. and Song, W.W. (2012) Assessment and Application of DMSP/ OLS Night Time Light Data in Spatial Structure of Urban System—A Case of Jiangxi Province in Nearly 16 Years. Resources and Environment in the Yangtze Basin, 21, 1297-1300.
[15]
Xu, M.J., Chen, L., Liu, H.J., et al. (2011) Pattern and Process of Urbanization in the Yangtze Delta Based on DMSP/OLS Data. Remote Sensing for Land & Resources, No. 9, 107-112.
[16]
Change, T. and Wu, S.H. (2014) Spatial-Temporal Characteristics of Yangtze River Delta Urban Agglomeration’s Geographic Expansion in Recent Decades—An Empirical Study Based on DMSP/OLS Night Light Data. Modern Urban Research, No. 7, 67-72.
[17]
Zhang, C., Wang, C.Y., Lv, Y.Q., et al. (2015) Research on City System Spatial Structure of the Yangtze River Economic Belt: Based on DMSP/OLS Night Time Light Data. Urban Development Studies, 22, 19-26.
[18]
Liu, J.S. and Chen, Y.G. (1999) Fractal Dimensions of Spatial Structure of an Urban System and the Methods of Their Determination. Geographical Research, 18, 172-178.
[19]
Wang, C.Y., Wu, G.Y. and Zhang, C. (2015) Research on Spatial Structure of the Chengdu-Chongqing Urban Agglomeration Based on the DMSP/OLS Night Time Light Data. Urban Development Studies, 22, C20-C24.
[20]
Gangopadhyay, K. and Basu, B. (2009) City Size Distribution for India and China. Physica A: Statistical Mechanics and Its Applications, 388, 2682-2688. https://doi.org/10.1016/j.physa.2009.03.019
[21]
Liu, J.S. and Chen, Y.G. (1999) A Study on Fractal Dimensions of Spatial Structure of Transport Networks and the Methods of Their Determination. Acta Geographica Sinica, 54, 472-477.
[22]
Shang, Z.Y. and Zhang, X.L. (2009) Urban System Fractal Characteristic of the Yangtze Delta Interlocking Metropolitan Areas. Resources and Environment in the Yangtze Basin, 18, 998-1002.
[23]
Song, J.C., Li, X.H., Lin, T., et al. (2015) A Method of Extracting Urban Built-Up Area Based on DMSP/OLS Nighttime Data and Google Earth. Journal of Geo-Information Science, 17, 750-756.
