PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (12): 1644-1652.doi: 10.18306/dlkxjz.2018.12.006

Special Issue: 人口与城市研究 粤港澳大湾区

• Special Column: Guangdong-Hong Kong-Macao Greater Bay Area • Previous Articles     Next Articles

Spatiotemporal changes of gridded urban population in the Guangdong-Hong Kong-Macao Greater Bay Area based on impervious surface-population correlation

Hui LIN1,2(), Hongsheng ZHANG1,2,*(), Yinyi LIN1, Shan WEI1, Zhifeng WU3   

  1. 1. Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong 999077, China
    2. Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, Guangdong, China
    3. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China
  • Received:2018-10-25 Revised:2018-12-07 Online:2018-12-28 Published:2018-12-28
  • Contact: Hongsheng ZHANG;
  • Supported by:
    The Research Grant Counsil of Hong Kong, No.CUHK14635916, No.CUHK14605917;National Natural Science Foundation of China, No.41401370


Urban population data are the basic data in various social and economy fields, and high-resolution spatialized urban population data are of great importance for the research in such fields. In this article, multi-source remote sensing data were used to extract the urban impervious surface changes in the Guangdong-Hong Kong-Macao (GHM) Greater Bay Area at a spatial resolution of 30 meters from 2007 to 2015. The Dasymetric mapping method was used to spatialize the population at different times to a resolution of 30 meters. We finally estimated the gridded population density distribution of 30 meters resolution, and analyzed the spatiotemporal changes of the urban population in the GHM Greater Bay Area from 2007 to 2015. Validated with Google Earth time series high-resolution images, the accuracy of the derived urban impervious surfaces in GHM is generally above 80%. Using the county-level demographic data, the consistency between the estimated population and the statistical data in the GHM Greater Bay Area was analyzed, and the correlation coefficient (R2) was generally above 0.7. Finally, according to the spatial distribution of urban population and the change of population density, urban expansion and population increase patterns of different cities in the GHM Greater Bay Area were analyzed. The research shows that the urban population of the GHM has special spatiotemporal characteristics: (1) Stable population distribution is observed for Hong Kong and Macao, but other urban areas have experienced expansion of population to different extents and in different directions. The population expansion of Guangzhou, Shenzhen, and Dongguan is most obvious. (2) The spatial distribution of urban population in GHM shows multi-scale and multi-center characteristics. In general, the population of GHM is concentrated in the core area centered at the Pearl River Estuary. The Zhaoqing, Jiangmen, and Huizhou areas are sparsely populated. In the core area, the distribution of urban population shows the characteristics of multi-center distribution on both urban and metropolitan scales. Hong Kong and Guangzhou have multiple urban centers, while Hong Kong, Macao, Shenzhen, and Guangzhou are the centers of the GHM. These four centers can drive the overall development of the GHM Greater Bay Area.

Key words: Guangdong-Hong Kong-Macao Greater Bay Area, impervious surface, multi-source remote sensing, population spatialized, urban population