Simulation of Urban Small-area Population Space-time Distribution Based on Building Extraction: Taking Beijing Donghuamen Subdistrict as an Example

  • 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2012-11-30

  Revised date: 2012-12-21

  Online published: 2013-02-25


Small-area population space-time distribution is the key point to urban planning, administration and warning for emergency. How to get the data of population distribution becomes the urgent task. While the urban buildings are the main place bearing population, it is necessary and meaningful to find and use the relationship between urban population and urban buildings. In this paper, buildings are extracted with high-resolution remote sensing images, and then a classification system of building functions is established. Based on the classification system, the extracted buildings are classified to 16 classes such as residential, office, financial, leisure, school, catering, accommodation, medical, business, comprehensive and then accommodating capacity coefficients of the buildings are estimated. Based on the survey and existing papers, population-attracting rate curve of buildings of all kinds of function are described. Model of space-time distribution of people is built to simulate the population distribution in Donghuamen Subdistrict of Beijing's Dongcheng District. According to the results of the simulation, the total capacity of all buildings in the target region is 693 thousands. The population distribution of 0:00, 6:00, 7:00, 8:00, 9:00, 10:00, 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, 18:00, 19:00 and 22:00 are simulated and exhibited in this paper. In order to make the results clearer, the region is divided into smaller regions: A, B, C and D, and the population quantity changes of the four regions are described as curves. Then reasons for the changes are analyzed. In the end, improvement methods for the research are discussed, i.e., finer classification system of building functions, a finer urban population bearing units classification, and a finer population-attracting rate curve of buildings.

Cite this article

LI Chu-Juan, WANG Li-Meng, DONG Na . Simulation of Urban Small-area Population Space-time Distribution Based on Building Extraction: Taking Beijing Donghuamen Subdistrict as an Example[J]. Journal of Geo-information Science, 2013 , 15(1) : 19 -28 . DOI: 10.3724/SP.J.1047.2013.00019


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