Journal of Geographical Sciences >
Modeling the spatial distribution of urban population during the daytime and at night based on land use: A case study in Beijing, China
*Corresponding author: Liu Shenghe (1967-), Professor, specialized in urban geography and land use. E-mail:liush@igsnrr.ac.cn
Author: Qi Wei (1989-), PhD, specialized in urban geography. E-mail:cc7v@163.com
Received date: 2014-05-26
Accepted date: 2014-06-27
Online published: 2015-06-15
Supported by
National Natural Science Foundation of China, No.41271174
National Science and Technology Support Program, No.2012BAI32B07
Copyright
Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ‘population, land use and time (daytime or night)’ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows: (1) The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. (2) Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. (3) The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.
QI Wei , LIU Shenghe , GAO Xiaolu , ZHAO Meifeng . Modeling the spatial distribution of urban population during the daytime and at night based on land use: A case study in Beijing, China[J]. Journal of Geographical Sciences, 2015 , 25(6) : 756 -768 . DOI: 10.1007/s11442-015-1200-0
Table 1 The relational model of ‘population - time (daytime and nighttime) - land use’ |
Types of land use (I) | Time | |
---|---|---|
Daytime (D) | Night (N) | |
I1 Farmland | PD1 Working population of primary industry | PN1 Nobody |
I2 Industry & Mining & Warehouse Land | PD2 Working population of secondary industry | PN2 Nobody |
I3 Commerce & Public Management & Service Land | PD3 Working population of tertiary industry (Those staff in PD4, PD5, PD6, PD7, PD11, PD12, PD13 are not involved) | PN3 Nobody |
I4 Kindergarten Land | PD4 Students and staff in kindergarten | PN4 Nobody |
I5 Primary School Land | PD5 Students and staff in primary school | PN5 Nobody |
I6 Vocational School & Middle School Land | PD6 Students and staff in vocational school & middle school | PN6 Nobody |
I7 Teaching & Research Land of Colleges & Universities | PD7 Students and staff in colleges & universities | PN7 Nobody |
I8 Urban & Township Residential Land | PD8 The elderly, infants, the unemployed in urban areas & townships | PN8 Urban resident population (Students in colleges & universities and inpatients are not involved) |
I9 Rural Homestead | PD9 The elderly, infants, the unemployed in rural areas | PN9 Rural resident population |
I10 Accommodations Land of Colleges & Universities | PD10 Nobody | PN10 Students in universities & colleges |
I11 Hotel Land | PD11 Staff in hotels | PN11 Hotel guests |
I12 Hospital Land | PD12 Staff, outpatients and inpatients | PN12 Inpatients |
I13 Scenic Land | PD13 Staff and visitors | PN13 Nobody |
I14 Others | PD14 Nobody | PN14 Nobody |
Note: I8 contains those staff dormitory areas of colleges & universities |
Table 2 Scenic area’s rank coefficient |
Scenic area’s rank | Minimal number of tourists in a year | Scenic area’s rank coefficient |
---|---|---|
5A | 0.6 million | 60 |
4A | 0.5 million | 50 |
3A | 0.3 million | 30 |
2A | 0.1 million | 10 |
A | 0.03 million | 3 |
Figure 1 Location of Haidian District, Beijing |
Table 3 Some parameters of the relational model of ‘population - time (daytime and nighttime) -land use’ in Haidian |
Types of land use | Population during the daytime | Population at night | The total area weights |
---|---|---|---|
I1 Farmland | 2290 | 0 | 58871726.5 |
I2 Industry & Mining & Warehouse Land | 164059 | 0 | 6773584.0 |
I3 Commerce & Public Management & Service Land | 1747151 | 0 | 32029209.4 |
I4 Kindergarten Land | 54441 | 0 | 203259.7 |
I5 Primary School Land | 128724 | 0 | 632876.7 |
I6 Vocational School & Middle School Land | 126868 | 0 | 1494705.7 |
I7 Teaching & Research Land of Colleges & Universities | 350997 | 0 | 10411515.0 |
I8 Urban & Township Residential Land | 459861 | 2936960 | 71400902.7 |
I9 Rural Homestead | 10335 | 72107 | 288723.6 |
I10 Accommodations Land of Colleges & Universities | 0 | 263256 | 2806573.0 |
I11 Hotel Land | 48836 | 23444 | 2251014.3 |
I12 Hospital Land | 43618 | 8347 | 1122445.8 |
I13 Scenic Land | 102226 | 0 | 52263207.8 |
Total | 3239406 | 3304114 |
Figure 2 The histogram of population density during the daytime and at night |
Figure 3 The histogram of population density during the daytime and at nightNote: 1. Yongfeng high-tech industrial base; 2. Wenquan Science &Techonology Park; 3. Shangdi Information Industry Park; 4. Zhongguancun; 5. University District; 6. Shijicheng; 7. Ganjiakou; 8. Wukesong; 9. Gongzhufen |
Figure 4 Schematic of types division method |
Figure 5 The spatial types division based on mean value |
Figure 6 The spatial coupling map of population based on difference value during the daytime and at night in HaidianNote: 1. Yongfeng high-tech industrial base; 2. Wenquan Science &Techonology Park; 3. Shangdi Information Industry Park; 4. Zhongguancun; 5. University District; 6. Shijicheng; 7. Ganjiakou; 8. Wukesong; 9. Gongzhufen |
The authors have declared that no competing interests exist.
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