An investigation of Indicators for Population Density and Immigration in Bangkok: A Comparative Study of Transportation, Economy, Residence, Healthcare and Education Factors
Keywords:
Population density, Population immigration, Krung Thep Maha Nakhon (Bangkok)Abstract
This research studies the factors which have effects on the population distribution and their migration. The researcher collected the data from 50 districts in Bangkok. The five main factors are transportation, economy, residence, medication and education. All factors comprise 18 variables in total, the data concerning each variable was collected from each district in Bangkok. For the data analysis, the Geo-detector software was used in the data processing stage. The results show that “there are 5 influential factors that mostly contribute to the population distribution and their migration” which are “the length of main roads”, “the nearest distance from Don Mueang International Airport”, “the nearest distance from Suvarnabhumi Airport”, “the average monthly expenses”, and “the number of condominiums”. When the 5 variables are detected with other factors, this leads to the population density and migration. Bangkok development planning can apply this software. It can help government agencies and state enterprises decide on the suitable projects. These findings beneficially support the decision involving Bangkok development plan since it can solve the problem concerning the unbalance population distribution which may occur in the future. For this research, the researcher has learned how to use Geo-detector software. Besides, the researcher can also use Geo-detector software to deal with other problems in Thailand.
References
P. Dasgupta, “The population problem: theory and evidence. Journal of economic literature,” Journal of Economic Literature, vol. 33, no. 4, pp. 1879–1902, 1995.
Y. Liu and F. Yamauchi, “Population density, migration, and the returns to human capital and land: Insights from Indonesia,” Food Policy, vol. 48, pp. 182–193, 2014, doi: 10.1016/j.foodpol.2014.05.003.
S. S. Kim, C. K. Lee and D. B. Klenosky, “The influence of push and pull factors at Korean national parks,” Tourism management, vol. 24, no. 2, pp. 169–180, 2003, doi: 10.1016/S0261-5177(02)00059-6.
E. Swyngedouw, F. Moulaert and A. Rodriguez, “Neoliberal urbanization in Europe: large–scale urban development projects and the new urban policy,” Antipode, vol. 34, no. 3, pp. 542–577, 2002, doi: 10.1111/1467-8330.00254.
D. L. Carr, L. Suter and A. Barbieri, “Population dynamics and tropical deforestation: state of the debate and conceptual challenges,” Population and Environment, vol. 27, no. 1, pp. 89–113, 2005, doi: 10.1007/s11111-005-0014-x.
Y. N. Guo, J. Cheng, Y. Y. Cao and Y. Lin, “A novel multi-population cultural algorithm adopting knowledge migration,” Soft computing, vol. 15, pp. 897–905, 2011, doi: 10.1007/s00500-010-0556-4.
P. H. Gleick, “Transitions to freshwater sustainability,”. Proceedings of the National Academy of Sciences, vol. 115, no.36, pp. 8863–8871, 2018, doi: 10.1073/pnas.1808
M. T. Hannan and J. Freeman, “The population ecology of organizations,” American journal of sociology, vol. 82, no. 5, pp. 929–964, 1977.
G. P. Li and X. X. Chen, “Empirical research on influencing factors on population growth of Beijing-Tianjin-Hebei Metropolitan Region,” Geographical. Research, vol. 28, pp. 191–202, 2009.
A. Lomnicki, “Individual-based models and the individual-based approach to population ecology,” in eLs, New York, NY, USA: John Wiley & Sons, Inc., 2011, [Online]. Available: http://doi.org/10.1002/9780470015902.a0003312.pub2
J. Damuth, “Population density and body size in mammals,” Nature, vol. 290, pp. 699–700, 1981, Art. no. 5808.
Y. Ren, L. Deng, S. Zuo, Y. Luo, G. Shao, X. Wei, L. Hua and Y.Yang, “Geographical modeling of spatial interaction between human activity and forest connectivity in an urban landscape of southeast China,” Landscape Ecology, vol. 29, pp. 1741–1758, 2014, doi: 10.1007/s10980-014-0094-z.
M. Renkow and D. Hoover, “Commuting, migration, and rural ‐ urban population dynamics,” Journal of regional science, vol. 40, no. 2, pp. 261–287, 2000, doi: 10.1111/0022-4146.00174.
J. Shen, N. Zhang, Gexigeduren, B. He, C. -Y. Liu, Y. Li, H. -Y. Zhang, , X. -Y. Chen and H. Lin, “Construction of a GeogDetector-based model system to indicate the potential occurrence of grasshoppers in Inner Mongolia steppe habitats,” Bulletin of Entomological Research, vol. 105, pp. 335–346, 2015, doi: 10.1017/S0007485315000152.
A. Shrestha, “Application of Geodetector Method and Other Statistical Methods to Study Groundwater Vulnerability to Nitrate Contamination in The Central Valley Aquifer, California,” Ph.D. dissertation, Dept. Geographic and Atmospheric Sciences, Northern Illinois Univ., Northeast Illinois, IL, USA, 2019.
L. Wang and L. Chen, “The impact of new transportation modes on population distribution in Jing-Jin-Ji region of China,” Scientific data, vol. 5, 2018, Art. no. 170204, doi: 10.1038/sdata.2017.204.
Walters, A. J. C. & Freeman, G. M. The quality of big (geo) data. Dia. In Hum. Geogr 3, 280–284 (2013).
J. F. Wang, X. H. Li, G. Christakos, Y. -L. Liao, T. Zhang, X. Gu and X. -Y Zheng, “Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China,” International Journal of Geographical Information Science, vol. 24, no. 1, pp. 107–217, 2010, doi: 10.1080/13658810802443457.
S. Uttayanin, A. Intaraksa and K. Duangmal, “Influences of Socio-Economic Factors Affecting to Population Dynamics in Thung Rangsit Area, Pathum Thani,” Journal of the Association of Researchers, vol. 24, no. 2, pp. 111–122, 2020.
H. Wang, J. Gao and W. Hou, “Quantitative attribution analysis of soil erosion in different geomorphological types in karst areas: Based on the geodetector method,” Journal of Geographical Sciences, vol. 29, pp. 271–286, 2019, doi: 10.1007/s11442-019-1596-z.
W. Xinge, X. Jianchao, Y. Dongyang, and C. Tian, “Spatial Differentiation of Rural Touristization and Its Determinants in China: A Geo-Detector-Based Case Study of Yesanpo Scenic Area,” Journal of Resources and Ecology, vol. 7, no. 6, pp. 464–471, 2016, doi: 10.5814/j.issn.1674-764x.2016.06.006.
Y. Yang, X. Yang, M. He and G. Christakos, “Beyond mere pollution source identification: Determination of land covers emitting soil heavy metals by combining PCA/APCS, GeoDetector and GIS analysis,” Catena, vol. 185, 2020, Art. no. 104297, doi: 10.1016/j.catena.2019.104297.
K. Kopczewska, P. Churski, A. Ochojski, and A. Polko, “SPAG: Index of spatial agglomeration,”. Papers in Regional Science, vol. 98, no. 6, pp. 2391–2424, 2019, doi: 10.1111/pirs.12470.
K. Zhang, D. Sun , S. Shen and Y. Zhu, “Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data,” Journal of Transport and Land Use, vol. 10, no. 1, pp. 675–694, 2017, doi: 10.5198/jtlu.2017.954.
C. Rodjam, “Factors affecting towards migration of labor from rural areas to Bangkok,” Rajapruk University, Nonthaburi, Thailand, Final Rep, 2011.(in Thai)
W. Khuan-arch and P. Thinphanga, “Definition of Urban and Urbanization,” in Urbanisation in Thailand, Bangkok, Thailand: Environment Institute, pp. 1–34, [Online] Available: http://www.tei.or.th/thaicityclimate/public/research-46.pdf
S. Wang, D. Yu, X. Ma and X. Xing, “Analyzing urban traffic demand distribution and the correlation between traffic flow and the built environment based on detector data and POIs,” European Transport Research Review, vol. 10, 2018, Art. no. 50, doi:10.1186/s12544-018-0325-5.
X. Wang, L. Gu, T. J. Kwon and T. Z. Qiu, “A geostatistical investigation into the effective spatiotemporal coverage of road weather information systems in Alberta,” Journal of Advanced Transportation, vol. 2018, 2018, Art. no. 5179694, doi:10.1155/2018/5179694.
X. Lin, J. Yang, Z. Tao, J. Song and T. Ren, “Transport investment, economic spatial aggregation, and multiple paths: A joint estimation by spatial panel and structural equation modeling,” Acta Geographica Sinica, vol. 73, no. 10, pp. 1970–1984, 2018, doi: 10.11821/dlxb201810011.
J. Cai, B. Xu , K. K. Y. Chan, X. Zhang, B. Zhang, Z. Chen and B. Xu, “Roles of different transport modes in the spatial spread of the 2009 influenza A(H1N1) pandemic in mainland China,” International Journal of Environmental Research and Public Health, vol. 16, no. 2, 2019, doi: 10.3390/ijerph16020222.
X. Lin, I. MacLachlan, T. Ren and F. Sun, “ Quantifying economic effects of transportation investment considering spatiotemporal heterogeneity in China: a spatial panel data model perspective,” The Annals of Regional Science, vol. 63, pp. 437–459, 2019, doi: 10.1007/s00168-019-00937-8.
X. Q. Hao, Y. P. Shi and X. N. Zhang XN, ”The distribution of traffic crashes and the geographical detection of influencing factors in county,” Transportation Engineering, vol. 19, no. 6, pp. 53-60, 2019.
J. B. Zhang and Q. L. Chen, “Analysis of spatial temporal evolution and influencing factor in regional integrated transport efficiency differences,” Journal of Guizhou University (Social Sciences) , vol. 37, no. 6, pp. 34-42, 2019.
S. Li, D. Lyu, G. Huang, X. Zhang, F. Gao, Y. Chen, X. Liu, “Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China,” Journal of Transport Geography, vol. 82, 2020, Art. no. 102631, doi: 10.1016/j.jtrangeo.2019.102631.
J. Liu, S. Nambisan, X. Li and X. Fu, “Are young Americans carless across the United States? A spatial analysis,” Transportation Research Part D, vol. 78, 2020, doi: 10.1016/j.trd.2019.11.026.
Y. Song, P. Wu, D. Gilmore and Q. Li, “A spatial heterogeneity-based segmentation model for analyzing road deterioration network data in multi-scale infrastructure systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 11, pp. 7073–7083, 2020, doi: 10.1109/TITS.2020.3001193.
B. Lu, M. Liu, Q. Ming, A. Liu and T. Li, “Coupling and coordination situation and dynamic mechanism between tourism and transportation industry in China,” World Regional Studies, vol. 29, no. 1, pp. 148–158, 2020, doi: 10.3969/j.issn.1004-9479.2020.01.2018429.
A. Shrestha and W. Luo, “An assessment of groundwater contamination in Central Valley aquifer, California using geodetector method,” Annals of GIS, vol. 23, no. 3, pp. 149–166, 2017 doi: 10.1080/19475683.2017.1346707.
A. Shrestha and W. Luo “Analysis of groundwater nitrate contamination in the central valley: comparison of the Geodetector Method, Principal Component Analysis and Geographically Weighted Regression,” ISPRS International Journal of Geo-Information, vol. 6, no. 10, pp. 297, 2017, doi: 10.3390/ijgi6100297.
W. Jinfeng. (2018). Geodetector & Its Applications in Natural & Social Sciences [Online]. Available: http://www.sssampling.cn/down/181203Geodetector-open.pdf
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The published articles are copyrighted by the School of Engineering, King Mongkut's Institute of Technology Ladkrabang.
The statements contained in each article in this academic journal are the personal opinions of each author and are not related to King Mongkut's Institute of Technology Ladkrabang and other faculty members in the institute.
Responsibility for all elements of each article belongs to each author; If there are any mistakes, each author is solely responsible for his own articles.
