Population distribution characteristics and its relationship with natural factors in karst mountainous areas of Northwest Guangxi

Shana Shi, Bingkang Xie, Baoqing Hu, Chuanyong Tang, Yan Yan, Xiaoqing Li

Article ID: 1303
Vol 3, Issue 1, 2020

VIEWS - 245 (Abstract) 130 (PDF)

Abstract


The smallest administrative unit of the sixth national census-township (town) is selected as the basic unit, the population spatial distribution characteristics at the township (town) level in karst mountainous areas of northwest Guangxi are analyzed by using Lorenz curve and spatial correlation analysis method, and the influence intensity of natural factors on regional population spatial distribution is detected by using geographic detector method. The results show that: 1. the spatial distribution of population at the township (town) level has the characteristics of imbalance, showing generally significant positive correlation and certain aggregation; 2. There are significant differences in the impact of the spatial distribution of various natural factors on the population distribution. For the towns without karst distribution in the northwest and central south of the study area, the population density increases with the increase of factors conducive to human residence, but the average population density is only 79 people/km2. In the towns with karst distribution in the East and south, the spatial distribution of population density and natural factors is not a simple increase or decrease relationship, but fluctuates with the change of karst distribution area. 3. The factor detection results of the geographic detector show that the altitude has the greatest impact on the spatial distribution of population. The interactive detection results show that the impact intensity of any two natural factors after superposition and interaction presents nonlinear enhancement and two factor enhancement. It can be seen that the karst mountain area in northwest Guangxi is similar to other areas. Altitude is one of the main factors affecting the spatial distribution of population, but the river network density and unique geological landform of karst mountain area have a strong catalytic effect on the spatial distribution of population. The superposition and interaction with other factors can further strengthen the impact on population distribution.


Keywords


Karst Mountain Area; Population Distribution Characteristics; Geographic Detectors; Northwest Guangxi; Guangxi

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References


1. Feng Z, Yang Y, You Z. Research on land resources restriction on population distribution in China, 2000–2010. Geographical Research 2014; 33(8): 1395–1405.

2. Shen S, Wang C, Tang J. Research on influential factors of population distribution in Henan province based on GWR model. Mathematics in Practice and Theory 2014; 44 (3): 165–174.

3. Zhang S. Population geography studies. Shanghai: East China Normal University Press; 1997.

4. Fang Y, Ouyang Z, Zheng H, et al. Natural forming causes of China population distribution. Chinese Journal of Applied Ecology 2012; 23(12): 3488–3495.

5. Hu H. The distribution of population in China. Acta Geographica Sinica 1935; 2(2): 33–74.

6. Small C, Cohen JE. Continental physiography, climate and the global distribution of human population. Current Anthropology 2004; 45(2): 269–277.

7. Liao Y, Wang J, Meng B, et al. Integration of GP and GA for mapping population distribution. International Journal of Geographical Information Science 2010; 24(1): 47–67.

8. Pan Q, Jin X, Zhou Y. Population change and spatiotemporal distribution of China in recent 300 years. Geographical Research 2013; 32(7): 1291–1302.

9. Yang Q, Li L, Wang Y, et al. Spatial distribution pattern of population and characteristics of its evolution in China during 1935–2010. Geographical Research 2016; 35(8): 1547–1560.

10. Dobson JE, Bright EA, Coleman PR, et al. Land Scan: A global population database for estimating populations at risk. Photogrammetric Engineering and Remote Sensing 2000; 66(7): 849–857.

11. Briggs DJ, Gulliver J, Fecht D, et al. Dasymetric modelling of small-area population distribution using land cover and light emissions data. Remote Sensing of Environment 2007; 108(4): 451–466.

12. Yue T, Wang Y, Liu J, et al. Surface modelling of human population distribution in China. Ecological Modelling 2004; 181(4): 461–478.

13. Feng Z, Tang Y, Yang Y, et al. The relief degree of land surface in China and its correlation with population distribution. Acta Geographica Sinica 2007; 62(10): 1073–1082.

14. Lv C, Fan J, Sun W. Population distribution and the influencing factors based on ESDA. Economic Geography 2009; 29(11): 1797–1802.

15. Song G, Li Z, Bao Y, et al. Spatial distribution regularity and influence factors of population density in the LRGR. Chinese Science Bulletin 2007; 52(2): 90–97.

16. Wang S, Yang C, Pang H, et al. Characteristics of population distribution in the Pearl River basin and the impact factors analysis. China Population. Resources and Environment 2014; 24(S2): 447–450.

17. Chen M, Xu C, Wang R. Key natural impacting factors of China’s human population distribution. Population and Environment 2007; 28(3): 187–200.

18. Small C. Global analysis of urban population distributions and the physical environment. Proceedings of the open meeting of the human dimensions of global environmental change research community. Riode Janeiro: Brazil Academy of Science; 2001. p. 6–8.

19. Balk DL, Deichmann U, Yetman G, et al. Determining global population distribution: Methods, applications and data. Advances in Parasitology 2006; 62: 119–156.

20. Zhang J, Liang J, Zhu Y, et al. Land and GDP’s function on population distribution in China. Scientia Geographica Sinica 2017; 37(7): 1006–1013.

21. Yang K. Population distribution and multicenter measurement of great Beijing. China Population. Resources and Environment 2015; 25(2): 83–89.

22. Feng Z, Yang Y, You Z, et al. Research on the suitability of population distribution at the county level in China. Acta Geographica Sinica 2014; 69(6): 723–737.

23. Zhang Z, Pan J, Da F. Population spatial structure evolution pattern and regulation pathway in Lanzhou city. Geographical Research 2012; 31(11): 2055–2068.

24. Liang H, Liu Y. Study on spatiotemporal change and simulation of population in Beijing based on census data. Acta Geographica Sinica 2014; 69(10): 1487–1495.

25. Che B, Qiu F. Spatiotemporal changes of population distribution at sub-district level in Jiangsu Province. Scientia Geographica Sinica 2015; 35(11): 1381–1387.

26. Bai Z, Wang J, Yang Y, et al. Characterizing spatial patterns of population distribution at town-ship level across the 25 provinces in China. Acta Geographica Sinica 2015; 70(8): 1229–1242.

27. Zhang S. Studies on vertical distribution of the population and reasonable redistribution in the Chinese mountain areas. Shanghai: East China Normal University Press; 1996.

28. Liao S, Sun J. Quantitative analysis of relationship between population distribution and environ-mental factors in Qinghai-Tibet Plateau. China Population. Resources and Environment 2003; 13(3): 65–70.

29. Zeng Y. Research on population distribution and its influence mechanism in plateau and alpine region by spatial econometric modeling. South China Population 2014; 29(3): 1–9.

30. Du B, Zhang Y. Characteristics of population distribution in plateau mountainous areas and their major influencing factors: A panel data analysis in Bijie area. Population Research 2011; 35(5): 90–101.

31. Li X, Zhang S. Study on the natural environmental factors affecting population distribution in the Guizhou karst plateau: Analysis on the main factors. Arid Zone Research 2007; 23(1): 120–125.

32. Li X. Study on the natural environmental factors affecting population distribution in the Guizhou karst plateau: Multivariate regression analysis and zonality. Arid Zone Research 2007; 23(2): 280–286.

33. Zhang X, Wang S, Bai X, et al. Relationships between the spatial distribution of karst land desertification and geomorphology, lithology, precipitation, and population density in Guizhou Province. Earth and Environment 2013; 41(1): 1–6.

34. Tang S, Wang S, Feng X, et al. System dynamic model for sustainable development of socio-economic and ecological environment in karst area of northwest Guangxi province in China. Journal of Safety and Environment 2001; 1(3): 36–40.

35. Zhang M, Wang K, Liu H, et al. Spatio-temporal variation of vegetation carbon storage and density in karst areas of northwest Guangxi based on remote sensing image. Chinese Journal of Eco Agriculture 2013; 21(12): 1545–1553.

36. Population Census Office under the State Council Department of Population, Employment Statistics under the National Bureau of Statistics (NBS). Tabulation on the 2010 population census of the People’s Republic of China. Beijing: China Statistics Press; 2012.

37. The Editorial Committee of Geomorphologic Atlas of People’s Republic of China. The geomorphologic atlas of People’s Republic of China (1:1000000). Beijing: Science Press; 2009.

38. Lorenz MO. Method of measuring the concentration of wealth. Publications of the American Statistical Association 1905; 70(9): 209–219.

39. Wang J, Xu C. Geodetector: Principle and prospective. Acta Geographica Sinica 2017; 72 (1): 116–134.

40. Wang J, Hu Y. Environmental health risk detection with Geog Detector. Environmental Modelling & Software 2012; 33(2): 114–115.

41. Lyu C, Lan X, Sun W. A study on the relationship between natural factors and population distribution in Beijing using geographical detector. Journal of Natural Resources 2017; 32(8): 1385–1397.

42. Li X. The influence of space structure of population in karst plateau and mountain area on sustainable development. Shanghai: East China Normal University; 2007.

43. Zhang D, Ouyang Z, Wang S. Population resources environment and sustainable development in the karst region of southwest China. China Population Resources and Environment 2001; 11(1): 78–82.




DOI: https://doi.org/10.24294/jgc.v3i1.1303

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