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Exploring the Temporal and Spatial Evolution of the Urbanization of “Belt and Road” Region Based on Nighttime Light Data

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Geoinformatics in Sustainable Ecosystem and Society (GSES 2019, GeoAI 2019)

Abstract

The “Belt and Road” area is one of the most economically dynamic and promising regions in the world. Exploring the level of urbanization and the evolution of time and space in the region has important practical significance for the “Belt and Road” construction. Taking the nighttime light detain 2003, 2008 and 2013 as the research data, this study extracts the city lights of the “Belt and Road” countries using the threshold method, and constructs the light intensity and light range index to measure the intensity and range of urbanization level in different countries. Statistical analyses are conducted to reveal the spatial and temporal evolution of the urbanization of the “Belt and Road” area. The results of this study indicates: (1) According to the spatial characteristics of urbanization in different regions, urbanization in the “Belt and Road” area includes three different models: the point model, the linear model, and the planar model. (2) Overall intensity and range of urbanization in the “Belt and Road” area has increased over the past 10 years. However, there are significant variations between different countries and regions. (3) Considering the intensity and range of urbanization, the types of urbanization in the “Belt and Road” area can be into six major categories: comprehensive, extended, lifted, stable, agglomerated, and stagnant. Based on these findings, development proposals are proposed for promoting urbanization in the “Belt and Road” area.

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References

  1. Wang, Y.: China connects the world: what is behind the Belt and Road initiative. Front. Educ. China 14(2), 335–338 (2019)

    Article  Google Scholar 

  2. Li, D.R., Han, R., Li, X.: The spatial-temporal pattern analysis of city development in countries along the belt and road initiative based on nighttime light data. Geomat. Inf. Sci. Wuhan Univ. 42, 711–720 (2017)

    Google Scholar 

  3. Chen, M., Sui, Y., Liu, H., et al.: Urbanization patterns and poverty reduction: a new perspective to explore the countries along the Belt and Road. Habitat Int. 84, 1–14 (2019)

    Article  Google Scholar 

  4. Liu, H., Fang, C., Miao, Y., et al.: Spatio-temporal evolution of population and urbanization in the countries along the Belt and Road 1950–2050. J. Geogr. Sci. 28(7), 919–936 (2018)

    Article  Google Scholar 

  5. Chen, M., Liu, W.: Evolution and assessment on China’s urbanization 1960–2010: under-urbanization or over-urbanization. Habitat Int. 178, 25–33 (2013)

    Article  Google Scholar 

  6. Wang, S., Ma, H., Zhao, Y.: Exploring the relationship between urbanization and the eco-environment—A case study of Beijing–Tianjin–Hebei region. Ecol. Ind. 45, 171–183 (2014)

    Article  Google Scholar 

  7. Michaels, G., Rauch, F., Redding, S.J.: Urbanization and structural transformation. Q. J. Econ. 127(2), 535–586 (2012)

    Article  MATH  Google Scholar 

  8. Taubenböck, H., Esch, T., Felbier, A., et al.: Monitoring urbanization in mega cities from space. Remote Sens. Environ. 117, 162–176 (2012)

    Article  Google Scholar 

  9. Zhang, Q., Seto, K.C.: Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data. Remote Sens. Environ. 115(9), 2320–2329 (2011)

    Article  Google Scholar 

  10. Gao, B., Huang, Q., He, C., et al.: Dynamics of urbanization levels in China from 1992 to 2012: perspective from DMSP/OLS nighttime light data. Remote Sens. 7(2), 1721–1735 (2015)

    Article  Google Scholar 

  11. Keola, S., Andersson, M., Hall, O.: Monitoring economic development from space: using nighttime light and land cover data to measure economic growth. World Dev. 66, 322–334 (2015)

    Article  Google Scholar 

  12. Wu, J., Wang, Z., Li, W., et al.: Exploring factors affecting the relationship between light consumption and GDP based on DMSP/OLS nighttime satellite imagery. Remote Sens. Environ. 134, 111–119 (2013)

    Article  Google Scholar 

  13. Ma, T., Zhou, C., Pei, T., et al.: Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: a comparative case study from China’s cities. Remote Sens. Environ. 124, 99–107 (2012)

    Article  Google Scholar 

  14. Small, C., Elvidge, C.D.: Night on Earth: mapping decadal changes of anthropogenic night light in Asia. Int. J. Appl. Earth Obs. Geoinf. 22, 40–52 (2013)

    Article  Google Scholar 

  15. Liu, Z.F., He, C.Y., Zhang, Q.F., et al.: Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landsc. Urban Plan. 106(1), 62–72 (2012)

    Article  Google Scholar 

  16. Zhao, M., Cheng, W.M., Zhou, C.H., et al.: Assessing spatiotemporal characteristics of urbanization dynamics in Southeast Asia using time series of DMSP/OLS nighttime light data. Remote Sens. 10(1), 20 (2018)

    Google Scholar 

  17. He, C., Li, J., Chen, J., et al.: The urbanization process of Bohai Rim in the 1990s by using DMSP/OLS data. J. Geogr. Sci. 16, 174–182 (2006)

    Article  Google Scholar 

  18. de Miguel, A.S., Zamorano, J., Gómez Castaño, J., et al.: Evolution of the energy consumed by street lighting in Spain estimated with DMSP-OLS data. J. Quant. Spectrosc. Radiat. Transf. 139, 109–117 (2014)

    Article  Google Scholar 

  19. Jiang, W., He, G., Leng, W., et al.: Characterizing light pollution trends across protected areas in China using nighttime light remote sensing data. Int. J. Appl. Earth Obs. Geoinf. 7(7), 18 (2018)

    Google Scholar 

  20. Li, X., Zhou, Y.: Urban mapping using DMSP/OLS stable night-time light: a review. Int. J. Remote Sens. 38(21), 6030–6046 (2017)

    Article  Google Scholar 

  21. Emre, Y., Arzu, E.: Examining urbanization dynamics in Turkey using DMSP–OLS and socio-economic data. J. Indian Soc. Remote Sens. 46(7), 1159–1169 (2018)

    Article  Google Scholar 

  22. Wu, J.S., He, S.B., Peng, G., et al.: Intercalibration of DMSP-OLS night-time light data by the invariant region method. Int. J. Remote Sens. 34(20), 7356–7368 (2013)

    Article  Google Scholar 

  23. Imura, H., Cao, X., Chen, J., et al.: A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data. Remote Sens. Environ. 113(10), 2205–2209 (2009)

    Article  Google Scholar 

  24. Zhou, Y., Smith, S.J., Elvidge, C.D., et al.: A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sens. Environ. 147, 173–185 (2014)

    Article  Google Scholar 

  25. Jang, W., He, G.J., Peng, Y., et al.: Application potentiality and prospects of nighttime light remote sensing in “The Belt and Road” initiative. J. Univ. Chin. Acad. Sci. 3, 296–303 (2017)

    Google Scholar 

  26. Song, J.L.: DBAR initiative: big Earth data for “Belt and Road” development. Bull. Chin. Acad. Sci. 30(2), 99–105 (2016)

    Google Scholar 

  27. Chen, Y.: Study on the economic logic of “The Belt and Road” initiative of China. Chin. Bus. Rev. 12, 573–584 (2016)

    Google Scholar 

  28. Chen, Y.B., Zheng, Z.H., Wu, Zh.F., et al.: Review and prospect of application of nighttime light remote sensing data. Progr. Geogr. 38, 205–223 (2019)

    Google Scholar 

  29. Wu, J., He, S., Peng, J., et al.: Intercalibration of DMSP-OLS night-time light data by the invariant region method. Int. J. Remote Sens. 34, 7356–7368 (2013)

    Article  Google Scholar 

  30. Liu, Y., Delahunty, T., Zhao, N.Z., et al.: These lit areas are undeveloped: delimiting China’s urban extents from thresholded nighttime light imagery. Int. J. Appl. Earth Obs. Geoinf. 50, 39–50 (2016)

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 41601163).

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Correspondence to Xu Zhang .

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Tang, P., Huang, J., Zhang, X., Yang, X., Shi, X. (2020). Exploring the Temporal and Spatial Evolution of the Urbanization of “Belt and Road” Region Based on Nighttime Light Data. In: Xie, Y., Li, Y., Yang, J., Xu, J., Deng, Y. (eds) Geoinformatics in Sustainable Ecosystem and Society. GSES GeoAI 2019 2019. Communications in Computer and Information Science, vol 1228. Springer, Singapore. https://doi.org/10.1007/978-981-15-6106-1_17

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  • DOI: https://doi.org/10.1007/978-981-15-6106-1_17

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