Nighttime light remote sensing reveals the pattern and process of urbanization evolution in northwest China since the 21st century

  • role: First author第一作者
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

  • Email:syliu@stu.ecnu.edu.cn
  • Introduction:E-mail syliu@stu.ecnu.edu.cn
LIU Shaoyang12,  
  • Affiliation:

    Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350116, China

    Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China

CHEN Zuoqi34,  
  • Affiliation:

    School of Geographical Sciences, Southwest University, Chongqing 400715, China

SHI Kaifang5,  
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

WU Bin12,  
  • Affiliation:

    School of Geographical Sciences, Northeast Normal University, Changchun 130024, China

WEI Ye6,  
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

WANG Congxiao12,  
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

LI Xia12,  
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

WU Jianping12,  
  • role: Corresponding author通信作者
  • Affiliation:

    Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

    School of Geographic Sciences, East China Normal University, Shanghai 200241, China

  • Email:blyu@geo.ecnu.edu.cn
  • Introduction:E-mail blyu@geo.ecnu.edu.cn
YU Bailang12*

реферат

Given that Xinjiang Uygur Autonomous Region is a strategic barrier and an important platform of opening up to the western region, assessing its urbanization is critical to promote the national reform strategy and the Belt and Road Initiative. Compared with traditional method, nighttime light (NTL) remote sensing has been proved to be able to monitor human activity intensity and regional comprehensive development level in a more objective, flexible spatial scale and wider coverage. NTL remote sensing data has been able to analyze the urbanization evolution process and the level of social and economic development, but it is still necessary to expand and enrich the breadth and depth of research, especially to explore its spatial pattern and long-term evolution process, so as to more comprehensively understand the urbanization process and social development balance in Xinjiang.This paper comprehensively analyzes and discusses the evolution process of NTL in Xinjiang since the 21st century from three dimensions: time change trend, spatial distribution pattern and social development equilibrium, using NTL remote sensing data of long time series from 2000 to 2020, time series decomposition, spatial standard deviation ellipse and Night Light Development Index (NLDI).(1) From 2000 to 2020, the total amount of NTL in all regions of Xinjiang Uygur Autonomous Region increased to varying degrees. In terms of spatial pattern, urbanization in northern and eastern Xinjiang developed steadily, while rapid development in southern Xinjiang. The planning and construction of transportation lines is one of the important driving forces for the spatial expansion of urbanization in Xinjiang. (2) In the past 20 years, the total amount of NTL in Xinjiang has increased by 5.30 times, and the growth trend is accelerating. The NTL intensity in rural areas of Xinjiang increased by 7.60 times, which was larger than that in urban areas (4.10 times). The process of urbanization in Xinjiang can be divided into three stages: slow development (before 2007), volatile growth (from 2008 to 2014), and rapid development (after 2015). Policy support and the transformation of industrial and agricultural development make Xinjiang’s urbanization transition from the slow development period to the volatile growth period. The growth rate of the volatile growth period is nearly three times that of the slow development period, but at the same time, it is also disturbed by various extreme events. (3) From 2000 to 2019, the NLDI in most areas of Xinjiang decreased, the distribution of population and infrastructure construction in the whole region and most cities in Xinjiang became more reasonable, and the social development showed a trend of balanced development. However, compared with urban areas, the balance in rural areas of Xinjiang is weaker. This is due to the low starting point of urbanization development in rural areas of Xinjiang, which is still in the stage of rapid development, and urbanization is undergoing a process of “from point to surface”, so the current social development balance in rural areas shows a trend of decline. In general, the urbanization process of Xinjiang has been developing rapidly and evenly since the 21st century.

ключеви́че слова́

nighttime light remote sensing;urbanization evolution;time series decomposition;Night Light Development Index;Xinjiang Uygur Autonomous Region

References

  1. 1.
    Ai H J and Jiang H P. 2017. Evaluation of modern agricultural development stage based on entropy value method in Xinjiang. Jiangsu Agricultural Sciences, 45(18): 318-321
  2. 2.
    Cao X, Wang J M, Chen J and Shi F. 2014. Spatialization of electricity consumption of China using saturation-corrected DMSP-OLS data. International Journal of Applied Earth Observation and Geoinformation, 28: 193-200
  3. 3.
    Chang H J and He L Z. 2013. Analysis on economic growth fluctuation of Xinjiang Province. Science and Technology Management Research, 33(5): 90-95, 108
  4. 4.
    Chen M X. 2015. Research progress and scientific issues in the field of urbanization. Geographical Research, 34(4): 614-630
  5. 5.
    Chen M X, Lu D D and Zhang H. 2009. Comprehensive evaluation and the driving factors of China’s urbanization. Acta Geographica Sinica, 64(4): 387-398
  6. 6.
    Chen X, Chang C, Bao A M, Wu S X and Luo G P. 2020. Spatial pattern and characteristics of land cover change in Xinjiang since past 40 years of the economic reform and opening up. Arid Land Geography, 43(1): 1-11
  7. 7.
    Chen Z Q, Yu B L, Song W, Liu H X, Wu Q S, Shi K F and Wu J P. 2017. A new approach for detecting urban centers and their spatial structure with nighttime light remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 55(11): 6305-6319
  8. 8.
    Chen Z Q, Yu B L, Yang C S, Zhou Y Y, Yao S J, Qian X J, Wang C X, Wu B and Wu J P. 2021. An extended time series (2000-2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration. Earth System Science Data, 13(3): 889-906
  9. 9.
    Cheng W M. 2016. Research on Regional Economic Disparity and Coordinated Development in Xinjiang Under the Background of “New Normal”. Urumqi: Xinjiang Normal University
  10. 10.
    Cleveland R B and Cleveland W S. 1990. STL: a seasonal-trend decomposition procedure based on Loess. Journal of Official Statistics, 6(1): 3-33
  11. 11.
    Croft T A. 1978. Nighttime images of the earth from space. Scientific American, 239(1): 86-98
  12. 12.
    Dietzel C, Herold M, Hemphill J J and Clarke K C. 2005. Spatio-temporal dynamics in California’s central valley: empirical links to urban theory. International Journal of Geographical Information Science, 19(2): 175-195
  13. 13.
    Dong W, Yang Y and Zhou Y S. 2011. Land use changes and evaluation of land use efficiency in an arid oasis city: a case of Urumqi, China. Arid Land Geography, 34(4): 679-685
  14. 14.
    Elvidge C D, Baugh K E, Anderson S J, Sutton P C and Ghosh T. 2012. The night light development index (NLDI): a spatially explicit measure of human development from satellite data. Social Geography, 7(1): 23-35
  15. 15.
    Elvidge C D, Baugh K E, Kihn E A, Kroehl H W, Davis E R and Davis C W. 1997. Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. International Journal of Remote Sensing, 18(6): 1373-1379
  16. 16.
    Elvidge C D, Sutton P C, Ghosh T, Tuttle B T, Baugh K E, Bhaduri B and Bright E. 2009. A global poverty map derived from satellite data. Computers and Geosciences, 35(8): 1652-1660
  17. 17.
    Fan X J, Zhang Y F and Cheng Z Z. 2019. Research on energy consumption of Xinjiang based on DMSP/OLS night light data from 1992 to 2013. Remote Sensing for Land and Resources, 31(1): 212-219
  18. 18.
    Friedmann J. 2006. Four theses in the study of China’s urbanization. International Journal of Urban and Regional Research, 30(2): 440-451
  19. 19.
    Gan C C and Nie C X. 2013. An analysis of development stages of regional economy in Xinjiang. Commercial Research, 55(4): 40-47
  20. 20.
    Gao Q and Kasimu A. 2017. Modeling the population spatial distribution of Tianshan north-slope urban agglomeration based on DMSP/OLS night lighting data. Northwest Population Journal, 38(3): 113-120
  21. 21.
    Gu C L, Hu L Q and Cook I G. 2017. China’s urbanization in 1949-2015: processes and driving forces. Chinese Geographical Science, 27(6): 847-859
  22. 22.
    Han C X, Ma Y F and Luo H. 2010. Economic spatial evolution and its mechanism in Xinjiang. Arid Land Geography, 33(3): 449-455
  23. 23.
    He C Y, Shi P J, Li J G, Chen J, Pan Y Z, Li J, Zhuo L and Toshiaki I. 2006. Reconstruction of spatial process of urbanization in mainland China in 1990s based on DMSP/OLS nighttime light data and statistical data. Chinese Science Bulletin, 51(7): 856-861
  24. 24.
    Huang D Y. 2006. On railway and the town construction in Xinjiang. China’s Borderland History and Geography Studies, 16(1): 89-96
  25. 25.
    Ju C Y, Zhou X and He Q. 2016. On the application of a concentric zone model (CZM) for classifying and extracting urban boundaries using night-time stable light data in Urumqi of Xinjiang, China. Remote Sensing Letters, 7(11): 1033-1042
  26. 26.
    Kasimu A, Tang B and Gulikezi T. 2013. Analysis of the spatial-temporal dynamic changes of urban expansion in oasis of Xinjiang based on RS and GIS. Journal of Glaciology and Geocryology, 35(4): 1056-1064
  27. 27.
    Kuechly H U, Kyba C C M, Ruhtz T, Lindemann C, Wolter C, Fischer J and Hölker F. 2012. Aerial survey and spatial analysis of sources of light pollution in Berlin, Germany. Remote Sensing of Environment, 126: 39-50
  28. 28.
    Li D R, Yu H R and Li X. 2017. The spatial-temporal pattern analysis of city development in countries along the Belt and Road Initiative based on nighttime light data. Geomatics and Information Science of Wuhan University, 42(6): 711-720
  29. 29.
    Li S X. 2016. Research on Spatio-Temporal Differentiation of Urbanization Development Quality in Xinjiang. Shihezi: Shihezi University
  30. 30.
    Li S X and Zhang J M. 2016. Evaluation on spatial association between cities along the Silk Road. Urban Problems, (5): 20-26
  31. 31.
    Li X P, Yang X D and Gong L. 2020. Evaluating the influencing factors of urbanization in the Xinjiang Uygur Autonomous Region over the past 27 years based on VIIRS-DNB and DMSP/OLS nightlight imageries. PLoS One, 15(7): e0235903
  32. 32.
    Li Y X, Chen K and Cheng X J. 2020. Analysis on the spatial pattern and causes of regional economic differences in Xinjiang: evidence from population activity and residents’ happiness. Journal of Shihezi University (Philosophy and Social Sciences), 34(1): 16-23
  33. 33.
    Lin J P, Lei J, Wu S X, Yang Z and Li J G. 2020. Spatial pattern and influencing factors of oasis rural settlements in Xinjiang, China. Geographical Research, 39(5): 1182-119
  34. 34.
    Liu B B and Cao Z R. 2013. Strategic position of Xinjiang in China and in China’s opening to the west. Research of Agricultural Modernization, 34(6): 659-663
  35. 35.
    Liu J B. 2015. Regional Space Economic Ties Research of Xinjiang Cities. Urumqi: Xinjiang University of Finance and Economics
  36. 36.
    Liu S W and Zhang P Y. 2012. Regional economic disparities analysis of Xinjiang from 1989 to 2010. Economic Geography, 32(9): 26-31
  37. 37.
    Lu B and Zhang X L. 2002. Study on coordination of urbanization and economic development in Xinjiang. Arid Land Geography, 25(2): 189-192
  38. 38.
    Ma T. 2019. Spatiotemporal characteristics of urbanization in China from the perspective of remotely sensed big data of nighttime light. Journal of Geo-information Science, 21(1): 59-67
  39. 39.
    Ma T, Zhou C H, Pei T, Haynie S and Fan J F. 2012. Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: a comparative case study from China’s cities. Remote Sensing of Environment, 124: 99-107
  40. 40.
    Meng Y S, Li L and Xia X G. 2013. Study on the coordinated development of new industrialization, agricultural and animal husbandry modernization and new urbanization in Xinjiang. Social Sciences in Xinjiang, (6): 45-51
  41. 41.
    National Development and Reform Commission, Ministry of Foreign Affairs of the People’s Republic of China, Ministry of Commerce of the People’s Republic of China. 2015-03-29(04). Vision and actions on jointly building silk road economic belt and 21st-century maritime silk road. People’s Daily (国家发展改革委, 外交部, 商务部. 2015-03-29(04). 推动共建丝绸之路经济带和21世纪海上丝绸之路的愿景与行动. 人民日报)
  42. 42.
    Northam R M. 1979. Urban Geography. New York: Wiley.
  43. 43.
    Peng B, Zhang Q, Liu L C and Sun W J. 2022. Estimating dynamics of development balance in Xinjiang autonomous region: evidence from the nighttime lighting dataset. Science of Surveying and Mapping, 47(1): 133-141.
  44. 44.
    Qiao X W. 2019. Research on Temporal and Spatial Pattern Changes of Xinjiang Cities Based on DMSP/OLS Nighttime Light Data. Hohhot: Xinjiang University
  45. 45.
    Qin F M and Sun Q F. 2011. General assessment of industrialization in Xinjiang. Journal of Xinjiang Normal University (Social Sciences), 32(1): 8-16
  46. 46.
    Ruzi T, Kasimu A, Gao P W and Zhao M C. 2020. Study on the spatiotemporal changes of Xinjiang urban expansion based on DMSP/OLS and NPP/VIIRS data. Journal of China Agricultural University, 25(9): 156-165
  47. 47.
    Sawuti R and Kasimu A. 2015. Spatio-temporal dynamic characteristics of major cities expansion in Xinjiang in 20 years. Arid Zone Research, 32(3): 606-613
  48. 48.
    Shi K F, Chen Y, Yu B L, Xu T B, Chen Z Q, Liu R, Li L Y and Wu J P. 2016a. Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis. Applied Energy, 168: 523-533
  49. 49.
    Shi K F, Chen Y, Yu B L, Xu T B, Yang C S, Li L Y, Huang C, Chen Z Q, Liu R and Wu J P. 2016b. Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data. Applied Energy, 184: 450-463
  50. 50.
    Sokal R R and Oden N L. 1978. Spatial autocorrelation in biology: 1. Methodology. Biological Journal of the Linnean Society, 10(2): 199-228
  51. 51.
    Song Y H and Wang N. 2019. Study on the city economic relation and regional economic development in northwest Xinjiang. Economic Forum, (5): 24-32
  52. 52.
    Tang B. 2013. Spatial and Temporal Evolution of Regional Urbanization Pattern in Xinjiang Based on ESDA. Urumqi: Xinjiang Normal University
  53. 53.
    Urban Social and Economic Survey Department of the National Bureau of Statistics. 2000-2020. China City Statistical Yearbook. Beijing: China Statistics Press
  54. 54.
    Wang B L and Zhang X L. 2010. The contribution of highway traffic infrastructure construction to economic growth in Xinjiang based on I-O and ESDA. Acta Geographica Sinica, 65(12): 1522-1533
  55. 55.
    Wang C H, Hao Y L and Ma Q L. 2013. An analysis of the factors affecting the regional development imbalance between the northern and southern Xinjiang. Journal of Xinjiang University (Philosophy, Humanities and Social Sciences), 41(2): 1-6
  56. 56.
    Wang G X. 2013. The basic theory of urbanization and problems and countermeasures of China's urbanization. Population Research, 37(6): 43-51
  57. 57.
    Wang K, Bai L Y and Feng J Z. 2017. Urbanization process monitoring in Northwest China based on DMSP/OLS nighttime light data. IOP Conference Series: Earth and Environmental Science, 57(1): 012057
  58. 58.
    Wei Y P. 2007. Study on the relationships between regional economic development and urbanization process in Xinjiang Province, China. Economic Geography, 27(4): 553-557
  59. 59.
    Xiao Y Q, Yang D G, Zhang X H, Pan W and Tang H. 2012. Spatio-temporal characteristics of regional economic differences in Xinjiang. Journal of Desert Research, 32(1): 244-251
  60. 60.
    Xie H Q, Wang Z, Huang F J and Zhang Z H. 2016. The interannual variation of rural per capita net income in the three prefectures of south Xinjiang based on noctilucent remote sensing. Journal of Glaciology and Geocryology, 38(3): 819-828
  61. 61.
    Xu H M, Yang H, Xi L T, Li X, Jin H R and Li D R. 2015. Multi-scale measurement of regional inequality in mainland China during 2005-2010 using DMSP/OLS night light imagery and population density grid data. Sustainability, 7(10): 13469-13499
  62. 62.
    Yan H L. 2014. Exploration and Practice of Xinjiang New Urbanization. Beijing: Economy and Management Publishing House
  63. 63.
    Yu B L, Shu S, Liu H X, Song W, Wu J P, Wang L and Chen Z Q. 2014. Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: a case study of China. International Journal of Geographical Information Science, 28(11): 2328-2355
  64. 64.
    Yu B L, Wang C X, Gong W K, Chen Z Q, Shi K F, Wu B, Hong Y C, Li Q X and Wu J P. 2021. Nighttime light remote sensing and urban studies: data, methods, applications, and prospects. National Remote Sensing Bulletin, 25(1): 342-364
  65. 65.
    Yue X M, Zhang S G and Xu X C. 2004. China’s economic growth rate: research and debate. Economic Herald, (1): 29-31
  66. 66.
    Zeng B. 2021. Evaluation of China's provincial economic resilience under the impact of COVID-19 epidemic. Journal of Industrial Technological Economics, 40(7): 127-133
  67. 67.
    Zhang J M. 2012. The urbanization process and driving forces in Xinjiang. Journal of Arid Land Resources and Environment, 26(4): 44-48
  68. 68.
    Zhang X F. 2017. Analysis of Xinjiang economic cycle fluctuation. China Finance, (3): 84-85
  69. 69.
    Zhang Y Y. 2019. Understanding the “Great Transformations Once in a Century”. International Economic Review, 5: 9-19, 4
  70. 70.
    Zhao J R. 2011. The characteristics and causation of infrequence continuous warming torrential storm weather in the Xinjiang Altay area. Journal of Arid Land Resources and Environment, 25(5): 117-123
  71. 71.
    Zhao J R, Yang X, Lin X L, Zhang Y H and Guo J Q. 2013. Analyses on multi-scale system configuration and district of a disaster snowstorm. Plateau Meteorology, 32(1): 201-210
  72. 72.
    Zhao L and Zhao Z Q. 2014. Projecting the spatial variation of economic based on the specific ellipses in China. Scientia Geographica Sinica, 34(8): 979-986
  73. 73.
    Zhou Y K, Ma T, Zhou C H and Xu T. 2015. Nighttime light derived assessment of regional inequality of socioeconomic development in China. Remote Sensing, 7(2): 1242-1262

Читать полностью

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website