Spatial Responses to the Polarization: Trickle-Down Effect in Hunan Based on Remote Sensing
Main Article Content
Keywords
remote sensing, urban built-up areas, polarization-trickling down effects, nighttime light data, Hunan province
Abstract
How regional spatial patterns adjust to the shifting balance between economic polarization and trickle-down effects remains insufficiently understood, especially in rapidly developing regions such as Hunan Province. A Regional Economic Score (RES) system is established using the entropy-weight method to depict long-term development trends, while the coefficient of variation and Theil index reveal a shift from polarization to convergence. A provincial core–periphery interaction model incorporating economic linkage strength further captures the radiation and spillover roles of the Chang-Zhu-Tan metropolitan area. Nighttime light-derived indicators, including centroid shifts and standard deviation ellipses, provide intuitive spatial evidence that complements statistical results and reflects general patterns of built-up area evolution. The analysis shows that Hunan’s development trajectory moved from a strong center-driven agglomeration toward a more multi-nodal, spillover-enhanced structure, with core cities exerting sustained positive influence on surrounding regions and stronger linkages reinforcing collaborative dynamics. Overall, the convergence of temporal, spatial, and economic evidence reveals clear surface manifestations of the polarization-trickle-down effect and offers empirical insights for provincial planning and coordinated regional development.
References
- [1] Cai, S. K. and Ni, P. F. Polarization or trickle-down: The impact of urban scale on agricultural modernization. Economist. 2017(7), pp. 46-55. https://doi.org/10.16158/j.cnki.51-1312/f.2017.07.006.
- [2] Fu, M. W., Luo, W. Y. and Li, F. High-speed railway opening and urban entrepreneurship: Polarization effect or trickle-down effect? Consumer Economics. 2025, pp. 1-17.
- [3] Li, A. M. Research on urban built-up area expansion & land use scale based on remote sensing images. Doctoral Dissertations, Zhengzhou: PLA Information Engineering University, 2009.
- [4] Shu, S., Yu, B. L., Wu, J. P. and Liu, H. X. Methods for deriving urban built-up area using night-light data:Assessment and application. Remote Sensing Technology and Application. 2011, 26(2), pp. 169-176.
- [5] Song, J. C., Li, X. H., Lin, T., Zhang, G. Q., Ye, H., He, X. Y. and Ge, R. B. A method of extracting urban built-up area based on DMSP/OLS nighttime data and google earth. Journal of Geo-Information Scienc. 2015, 17(06), pp. 750-756.
- [6] Song, Y. Spatiotemporal evolution characteristics and driving force analysis of urban built-up areas in Guizhou Province based on nighttime light data. Master's Thesis, Guizhou: Guizhou Normal University, 2025. https://doi.org/10.27048/d.cnki.ggzsu.2025.000828.
- [7] He, P. Z., Hu, X. H., Liu, T. and Ren, J. Spatial-temporal expansion of urban built-up areas based on lighttime lighting data : A case study of Hohhot. Huazhong Architecture. 2025, 43(6), pp. 29-33. https://doi.org/10.13942/j.cnki.hzjz.2025.06.020.
- [8] An, Q., Li, X. J. and Lü, K. W. A research on the spatial structure and efficiency of China's expansion of urban built-up area (1990-2009). Economic Geography. 2012, 32(6), pp. 37-45. https://doi.org/10.15957/j.cnki.jjdl.2012.06.007.
- [9] Chen, J. H. and Lü, Y. F. Bibliometric analysis of nighttime light remote sensing applications in urbanization spatial studies. Journal of Changchun Normal University. 2025, 44(6), pp. 107-112. https://doi.org/10.3969/j.issn.1008-178X.2025.06.017.
- [10] Se, W. A worldly political economist: The life and thoughts of Albert O. Hirschman. Fudan Journal. 2015(1), pp. 1-15.
- [11] Mu, F. Y., Zhang, Z. X., Chi, Y. B., Liu, B., Zhou, Q. B., Wang, C. Y. and Tan, W. B. Dynamic monitoring of built-up area in Beijing during 1973—2005 based on multi-original remote sensed images. Journal of Remote Sensing. 2007(02), pp. 257-268.
- [12] Huang, Z. H., Huang, J. X. and Dang, A. R. Collaborative development and optimization strategies of the Huaihe River Basin Metropolitan Area: An empirical analysis based on nighttime light remote sensing. Geographical Science. 2025, 45(11), pp. 2430-2440. https://doi.org/10.13249/j.cnki.sgs.20231000.
- [13] Li, Q. M., Zheng, B. H. and Xiong, Y. J. Spatio-temporal expansion of the dongting lake eco-economic zone urban agglomeration based on nighttime light remote sensing data. Economic Geography. 2021, 41(2), pp. 92-102. https://doi.org/10.15957/j.cnki.jjdl.2021.02.010.
- [14] Hunan Provincial People's Government. Hunan Provincial Profile. Available from: https://www.hunan.gov.cn/jxxx/hngk/sqjs/sqjs_m.html (accessed 22 December 2025).
- [15] Hunan Provincial Bureau of Statistics. Statistical bulletins of all prefecture-level cities. Available from: https://tjj.hunan.gov.cn/tjjf/tjgb/szgb/ (accessed 22 December 2025).
- [16] Zhang, L., Ren, Z. and Chen, B. A prolonged artificial nighttime-light dataset of China (1984–2020). Available from: http://www.gis5g.com/data/dgsj?id=247 (accessed 22 December 2025).
- [17] Liu, Z. Y., Yin, H. J., Li, M. Y., Zong, F. and Dong, Y. N. Analysis of economic development in representative regions of China's three major economic belts using multi-source remote sensing data. Geomatics and Information Science of Wuhan University. 2025, pp. 1-17. https://doi.org/10.13203/j.whugis20240233.
- [18] Samha, S., Gao, Y. X. and Deng, W. B. Analysis of spatial-temporal pattern characteristics of economic development in four prefectures of southern Xinjiang based on integration of nightlight remote sensing data. Remote Sensing Technology and Application. 2024, 39(1), pp. 234-247. https://doi.org/10.11873/j.issn.1004-0323.2024.1.0234.
- [19] Wu, B. Urban spatial form and driving forces of Guiyang's built-up area. Master's Thesis, Guiyang: Guizhou University, 2023.
Article Sidebar
This work is licensed under a Creative Commons Attribution 4.0 International License.