A Quantified Analysis of Urban Sprawl Based on High-Resolution Satellite Remote Sensing


Dongmiao Zhao, Guangyi Zhang, Xiuhe Yuan, Chao Liu, Yansu Qi, Xingtian Wang, Journal of Information Processing Systems Vol. 21, No. 3, pp. 308-317, Jun. 2025  

https://doi.org/10.3745/JIPS.04.0351
Keywords: Ecological Balance, GF-2, High-Resolution Satellite Images, Sprawl
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Abstract

Under the circumstance of global sustainability, the expansion of urban has been paid serious attention by governments. To obtain the harmonious symbiosis with nature, decision-makers need a reasonable method to quantify and monitor the urban expansion. This paper analyzes a particular area through spatiotemporal identification and quantification by using high-resolution satellite images. The change trend and ratio of artificial construction areas in the research area from 2016 to 2023 are analyzed. Optical flow is chosen for visualization and analyzing the characteristics of urban expansion in the research area, directly expressing the quantity and direction of construction in the process of urban expansion, which cannot be reflected in the traditional image quantitative analysis. The results show that the urban is expanding to the coastline and causing irreversible damage to local natural environment. The proportion of vegetation coverage should be strictly controlled.


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Cite this article
[APA Style]
Zhao, D., Zhang, G., Yuan, X., Liu, C., Qi, Y., & Wang, X. (2025). A Quantified Analysis of Urban Sprawl Based on High-Resolution Satellite Remote Sensing. Journal of Information Processing Systems, 21(3), 308-317. DOI: 10.3745/JIPS.04.0351.

[IEEE Style]
D. Zhao, G. Zhang, X. Yuan, C. Liu, Y. Qi, X. Wang, "A Quantified Analysis of Urban Sprawl Based on High-Resolution Satellite Remote Sensing," Journal of Information Processing Systems, vol. 21, no. 3, pp. 308-317, 2025. DOI: 10.3745/JIPS.04.0351.

[ACM Style]
Dongmiao Zhao, Guangyi Zhang, Xiuhe Yuan, Chao Liu, Yansu Qi, and Xingtian Wang. 2025. A Quantified Analysis of Urban Sprawl Based on High-Resolution Satellite Remote Sensing. Journal of Information Processing Systems, 21, 3, (2025), 308-317. DOI: 10.3745/JIPS.04.0351.