Paper
30 August 2023 Impervious surface extraction and spatiotemporal analysis in the main urban area of Zhengzhou
Author Affiliations +
Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127971H (2023) https://doi.org/10.1117/12.3007445
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China
Abstract
Increased coverage of impervious surfaces is an important measure of urban sprawl, and understanding spatiotemporal dynamics of impervious surfaces is vital for regional and local development. Combining vegetation-impervious-surfaces oil model and linear spectral unmixing model, this paper used the Landsat TM and OLI remote sensing data from 2009 to 2019 to study the temporal and spatial variation characteristics of the impervious surfaces of Zhengzhou, and discussed the main driving factors leading to urban expansion. We found that impervious surface growth in the main urban area of Zhengzhou City was obvious, and the area of impervious surfaces increased from 337.52 km2 in 2009 to 464.93 km2 in 2019, with an average expansion speed of 12.69 km2 /year. The impervious surfaces pattern of the research area changed significantly, and the expansion of impervious surface showed a flaky development in all directions. From 2009 to 2014, Zhengzhou’s expansion was mainly concentrated in Hi-Tech Industrial Development Zone, Zhongyuan District, as well as Economic and Technological Development Zone. Most of the expansion between 2014 and 2019 was concentrated in Zhengdong New District and Huiji District. Physical geography, urban population, GDP and national policies were the main drivers affecting the expansion of impervious surfaces.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaoping Zhang, Fang Lu, Dongsheng Liu, Yongyong Li, and Ying Lv "Impervious surface extraction and spatiotemporal analysis in the main urban area of Zhengzhou", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127971H (30 August 2023); https://doi.org/10.1117/12.3007445
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KEYWORDS
Landsat

Remote sensing

Analytical research

Geography

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