Mapping Impervious Surface with 2 m Using Multi-source High Resolution Remote Sensing Images

SHAO Zhenfeng; ZHANG Yuan; HUANG Xin; ZHU Xiuli; WU Liang; WAN Bo

doi:10.13203/j.whugis20180196

Volume 43 Issue 12

Dec. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(12): 1909-1915. > DOI: 10.13203/j.whugis20180196

SHAO Zhenfeng, ZHANG Yuan, HUANG Xin, ZHU Xiuli, WU Liang, WAN Bo. Mapping Impervious Surface with 2 m Using Multi-source High Resolution Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 1909-1915. DOI: 10.13203/j.whugis20180196

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Mapping Impervious Surface with 2 m Using Multi-source High Resolution Remote Sensing Images

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
3.
The National Geomatics Center of China, Beijing 100830, China
4.
Faculty of Information Engineering, China University of Geosciences(Wuhan), Wuhan 430074, China

Funds:

The National Key R & D Plan on Strategic International Scientific and Technological Innovation Cooperation Special Project 2016YFE0202300

Wuhan Chenguang Project, 2016070204010114

Guangzhou Science and Technology Project 201604020070

Special Task of Technical Innovation in Hubei Province 2016AAA018

the National Natural Science Foundation of China 61671332

the National Natural Science Foundation of China 41771452

the National Natural Science Foundation of China 41771454

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Author Bio:
SHAO Zhenfeng, professor. He is concentrated on the research and education in spatial information science and technology represented by urban remote sensing, etc. E-mail:shaozhenfeng@whu.edu.cn
Received Date: May 17, 2018
Published Date: December 04, 2018

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Abstract

Abstract

Impervious rate is an important indicator to evaluate the urban ecological environment. Currently, there is only 1 km and 30 m resolution of impervious surface thematic information in the global scope, which cannot meet the needs of urban scale hydrological modeling, sponge city planning and construction. In this paper, an impervious surface extraction model incorporated spectral and texture information is proposed, and a new method based on deep learning is implemented to estimate imper-vious surface information. In addition the software for extracting and monitoring of impervious surface is also developed. Based on multi-source high spatial resolution imagery, impervious surface map with 2 m spatial resolution in mainland China including 31 provinces (municipalities, autonomous regions) is accomplished, just supports the high resolution data to research and monitor sponge and ecological cities.
- land cover datasets,
- impervious surface extraction model,
- deep learning,
- high spatial resolution imagery

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References (20)

References

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