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Remote Sensing
Volume 16
Issue 17
10.3390/rs16173181
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Ship Lock Extraction from High-Resolution Remote Sensing Images Based on Fuzzy Theory and Prior Knowledge

by
Bingsun Chen
1,†,
Yi Bao
1,†,
Yanjiao Song
1,
Ziyang Li
2,
Zhe Wang
1,
Xi Wang
1,
Runsheng Ma
1,
Lingkui Meng
1,
Wen Zhang
1 and
Linyi Li
1,*
1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
The National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Remote Sens. 2024, 16(17), 3181; https://doi.org/10.3390/rs16173181
Submission received: 18 July 2024 / Revised: 15 August 2024 / Accepted: 27 August 2024 / Published: 28 August 2024
Versions Notes

Abstract

As crucial water conservancy projects, ship locks play a key role in flood control, shipping, water resource allocation, and promoting regional economic development, making them an indispensable part of the modern water transportation system. Utilizing satellite remote sensing for lock extraction can significantly reduce manual workload and costs, assist in the daily dynamic maintenance of lock hubs, and provide more comprehensive data support for the construction and management of water transport infrastructure. In this context, this paper proposes a new method for ship lock object extraction. Leveraging fuzzy theory and prior knowledge of locks, the extraction of lock objects is achieved from Gaofen-1 (GF-1) high-resolution remote sensing images. The experimental results demonstrate that the proposed algorithm can effectively extract small lock objects in remote sensing images, achieving an average extraction accuracy of 80.9% in the study area.
Keywords: ship lock extraction; fuzzy classification; prior knowledge; Gaofen-1 ship lock extraction; fuzzy classification; prior knowledge; Gaofen-1

Share and Cite

MDPI and ACS Style

Chen, B.; Bao, Y.; Song, Y.; Li, Z.; Wang, Z.; Wang, X.; Ma, R.; Meng, L.; Zhang, W.; Li, L. Ship Lock Extraction from High-Resolution Remote Sensing Images Based on Fuzzy Theory and Prior Knowledge. Remote Sens. 2024, 16, 3181. https://doi.org/10.3390/rs16173181

AMA Style

Chen B, Bao Y, Song Y, Li Z, Wang Z, Wang X, Ma R, Meng L, Zhang W, Li L. Ship Lock Extraction from High-Resolution Remote Sensing Images Based on Fuzzy Theory and Prior Knowledge. Remote Sensing. 2024; 16(17):3181. https://doi.org/10.3390/rs16173181

Chicago/Turabian Style

Chen, Bingsun, Yi Bao, Yanjiao Song, Ziyang Li, Zhe Wang, Xi Wang, Runsheng Ma, Lingkui Meng, Wen Zhang, and Linyi Li. 2024. "Ship Lock Extraction from High-Resolution Remote Sensing Images Based on Fuzzy Theory and Prior Knowledge" Remote Sensing 16, no. 17: 3181. https://doi.org/10.3390/rs16173181

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