GIS数据约束的海岸带SAR图像多尺度分割

doi:10.3969/j.issn.0255-8297.2013.01.013

Journal of Applied Sciences ›› 2013, Vol. 31 ›› Issue (1): 79-83.doi: 10.3969/j.issn.0255-8297.2013.01.013

• Signal and Information Processing • Previous Articles Next Articles

GIS-Constrained Multi-scale Coastal SAR Image Segmentation

ZHU Jun-jie1,2, DU Xiao-ping1,2, FAN Xiang-tao1,2, GUO Hua-dong1,2

1. Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing 100094, China
2. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Received:2011-09-02 Revised:2011-12-08 Online:2013-01-31 Published:2012-02-08

Abstract

Abstract: Both geographic information system (GIS) data and remote sensing imagery are spatial data with multi-scale features although they are concerned with different types of information. This paper discusses the multi-scale segmentation of high-resolution synthetic aperture radar (SAR) images near coastal zones constrained by GIS vector data. To obtain the first level segmentation results at the county-level scale, the high-resolution SAR image is segmented using the fractal network evolution method with the constraint of GIS data. Then, at the province-level scale, the first level results are aggregated to obtain the second level segmentation results. This segmentation results satisfy both the constraint of GIS vector data and the scattering characteristics of SAR images. False coastlines in the SAR images are eliminated. Experimental results show that the proposed method is effective, and the segmentation results can be used for further image statistics and analyses.

Key words: multi-scale, segmentation, coastal zone, remote sensing, geographic information system (GIS), synthetic aperture radar (SAR)

CLC Number:

TP79

ZHU Jun-jie1,2, DU Xiao-ping1,2, FAN Xiang-tao1,2, GUO Hua-dong1,2. GIS-Constrained Multi-scale Coastal SAR Image Segmentation[J]. Journal of Applied Sciences, 2013, 31(1): 79-83.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: https://www.jas.shu.edu.cn/EN/10.3969/j.issn.0255-8297.2013.01.013

https://www.jas.shu.edu.cn/EN/Y2013/V31/I1/79

[1]	YUAN Shuai, YU Lei, YAO Tian, XIONG Bangshu. Human Action Recognition in Infrared Images Based on Median-Guided Multi-scale Feature Fusion [J]. Journal of Applied Sciences, 2026, 44(2): 266-281.
[2]	LEI Xiaochun, PAN Yiwei, ZHANG Yongya, JIANG Zetao, LI Mengtong. Real-Time Semantic Segmentation Based on Composite Three-Branch and Deep Feature Encoding [J]. Journal of Applied Sciences, 2026, 44(2): 250-265.
[3]	XU Kai, CHI Mingde, WANG Qi, LI Jianzhou, ZHANG Hui. Multi-granularity Semantic Aspect-Based Sentiment Analysis Model with Fusion of BERT Encoding Layers [J]. Journal of Applied Sciences, 2026, 44(1): 149-165.
[4]	JIN Zhengyang, YAN Shaohong, ZHANG Yanbo, YAO Xulong, TAO Zhigang, CHEN Zhiyuan. Three-Dimensional Fuzzy Clustering Algorithm Integrating Spatial Texture Features [J]. Journal of Applied Sciences, 2026, 44(1): 134-148.
[5]	LIU Yongchang, DU Yiying, WU Cuiying, LIU Yawen. Aerial Image-Guided LiDAR Point Cloud Semantic Segmentation [J]. Journal of Applied Sciences, 2025, 43(6): 922-934.
[6]	HUANG Tiantian, MA Xiuli, HUANG Wei. Two-Stage Organ Segmentation Based on Feature Fusion Network [J]. Journal of Applied Sciences, 2025, 43(5): 808-816.
[7]	XIONG Jun, LIU Shouquan, AN Xu, GUO Tian, TAI Baoyu. A Method of Building Segmentation in Remote Sensing Image Based on Contour Measurement of Convolutional Neural Network [J]. Journal of Applied Sciences, 2025, 43(4): 709-720.
[8]	YE Qing, XU Yehui, LI Huichuan, MA Dan, ZHANG Liming. Prediction of Soil Organic Carbon for Cultivated Lands in Jianyang District of Nanping City Based on Soil Texture [J]. Journal of Applied Sciences, 2025, 43(3): 519-529.
[9]	ZHANG Yongbin, LI Chunyu, LIU Mingyue, MAN Weidong, SONG Tanglei, LIU Yahui. Coupling Analysis of Urbanization and Ecological Environment in Beijing-Tianjin-Hebei Urban Agglomeration from 2000 to 2020 [J]. Journal of Applied Sciences, 2025, 43(3): 475-490.
[10]	JIANG Xiao, QIU Chunxia, ZHANG Chunsen, GE Yingwei. Mesh Simplification Based on Multi-source Point Cloud Feature Information [J]. Journal of Applied Sciences, 2025, 43(2): 301-314.
[11]	WU Xiang, XIAO Jian, JI Genlin. Video Anomaly Detection Method Based on Multi-scale Feature Fusion and Attention Mechanism [J]. Journal of Applied Sciences, 2025, 43(2): 234-244.
[12]	DUAN Xintao, BAI Luwei, XU Kaiou, ZHANG Meng, BAO Mengru, WU Yinhang, QIN Chuan. Lightweight and Efficient Image Steganography Based on Convolutional Neural Network [J]. Journal of Applied Sciences, 2025, 43(1): 80-93.
[13]	LIAN Xiaofeng, KANG Maomao, TAN Li, WANG Yanli. A Semantic Segmentation Network Based on Lightweight Convolutional Modules [J]. Journal of Applied Sciences, 2025, 43(1): 66-79.
[14]	HUANG Kewen, MENG Yanxi, YU Haotian, JIA Tao. A Calculation Method for Tilt Angle of Power Tower Based on Laser Point Cloud [J]. Journal of Applied Sciences, 2024, 42(6): 988-999.
[15]	PEI Gang, ZHANG Sunjie, ZHANG Jiapeng, PANG Jun. ECG-UNet: a Lightweight Medical Image Segmentation Algorithm Based on U-Shaped Structures [J]. Journal of Applied Sciences, 2024, 42(6): 922-933.

GIS-Constrained Multi-scale Coastal SAR Image Segmentation

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments