Remote Sensing Applications and Decision Support

Improving the quality of interferometric synthetic aperture radar digital elevation models through a segmentation-based coregistration approach

[+] Author Affiliations
Yu-Ching Lin, Ming-Da Tsai

National Defense University, Chung Cheng Institute of Technology, Department of Environmental Information and Engineering, No. 75, Shiyuan Road, Daxi District, Taoyuan, Taiwan

Shih-Yuan Lin

National Chengchi University, Department of Land Economics, No. 64, Sec. 2, Zhinan Road, Wenshan District, Taipei, Taiwan

Pauline Miller

James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, United Kingdom

J. Appl. Remote Sens. 10(4), 046024 (Dec 07, 2016). doi:10.1117/1.JRS.10.046024
History: Received July 8, 2016; Accepted November 11, 2016
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Abstract.  With the rapid development of remote sensing, multiple techniques are now capable of producing digital elevation models (DEMs), such as photogrammetry, Light Detection and Ranging (LiDAR), and interferometric synthetic aperture radar (InSAR). Satellite-derived InSAR DEMs are particularly attractive due to their advantages of large spatial extents, cost-effectiveness, and less dependence on the weather. However, several complex factors may limit the quality of derived DEMs, e.g., the inherited errors may be nonlinear and spatially variable over an entire InSAR pair scene. We propose a segmentation-based coregistration approach for generating accurate InSAR DEMs over large areas. Two matching algorithms, including least squares matching and iterative closest point, are integrated in this approach. Three Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) InSAR DEMs are evaluated, and their root mean square errors (RMSEs) improved from 17.87 to 9.98 m, 51.94 to 15.80 m, and 27.12 to 12.26 m. Compared to applying a single global matching strategy, the segmentation-based strategy further improved the RMSEs of the three DEMs by 3.27, 13.01, and 9.70 m, respectively. The results clearly demonstrate that the segmentation-based coregistration approach is capable of improving the geodetic quality of InSAR DEMs.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yu-Ching Lin ; Shih-Yuan Lin ; Pauline Miller and Ming-Da Tsai
"Improving the quality of interferometric synthetic aperture radar digital elevation models through a segmentation-based coregistration approach", J. Appl. Remote Sens. 10(4), 046024 (Dec 07, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.046024


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