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Remote Sens. 2014, 6(4), 3349-3368; doi:10.3390/rs6043349

A Hierarchical Multi-Temporal InSAR Method for Increasing the Spatial Density of Deformation Measurements

1
Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China
2
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong 999077, China
3
Center of Remote Sensing, Tianjin University, Tianjin 300100, China
*
Author to whom correspondence should be addressed.
Received: 12 February 2014 / Revised: 1 April 2014 / Accepted: 4 April 2014 / Published: 15 April 2014
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Abstract

Point-like targets are useful in providing surface deformation with the time series of synthetic aperture radar (SAR) images using the multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology. However, the spatial density of point-like targets is low, especially in non-urban areas. In this paper, a hierarchical MTInSAR method is proposed to increase the spatial density of deformation measurements by tracking both the point-like targets and the distributed targets with the temporal steadiness of radar backscattering. To efficiently reduce error propagation, the deformation rates on point-like targets with lower amplitude dispersion index values are first estimated using a least squared estimator and a region growing method. Afterwards, the distributed targets are identified using the amplitude dispersion index and a Pearson correlation coefficient through a multi-level processing strategy. Meanwhile, the deformation rates on distributed targets are estimated during the multi-level processing. The proposed MTInSAR method has been tested for subsidence detection over a suburban area located in Tianjin, China using 40 high-resolution TerraSAR-X images acquired between 2009 and 2010, and validated using the ground-based leveling measurements. The experiment results indicate that the spatial density of deformation measurements can be increased by about 250% and that subsidence accuracy can reach to the millimeter level by using the hierarchical MTInSAR method. View Full-Text
Keywords: hierarchical processing strategy; distributed target; multi-temporal InSAR; Pearson correlation coefficient hierarchical processing strategy; distributed target; multi-temporal InSAR; Pearson correlation coefficient
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Li, T.; Liu, G.; Lin, H.; Jia, H.; Zhang, R.; Yu, B.; Luo, Q. A Hierarchical Multi-Temporal InSAR Method for Increasing the Spatial Density of Deformation Measurements. Remote Sens. 2014, 6, 3349-3368.

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