InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances

被引:75
作者
Even, Markus [1 ]
Schulz, Karsten [1 ]
机构
[1] Fraunhofer IOSB, Gutleuthausstr 1, D-76275 Ettlingen, Germany
来源
REMOTE SENSING | 2018年 / 10卷 / 05期
关键词
InSAR; Persistent Scatterer; Distributed Scatterer; preprocessing; adaptive neighborhood; covariance; coherence; deformation; SATELLITE RADAR INTERFEROMETRY; COVARIANCE-MATRIX ESTIMATION; COHERENCE ESTIMATION; ADAPTIVE MULTILOOKING; SURFACE DEFORMATION; SAR INTERFEROMETRY; PHASE STATISTICS; TEMPORAL DECORRELATION; PERMANENT SCATTERERS; SERIES;
D O I
10.3390/rs10050744
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique able to measure deformation of the earth's surface over large areas. InSAR deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS are characterized by a high signal-to-noise ratio and predominantly occur as single pixels, DS possess a medium or low signal-to-noise ratio and can only be exploited if they form homogeneous groups of pixels that are large enough to allow for statistical analysis. Although DS have been used by InSAR since its beginnings for different purposes, new methods developed during the last decade have advanced the field significantly. Preprocessing of DS with spatio-temporal filtering allows today the use of DS in PS algorithms as if they were PS, thereby enlarging spatial coverage and stabilizing algorithms. This review explores the relations between different lines of research and discusses open questions regarding DS preprocessing for deformation analysis. The review is complemented with an experiment that demonstrates that significantly improved results can be achieved for preprocessed DS during parameter estimation if their statistical properties are used.
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页数:30
相关论文
共 128 条
[1]   Interferometric SAR coherence magnitude estimation using second kind statistics [J].
Abdelfattah, Riadh ;
Nicolas, Jean-Marie .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (07) :1942-1953
[2]  
Adam N., 2012, ISPRS ANN PHOTOGR RE, VI-7, P29, DOI [10.5194/isprsannals-I-7-29-2012, DOI 10.5194/ISPRSANNALS-I-7-29-2012]
[3]  
[Anonymous], 2001, RADAR INTERFEROMETRY
[4]  
[Anonymous], 2017, THESIS TU DELFT DELF
[5]  
[Anonymous], 2014, THESIS TU MUNICH MUN
[6]   Sequential Estimator: Toward Efficient InSAR Time Series Analysis [J].
Ansari, Homa ;
De Zan, Francesco ;
Bamler, Richard .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (10) :5637-5652
[7]   Synthetic aperture radar interferometry [J].
Bamler, R ;
Hartl, P .
INVERSE PROBLEMS, 1998, 14 (04) :R1-R54
[8]   A GENERALIZATION OF A.A-1-GREATER-THAN-OR-EQUAL-TO-I [J].
BAPAT, RB ;
KWONG, MK .
LINEAR ALGEBRA AND ITS APPLICATIONS, 1987, 93 :107-112
[9]   A modification to the Goldstein radar interferogram filter [J].
Baran, I ;
Stewart, MP ;
Kampes, BM ;
Perski, Z ;
Lilly, P .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (09) :2114-2118
[10]   A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms [J].
Berardino, P ;
Fornaro, G ;
Lanari, R ;
Sansosti, E .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2002, 40 (11) :2375-2383