Next Article in Journal
Preliminary Investigation of a New AHI Aerosol Optical Depth (AOD) Retrieval Algorithm and Evaluation with Multiple Source AOD Measurements in China
Next Article in Special Issue
Coherence Change-Detection with Sentinel-1 for Natural and Anthropogenic Disaster Monitoring in Urban Areas
Previous Article in Journal
A Descriptor-less Well-Distributed Feature Matching Method Using Geometrical Constraints and Template Matching
Previous Article in Special Issue
Modeling Orbital Error in InSAR Interferogram Using Frequency and Spatial Domain Based Methods
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessReview

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

Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany
*
Author to whom correspondence should be addressed.
Worked at IOSB until June 2017.
Remote Sens. 2018, 10(5), 744; https://doi.org/10.3390/rs10050744
Received: 31 March 2018 / Revised: 26 April 2018 / Accepted: 9 May 2018 / Published: 13 May 2018
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications)
  |  
PDF [1324 KB, uploaded 16 May 2018]
  |  

Abstract

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. View Full-Text
Keywords: InSAR; Persistent Scatterer; Distributed Scatterer; preprocessing; adaptive neighborhood; covariance; coherence; deformation InSAR; Persistent Scatterer; Distributed Scatterer; preprocessing; adaptive neighborhood; covariance; coherence; deformation
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed
Printed Edition Available!
A printed edition of this Special Issue is available here.

Share & Cite This Article

MDPI and ACS Style

Even, M.; Schulz, K. InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances. Remote Sens. 2018, 10, 744.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top