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Geophysical Research Letters
Article . 2007 . Peer-reviewed
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Persistent scatterer selection using maximum likelihood estimation

Authors: Piyush Shanker; Howard Zebker;

Persistent scatterer selection using maximum likelihood estimation

Abstract

We present here a new InSAR persistent scatterer selection method using maximum likelihood estimation to identify persistent scattering pixels, which results in a denser network of reliable phase measurements than do existing methods. We analyze the phase of each pixel in a series of interferograms and estimate the relative strength of any slowly fluctuating component of the radar echo from a dominant scatterer to the background scattering within a pixel. We find a fairly dense network of scatterers with stable phase characteristics in areas where conventional InSAR fails due to decorrelation. We examined data over two vegetated regions in the San Francisco Bay Area. The average phases of these pixels clearly show the slip along the Hayward fault, and set upper bounds on any slip along the Bay Area segment of the San Andreas fault.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
65
Top 10%
Top 10%
Average
gold