Abstract
AbstractRadar interferometry (InSAR, interferometric synthetic aperture radar) is routinely used to measure surface deformation prior to, during, and after volcanic events, although not in a monitoring capacity. The improved data availability of some current satellite missions presents us with the opportunity to do just that. We present here a fast and flexible algorithm to estimate coherence and select points on an interferogram‐by‐interferogram basis, which overcomes limitations of the conventional boxcar ensemble method in areas of marginal coherence. Time series methods, which offer an alternative way to select coherent points, are typically slow, and do not allow for insertion of new data without reprocessing the entire data set. Our new algorithm calculates the coherence for each point based on an ensemble of points with similar amplitude behavior throughout the data set. The points that behave similarly are selected prior to new images being acquired, on the assumption that the behavior of these nearby points does not change rapidly through time. The resulting coherence estimate is superior in resolution and noise level to the boxcar method. In contrast to most other time series methods, we select a different set of coherent points for each interferogram, avoiding the selection compromise inherent to other time series methods. The relative simplicity of this strategy compared to other time series techniques means we can process new images in about 1 h for a typical setup.
Highlights
Interferometric synthetic aperture radar (InSAR) uses radar signal interferometry to obtain high-resolution surface deformation measurements with millimeter to centimeter level accuracy, covering areas of hundreds to thousands of square kilometers per interferogram [Bamler and Hartl, 1998; Hanssen, 2001]
We demonstrate the effectiveness of RapidSAR on data sets covering the Eyjafjallajökull and Bárðarbunga volcanoes, Iceland
We present RapidSAR, a new algorithm that is able to handle the high volumes of data that current generation SAR satellites generate and produce high signal-to-noise ratio deformation maps in a timely fashion
Summary
Interferometric synthetic aperture radar (InSAR) uses radar signal interferometry to obtain high-resolution surface deformation measurements with millimeter to centimeter level accuracy, covering areas of hundreds to thousands of square kilometers per interferogram [Bamler and Hartl, 1998; Hanssen, 2001]. They are better able to extract pixels containing many scatterers, known as distributed scatterers, that might decorrelate in longer baseline combinations Both types of method select a set of points that are deemed coherent throughout all the interferograms used in the time series. The algorithm, which we refer to as Rapid Time Series InSAR (RapidSAR), uses sibling information not for preprocessing prior to time series processing like the SqueeSAR method, but to quickly estimate the coherence for each pixel in newly formed interferograms. This avoids many of the problems of boxcar coherence estimation, while retaining much of its speed and flexibility. We demonstrate the effectiveness of RapidSAR on data sets covering the Eyjafjallajökull and Bárðarbunga volcanoes, Iceland
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