Permanent Scatterers: precision assessment and multi-platform analysis

Abstract

The Permanent Scatterers (PS) technique is an advanced tool for processing series of interferometric SAR data aiming at millimetric precision ground deformation mapping. The approach is based on a joint time-space-acquisition geometry analysis that is carried out at individual point-wise radar targets. The aim of this paper is twofold: (1) describe the main issues related to the precision of PS products; (2) show preliminary PS results obtained using, instead of ESA-ERS scenes, data acquired by other spaceborne SAR platforms characterized by different acquisition parameters (namely RADARSAT and JERS). I.PRECSION ASSESMENT The estimation of the precision of PS output products (Line of Sight (LOS) displacement measurements, average deformation rate and PS elevation) is not an easy task to perform. The three main factors impacting on the precision of PS measurements are:1. atmospheric phase artifacts (tropospheric and ionospheric delays), creating the so-called Atmospheric Phase Screen (APS) superimposed on each SAR acquisition; 2. state vectors errors, creating the so-called "orbital fringes" (low order phase polynomials) on the differential interferograms; 3. temporal and geometrical decorrelation, affecting individual PS. A full statistical characterization of these contributions is not straightforward [3], here it will suffice to recall that tropospheric phase components are characterized by high spatial correlation, baseline errors and ionospheric effects usually generate phase pattern well fitted by means of a low order phase polynomial, and decorrelation phenomena give rise to phase noise that is uncorrelated both spatially and temporally. In the following, we will briefly discuss how important is the use of a multi-interferogram approach to improve DInSAR data quality and we will highlight the major statistical features of PS results.One of the first steps of PS Technique is the generation of N differential interferograms with respect to the same master acquisition [1] [2]. This operational strategy allows one to carry out the interferometric analysis in a simple, effective, and elegant mathematical framework, where the user can find useful tools also for accuracy and precision assessment. Problems related to optimum data selection and clustering (which data should I use? How many and what interferograms should I generate?) as well as the difficulties related to the correlation of partial results (most of the times data coming from different interferograms cannot be considered independent, since they have common images) are no more present. For each interferogram i, the phase can be modeled as:

Geomechanical response to seasonal gas storage in depleted reservoirs: A case study in the Po River basin, Italy

“…The resolution achieved by the identification of these PS targets in long temporal series of SAR images creates a data set consisting of many "radar benchmarks" where target displacement information can be accurately estimated due to favorable reflectivity conditions. The advantages of the PS methodology are: (1) good phase coherence over the sparse PS grid, from nearly all radar scenes, regardless of geometrical baseline (i.e., separation of satellite trajectories involved in the generation of the interferograms); (2) as all interferograms are generated using a single master scene, the mathematical framework allows the user to take advantage of procedures for the assessment of the precision [Colesanti et al, 2003a]; and (3) by exploiting a long time series of radar data, atmospheric phase contributions can be estimated and removed from the deformation phase signal by proper filtering procedures, thus significantly increasing the accuracy of the measurements. PSs correspond to persistent, bright radar reflectors, such as buildings, poles, metallic structures, exposed rocks or other similar objects.…”

On the applicability of Persistent Scatterers Interferometry (PSI) analysis for long term CO2 storage monitoring

“…Colesanti et al (2003) suggested that in an 223 operational context under very good conditions (large data sets -i.e. >30 images, dense PS 224 network, quasi linear deformation regimes), the precision could reach 0.5 mm/y for the annual 225 deformation rate and 3 mm for the displacement values at given acquisition dates for PSI 226 based on data from ERS, Envisat/ASAR or equivalent (C-band, resolution ~10m, 227 repetitiveness of ~ 1 month).…”

Subsidence Trends of Volturno River Coastal Plain (Northern Campania, Southern Italy) Inferred by SAR Interferometry Data

“…Each point of the four PS shapefile datasets is identified by coordinates (North, East) and a set of attributes, including: (a) identifier code; (b) average velocity of entire acquisition time period, expressed in mm year −1 ; (c) standard deviation of the average velocity; (d) coherence; and (e) a subset of measurements (expressed in mm) of the displacement along the LOS of each PS. The PS coherence is a normalized index of the local signal-to-noise ratio of the interferometric phase and reflects the accuracy of PS measurements [14,[74][75][76]. PSI processing allows us to obtain very accurate measurements within 1.0 mm/year for the PS average velocity along the LOS by assuming a threshold value of 0.65 for coherence [33,71,75,77,78] thanks to the large number of SAR images used for the processing (Table 1).…”

“…The PS coherence is a normalized index of the local signal-to-noise ratio of the interferometric phase and reflects the accuracy of PS measurements [14,[74][75][76]. PSI processing allows us to obtain very accurate measurements within 1.0 mm/year for the PS average velocity along the LOS by assuming a threshold value of 0.65 for coherence [33,71,75,77,78] thanks to the large number of SAR images used for the processing (Table 1).…”