Statistical analysis of atmospherical components in ERS SAR data
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1 Statistical analysis of atmospherical components in ERS SAR data A.Ferretti *^, F.Novali ^, E. Passera^, C. Prati*, F.Rocca* FRINGE05 ESRIN Frascati (*) Politecnico di Milano (^) Tele-Rilevamento Europa - TRE a POLIMI spin-off company COPYRIGHT - Tele-Rilevamento Europa Copyright - Tele-Rilevamento Europa
2 Rationale Lately, PSInSAR (and similar multi-interferogram techniques) has been widely used as a geodetic technique since it allows to infer precise information on possible variations of the sensor-to-target distance. The assessment of the impact of atmospheric disturbances on phase data, as well as the identification of possible mitigation strategies, has become more and more important. The number of data available at TRE (>9,000 ESA, >800 RADARSAT scenes) allows us to start a statistical analysis of the Atmospheric Phase Screen (APS). Results presented here should be consider as preliminary, since they refer to ~250 ERS scenes. COPYRIGHT - Tele-Rilevamento Europa
3 PSInSAR: a 2-step algorithm (PSC vs. PS) COPYRIGHT - Tele-Rilevamento Europa
![Final PS grid Velocity field [mm/yr] of Etna volcano estimated](/docs-images/74/69800037/images/4-1.jpg "from 55 ESA-ERS data (95-00) COPYRIGHT - Tele-Rilevamento Europa")
4 Final PS grid Velocity field [mm/yr] of Etna volcano estimated from 55 ESA-ERS data (95-00) COPYRIGHT - Tele-Rilevamento Europa
5 Aims of the study FACT: Estimation and removal of atmospheric disturbances (APS) is a key-step in PSInSAR QUESTIONS: 1. How can we characterize APS? APS is a white process? 2. Is it possible to improve PS results by better estimating APS? 3. How can we take advantage of the data available in the ESA archive? 4. What, if no auxiliary information (e.g. meteo-radar, GPS) is available? 5. Can easy-to-access meteo data help in APS estimation? COPYRIGHT - Tele-Rilevamento Europa
6 Estimation and Interpolation Q: What is the best algorithm to interpolate the APS estimated on the sparse PSC grid? α = τ + τ + ς turbulence topography Turbulence phenomena can be described by a variogram (ie a structure function) exhibiting a power law behavior: E [ ] 2 β ( τ(p) + τ(p,d)) = C d with < β < 3 Topography dependent components are related to different atmospheric profiles at the time of the acquisitions. Different models are available (e.g. Saastamoinen model used in dgps) Ionospheric/orbital effects ζ can be easily estimated by fitting a low order polynomial to the estimated APS COPYRIGHT - Tele-Rilevamento Europa
7 Data analysis (Gardanne - France) APS values estimated by the PS processing on the sparse PSC grid, compensated for ionospheric/orbital components COPYRIGHT - Tele-Rilevamento Europa
8 Data analysis (Etna - Italy) COPYRIGHT - Tele-Rilevamento Europa
9 A mathematical model for APS APS( x, y) = τ turbulence ( x, y) + K z( x, y) + Ax + By + C Kriging interpolation after variogram estimation N d ( + L S 1 e α ) K,A,B,C LMS from the data Z from a DEM 4-parameter model COPYRIGHT - Tele-Rilevamento Europa
10 Application (Gardanne- FR) COPYRIGHT - Tele-Rilevamento Europa
11 Estimated ionospheric/orbital fringes σ =1.2 rad From LMS of A,B,C COPYRIGHT - Tele-Rilevamento Europa
12 Topography dependent components σ =0.5 rad From SRTM data + LMS of K COPYRIGHT - Tele-Rilevamento Europa
13 Turbulent components σ =0.7 rad From kriging interpolation of the residual phase components COPYRIGHT - Tele-Rilevamento Europa
14 Combination: final result σ =1.5 rad COPYRIGHT - Tele-Rilevamento Europa
15 APS estimation procedure Model Parameters DEM COPYRIGHT - Tele-Rilevamento Europa
16 Does it work? PS results Etna COPYRIGHT - Tele-Rilevamento Europa
17 PS results Etna (new algorithm for APS) COPYRIGHT - Tele-Rilevamento Europa
18 Seasonal behavior of APS power (1) Gardanne 78 ERS data h = 1100m σ = 300 m COPYRIGHT - Tele-Rilevamento Europa
19 Seasonal behavior of APS power (2) Etna 55 ERS data h = 3300m σ = 720 m COPYRIGHT - Tele-Rilevamento Europa
20 Gaussianity Test Only 33% of the data pass the test for normality (D Agostino-Pearson - 90% confidence level) COPYRIGHT - Tele-Rilevamento Europa
21 Signal anisotropy (1/2) A statistical analysis carried out by a 2D spatial variogram shows that more than 50% of the APS exhibit anisotropic behavior, even on a full scene (100x100 km) COPYRIGHT - Tele-Rilevamento Europa
22 Signal anisotropy (2/2) Although a quantitative analysis is still in progress, the adoption of 2D variograms in the kriging interpolation does not increase the final PS density significantly COPYRIGHT - Tele-Rilevamento Europa
23 Variogram parameters 5/3 2/3 COPYRIGHT - Tele-Rilevamento Europa
24 Exploitation of meteo-data Topography-dependent APS components can be correlated in time (since they exhibit a seasonal behavior). This can prevent the application of the standard PS approach. The exploitation of meteodata can mitigate this phenomenon acting as a whitening filter. COPYRIGHT - Tele-Rilevamento Europa
25 Exploitation of meteo-data Topography-dependent APS components can be correlated in time (since they exhibit a seasonal behavior). This can prevent the application of the standard PS approach. The exploitation of meteodata can mitigate this phenomenon acting as a whitening filter. Whitening of the time-series COPYRIGHT - Tele-Rilevamento Europa
26 Mean variograms at different latitudes COPYRIGHT - Tele-Rilevamento Europa
27 Conclusions Apart from ionospheric components and orbital fringes, both topography dependent and turbulent tropospheric components have to be taken into account in DInSAR and PSInSAR. Data show that, as a first approximation, a linear model can be applied to fit topography dependent components. SRTM data can be successfully exploited to better interpolate APS data sampled on a sparse PS grid. APS RMS values can exceed 2π rad in areas of rough topography at mid-latitudes. Mean power and variogram is latitudedependent. APS components usually do not exhibit a gaussian statistics % reduction in APS power can be obtained using (P,T,h) information (even for moderate topographic profiles). COPYRIGHT - Tele-Rilevamento Europa
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