Terrafirma Persistent Scatterer Processing Validation

Terrafirma Persistent Scatterer Processing Validation Nico Adam (1), Alessandro Parizzi (1), Michael Eineder (1), Michele Crosetto () (1) Remote Sensing Technology Institute () Institute of Geomatics

Signal and Noise Flow radar Focus InSAR Focus : Focus clutter SAR focussing (CEOS test) noise signal + InSAR Coregistration Linear LOS displacement Interferometric phase (extraction) DEM update PS detection? performance Estimator PS : E{s defo(g)} bias priority CR hupdate vdisplacement PS stability estimation (DA,SCR) PS density Misdetection by sidelobes Temporal limited PS APS Relative to absolute conversion Higher order PS Scene calibration Folie Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

DLR Amsterdam ASAR ±4 mm/year Folie 3

DLR Alkmaar ERS ±4 mm/year Folie 4

DLR Alkmaar ASAR ±4 mm/year Folie 5

Data Selection Test for suitability of the baseline-time distribution Pre-screening of the data Determine reference scene free of artefacts moderate Doppler frequency moderate APS contribution Defined processing areas Example data for cropping Folie 6 Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

Check for Correct Input Data Phase Offset Test Coregistration Check Folie 7

DLR Sidelobe Risk Map Amsterdam ASAR Folie 8

OSP Misdetection Sidelobe Risk 0.4: 4.% 0.6: 0.5% 0.8: 0.08% Folie 9 Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

One or Two Dominant Point Scatterers standard PS estimation fails PS density reduces 100 m 8 m 56 m LOS Stadt Folie 10

Principle of Two Scatterer Detection Two models for amplitude fading depending on baseline & sin( B ( ' + ) # i = a ( $! % B ( ' + ) " ( B #" + "!) i = a + a + # a # a # cos h 0 1 0 1 Example: Folie 11

DLR Risk Map for Two Scatterers Inside of a single Resolution Cell Tested scatterers Nearly all to have full overlap with OSP Folie 1 Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

DLR: Risk Map for Two Scatterers Inside of Resolution Cell 3956 out of 41 9.3% of used PS All OSPs ca. 1% Folie 13 Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

DLR OSP Amsterdam ASAR deformation scatter plot: coherence 0.95 1.00 Folie 14

DLR OSP Amsterdam ASAR deformation std. deviation depending on coherence!=0.40 mm/year!=0.35 mm/year coh: 0.9644 0.9369 0.87404 0.83669 0.773845 0.7400 0.679511 err: 0.3531 0.39500 0.4714 0.545348 0.64351 0.679346 0.741088 Folie 1

Typically best measured Deformation Error Best available PS with! = 0.96 are expected to have a 0.35 mm/year standard deviation (two systems)! best =0.35 mm/year Relative measurement: 1! 0.35 = 0.5 mm/year Folie

Theoretical Limit of Deformation Error PS with! = 1.0 are expected to have a 0.3 mm/year standard deviation (two systems)! lim =0.3 mm/year Relative measurement: 1! 0.30 = 0.1mm/year Folie 3

Absolute Deformation std. Deviation " defo = N free # "! S INSAR measured S = N = N free free " k " k " Var! T " 1 { T } i theory Folie 4

Corrected Absolute Deformation std. Deviation (" )! + PSI =!! defo floor! floor =! +! +! +! K radar focus = 0.1 [ mm / year] coreg approx Folie 5

Interpretation of Accuracy Estimates PU 0.5 mm/y is the practically achievable deformation precision 0.5 mm/y is the standard deviation of the slope of the fitted line 0.5 mm 1 year std. dev. of slope uncertainty: 0.5 mm/y The deviation of single points can be arbitrarily, it depends on the actual SCR coregistration f DC APS compensation Folie 6

Expected Precision for Topography F. Rocca:! h x = 8.77 N Amsterdam ASAR Alkmaar ASAR Alkmaar ERS DLR: N # $ $ h = N # N! bj "! j APS, SCR ( ) N b x measured j j Folie 7

DLR s Work Quality of estimation varies in the test site (e.g. SCR of PS) Actual estimation performance Measured for typical scatterers Predicted for optimal scatterer Derived and compared with theory Introduction of two contrary concepts: 1. Detection: For spatial visualisations Requires high PS density Allows the use of low quality scatterers. Measurement: For time series visualisation Allows the use of best quality scatterers only Folie 8 Institut für MethodikRemote der Fernerkundung bzw. Deutsches Fernerkundungsdatenzentrum Sensing Technology Institute

DLR Amsterdam ASAR ±4 mm/year 1 Folie 9

DLR Alkmaar ERS ±4 mm/year 1 Folie 30

DLR Alkmaar ASAR ±4 mm/year 1 Folie 31

Geocoding by Christian Minet Folie 3

Geocoding by Christian Minet Folie 33