PSI Precision, accuracy and validation aspects
|
|
- Louise Shepherd
- 5 years ago
- Views:
Transcription
1 PSI Precision, accuracy and validation aspects Urs Wegmüller Charles Werner Gamma Remote Sensing AG, Gümligen, Switzerland,
2 Contents Aim is to obtain a deeper understanding of what PSI can do, where it works as well as limitations and errors - PSI Rational, limitations of 2D continuous interferometry - PSI processing strategy - Nature of PS interferometric characteristics and identification of PS - Precision vs Accuracy - Systematic errors - Atmospheric effects Wet and Dry Delay, filtering - Phase unwrapping PSI temperal and spatial unwrapping - Reference point central role in processing, selection and phase filtering - Time series potential and limitations 2
3 SAR Radar Image Formation Z European Space Agency ERS-1 v Launch: July, > 2000 X SAR Frequency: C-Band 5.3 GHz, 5.6 cm Bandwidth: MHz Incidence angle: 23.5 degrees n Sla r0 Pixels: 4m range, 7.9m slant range an tr h θ ge 0 Orbit: 800 km, 35 day repeat im z A h ut Image swath: 100 km Y 2v l 2v cosθ fd = = λ λ Spacecraft travels along-track and is sidelooking recording echoes as a function of slant range Successive echoes are recorded coherently (phase) and processed as an ensemble 3-dimensional scene is projected into 2 dimensions (slant range, azimuth) Range sphere is surface of constant range Doppler cone: Surface of constant Doppler. Intersection with ground is a hyperbola 3
4 SAR Coherent Speckle Backscatter phase is determined by the coherent sum of contributions from all elemental scatterers in the resolution element. The phase recorded at the radar includes a propagation phase delay, a function of the slant range ρ and wavelength λ. 4π φ = ρ λ 4
5 SAR Interferometric Repeat Track Geometry B γ B ρ22 = ρ12 + B 2 2 Bρ1 cos γ α ρ B cos γ = B B θ ρ1 φ = ρ2 2πp ρ λ φm = φ mod 2π T Path and phase difference Angle Sensitivity: Interferometrically measured phase φ 4π 4π = B sin γ = B θ λ λ Slant Range The difference in the slant range vectors ρ is one component in offset between SLC images used to form the interferogram. Other components in the shift between SLCs include azimuth shift due to the exact lines processed 5
6 Differential Interferometric Phase φ=φtopo φdispl φ atmos φ noise 4π 4π 4π φ= B r displ r atmos φnoise λ λ λ The interferometric phase is linearly proportional to the path length but is wrapped (modulo 2PI). This gives radar interferometry very high sensitivity to deformation. The deformation signal has the same magnitude as the atmospheric phase Hence a strategy to obtain accurate estimates of the deformation phase include: 1. Accurate modeling of noise and signal 2. Numerous data acquisitions 3. Selection of wavelength, resolution, and geometry to maximize SNR 6
7 Interferometric Phase Noise Sources of Phase noise in the interferometric signal include: 1. Thermal noise from the environment and electronics ~ktb 2. Interferometric decorrelation due to movement of scatterers, baseline related decorrelation (spectral shift), track rotation 3. Atmospheric propagation delay (non-dispersive, essentially same for all frequencies) 4. Ionospheric propagation effects dispersive delay, Faraday rotation of the polarization 5. DEM errors (insufficient resolution) 6. Baseline error 7. Phase unwrapping errors 7
8 PSI Processing Approach 1. Find a set of points in the image that are phase stable for at least a period of time in the scene. If interferograms with large baselines are used for analysis, these points must be dominated by a single scatterer 2. Estimate corrections to the height and a nominal linear velocity to assist with unwrapping the phase. Subtracting phase contributions from topography, atmosphere, or any apriori knowledge of the deformation. 3. Phase unwrapping can occur in either space or time or both dimensions. To unwrap the phase, phase differences must be below PI between points or the multiple of 2PI cannot be estimated. 4. Once the phase has been unwrapped, partition the phase between velocity, atmosphere, topographic phase, and noise 8
9 Precision and accuracy Precision The precision relates to the separation of values that can be distinguished in a measurement Accuracy The accuracy of a measurements relates to how well the measurement corresponds to the truth 9
10 Precision in DINSAR and PSI context Precision of SAR phase measurement is a very small fraction of a phase cycle precision < 0.1mm Interferometric phase difference partial decorrelation of signal reduced coherence (0.9) higher phase noise reduced precision (e.g. 0.3 radian precision 1.3mm); this value can be improved by spatial averaging Considering the atmospheric path delay effects as an uncertainty of the measurement results in a phase standard deviations of the order of 1.5 radian precision 7mm A PSI result is based on many observations. So the estimation of an average deformation rate based on 50 observations over 5 years results in a precision < 1mm/year 10
11 Precision in DINSAR and PSI context (cont.) This precision of the linear rate estimation can be calculated with or without subtracting atmospheric phase screens typical precisions as small as 0.1mm/year if atmospheric phase screens are subtracted and precisions around 0.4mm/year if atmospheric phase screens are included in the statistical uncertainty estimation Precision of linear rates at outer boundary of a result and next to spatial gaps is lower. The precision of a specific observation in the time series is again different. There the conservative assumption is that it corresponds to the uncertainty of the single observation (precision of 7mm). Assuming that some of the atmosphere can be modeled results in lower values (e.g. 3mm). In any case it is significantly larger than just the coherence related signal noise unless we are sure that we can reliably model the atmospheric delay. Precision of specific observation is at beginning and end of series (and next to longer gaps in temporal coverage) is lower. 11
12 Accuracy in PSI context The accuracy of a measurements relates to how well the measurement corresponds to the truth. The precision of the measurement is one factor that relates to the accuracy (but often not the main one). Other relevant factors potentially affecting the accuracy of the deformation rate include: - phase unwrapping errors (see below) - overall tilts of the result (see below) - errors related to subtracted atmospheric phase screens (see below) 12
13 Estimation of accuracy of a PSI result Based on the data itself the precision can be estimated statistically. Based on the result the temporal and spatial consistence can be checked (e.g. to detect and discard outliers). During the TF project special processing was conducted to crosscompare results obtained by the different OSP and to compare the results against in-situ observations (see contributions / reports by Michele Crossetto). Validation with in-situ measurements can be done. In practice this is often not trivial due to non-identical locations and observation times. 13
14 Systematic errors (1) Large scale tilts There are causes to have large scale phase trends (e.g. phase ramps) across the image (related to SAR processing, slight errors in baseline model, ). A typical approach to scope with these is to assume that the terrain is not tilting at large scale. If that is a correct assumption then such tilts are correctly removed. Nevertheless, if the area shows a real large scale tilting (e.g. significant subsidence near the left border of the processed section) then the processing possibly removes this trend. This problem is most critical in the case of tectonic movements which are at scales larger than the size of the typical area processed. Be aware of this possibility; consider this in selection of area to be processed (ideally stable part around moving area) 14
15 Systematic errors (2) Underestimation of deformation rates Some people postulate a general underestimation of deformation rates in PSI results. There are clear limitations to the applicability of PSI in the case of fast deformations. Slower moving targets may be more easily identified as PS than moving targets, especially than non-uniformly moving targets. In the validation experiments we did not really identify such a general underestimation. 15
16 Atmospheric component (1) Scope and Approach Atmospheric path delay heterogeneity causes a phase component not related to the deformation. - Temporally and spatially variable - Altitude dependent - Fronts and waves between layers - Diurnal effects and sensitivity to surface heating This atmospheric phase is spatially quite smooth. A typical approach is to estimate the uniform movement, identify then for each pair the residual phase not modeled by the uniform motion model, to spatially filter this and to subtract it as atmospheric phase. This approach permits to significantly reduce the noise on the time series considered. A limitation of this approach is that non-uniform motion at intermediate and large spatial scale is may also be removed from the result. 16
17 Valais, Switzerland Temperatures -3 to +15C Obtain limits on phase stability over 3 days High Coherence Altitude: 2500m
18 Short-Time Diff. Interferograms, Valais interferograms, t =15 min/interferogram, starting time: 11:45 Delay close to the antenna affects entire range line 1 rad= GHz 18
19 Reconstructed Time Series, Valais interferograms, covering13.5 hrs Starting time: 11:45 1cycle = GHz 19
20 Atmospheric component (2) Height dependent atmospheric component The atmospheric path delay has a term relating to the dry atmosphere and a part relating to the water vapor. Depending on the topographic height of the terrain there is more or less atmosphere and water vapor above a site height dependent atmospheric component Simple linear model can be used to approximate height dependent atmospheric component modeling and compensation Possible errors: - height dependent atmospheric component may be interpreted as deformation -deformation that correlates with terrain height may be reduced by correction of height dependent atmospheric component 20
21 Phase unwrapping (1) Phase unwrapping is the most challenging step in SAR interferometry as well as in PSI Limits applicability Possible source for errors An unwrapping (ambiguity) error results in an offset of 2.8 cm (at Cband). Spatial or temporal steps in the deformation values (not rates) of 2.8 cm may be cause by an unwrapping error. For spatially and temporally smooth motion patterns and low deformation values between observations there is a high spatiotemporal consistency of the result high reliability of result, robustness of processing 21
22 Phase unwrapping (2) Higher probability for unwrapping errors in case of: - Faster deformation / higher deformation gradients - Coarse spatial coverage (areas with few points) - Non-uniform motion - Coarse temporal sampling (e.g. gap between 2001 and 2003) - Noisy data Characteristics of unwrapping error: - Single point, single date - Single point dates after a specific date - Entire section (=several to many points, e.g. patch or isolated region with points) 22
23 Reference point PSI result is relative to a spatial reference point Reference point can be changed - to transform average deformation rate result subtract reference point rate from all other values - subtract reference point values from all other point s time series 23
24 Time series potential and limitations PSI time series potential? What is included in a PSI time series? - terms included : linear model phase + noise + non-linear model What is not included in a PSI time series? - terms excluded : - subtracted topographic phase - atmospheric phase - orbital phase - residual linear or quadratic phase trends ( see also tilts) PSI time series provides some quality information (on reliability of average rate estimate / detection of potential unwrapping errors) -PSI time series provides some information on non-uniform motion 24
25 Non-uniform motion potential and limitations Potential of PSI with respect to non-uniform movements - Very localized, low amplitude ( good potential with PSI) - Intermediate to large scale, low amplitude (separation from atmospheric phase is critical as overlapping spatial scale) - Intermediate to large scale, high amplitude (PSI processing very challenging, standard processing may fail gap in result) - Sensors with good spatial resolution and good temporal coverage improve potential of PSI for non-uniform motion monitoring 25
MULTI-TEMPORAL INTERFEROMETRIC POINT TARGET ANALYSIS
MULTI-TEMPORAL INTERFEROMETRIC POINT TARGET ANALYSIS U. WEGMÜLLER, C. WERNER, T. STROZZI, AND A. WIESMANN Gamma Remote Sensing AG. Thunstrasse 130, CH-3074 Muri (BE), Switzerland wegmuller@gamma-rs.ch,
More informationGAMMA Interferometric Point Target Analysis Software (IPTA): Users Guide
GAMMA Interferometric Point Target Analysis Software (IPTA): Users Guide Contents User Handbook Introduction IPTA overview Input data Point list generation SLC point data Differential interferogram point
More informationIn addition, the image registration and geocoding functionality is also available as a separate GEO package.
GAMMA Software information: GAMMA Software supports the entire processing from SAR raw data to products such as digital elevation models, displacement maps and landuse maps. The software is grouped into
More informationScene Matching on Imagery
Scene Matching on Imagery There are a plethora of algorithms in existence for automatic scene matching, each with particular strengths and weaknesses SAR scenic matching for interferometry applications
More informationA Correlation Test: What were the interferometric observation conditions?
A Correlation Test: What were the interferometric observation conditions? Correlation in Practical Systems For Single-Pass Two-Aperture Interferometer Systems System noise and baseline/volumetric decorrelation
More informationSentinel-1 Toolbox. Interferometry Tutorial Issued March 2015 Updated August Luis Veci
Sentinel-1 Toolbox Interferometry Tutorial Issued March 2015 Updated August 2016 Luis Veci Copyright 2015 Array Systems Computing Inc. http://www.array.ca/ http://step.esa.int Interferometry Tutorial The
More informationAPPLICATION OF SAR INTERFEROMETRIC TECHNIQUES FOR SURFACE DEFORMATION MONITORING
APPLICATION OF SAR INTERFEROMETRIC TECHNIQUES FOR SURFACE DEFORMATION MONITORING Urs Wegmüller, Charles Werner, Tazio Strozzi, and Andreas Wiesmann Gamma Remote Sensing, Worbstrasse 225, 3073 Gümligen,
More informationLateral Ground Movement Estimation from Space borne Radar by Differential Interferometry.
Lateral Ground Movement Estimation from Space borne Radar by Differential Interferometry. Abstract S.Sircar 1, 2, C.Randell 1, D.Power 1, J.Youden 1, E.Gill 2 and P.Han 1 Remote Sensing Group C-CORE 1
More informationInterferometry Tutorial with RADARSAT-2 Issued March 2014 Last Update November 2017
Sentinel-1 Toolbox with RADARSAT-2 Issued March 2014 Last Update November 2017 Luis Veci Copyright 2015 Array Systems Computing Inc. http://www.array.ca/ http://step.esa.int with RADARSAT-2 The goal of
More informationTerrafirma: a Pan-European Terrain motion hazard information service.
Terrafirma: a Pan-European Terrain motion hazard information service www.terrafirma.eu.com The Future of Terrafirma - Wide Area Product Nico Adam and Alessandro Parizzi DLR Oberpfaffenhofen Terrafirma
More informationSentinel-1 Toolbox. TOPS Interferometry Tutorial Issued May 2014
Sentinel-1 Toolbox TOPS Interferometry Tutorial Issued May 2014 Copyright 2015 Array Systems Computing Inc. http://www.array.ca/ https://sentinel.esa.int/web/sentinel/toolboxes Interferometry Tutorial
More informationThe 2017 InSAR package also provides support for the generation of interferograms for: PALSAR-2, TanDEM-X
Technical Specifications InSAR The Interferometric SAR (InSAR) package can be used to generate topographic products to characterize digital surface models (DSMs) or deformation products which identify
More information2-PASS DIFFERENTIAL INTERFEROMETRY IN THE AREA OF THE SLATINICE ABOVE- LEVEL DUMP. Milan BOŘÍK 1
2-PASS DIFFERENTIAL INTERFEROMETRY IN THE AREA OF THE SLATINICE ABOVE- LEVEL DUMP Milan BOŘÍK 1 1 Department of Mathematics, Faculty of Civil Engineering, Czech Technical University in Prague, Thákurova
More informationInterferometric Synthetic-Aperture Radar (InSAR) Basics
Interferometric Synthetic-Aperture Radar (InSAR) Basics 1 Outline SAR limitations Interferometry SAR interferometry (InSAR) Single-pass InSAR Multipass InSAR InSAR geometry InSAR processing steps Phase
More informationIDENTIFICATION OF THE LOCATION PHASE SCREEN OF ERS-ENVISAT PERMANENT SCATTERERS
IDENTIFICATION OF THE LOCATION PHASE SCREEN OF ERS-ENVISAT PERMANENT SCATTERERS M. Arrigoni (1), C. Colesanti (1), A. Ferretti (2), D. Perissin (1), C. Prati (1), F. Rocca (1) (1) Dipartimento di Elettronica
More informationIndividual Interferograms to Stacks!
Individual Interferograms to Stacks! Piyush Agram! Jet Propulsion Laboratory!! Jun 29, 2015! @UNAVCO! Thanks to my colleagues from JPL, Caltech, Stanford University and from all over the world for providing
More informationDo It Yourself 8. Polarization Coherence Tomography (P.C.T) Training Course
Do It Yourself 8 Polarization Coherence Tomography (P.C.T) Training Course 1 Objectives To provide a self taught introduction to Polarization Coherence Tomography (PCT) processing techniques to enable
More informationSentinel-1 InSAR AP workshop
Sentinel-1 InSAR AP workshop Sentinel-1 InSAR progress and experience at GAMMA U. Wegmüller, C. Werner, A. Wiesmann, T. Strozzi Gamma Remote Sensing AG - Progress made since S1A Expert Users meeting at
More informationFiltering, unwrapping, and geocoding R. Mellors
Filtering, unwrapping, and geocoding R. Mellors or what to do when your interferogram looks like this correlation Haiti ALOS L-band (23 cm) ascend T447, F249 3/9/09-1/25/10 azimuth phase Bperp = 780 (gmtsar)
More informationSAR Interferometry. Dr. Rudi Gens. Alaska SAR Facility
SAR Interferometry Dr. Rudi Gens Alaska SAR Facility 2 Outline! Relevant terms! Geometry! What does InSAR do?! Why does InSAR work?! Processing chain " Data sets " Coregistration " Interferogram generation
More informationSAOCOM 1A INTERFEROMETRIC ERROR MODEL AND ANALYSIS
SAOCOM A INTERFEROMETRIC ERROR MODEL AND ANALYSIS Pablo Andrés Euillades (), Leonardo Daniel Euillades (), Mario Azcueta (), Gustavo Sosa () () Instituto CEDIAC FI UNCuyo & CONICET, Centro Universitario,
More informationDINSAR: Differential SAR Interferometry
DINSAR: Differential SAR Interferometry Fabio Rocca 1 SAR interferometric phase: ground motion contribution If a scatterer on the ground slightly changes its relative position in the time interval between
More informationInSAR Operational and Processing Steps for DEM Generation
InSAR Operational and Processing Steps for DEM Generation By F. I. Okeke Department of Geoinformatics and Surveying, University of Nigeria, Enugu Campus Tel: 2-80-5627286 Email:francisokeke@yahoo.com Promoting
More informationIndividual Interferograms to Stacks
Individual Interferograms to Stacks Piyush Agram Jet Propulsion Laboratory Aug 1, 2016 @UNAVCO Thanks to my colleagues from JPL, Caltech, Stanford University and from all over the world for providing images
More informationERS AND ENVISAT DIFFERENTIAL SAR INTERFEROMETRY FOR SUBSIDENCE MONITORING
ERS AND ENVISAT DIFFERENTIAL SAR INTERFEROMETRY FOR SUBSIDENCE MONITORING Urs Wegmüller 1, Tazio Strozzi 1, and Luigi Tosi 2 1 Gamma Remote Sensing, Thunstrasse 130, CH-3074 Muri b. Bern, Switzerland Tel:
More informationSENTINEL-1 SUPPORT IN THE GAMMA SOFTWARE
SENTINEL-1 SUPPORT IN THE GAMMA SOFTWARE Urs Wegmüller, Charles Werner, Tazio Strozzi, Andreas Wiesmann, Othmar Frey, and Maurizio Santoro Gamma Remote Sensing, Worbstrasse 225, 3073 Gümligen BE, Switzerland
More informationRadar Coherent Backscatter!
Radar Coherent Backscatter! Pixels in a radar image are a complex phasor representation of the coherent backscatter from the resolution element on the ground and the propagation phase delay! Interferometric
More informationALOS-2 PALSAR-2 support in GAMMA Software
ALOS-2 PALSAR-2 support in GAMMA Software Urs Wegmüller, Charles Werner, Andreas Wiesmann, Gamma Remote Sensing AG CH-3073 Gümligen, http://www.gamma-rs.ch 11-Sep-2014 1. Introduction JAXA has made available
More informationSynthetic Aperture Radar Interferometry (InSAR)
CEE 6100 / CSS 6600 Remote Sensing Fundamentals 1 Synthetic Aperture Radar Interferometry (InSAR) Adapted from and the ESA Interferometric SAR overview by Rocca et al. http://earth.esa.int/workshops/ers97/program-details/speeches/rocca-et-al/
More informationInterferometric processing. Rüdiger Gens
Rüdiger Gens Why InSAR processing? extracting three-dimensional information out of a radar image pair covering the same area digital elevation model change detection 2 Processing chain 3 Processing chain
More informationRelease Notes GAMMA Software, Linux Distribution Windows Distribution Mac OSX GAMMA Software Training Courses
Release Notes GAMMA Software, 20141201 (Urs Wegmüller, Charles Werner, Andreas Wiesmann, Othmar Frey 1-Dec-2014) Gamma Remote Sensing AG Worbstrasse 225, CH-3073 Gümligen http://www.gamma-rs.ch This information
More informationFirst TOPSAR image and interferometry results with TerraSAR-X
First TOPSAR image and interferometry results with TerraSAR-X A. Meta, P. Prats, U. Steinbrecher, R. Scheiber, J. Mittermayer DLR Folie 1 A. Meta - 29.11.2007 Introduction Outline TOPSAR acquisition mode
More informationIMPROVING DEMS USING SAR INTERFEROMETRY. University of British Columbia. ABSTRACT
IMPROVING DEMS USING SAR INTERFEROMETRY Michael Seymour and Ian Cumming University of British Columbia 2356 Main Mall, Vancouver, B.C.,Canada V6T 1Z4 ph: +1-604-822-4988 fax: +1-604-822-5949 mseymour@mda.ca,
More informationMac OSX The software in this version has been compiled again using Snow Leopard 10.6 with 64-bits.
Release Notes GAMMA Software, 20131205 (Urs Wegmüller, Charles Werner, 5-Dec-2013) Gamma Remote Sensing AG Worbstrasse 225, CH-3073 Gümligen http://www.gamma-rs.ch This information is provided to users
More informationThree-dimensional digital elevation model of Mt. Vesuvius from NASA/JPL TOPSAR
Cover Three-dimensional digital elevation model of Mt. Vesuvius from NASA/JPL TOPSAR G.ALBERTI, S. ESPOSITO CO.RI.S.T.A., Piazzale V. Tecchio, 80, I-80125 Napoli, Italy and S. PONTE Department of Aerospace
More informationThe STUN algorithm for Persistent Scatterer Interferometry
[1/27] The STUN algorithm for Persistent Scatterer Interferometry Bert Kampes, Nico Adam 1. Theory 2. PSIC4 Processing 3. Conclusions [2/27] STUN Algorithm Spatio-Temporal Unwrapping Network (STUN) 4 1D
More informationNOISE SUSCEPTIBILITY OF PHASE UNWRAPPING ALGORITHMS FOR INTERFEROMETRIC SYNTHETIC APERTURE SONAR
Proceedings of the Fifth European Conference on Underwater Acoustics, ECUA 000 Edited by P. Chevret and M.E. Zakharia Lyon, France, 000 NOISE SUSCEPTIBILITY OF PHASE UNWRAPPING ALGORITHMS FOR INTERFEROMETRIC
More informationfraction of Nyquist
differentiator 4 2.1.2.3.4.5.6.7.8.9 1 1 1/integrator 5.1.2.3.4.5.6.7.8.9 1 1 gain.5.1.2.3.4.5.6.7.8.9 1 fraction of Nyquist Figure 1. (top) Transfer functions of differential operators (dotted ideal derivative,
More informationINTERFEROMETRIC MULTI-CHROMATIC ANALYSIS OF HIGH RESOLUTION X-BAND DATA
INTERFEROMETRIC MULTI-CHROMATIC ANALYSIS OF HIGH RESOLUTION X-BAND DATA F. Bovenga (1), V. M. Giacovazzo (1), A. Refice (1), D.O. Nitti (2), N. Veneziani (1) (1) CNR-ISSIA, via Amendola 122 D, 70126 Bari,
More informationInterferometric SAR Processing
Documentation - Theory Interferometric SAR Processing Version 1.0 November 2007 GAMMA Remote Sensing AG, Worbstrasse 225, CH-3073 Gümligen, Switzerland tel: +41-31-951 70 05, fax: +41-31-951 70 08, email:
More informationMemorandum. Clint Slatton Prof. Brian Evans Term project idea for Multidimensional Signal Processing (EE381k)
Memorandum From: To: Subject: Date : Clint Slatton Prof. Brian Evans Term project idea for Multidimensional Signal Processing (EE381k) 16-Sep-98 Project title: Minimizing segmentation discontinuities in
More informationCoherence Based Polarimetric SAR Tomography
I J C T A, 9(3), 2016, pp. 133-141 International Science Press Coherence Based Polarimetric SAR Tomography P. Saranya*, and K. Vani** Abstract: Synthetic Aperture Radar (SAR) three dimensional image provides
More information3 - SYNTHETIC APERTURE RADAR (SAR) SUMMARY David Sandwell, SIO 239, January, 2008
1 3 - SYNTHETIC APERTURE RADAR (SAR) SUMMARY David Sandwell, SIO 239, January, 2008 Fraunhoffer diffraction To understand why a synthetic aperture in needed for microwave remote sensing from orbital altitude
More informationAMBIGUOUS PSI MEASUREMENTS
AMBIGUOUS PSI MEASUREMENTS J. Duro (1), N. Miranda (1), G. Cooksley (1), E. Biescas (1), A. Arnaud (1) (1). Altamira Information, C/ Còrcega 381 387, 2n 3a, E 8037 Barcelona, Spain, Email: javier.duro@altamira
More informationMission Status and Data Availability: TanDEM-X
Mission Status and Data Availability: TanDEM-X Irena Hajnsek, Thomas Busche, Alberto Moreira & TanDEM-X Team Microwaves and Radar Institute, German Aerospace Center irena.hajnsek@dlr.de 26-Jan-2009 Outline
More informationSentinel-1 processing with GAMMA software
Documentation User s Guide Sentinel-1 processing with GAMMA software Including an example of Sentinel-1 SLC co-registration and differential interferometry Version 1.1 May 2015 GAMMA Remote Sensing AG,
More informationConcept and methodology of SAR Interferometry technique
Concept and methodology of SAR Interferometry technique March 2016 Differen;al SAR Interferometry Young s double slit experiment - Construc;ve interference (bright) - Destruc;ve interference (dark) http://media-2.web.britannica.com/eb-media/96/96596-004-1d8e9f0f.jpg
More informationAirborne Differential SAR Interferometry: First Results at L-Band
1516 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 6, JUNE 2003 Airborne Differential SAR Interferometry: First Results at L-Band Andreas Reigber, Member, IEEE, and Rolf Scheiber Abstract
More informationGround Subsidence Monitored by L-band Satellite Radar. Interferometry
Ground Subsidence Monitored by L-band Satellite Radar Interferometry Hsing-Chung Chang, Ming-han Chen, Lijiong Qin, Linlin Ge and Chris Rizos Satellite Navigation And Positioning Group School of Surveying
More informationOperational process interferometric for the generation of a digital model of ground Applied to the couple of images ERS-1 ERS-2 to the area of Algiers
Operational process interferometric for the generation of a digital model of ground Applied to the couple of images ERS-1 ERS-2 to the area of Algiers F. Hocine, M.Ouarzeddine, A. elhadj-aissa,, M. elhadj-aissa,,
More information2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes
2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or
More informationGMES TERRAFIRMA. Validation of existing processing chains in Terrafirma stage 2 LIST OF OSP DELIVERABLES EXTENDED
GMES TERRAFIRMA ESRIN/Contract no. 19366/05/I-E Validation of existing processing chains in Terrafirma stage 2 LIST OF OSP DELIVERABLES EXTENDED 5 th July 2007 Final version - ERS M. Crosetto, M. Agudo
More informationRADARGRAMMETRY AND INTERFEROMETRY SAR FOR DEM GENERATION
RADARGRAMMETRY AND INTERFEROMETRY SAR FOR DEM GENERATION Jung Hum Yu 1, Xiaojing Li, Linlin Ge, and Hsing-Chung Chang School of Surveying and Spatial Information Systems University of New South Wales,
More informationICE VELOCITY measurements are fundamentally important
102 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 4, NO. 1, JANUARY 2007 Synergistic Fusion of Interferometric and Speckle-Tracking Methods for Deriving Surface Velocity From Interferometric SAR Data
More informationMULTI-TEMPORAL SAR DATA FILTERING FOR LAND APPLICATIONS. I i is the estimate of the local mean backscattering
MULTI-TEMPORAL SAR DATA FILTERING FOR LAND APPLICATIONS Urs Wegmüller (1), Maurizio Santoro (1), and Charles Werner (1) (1) Gamma Remote Sensing AG, Worbstrasse 225, CH-3073 Gümligen, Switzerland http://www.gamma-rs.ch,
More informationPlaya del Rey, California InSAR Ground Deformation Monitoring
Playa del Rey, California InSAR Ground Deformation Monitoring Master Document Ref.: RV-14524 July 13, 2009 SUBMITTED TO: ATTN: Mr. Rick Gailing Southern California Gas Company 555 W. Fifth Street (Mail
More informationDETECTION AND QUANTIFICATION OF ROCK GLACIER. DEFORMATION USING ERS D-InSAR DATA
DETECTION AND QUANTIFICATION OF ROCK GLACIER DEFORMATION USING ERS D-InSAR DATA Lado W. Kenyi 1 and Viktor Kaufmann 2 1 Institute of Digital Image Processing, Joanneum Research Wastiangasse 6, A-8010 Graz,
More informationWIDE BASELINE INTERFEROMETRY WITH VERY LOW RESOLUTION SAR SYSTEMS
1 of 25 26/03/2008 22.35 ne previo WIDE BASELINE INTERFEROMETRY WITH VERY LOW RESOLUTION SAR SYSTEMS Abstract: A. Monti Guarnieri, C. Prati, F. Rocca and Y-L. Desnos (*) Dipartimento di Elettronica e Informazione
More informationRepeat-pass SAR Interferometry Experiments with Gaofen-3: A Case Study of Ningbo Area
Repeat-pass SAR Interferometry Experiments with Gaofen-3: A Case Study of Ningbo Area Tao Zhang, Xiaolei Lv, Bing Han, Bin Lei and Jun Hong Key Laboratory of Technology in Geo-spatial Information Processing
More informationTANDEM-X: DEM ACQUISITION IN THE THIRD YEAR ERA
TANDEM-X: DEM ACQUISITION IN THE THIRD YEAR ERA D. Borla Tridon, M. Bachmann, D. Schulze, C. J. Ortega Miguez, M. D. Polimeni, M. Martone and TanDEM-X Team Microwaves and Radar Institute, DLR 5 th International
More informationRange Sensors (time of flight) (1)
Range Sensors (time of flight) (1) Large range distance measurement -> called range sensors Range information: key element for localization and environment modeling Ultrasonic sensors, infra-red sensors
More informationResults of UAVSAR Airborne SAR Repeat-Pass Multi- Aperture Interferometry
Results of UAVSAR Airborne SAR Repeat-Pass Multi- Aperture Interferometry Bryan Riel, Ron Muellerschoen Jet Propulsion Laboratory, California Institute of Technology 2011 California Institute of Technology.
More informationUpcoming altimeter measurements : nadir altimetry from Ku/C to Ka-band, SAR mode, interferometric SAR
Upcoming altimeter measurements : nadir altimetry from Ku/C to Ka-band, SAR mode, interferometric SAR Jean-Claude Souyris CNES, Service Altimétrie & Radar Acknowledgments : Nathalie Steunou, Roger Fjortoft,
More informationSUBSIDENCE MONITORING USING CONTIGUOUS AND PS-INSAR: QUALITY ASSESSMENT BASED ON PRECISION AND RELIABILITY
Proceedings, 11 th FIG Symposium on Deformation Measurements, Santorini, Greece, 2003. SUBSIDENCE MONITORING USING CONTIGUOUS AND PS-INSAR: QUALITY ASSESSMENT BASED ON PRECISION AND RELIABILITY Ramon F.
More informationPlaya del Rey, California InSAR Ground Deformation Monitoring
Document Title Playa del Rey, California InSAR Ground Deformation Monitoring Prepared By: (signature / date) Ref.: RV-14524 Project Manager: xxxxxx July 13, 2009 SUBMITTED TO: ATTN: Mr. Rick Gailing Southern
More informationNew Results on the Omega-K Algorithm for Processing Synthetic Aperture Radar Data
New Results on the Omega-K Algorithm for Processing Synthetic Aperture Radar Data Matthew A. Tolman and David G. Long Electrical and Computer Engineering Dept. Brigham Young University, 459 CB, Provo,
More informationLetter. Wide Band SAR Sub-Band Splitting and Inter-Band Coherence Measurements
International Journal of Remote Sensing Vol. 00, No. 00, DD Month 200x, 1 8 Letter Wide Band SAR Sub-Band Splitting and Inter-Band Coherence Measurements D. DERAUW, A. ORBAN and Ch. BARBIER Centre Spatial
More informationBrix workshop. Mauro Mariotti d Alessandro, Stefano Tebaldini ESRIN
Brix workshop Mauro Mariotti d Alessandro, Stefano Tebaldini 3-5-218 ESRIN Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano Outline A. SAR Tomography 1. How does it work?
More informationInterferometry Module for Digital Elevation Model Generation
Interferometry Module for Digital Elevation Model Generation In order to fully exploit processes of the Interferometry Module for Digital Elevation Model generation, the European Space Agency (ESA) has
More informationLINEAR AND NON-LINEAR LONG-TERM TERRAIN DEFORMATION WITH DINSAR (CPT: COHERENT PIXELS TECHNIQUE)
LINEAR AND NON-LINEAR LONG-TERM TERRAIN DEFORMATION WITH DINSAR (CPT: COHERENT PIXELS TECHNIQUE) Jordi J. Mallorquí (1), Oscar Mora (1,2), Pablo Blanco (1), Antoni Broquetas (1) (1) Universitat Politècnica
More informationMulti Baseline Interferometric Techniques and
Pagina 1 di 11 FRINGE 96 Multi Baseline Interferometric Techniques and Applications A.Ferretti, A. Monti Guarnieri, C.Prati and F.Rocca Dipartimento di Elettronica e Informazione (DEI) Politecnico di Milano
More informationPolSARpro v4.03 Forest Applications
PolSARpro v4.03 Forest Applications Laurent Ferro-Famil Lecture on polarimetric SAR Theory and applications to agriculture & vegetation Thursday 19 April, morning Pol-InSAR Tutorial Forest Application
More informationDIGITAL ELEVATION MODEL GENERATION FROM INTERFEROMETRIC SYNTHETIC APERTURE RADAR USING MULTI-SCALE METHOD
DIGITAL ELEVATION MODEL GENERATION FROM INTERFEROMETRIC SYNTHETIC APERTURE RADAR USING MULTI-SCALE METHOD Jung Hum Yu 1, Linlin Ge, Chris Rizos School of Surveying and Spatial Information Systems University
More informationINSAR QUALITY CONTROL: ANALYSIS OF FIVE YEARS OF CORNER REFLECTOR TIME SERIES
INSAR QUALITY CONTROL: ANALYSIS OF FIVE YEARS OF CORNER REFLECTOR TIME SERIES Petar Marinkovic, Gini Ketelaar, Freek van Leijen, and Ramon Hanssen Delft University of Technology, Delft Institute of Earth
More informationInterferometric Evaluation of Sentinel-1A TOPS data
Interferometric Evaluation of Sentinel-1A TOPS data N. Yague-Martinez, F. Rodriguez Gonzalez, R. Brcic, R. Shau Remote Sensing Technology Institute. DLR, Germany ESTEC/Contract No. 4000111074/14/NL/MP/lf
More informationRESOLUTION enhancement is achieved by combining two
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 3, NO. 1, JANUARY 2006 135 Range Resolution Improvement of Airborne SAR Images Stéphane Guillaso, Member, IEEE, Andreas Reigber, Member, IEEE, Laurent Ferro-Famil,
More informationINTEGRATED USE OF INTERFEROMETRIC SAR DATA AND LEVELLING MEASUREMENTS FOR MONITORING LAND SUBSIDENCE
INTEGRATED USE OF INTERFEROMETRIC SAR DATA AND LEVELLING MEASUREMENTS FOR MONITORING LAND SUBSIDENCE Yueqin Zhou *, Martien Molenaar *, Deren Li ** * International Institute for Aerospace Survey and Earth
More informationRange Imaging Through Triangulation. Range Imaging Through Triangulation. Range Imaging Through Triangulation. Range Imaging Through Triangulation
Obviously, this is a very slow process and not suitable for dynamic scenes. To speed things up, we can use a laser that projects a vertical line of light onto the scene. This laser rotates around its vertical
More informationAIRBORNE synthetic aperture radar (SAR) systems
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL 3, NO 1, JANUARY 2006 145 Refined Estimation of Time-Varying Baseline Errors in Airborne SAR Interferometry Andreas Reigber, Member, IEEE, Pau Prats, Student
More informationSEA SURFACE SPEED FROM TERRASAR-X ATI DATA
SEA SURFACE SPEED FROM TERRASAR-X ATI DATA Matteo Soccorsi (1) and Susanne Lehner (1) (1) German Aerospace Center, Remote Sensing Technology Institute, 82234 Weßling, Germany, Email: matteo.soccorsi@dlr.de
More informationInSAR DEM; why it is better?
InSAR DEM; why it is better? What is a DEM? Digital Elevation Model (DEM) refers to the process of demonstrating terrain elevation characteristics in 3-D space, but very often it specifically means the
More information10/5/09 1. d = 2. Range Sensors (time of flight) (2) Ultrasonic Sensor (time of flight, sound) (1) Ultrasonic Sensor (time of flight, sound) (2) 4.1.
Range Sensors (time of flight) (1) Range Sensors (time of flight) (2) arge range distance measurement -> called range sensors Range information: key element for localization and environment modeling Ultrasonic
More informationA STATISTICAL-COST APPROACH TO UNWRAPPING THE PHASE OF INSAR TIME SERIES
A STATISTICAL-COST APPROACH TO UNWRAPPING THE PHASE OF INSAR TIME SERIES Andrew Hooper Delft Institute of Earth Observation and Space Systems, Delft University of Technology, Delft, Netherlands, Email:
More informationTanDEM-X Interferometric Processing Chain and SAR Products. Thomas Fritz H. Breit, M. Eineder, M. Lachaise & ITP Development Team
TanDEM-X Interferometric Processing Chain and SAR Products Thomas Fritz H. Breit, M. Eineder, M. Lachaise & ITP Development Team TanDEM-X Science Meeting Nov. 2008 From Acquisitions to Products - The TanDEM-X
More informationThe Staggered SAR Concept: Imaging a Wide Continuous Swath with High Resolution
The Staggered SAR Concept: Imaging a Wide Continuous Swath with High Resolution Michelangelo Villano *, Gerhard Krieger *, Alberto Moreira * * German Aerospace Center (DLR), Microwaves and Radar Institute
More informationFAST SOLUTION OF PHASE UNWRAPPING PARTIAL DIFFERENTIAL EQUATION USING WAVELETS
Tenth MSU Conference on Differential Equations and Computational Simulations. Electronic Journal of Differential Equations, Conference 23 (2016), pp. 119 129. ISSN: 1072-6691. URL: http://ejde.math.txstate.edu
More informationGAMMA Software. Introduction:
v1.1, 1-Dec-2017 page 1 GAMMA Software Introduction: GAMMA Software supports the entire processing chain from SAR raw data to products such as digital elevation models, displacement maps and landuse maps.
More informationGMES TERRAFIRMA: VALIDATION OF PSI FOR USERS RESULTS OF THE PROVENCE INTER-COMPARISON
GMES TERRAFIRMA: VALIDATION OF PSI FOR USERS RESULTS OF THE PROVENCE INTER-COMPARISON Crosetto, M. (1), Agudo, M. (1), Capes, R. (2), Marsh, S. (3) (1) Institute of Geomatics, Parc Mediterrani de la Tecnologia,
More informationWIDE AREA DEFORMATION MAP GENERATION WITH TERRASAR-X DATA: THE TOHOKU-OKI EARTHQUAKE 2011 CASE
WIDE AREA DEFORMATION MAP GENERATION WITH TERRASAR-X DATA: THE TOHOKU-OKI EARTHQUAKE 2011 CASE Nestor Yague-Martinez (1), Michael Eineder (2), Christian Minet (2), Birgitt Schättler (2) (1) Starlab Barcelona
More informationHeath Yardley University of Adelaide Radar Research Centre
Heath Yardley University of Adelaide Radar Research Centre Radar Parameters Imaging Geometry Imaging Algorithm Gamma Remote Sensing Modular SAR Processor (MSP) Motion Compensation (MoCom) Calibration Polarimetric
More informationPrecise coregistration of Sentinel-1A TOPS data. Heresh Fattahi, Piyush Agram, Mark Simons
Precise coregistration of Sentinel-1A TOPS data Heresh Fattahi, Piyush Agram, Mark Simons Sentinel-1A TOPS Burst N Burst 3 Burst 2 Burst 1 [Prats-Iraola et al, 212] Swath1 Swath2 Swath3 [Sakar et al, 215]
More informationInSAR Processing. Sentinel 1 data Case study of subsidence in Mexico city. Marie-Pierre Doin, Cécile Lasserre, Raphaël Grandin, Erwan Pathier
1 InSAR Processing Sentinel 1 data Case study of subsidence in Mexico city Marie-Pierre Doin, Cécile Lasserre, Raphaël Grandin, Erwan Pathier NSBAS processing chain (based on ROI_PAC): ROI-PAC: Rosen et
More informationMotion compensation and the orbit restitution
InSA R Contents Introduction and objectives Pi-SAR Motion compensation and the orbit restitution InSAR algorithm DEM generation Evaluation Conclusion and future work Introduction and Objectives L-band
More informationALOS-PALSAR performances on a multiple sensor DInSAR scenario for deformation monitoring
ALOS-PALSAR performances on a multiple sensor DInSAR scenario for deformation monitoring Pablo Blanco, Roman Arbiol and Vicenç Palà Remote Sensing Department Institut Cartogràfic de Catalunya (ICC) Parc
More informationFIRST RESULTS OF THE ALOS PALSAR VERIFICATION PROCESSOR
FIRST RESULTS OF THE ALOS PALSAR VERIFICATION PROCESSOR P. Pasquali (1), A. Monti Guarnieri (2), D. D Aria (3), L. Costa (3), D. Small (4), M. Jehle (4) and B. Rosich (5) (1) sarmap s.a., Cascine di Barico,
More informationSAR Interferogram Phase Filtering Using Wavelet Transform
Formatted: Font: 16 pt, Nazanin, 16 pt, (Complex) Farsi, 12 pt SAR Interferogram Phase Filtering Using Wavelet Transform V. Akbari, M. Motagh and M. A. Rajabi 1 Dept. o Surveying Eng., University College
More informationA NEW APPROACH FOR LONG TERM MONITORING OF DEFORMATIONS BY DIFFERENTIAL SAR INTERFEROMETRY
A NEW APPROACH FOR LONG TERM MONITORING OF DEFORMATIONS BY DIFFERENTIAL SAR INTERFEROMETRY A NEW APPROACH FOR LONG TERM MONITORING OF DEFORMATIONS BY DIFFERENTIAL SAR INTERFEROMETRY PROEFSCHRIFT ter verkrijging
More informationPersistent Scatterer InSAR for Crustal Deformation Analysis, with Application to Volcán Alcedo, Galápagos
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. XXX, XXXX, DOI:1.19/6JB4763, 7 Persistent Scatterer InSAR for Crustal Deformation Analysis, with Application to Volcán Alcedo, Galápagos A. Hooper Department of Geophysics,
More informationIce surface velocities using SAR
Ice surface velocities using SAR Thomas Schellenberger, PhD ESA Cryosphere Remote Sensing Training Course 2018 UNIS Longyearbyen, Svalbard 12 th June 2018 thomas.schellenberger@geo.uio.no Outline Synthetic
More informationDEFORMATION MEASUREMENT USING INTERFEROMETRIC SAR DATA
DEFORMATION MEASUREMENT USING INTERFEROMETRIC SAR DATA M. Crosetto Institute of Geomatics, Campus de Castelldefels, 08860 Castelldefels (Barcelona), Spain - michele.crosetto@ideg.es Commission II, WG II/2
More information