InSAR practical considerations

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• InSAR practical considerations

How to get data Understanding the Line of
Sight Sources of error
Matthew Pritchard Cornell University
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How to access data

• Overview of available data sources most
  up-to-date info is at roipac.org/AccessToData
• A tool to search for available ERS and Envisat
  data is freely available for download from ESA
  called EOLISA
• If you would like information on baselines
  between potential datatakes, visit roipac.org
• No Cost data -- but need to apply for access
• Supersites available for small areas of
  interest (Mt. Etna, Los Angeles, etc.) see
  roipac.org for link
• GeoEarthscope http//geoes-insar.unavco.org
• If at a research institution, write a Mini-Cat
  proposal
• (ERS, Envisat, Radarsat over North America)
• Alaska Satellite Facility http//asf.alaska.edu
• ALOS datapool -- if a WInSAR member, sign a form
  and get access
• ERS/JERS within ASF satellite disk mask, Radarsat
  almost anywhere in the world -- write a 1-page
  proposal
• Western North America InSAR Consortium
  http//winsar.unavco.org
• (ERS, Envisat over North America)
• Your institution must be a member (no cost to
  join!), need password

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Intro to InSAR How does it work?

• Two Radar images from space
• Data is complex has amplitude and phase
• Phase change between images depends on several
  factors that must be removed before measuring
  deformation

Wright, 2002
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Intro to InSAR How does it work?

• Two Radar images from space
• Data is complex has amplitude and phase
• Phase change between images depends on several
  factors that must be removed before measuring
  deformation

Wright, 2002
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Interferogram Formation
1999/04/21
1999/05/26
Amplitude

Amplitude

Phase
Phase
Modified from Rowena Lohman
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Where in the world am I?
Magnitude 6.6 earthquake 26 December 2003 in
Bam, Iran Arid and mountainous region with
frequent earthquakes (collision between Arabian
and Eurasian plates)
From Farsinet.com
Previously unmapped fault (right-lateral
strike-slip)

• North

Bam
Baravat
20 km
10 km
Landsat satellite image from 1999, from Funning
et al., 2005
Interferogram courtesy of Yuri Fialko
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What am I looking at?
Each fringe contour of ground deformation in
direction of satellite radar beam

• North

• Each scene
• 20 meters per pixel
• 100s of km per image
• Resolve deformation mm/year
• This example
• From European space Agency Envisat satellite (5.6
  cm radar wavelength)
• Each fringe is 2.8 cm of deformation

20 km
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Visualizing 3D deformation in a 1D interferogram
Step 1 Fault motion produces 3D deformation
field
Both images Funning et al., 2005
Step 2 Project 3D deformation onto satellite
radar line-of-sight Trade-off between horizontal
and vertical deformation creates asymmetric
pattern
Step 3 Create a fringe every ?/2 centimeters
(wrapped image)
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Reconstructing the full 3D deformation field

• Use interferograms from different satellite look
  directions

• PLUS use the amplitude images to track pixels
  that moved

Observed interferograms
Observed pixel tracking
Inferred horizontal displacement
Inferred vertical displacement
Fault
Fialko et al., 2005
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SAR Track/Frame Geometry
Iran
Modified from Rowena Lohman
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Hector Mine EQ
LOS
LOS
Descending
Ascending
Modified from Rowena Lohman
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• What are the sources of error?
• How do we evaluate them?

Unwrapping errors assess by looking a image
with different wrap rates Atmospheric/ionosphe
ric errors use multiple images and pairwise
logic (e.g., Feigl Massonnet, 1995) Orbital
errors understand their basic characteristics,
try different orbital estimates, process tracks
of different lengths, tandem pairs can be
useful DEM errors inspect the raw DEM,
process interferograms with different baselines
and timespans, tandem pairs can be useful
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Wrapped vs. Unwrapped
Hector Mine EQ
LOS
LOS
Color Cycle 300 cm
Color Cycle 3 cm
Modified from Rowena Lohman
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Modified from Rowena Lohman
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Modified from Rowena Lohman
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Modified from Rowena Lohman
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Unwrapped before masking
Unwrapped after masking
Modified from Rowena Lohman
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Orbital Errors (Ramps)

• 0.1-1 m uncertainty in satellite positions
• Orbital fringes not always 100 removed
• In particular, not sensitive to long wavelength
  deformation
• How to overcome?
• Simultaneously solve for position and geophysics

Reported vs. Actual
Modified from Rowena Lohman
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Atmospheric contamination Two types
Turbulence
Vertical stratification
Both From Pritchard Simons, 2004
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• Can we remove the atmospheric signal from
  interferograms?

0) Use interferograms themselves to estimate
linear or exponential phase with elevation
constant for image or spatially variable 1)
Direct water vapor and dry delay
observations From satellite (e.g., Li et al.,
2005) From GPS other ground sensors (e.g.,
Webley et al., 2002) 2) Data stacks or APS
Assume atmosphere random in time or low-pass time
domain filtering (e.g., Ferretti et al., 2001
Simons and Rosen, 2007) 3) Global and Regional
Models computed by data center (100 km
horizontal resolution by ECMWF, NCEP North
American RR 32 km) (e.g., Doin et al., 2007
Elliott et al., 2007) 4) Regional or Local Model
computed by user (lt3 km horizontal resolution)
(e.g., Foster et al., 2006)
Based on several studies, we cant remove
everything. Will likely always need to account
for atmosphere via covariance matrix
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Ionosphere C- and L- bands, spanning 4000 km
Azimuthal streaking seen in polar regions
(e.g., Joughin et al., 1996 Gray et al., 2000)
ALOS Dec. 2007- Dec. 2006 B-perp 1.1 km
ALOS Feb. 2008-Aug. 2007 500 m B-perp
ALOS Mar. 2008-Mar. 2007 600 m B-perp
ERS 1993-1997 From Pritchard, 2003
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Ionosphere

• Types of effects
• 1) Broad phase delay (Ecuador example?)
• 2) Turbulent effects (scintillation or spread F
  origin of Chile and Wenchuan examples?)
• 3) Faraday rotation

From NOAA

• Ionospheric corrective measures
• 1) Throw out bad scenes
• 2) Split spectrum
• 3) Optimium time of day

From Xu et al.,, 2004 originally from Aarons,
1982