Transcript Slide 1

2009-10 CEGEG046 / GEOG3051
Principles & Practice of Remote Sensing (PPRS)
9: RADAR 2 - interferometry
Dr. Mathias (Mat) Disney
UCL Geography
Office: 113, Pearson Building
Tel: 7670 05921
Email: [email protected]
www.geog.ucl.ac.uk/~mdisney
Definitions and terms
• IfSAR or InSAR – Interferometric SAR
• DifSAR – Differential Interferometric SAR
References
• http://www.intermap.com/customer/papers.cfm
• http://www.ae.utexas.edu/courses/ase389/midterm/masa/masa1
.html
• http://www.jpl.nasa.gov/srtm/missionoverview.html
• http://www.jpl.nasa.gov/srtm/instrumentinterfmore.html
• http://southport.jpl.nasa.gov/
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Mt Hokkaido, Japan
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INSAR
• Interferometry is a technique for combining
coherent measurements
• Essentially looks at the difference in phase
between two coherent measurements and
deduces distance information from this
• SAR interferometry needs at least (i) two radars or
(ii) radar imaging from two places
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Principle of SAR Interferometry
A2
B
A1

R  p

R
A1 and A2 are known
Positions determined
From satellite orbit or
GPS/INS
The range difference is
determined from , the
measured phase
difference.
H
h
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• Though ERS images are usually presented as amplitude (e.g.
PRI images), the radar measurements are actually complex
(e.g. SLC).
• Strictly speaking we have two images, which encode amplitude
and phase
• To derive an amplitude image, we throw away the phase
information
• The phase image on its own may have no useful information
• To derive an interferogram, we take the difference of two phase
images
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INSAR
• phase is a measure of “how far the wave has travelled”
0
2p
4p
6p...
• The relationship between phase and distance is (in general)
f = 2pd / l
• i.e. if we have travelled by a wavelength (d=l) then the phase has
changed by 2p.
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INSAR
•
•
Interferometry depends on the fact that we are using waves (electric fields).
Two waves can interact to give brighter light (constructive interference) but also
darker radiation patterns (destructive interference) darkness.
+
=
CONSTRUCTIVE
+
=
DESTRUCTIVE
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INSAR
• Phase information is effectively random noise in a single
SAR image (because the phases are randomised by all
the scattering on the Earth’s surface)
• However, if we view from another position very close to the
first, then the differences in phase tell us about the
differences in distance.
• Then it is just a matter of geometry...
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Difference between the two path
lengths related to the difference in
phase of the received electric fields,
Interferometry used to generate two
sorts of products - a coherence
image, and a phase image (called
the interferogram)
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Phase difference
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Interferogram
For generating an interferogram, two co-registered SAR images
covering the same area are multiplied in a complex fashion.
The result of this complex multiplication is the average of the
two SAR images and the difference of their corresponding
phase values. The interference pattern, also called FRINGE, is
stored in a range of [ -π , π ].
Interferograms show differences in phase. This phase
difference is the result of a path length difference that can be
caused by elevation differences, motion, or deformation.
Hence, we can use interferograms to derive accurate elevation
maps, monitor small motions, and detect tiny deformations.
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Registration
The phase difference can only be determined from two images
taken from slightly different positions – both images are therefore
almost identical
The phase difference is determined at pixel level on the two images,
therefore pixels must correspond.
Registration is done by standard correlation and transformation
techniques
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Shuttle Radar Topography Mission SRTM
11-day mission Feb 2000
http://www2.jpl.nasa.gov/srtm/instrumentinterfmore.html
http://www2.jpl.nasa.gov/srtm/
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Shuttle Radar Topography Mission SRTM
http://www2.jpl.nasa.gov/srtm/
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INSAR
• Note that with two images, we can create two
products:– An entire image of the phase information is known as
the interferogram
– An image of the coherence (i.e. the correlation
between the two images)
• coherence near 1 means the phase information is reliable (and
the images have high degree of correlation)
• coherence < ~ 0.3 means the images have low correlation
(noisy). In this case, the phase information is probably not
useful.
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Coherence
The coherence is a measure of the
correlation of the phase information of two
corresponding signals and varies in the
range of 0 to 1.
The degree of coherence can be used as a
quality measure because it significantly
influences the accuracy of phase
differences and height measurements.
Bright areas indicate regions of high
coherence, whereas dark areas represent
low coherence regions.
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Coherence
•
•
•
•
•
•
There are several factors decreasing the coherence. In
approximate order:
Local slope (steep slopes lead to low coherence)
Properties of the surface being imaged (vegetated or
moving surfaces have low coherence).
Time difference between the passes in an interferogram
(long time difference lead to low coherence)
The baseline (large baselines lead to low coherence)
Technical details of the generation of the interferogram
(poor co-registration or resampling leads to low
coherence)
Atmosphere
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Phase unwrapping
Phase can only be detected between and -π, π but the actual phase shift
between two waves is often more than
this. Phase unwrapping is the process of
reconstructing the original phase shift
from this "wrapped" representation. It
consists of adding or subtracting
multiples of 2 in the appropriate places
to make the phase image as smooth as
possible. To convert interferometric
phase into elevation, you must perform
phase unwrapping.
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Mount
Vesuvius
ERS
SAR
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Interferogram
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DEM
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Mt Etna interferogram
X-band
(SIR-C/X-SAR mission)
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Data acquisition
• Configuration can come from:
Repeat pass
– ERS-1, Radarsat, ENVISAT
Single Pass
– Shuttle Radar Topography Mission SRTM
– Aircraft
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Sources of IfSAR data
Satellite/
operator
ERS 1
and 2
tandem mission
(ESA)
SRTM
(JPL)
RADARSAT 1
Canada
RADARSAT 2
Canada
ALOS
NASDA (Japan)
(Proposed)
launch date
1991
1995
Sensors
Products
C band
Images
DEM
2000
IfSAR
C band
C
band
SAR
C
band
SAR
PALSAR
L band
ENVISAT
ESA
2002
DEM
Images
Fine
Standard
Ultrafine
Standard
Fine
ScanSAR
Polarimetric
Image mode
1995
2005
2005
ASAR
C band
Spatial
resolution
30m
8m
30m
3m
28m
7-44m
100m
24-89m
12.5m
Swath
100km
45km
100km
20km
100km
100km
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Problems
• Physical changes between two acquisitions cause
loss of coherence (eg rainfall, wind, field
ploughing, vegetation growth)
• TEMPORAL DECOHERENCE (degradation in the
quality of the phase measurement)
• Differential Interferometry - generate two
interferograms and then take the difference
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ERS 1 and 2
geometry
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ERS Tandem Mission
• ERS-1 and ERS-2 in same orbit with a repeat
cycle of 35 days
• ERS-2 35 minutes behind ERS-1 – this gives
coincidence of ground track after 24 hours
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RADARSAT
Radarsat has variable look angle – therefore more frequent revisit
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SRTM http://semana2.terra.com.co/imagesSemana/documentos/SRTM_Eos_vi
damodmapanasa.doc
The Level-2 Terrain Height Data Sets contain the digital topography data
processed from the C-Band data collected during the mission.
For data between the equator to 50 degrees latitude, the postings are
spaced at 1" (one arcsecond) latitude by 1" longitude. At the equator,
these are spacings of approximately 30 meters by 30 meters.
The absolute horizontal accuracy (90% Circular Error) is 20 meters.
The absolute vertical accuracy (90% Linear Error) is 16 meters.
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Processing of SRTM data
• Measurement of base length is critical
• SRTM mast not stable
• Therefore movement of outboard antenna must be
monitored and correction made
• Unexpected movement of the shuttle can cause
problems
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Orientation and movement sensors
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Accuracy of IfSAR
• Theoretical accuracy very high – sub wave length
• Dependent on
–
–
–
–
Base length
Terrain
Atmosphere
Coherence
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Global SRTM Accuracy
Verification Data Sets
• Kinematic GPS: Data collected by NIMA for SRTM validation using
kinematic GPS data processing (estimated accuracy: <50 cm). The
total number of globally distributed KGPS points is: 20,150,000
• DTED-2: 21 DTED level 2 patches. Height posting identical to SRTM.
Height accuracy similar to SRTM.
• DEM Patches: 50 small patches similar to DTED-2 prior to editing in
accuracy.
• Ground Control Points:
– 50,000 NIMA land GCPs with varying height accuracy.
– Millions of ocean GCP’s from mean sea surface and tidal model
with an accuracy better than 50 cm.
• GeoSAR Data: meter level accuracy and geolocation for X-band
interferometer data.
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Global SRTM Accuracy
Gelocation Error from KGPS Tracks
• Geolocation errors can be estimated by matching the KGPS tracks
with roads identifiable in the radar imagery
• In addition, geolocation can also be estimated by matching the road
KGPS topography with the SRTM topography.
• The accuracy of the estimate depends on scene contrast, road
geometry, and topography.
• Africa 90% geolocation error: 11.9 m
• Australia 90% geolocation error: 7.2 m
• Eurasia 90% geolocation error: 8.8 m
• North America 90% geolocation error: 12.6 m
• South America 90% geolocation error: 9.0 m
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Comparison of IfSAR with Lidar DTM
Comparis
on
Terrain
Type
Land
cover
n
Vmin
vmax
vMean
 [m]
Rmse z
[m]
Lidar DTM
vs. IfSAR
DTM (5m)
Mixed
(hilly,
flat)
Bald
earth
8536
2
-9.2
12.0
-0.2
1.0
1.01
Aerial photography
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Lidar vs IfSAR over
homogeneous bare earth
areas
SUB AREA
COMPARISON
Terrain
Type
Land
cover
n
vmin
vmax
vMean
[m]
RMSE Z [m]
1
Lidar DSM (5m) vs.
IfSAR DSM (5m)
hilly
(46-61m)
crops
11484
-10.3
0.9
-0.6
0.47
0.77
1
Lidar EA DSM (5m)
vs. IfSAR DTM (5m)
hilly
(46-61m)
crops
11484
-1.6
0.6
-0.4
0.30
0.48
1
Lidar EA DTM (5m)
vs. IfSAR DTM (5m)
hilly
(46-61m)
crops
11484
-1.6
0.5
-0.4
0.30
0.48
2
Lidar DSM (5m) vs.
IfSAR DSM (5m)
Flat
(49-53m)
crops
2166
-1.7
0.7
-0.6
0.36
0.73
2
Lidar DSM (5m) vs.
IfSAR DTM (5m)
Flat
(49-53m)
crops
2166
-1.1
0.0
-0.4
0.20
0.46
2
Lidar EA DTM (5m)
vs. IfSAR DTM (5m)
Flat
(49-53m)
crops
2166
-1.1
0.0
-0.4
0.20
0.46
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The LANDMAP project
•
•
•
•
•
Generation of IfSAR DEM from ERS data
Geocoding of ERS images
QA of strips
Mosaic of strips
Geocoding and mosaicing
of other image datasets
http://www.landmap.ac.uk/
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Differential IfSAR
Movement of objects creates parallax
Two images from different positions Two images from same position at
parallax from bottom
different times:
object moves, parallax created
parallax from top
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Differential IfSAR
• If two images taken from identical positions, then
any parallax will come from movement of object.
But…
• Sensor not in the same position nor orientation
• Baseline, viewing angle and attitude can be
determined using ground control.
• Cannot resolve difference in plan and elevation
movement unless sensor vertically above
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Requirements
•
•
•
•
Images from near nadir
DEM to correct off nadir effects
Ground control to determine orientation
Fairly constant movement so that measurements
can be averaged
• Sub pixel correlation
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Subsidence from Differential IfSAR
Examples from NPA Group
http://www.npagroup.com/index.htm
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