GEOGG141 / GEOG3051Principles & Practice of Remote Sensing (PPRS) RADAR II: Interferometry

Dr. Mathias (Mat) Disney

UCL Geography

Office: 113, Pearson Building

Tel: 7670 05921

Email: mdisney@ucl.geog.ac.uk

www.geog.ucl.ac.uk/~mdisney

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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

A1 and A2 are known Positions determined From satellite orbit orGPS/INS

The range difference is determined from , the measured phase difference.

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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”

• The relationship between phase and distance is (in general) = 2d /

• i.e. if we have travelled by a wavelength (d=) then the phase has changed by 2.

0 2 46

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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

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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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MountVesuvius

ERSSAR

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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

(Proposed) launch date

Sensors Products Spatial resolution

Swath

ERS 1 and 2 tandem mission (ESA)

1991 1995

C band Images DEM

30m 100km

SRTM (JPL)

2000 IfSAR C band

DEM Images

RADARSAT 1 Canada

1995 C band SAR

Fine Standard

8m 30m

45km 100km

RADARSAT 2 Canada

2005 C band SAR

Ultrafine Standard

3m 28m

20km 100km

ALOS NASDA (Japan)

2005 PALSAR L band

Fine ScanSAR Polarimetric

7-44m 100m 24-89m

ENVISAT ESA

2002 ASAR C band

Image mode 12.5m 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 2geometry

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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_vidamodmapanasa.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 AccuracyVerification 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 AccuracyGelocation 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

Aerial photography

Comparison

TerrainType

Land cover

n Vmin vmax vMean [m] Rmse z

[m]

Lidar DTM vs. IfSAR DTM (5m)

Mixed (hilly, flat)

Bald earth

85362

-9.2 12.0 -0.2 1.0 1.01

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Lidar vs IfSAR over homogeneous bare earth areas

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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 parallax from bottom parallax from top

Two images from same position atdifferent times:object moves, parallax created

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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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Examples from NPA Group

Subsidence from Differential IfSAR

http://www.npagroup.com/index.htm