keith morrison & muhammad yasin

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The Extraction of InSAR The Extraction of InSAR Information from Imagery of a Information from Imagery of a Wind-Blown Wind-Blown Tree Canopy with a Ground-Based Tree Canopy with a Ground-Based SAR SAR Keith Morrison & Muhammad Yasin Keith Morrison & Muhammad Yasin Department of Aerospace, Power and Sensors, Department of Aerospace, Power and Sensors, University of Cranfield, Shrivenham, UK University of Cranfield, Shrivenham, UK & & DLR, Institut für Hochfrequenztechnik und Radarsysteme DLR, Institut für Hochfrequenztechnik und Radarsysteme Weßling, Germany Weßling, Germany

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The Extraction of InSAR Information from Imagery of a Wind-Blown Tree Canopy with a Ground-Based SAR. Keith Morrison & Muhammad Yasin Department of Aerospace, Power and Sensors, University of Cranfield, Shrivenham, UK & - PowerPoint PPT Presentation

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Page 1: Keith Morrison & Muhammad Yasin

The Extraction of InSAR Information from The Extraction of InSAR Information from Imagery of a Wind-Blown Imagery of a Wind-Blown

Tree Canopy with a Ground-Based SARTree Canopy with a Ground-Based SAR

Keith Morrison & Muhammad YasinKeith Morrison & Muhammad Yasin

Department of Aerospace, Power and Sensors, Department of Aerospace, Power and Sensors, University of Cranfield, Shrivenham, UKUniversity of Cranfield, Shrivenham, UK

& & DLR, Institut für Hochfrequenztechnik und RadarsystemeDLR, Institut für Hochfrequenztechnik und Radarsysteme

Weßling, GermanyWeßling, Germany

Page 2: Keith Morrison & Muhammad Yasin

The GB-SAR SystemThe GB-SAR System

• Portable SAR / InSAR Imaging System

• All-weather

• L through X-band (1-12GHz)

• Fully polarimetric VV,HH,VH,HV

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RationaleRationale

Particular open questions relate to the conditions under which PolInSAR produces accurate measurements of biomass, with respect to:

• canopy structure (species, density, height distribution)

• technical sensor specifications

• imaging conditions (spatial and temporal)

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PresentationPresentation

Can the GB-SAR system be used to obtain meaningful PolInSAR measurements of forest canopies?

Considerations

GB-SAR imaging timescale on order of tens of minutes

Can expect wind-induced target motion

Can the results be related to air- and space-borne ?

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SAR Imaging of TreeSAR Imaging of Tree

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Sweet Chestnut Sweet Chestnut (castanea sativa mills)(castanea sativa mills)

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Tree spatially isolated Tree spatially isolated in grassy parklandin grassy parkland

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Tree DimensionsTree Dimensions

• Trunk Height = 25m• Trunk diameter at DBH = 1.7m• Trunk Circumference at DBH = 5.6m• Maximum tree width (2m from ground) = 15m• Tree width at ¾ of tree height = 12 m• Maximum tree depth = 18m• Tree depth at ¾ of tree height = 11m

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9.6m

14m

25m

5m

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Winter View, Winter View, from backfrom back

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Radar ParametersRadar Parameters

SF-CW Radar Type13th July 2005 Date of observation4.000GHz Start frequency (GHz)6.000GHz End frequency1601 Number of frequencies per sweep1.25MHzFrequency step interval3000Hz VNA IF bandwidth+8dBm Effective transmit power at antennaVV Polarisation20mm Aperture elemental sampling, dx3680mmAperture size, D185 Number of aperture samples1 or 8 Data averaging factor9.6m Antenna height above ground0.9s Tsweep, frequency sweep time1.1s Tmove, antenna movement time

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Scan Start Time End Time Duration Averaging Lapsed

1 16:02:18 16:08:58 6.7 min 1 -

2 16:32:37 16:39:18 6.7 min 1 0 min

3 16:41:18 16:47:58 6.7 min 1 8.7 min

4 16:48:46 16:55:27 6.7 min 1 16.2 min

5 16:57:10 17:03:51 6.7 min 1 24.6 min

6 17:04:44 17:11:24 6.7 min 1 32.1 min

7 17:12:50 17:19:30 6.7 min 1 40.2 min

8 17:20:45 17:27:25 6.7 min 1 48.1 min

9 17:28:34 17:35:15 6.7 min 1 56.0 min

10 17:38:00 18:08:08 30.1 min 8 77.1 min

11 18:13:06 18:43:13 30.1 min 8 112.2 min

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Scans 1-9. Av. Factor 1

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Scans 10 & 11. Av Factor 8

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Antenna & Space-loss Antenna & Space-loss

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Corrected ImagesCorrected Images

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Bulk Averaging - TreeBulk Averaging - Tree

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Canopy AttenuationCanopy Attenuation

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InSAR DecorrelationInSAR Decorrelation

γ = γNoise . γSpatial . γSystem . γTemporal

1/(1+SNR-1)

22

43

min 4 mNNN

FLL

GG

R

P

P

avxf

rt

rtt

r

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Coherence AnalysisCoherence Analysis

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Coherence vs AmplitudeCoherence vs Amplitude

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Coherent SummationCoherent Summation

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Distribution of CoherenceDistribution of Coherence

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Regression AnalysisRegression Analysis

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y = m.x + cy = m.x + c

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Regression Fit – Gradient (m)Regression Fit – Gradient (m)

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Regression Fit - Constant (c)Regression Fit - Constant (c)

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Standard Deviation From FitStandard Deviation From Fit

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Model SimulationsModel Simulations

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Effects of Wind-MotionEffects of Wind-Motion

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Motion Motion SimulationSimulation

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Sim_1a vs Sim_1b Sim_1a vs Sim_2a

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InSAR PhaseInSAR Phase

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InSAR Phase vs CoherenceInSAR Phase vs Coherence

The curves show the frequency of occurrence with phase for varying coherence ranges. The outermost curve is over the entire coherence range 0-1. The next innermost curve shows the distribution 0.1-1, then 0.2-1, and so on. The innermost curve shows the phase distribution 0.9-1.

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Non-Zero BaselineNon-Zero Baseline

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ConclusionsConclusions

• Meaningful SAR Imaging of trees is feasible

• Wind motion produces spreading of IPR into broadband unstructured azimuthal arcs

• Good coherences obtained by observation in low wind conditions

• Recovery of ‘static’ backscatter pattern by temporal averaging

• Averaging also improves the coherence

• However, latter might bias InSAR phase / height retrieval to stronger coherent features in canopy

Investigation into whether the GB-SAR system can be used for InSAR & PolInSAR