The document discusses the importance of measuring change using RADAR imagery. It provides examples of how RADAR has been used to monitor natural disasters like tornadoes, earthquakes, floods, and oil spills. RADAR data is well-suited for change measurement because it can see through clouds and darkness and man-made structures provide strong reflections. Interferometric processing of RADAR data pairs enables coherence change detection and displacement mapping with centimeter accuracy, allowing monitoring of subsidence from activities like resource extraction. The document also describes how ERDAS Imagine software and its radar tools were used by Kongsberg Satellite Services to develop an oil spill and vessel detection system from satellite imagery within 30 minutes of acquisition.

1. Measuring Change With RADAR Imagery
Richard Goodman
Intergraph (UK) Ltd
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2. Why is change measurement important
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3. Why is change measurement important?
Devastation caused by tornadoes in Alabama, 2011
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4. Why is change measurement important?
Magnitude 9.0 earthquake in Japan, 2011
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5. Why is change measurement important?
Mississippi river flooding in Memphis, Tennessee, 2011
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6. UK Floods, 2007
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7. Why is change measurement important?
Oil spills
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8. So why use RADAR data in change
measurement
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9. The Mysterious RADAR image…
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10. Why use RADAR data in change measurement?
• Active sensor
• No sun illumination required
• Imagery collected in cloudy weather
• Pulse sent from sensor, reflected off features, return captured by
antenna
• SINGLE LOOK COMPLEX (SLC) data format
• RADARSAT 1 / 2, COSMO-SkyMed, TerraSAR-X
• 2 bands of data
• Magnitude (strength of return)
• Phase (position of wave on return to antenna)
• Man-made features and infrastructure give
strong returns
• Buildings
• Steel/metals
• Sub-surface features
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11. Why use RADAR data in change measurement?
• Interferometric processing
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Interferometric pairs
Make use of both magnitude and phase layers
Coherence Change Detection (CCD)
Differential Interferometric Displacement Mapping (D-InSAR)
• Accuracy to cm level
• Monitoring subsidence
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Subsurface oil and water extraction
Mining
Natural disasters – earthquakes, volcanoes
Human activities
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12. Why use RADAR data in change measurement?

13. ERDAS Imagine Radar Tools
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14. ERDAS Imagine Radar Tools
• Radar Mapping Suite
• Add-on module
• Operational software
• Not a toolkit!
• Directly read data into viewer
• No import required
• No resampling of data
• New Radar Analyst ribbon
• Fast feature extraction
• Visualisation aids
• Interferometry tools
• CCD
• D-InSAR
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15. ERDAS Imagine Radar Tools
• New Radar Analyst ribbon
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16. ERDAS Imagine Radar Tools
1. Project Setup
2. Processing Steps
• Interferometry tools – CCD & D-InSAR
• Wizard-based workflows
• Intelligent defaults for parameters
• Experts can take full control
3. Visual
Interpretation
• Phase Un-Wrap algorithm
• The heart of the CCD and D-InSAR
• Developed in conjunction with German Aerospace Agency (DLR)
4. Automatic Detection
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17. Case Studies
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18. KSAT
Data Analysis and Classification Tool
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19. KSAT DACT Case Study
• Who/What is KSAT
• Kongsberg Satellite Services AS (KSAT) is a commercial
Norwegian enterprise
• Provides services to European Maritime Safety Agency to detect
and report oil spills using RADAR satellite imagery
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20. KSAT DACT Case Study
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21. KSAT DACT Case Study
• Locations
Svalbard Satellite Station (SvalSat)
at 78°15´N 15°80´E
19 employees
Tromsø Station & Offices at
69°39´N 18°56´E.
80 Employees
Grimstad, (South Norway) at
58°20´N 8°21´E
4 employees
And TrollSat (Antarctica) at 72°S 2°E – That s far far south…
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22. KSAT DACT Case Study
• The DACT Project
• KSAT has provided a service using satellite images for detection of
oil spills since 1994
• Can deliver oil spill reports to European end users promptly
• New user requirements had KSAT develop the Data Analysis and
Classification Tool with emphasis on oil spill and vessel detection
from satellite imagery
• Radar imagery ideal for quickly identifying oil spills and linking them
to possible sources (vessels/platforms)
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23. KSAT DACT Case Study
• The System
• Customised Imagine ribbon interface with KSAT tab
• Contains shortcuts to common tools used in identification, extraction
of oil spills
• External data sources, shipping tracks, wind, wave, current, oil
platforms used to identify possible sources of spill
• Reports generated for each radar scene (clean sea, warning,
notification)
• Target turnaround time is 30 minutes from when imagery available to
report sent
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24. KSAT DACT Case Study
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25. Interferometry Tools Examples
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26. Qualitative Change Mapping with CCD
Geoinformatics magazine, July/August 2010
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27. Qualitative Change Mapping with CCD
Magnitude Change
Average Radar Magnitude
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Coherence Change
Phase Coherence
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28. Quantitative Change Mapping with D-InSAR
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29. Quantitative Change Mapping with D-InSAR
Using the IMAGINE D-InSAR tool
users can map Vertical
Displacement
Max Subsidence = -16.5 cm
Max Uplift = +26.6 cm
Published Displacement: +30/-18
Xia,Ye. Bam earthquake: Surface deformation
measurement using radar interferometry. Acta
Seismologicia Sinica, Vol.18 No.4 (451~459), July,
2005
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30. Summary – Operational Change Measurement Workflow
Input raw RADAR data
Vector output
Detected change
Report
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31. Questions?
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