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Measuring Change with Radar Imagery_Richard Goodman - Intergraph Geospatial World Tour 2013
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Transcript of Measuring Change with Radar Imagery_Richard Goodman - Intergraph Geospatial World Tour 2013
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SMARTERDECISIONS
Richard Goodman
Intergraph (UK) Ltd
Measuring Change With RADAR Imagery
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8/29/2013 ©2012 Intergraph Corporation 2
Why is change measurement important
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Why is change measurement important?
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Devastation caused by tornadoes in Alabama, 2011
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Why is change measurement important?
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Magnitude 9.0 earthquake in Japan, 2011
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Why is change measurement important?
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Mississippi river flooding in Memphis, Tennessee, 2011
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UK Floods, 2007
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Why is change measurement important?
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Oil spills
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So why use RADAR data in change
measurement
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The Mysterious RADAR image…
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Why use RADAR data in change measurement?
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• 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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Why use RADAR data in change measurement?
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• Interferometric processing• 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• Subsurface oil and water extraction
• Mining
• Natural disasters – earthquakes, volcanoes
• Human activities
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Why use RADAR data in change measurement?
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SMARTERDECISIONS
ERDAS Imagine Radar Tools
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ERDAS Imagine Radar Tools
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• 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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ERDAS Imagine Radar Tools
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• New Radar Analyst ribbon
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ERDAS Imagine Radar Tools
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• Interferometry tools – CCD & D-InSAR
• Wizard-based workflows• Intelligent defaults for parameters
• Experts can take full control
• Phase Un-Wrap algorithm• The heart of the CCD and D-InSAR
• Developed in conjunction with German Aerospace Agency (DLR)
3. Visual Interpretation
4. Automatic Detection
1. Project Setup2. Processing Steps
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SMARTERDECISIONS
Case Studies
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SMARTERDECISIONS
KSAT
Data Analysis and Classification Tool
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KSAT DACT Case Study
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• 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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KSAT DACT Case Study
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KSAT DACT Case Study
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• Locations
Tromsø Station & Offices at 69°39´N 18°56´E.
80 Employees
Svalbard Satellite Station (SvalSat) at 78°15´N 15°80´E
19 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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KSAT DACT Case Study
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• 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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KSAT DACT Case Study
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• 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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KSAT DACT Case Study
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SMARTERDECISIONS
Interferometry Tools Examples
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Qualitative Change Mapping with CCD
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Geoinformatics magazine, July/August 2010
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Qualitative Change Mapping with CCD
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Magnitude Change Coherence ChangePhase CoherenceAverage Radar Magnitude
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Quantitative Change Mapping with D-InSAR
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Quantitative Change Mapping with D-InSAR
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Using the IMAGINE D-InSAR tool users can map VerticalDisplacement
Max Subsidence = -16.5 cm
Max Uplift = +26.6 cm
Published Displacement: +30/-18
Xia,Ye. Bam earthquake: Surface deformation measurement using radar interferometry. ActaSeismologicia Sinica, Vol.18 No.4 (451~459), July, 2005
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Summary – Operational Change Measurement Workflow
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Input raw RADAR data
Detected change
Report
Vector output
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Questions?
SMARTERDECISIONS8/29/2013 33©2012 Intergraph Corporation