ice velocity mapping using tops sar data and offset...
TRANSCRIPT
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Ice Velocity Mapping Using TOPS SAR Data and Offset Tracking
Jørgen Dall1, Anders Kusk1, Ulrik Nielsen1, John Peter Merryman Boncori2 1 Technical University of Denmark, 2 Instituto Nazionale di Geofisica e Vulcanologia, Italy
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Outline
• Introduction • Problem (TOPS + large displacements) • Method • Results • Conclusions
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Offset tracking
Feature tracking Speckle tracking
Method Cross-correlation Cross-correlation
Data type Detected Detected or complex
Features Required Not required
Coherence Not required Required
Patch size Larger Smaller
Accuracy Coarser Finer
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TOPS
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TOPS
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Offset tracking with TOPS data
1st acquisition
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Offset tracking with TOPS data
1st acquisition
IW SLC product: • Spatial overlap • No spectral overlap => speckle pattern differs
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Offset tracking with TOPS data
1st acquisition
2nd acquisition
GRD product: features are preserved when crossing the burst seam
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Offset tracking with TOPS data
1st acquisition
2nd acquisition
GRD product: Speckle changes when crossing the burst seam => gap
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Offset tracking with TOPS data
1st acquisition
2nd acquisition
SLC product: gaps can also be avoided with speckle tracking if ice displacement + patch size < overlap
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Offset tracking with TOPS data
1st acquisition
2nd acquisition
SLC product: gaps can also be avoided with speckle tracking if ice displacement + patch size < overlap
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SLC product: gaps can also be avoided with speckle tracking if ice displacement + patch size < overlap
Offset tracking with TOPS data
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IPP processor
• Intended for DInSAR (DEM elimination & Double Difference)
• Upgraded for ESA’s Climate Change Initiative (GrIS CCI, AIS CCI): - Offset Tracking - Bulk processing (cloud computing) - Sentinel-1 IW SLC products
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Upernavik glaciers
M. Fahnestock et al., 1992
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Ice velocity (Sentinel-1 IW SLC) Upernavik, Oct-Dec 2014 Greenland Ice Sheets CCI Normalized cross-correlation:
Figures of merit: • max(NCC) • ’signal-to-noise ratio’ (SNR)
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Approach
1st acquisition
2nd acquisition
Corresponding bursts (exploited by IPP)
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Approach
1st acquisition
2nd acquisition
Corresponding bursts (exploited by IPP)
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Approach
2nd acquisition
1st acquisition Consecutive bursts
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Approach
1st acquisition
Patch: 256 x 64 (ra x az pixels)
Increment: 40, 10 (ra, az pixels)
2nd acquisition
Consecutive bursts (analysed in this study)
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Questions addressed
Questions: • In the overlap area four multi-temporal cross-correlations can
be computed. Which ones are useful? • Where do consecutive (multi-temporal) bursts decorrelate? • Does the GRD product lead to more velocity gaps? • Do the dual squint angles within the burst overlap provide
valuable glaciological information?
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Results: NCC IW2
IW1
IW3
1
.5
0
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Results: NCC IW2
IW1
IW3
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Results: NCC IW2
IW1
IW3
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Results: azimuth displacement IW1
IW3 IW2
5
-5
0
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Results: azimuth displacement IW1
IW3 IW2
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Results: azimuth displacement IW1
IW3 IW2
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Results: azimuth displacement IW1
IW3 IW2
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Results: SNR
IW3 IW2
0
100
IW1
50
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Results: SNR
IW3 IW2
IW1
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Results: SNR
IW3 IW2
IW1
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Landsat imagery
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Landsat imagery
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Landsat imagery
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Conclusions
• Velocity map successfully generated from Sentinel-1 IW SLC data in areas with and without features
• At high elevations, two corresponding (multi-temporal) bursts can be successfully cross-correlated, but two consecutive bursts cannot (presumably due to a lack of ice features)
• At low elevations (where ice features are often abundant) also consecutive (multi-temporal) bursts can often be successfully cross-correlated
• The IW GRD product may be applicable for (gap-free) feature tracking
• The IW SLC product is required for (gap-free) speckle tracking