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imaginlabs.com Patent U.S. 8,121,433 B2 California Institute of Technology COSI-Corr Automatic Detection of Landslides and Ground Changes around the Hollywood Reservoir Storm events, January 2005 Sebastien Leprince Francois Ayoub Jiao Lin Jean-Philippe Avouac leprincs@caltech.edu Office: 626-395-2912 Cell: 626-240-9041 California Institute of Technology
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Case Study: Hollywood Reservoir, 2005 storms Data: Worldview panchromatic image pair, ortho-ready processing level (courtesy of DigitalGlobe): - Image 1 acquired on December 19, 2004 - Image 2 acquired on January 19, 2005 Goal: Comparing images bracketing the January 2005 storm, which produced heavy rain and triggered landslides. Goal is to identify the location of landslides and related ground changes. Applications: Rapid assessment of damages, documentation of past events, insurance claims verification.
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Processed Image from December 2004:
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Anomaly Detection between Dec 2004 and Jan 2005 2 3 4 In Red: most meaningful detected anomalies Next: Zooming-in on detected anomalies (green boxes) 1
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Anomaly #1 Dec. 19, 2004
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Anomaly #1 Jan. 19, 2005 Detected Landslides Although not done in this study, note that we could directly measure the reservoir water level variations
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Anomaly #1 Detected Landslides Detection Map
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Anomaly #2 Dec. 19, 2004
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Anomaly #2 Jan. 19, 2005 Detected Landslide
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Anomaly #2 Detection Map Detected Landslide
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Anomaly #3 Dec. 19, 2004
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Anomaly #3 Jan. 19, 2005 Mud wash in Hollywood Bowl parking lot
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Anomaly #3 Detection Map Mud wash in Hollywood Bowl parking lot
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Anomaly #4 Dec. 19, 2004
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Anomaly #4 Jan. 19, 2005 Changes at a construction site?
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Anomaly #4 Dec. 19, 2004 Changes at a construction site?
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Conclusions COSI-Corr Automatic anomaly detection delivered high quality detection of landslides triggered by storm events. The analysis is quick and automatic. Three main areas of catastrophic landslides were detected, as well as significant mud wash over the Hollywood Bowl parking lot. This technique also allows monitoring of the water level in the reservoir. Strong shadows and complex urban features did not impair the automatic detection. Automatic detection on panchromatic imagery could be completed with information from multi-spectral imagery to reduce the number of false positives. The results of this study are preliminary and could be improved. They could also be adapted to different detections or purposes. In particular, landslide volume may be calculated when high resolution imagery is available. Please contact the authors for more information.
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