| Presentation | 2005-06-29 Supporting Disaster Monitoring with Near-Real Time SAR data Jeremy NICOLL, Rudiger GENS, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Synthetic aperture radar (SAR) has served as a valuable data source for disaster monitoring. Numerous studies have shown the all-weather advantages of SAR data to help monitor fires, landslides, hurricanes, oil spills and earthquakes. Advances in SAR interferometry (InSAR) technology have helped the study of even subtle changes in a far more comprehensive way, proving invaluable in earthquake and volcanic eruption damage assessment. SAR data has also been fused with optical data, and then used extensively for flood monitoring. The ability to measure roughness of the ocean surface makes SAR suitable for characterizing features such as wind speed and oil spills on the ocean. The Alaska Satellite Facility has supported scientists and agencies in assessing hazards by providing data downlink, processing, and technical assistance to various agencies. When Hurricane Isabel hit the US east coast Radarsat imagery provided by ASF helped the Federal Emergency Management Agency and other scientists to monitor the flooding caused by the hurricane. Nominal riverbeds and ocean levels could be established from archived data. The near real time data were used to determine flooded areas in Pennsylvania and the degree of coastal inundation in the Chesapeake Bay area. As part of the GhostNet project, a NASA funded research project designed to demonstrate the feasibility of identifying derelict fishing nets and other anthropogenic marine debris using data from satellite remote sensing, airborne and in situ buoy measurements, ASF provided support through acquisition planning, image processing and SAR image interpretation. In response to an oil spill that occurred at Skan Bay near Unalaska Island, Alaska, in December 2004, ASF supplied the US coast guard with geocoded data in GeoTiff format for their analysis system and ensured that further data was acquired to monitor the progress of the oil spill. Near real time support for disaster monitoring is at times limited by the type of disaster that is to be monitored. For example, the location of natural disasters such as earthquake, hurricanes and tsunamis is difficult to predict with enough certainty to plan sufficient data acquisitions. Researchers have relied on serendipity and statistical probability to acquire imagery coincident with a number of disasters. Even if data are acquired, a poor imaging geometry or mode can yield a product not useful for a particular event. As an example, when ASF tried to support the monitoring of forest fires in Alaska in 2004 the polarization of the RADARSAT-1 data (HH) was not suitable to detect the burning areas clearly enough in the imagery. In order to detect changes making quantitative estimates a reference data set of some sort is required that often is not available. The number of space-borne civilian SAR platforms is very small; RADARSAT-1, ERS-2, ENVISAT, and the future launches of ALOS, RADARSAT-2, and TerraSAR-X, plus a few smaller platforms still in the planning stage. Because there are so few, competition for the resource can be fierce. There are also many logistical obstacles between acquisition and disaster monitoring tool. Data acquisition can sometimes take a circuitous route to user, with on-board recorders, satellite relay, station to station internet transfer, and finally electronic transfer of the finished product. Processing of SAR data can take a significant amount of time; from 30 minutes to 3 hours, not counting queue delays. SAR geometry and radiometry peculiarities and processing artifacts can make image comprehension difficult for the uninitiated, necessitating interpretation, automated or manual, to a product in the domain of the disaster response team. While research and proof of concept efforts have demonstrated the potential for SAR in disaster monitoring, logistics and infrastructure work remains before a viable operational system can tap this potential. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Synthetic Aperture Radar / disaster monitoring / near-real tim |
| Paper # | SANE2005-23 |
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| Conference Information | |
| Committee | SANE |
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| Conference Date | 2005/6/22(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
| Secretary | |
| Assistant | |
| Paper Information | |
| Registration To | Space, Aeronautical and Navigational Electronics (SANE) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Supporting Disaster Monitoring with Near-Real Time SAR data |
| Sub Title (in English) | |
| Keyword(1) | Synthetic Aperture Radar |
| Keyword(2) | disaster monitoring |
| Keyword(3) | near-real tim |
| 1st Author's Name | Jeremy NICOLL |
| 1st Author's Affiliation | Alaska Satellite Facility, Geophysical Institute, University of Alaska Fairbanks() |
| 2nd Author's Name | Rudiger GENS |
| 2nd Author's Affiliation | Alaska Satellite Facility, Geophysical Institute, University of Alaska Fairbanks |
| Date | 2005-06-29 |
| Paper # | SANE2005-23 |
| Volume (vol) | vol.105 |
| Number (no) | 158 |
| Page | pp.pp.- |
| #Pages | 2 |
| Date of Issue | |