DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_uavsar

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Service Description: <b>Dates of Images:</b><div><b><br /></b></div><div><div>Sept 17, 2018 (1700), Sept 20, 2018 (1410), Sept 22, 2018 (1705), Sept 23, 2018 (1545), all times are UTC</div><div><br /></div><div><b>Date of Next Image:</b></div><div><b><br /></b></div><div>None</div><div><br /></div><div><b>Summary:</b></div><div><b><br /></b></div><div><div>UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), a NASA facility instrument mounted on a Gulfstream-III aircraft, is an airborne radar system capable of monitoring rapidly evolving flood events regardless of cloud cover. It can support daily flood extent maps that track flood cresting and recession following hurricane landfall or periods of heavy precipitation. </div><div><br /></div><div>The UAVSAR radar produces an L-band signal that can detect open water as well as water under canopies. This makes it especially useful for identifying flooding in places where it may not be visible in other aerial or satellite images.</div><div><br /></div><div><div>The flood extend map described here identifies the following classes: open water, flooded vegetation, not flooded, and no data.</div><div>Repeated UAVSAR acquisitions fill gaps between satellite passes and support both:</div><div><ul><li><i>Response phase:</i> providing high-resolution detection of active flooding, identifying flood-crest locations, and extending situational awareness in areas not covered by stream, tide, or rain-gauge networks.</li><li><i>Recovery phase: </i>documenting peak flood extent and areas of sustained inundation, supporting damage assessment, access planning, and post-event impact analyses.</li></ul></div><div>The map legend has been reconciled with the OPERA Dynamic Surface Water Extent product from Sentinel-1 (DSWx-S1), specifically the WTR layer. The product specification document for OPERA can be found here: <a href='https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite/' target='_blank'>https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite/</a></div></div><div style='font-weight:bold;'><br /></div></div><div>UAVSAR-derived flood inundation products were used to characterize both storm-surge and riverine flooding in North Carolina following Hurricane Florence, which made landfall on September 14, 2018. The Gulfstream-III aircraft flew over impacted areas on September 17, 20, 22, and 23, capturing the progression of floodwaters as they receded.</div></div><div><br /></div><div><b>Suggested Use:</b></div><div><b><br /></b></div><div><i>Legend Classifications:</i></div><div><div style='font-style:italic;'><br /></div><div><ul><li><i>Blue – Open Water:</i> Areas that are completely covered by water and clearly visible from above. This means the sensor has a direct view of the water surface, with no blockage from trees, buildings, or terrain. This class includes lakes, rivers, and flooded areas where land is completely covered by water.</li><li><br /></li><li><i>Green – Flooded Vegetation: </i>Areas where water is present but partially hidden by vegetation. This includes places like flooded forests (water under trees), agricultural fields, wetlands, golf courses, and urban green spaces with standing water.</li><li><br /></li><li><span><i>White – Not Flooded: </i></span>Areas without flooding. This includes both vegetated land (like forests or grass) and non-vegetated surfaces (such as bare soil, roads, and parking lots).</li><li><br /></li><li><span><i>Transparent – No Data: </i></span>Areas where no information is available. This happens either because the sensor did not capture data there or those areas were excluded from the current map.</li><li><br /></li><li><i>Things to keep in mind: </i>Users are advised to examine the spatial context and multiple observation dates to infer flooding in roads.</li></ul></div></div><div><br /></div><div>While SAR-based flood classification typically achieves high accuracy (>80%), two persistent challenges remain: (1) distinguishing open water from other low-backscatter surfaces (e.g., roads), and (2) separating flooded vegetation from built-up areas, which generate similar double-bounce scattering responses.</div><div><br /></div><div>Additional documentation on this data can be found <a href='https://uavsar.jpl.nasa.gov/science/documents/polsar-format.html' target='_blank'>here</a>. Data can be downloaded <a href='https://uavsar.jpl.nasa.gov/cgi-bin/deployment.pl?id=L20180915' target='_blank'>here</a>.</div><div><br /></div><div><b>Satellite/Sensor/Resolution:</b></div><div><b><br /></b></div><div><i>Instrument: </i>UAVSAR L-band Synthetic Aperture Radar.</div><div><i><br /></i></div><div><i>Model:</i> this classification followed Denbina et al. (2020) DOI: 10.1109/IGARSS39084.2020.9324379. </div><div><i><br /></i></div><div><i>Spatial grain: </i>The pixel posting is approximately 30 meters (0.0002778 degrees) and the original UAVSAR images used to make this map have approximately 6 meters posting.<br /><br /><b>Credits:</b></div><div><b><br /></b></div><div>This map was created by Richard Chen and Annemarie Peacock (NASA/JPL) with imagery from the UAVSAR sensor (<a href='https://uavsar.jpl.nasa.gov' target='_blank'>https://uavsar.jpl.nasa.gov</a>). For questions, please contact UAVSAR Project Manager, Yunling Lou (ylou@jpl.nasa.gov).</div>

Map Name: uavsarsplit_epsg

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Copyright Text: This map was created by Richard Chen and Annemarie Peacock (NASA/JPL) with imagery from the UAVSAR sensor (https://uavsar.jpl.nasa.gov). For questions, please contact UAVSAR Project Manager, Yunling Lou (ylou@jpl.nasa.gov)

Spatial Reference: 102100 (3857) LatestVCSWkid(0)

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Units: esriMeters

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Child Resources: Info Dynamic Layer

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DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_uavsar_MIL (MapServer)