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DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_s1 (MapServer)

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Service Description: <div style='text-align:Left;'><p><span style='font-weight:bold;'>Dates of Images:</span></p><p style='margin:0 0 0 0;'><span><span>20220422T1234, 20220427T1242, 20220501T0015, 20220504T1234, 20220509T1242, 20220516T1234, 20220528T1234 (GMT) (YYYYMMDD: HHMM)</span></span></p><p style='margin:0 0 0 0;'><span><span><br /></span></span></p><p><span style='font-weight:bold;'>Summary:</span></p><p style='margin:0 0 16 0;'><span><span>The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at the Jet Propulsion Laboratory, California Institute of Technology produced flood mapping products using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) dataset. These products provide a rapid assessment of surface water extent to support emergency response and situational awareness during flood events.</span></span></p><p style='margin:16 0 16 0;'><span><span>The dataset provided includes three products:</span></span></p><ol><li><p style='margin:16 0 0 0;'><span><span>Surface Water Extent maps on individual dates</span></span></p></li><li><p style='margin:0 0 0 0;'><span><span>Water Gain maps, showing areas where water increased between two dates</span></span></p></li><li><p style='margin:0 0 16 0;'><span><span>Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period</span></span></p></li></ol><p style='margin:16 0 16 0;'><span><span>Dates and Input Data:</span></span></p><ul><li><p style='margin:16 0 0 0;'><span><span>Pre-event image: April 22, 2022 </span></span></p></li><li><p style='margin:0 0 0 0;'><span><span>Flood images: April 27, 2022, May 01, 2022, May 05, 2022, May 16, 2022, May 28, 2022</span></span></p></li><li><p style='margin:0 0 16 0;'><span><span>Products are generated from OPERA DSWx-S1 satellite imagery and mosaicked across tiles to provide continuous coverage.</span></span></p></li></ul><p style='margin:16 0 16 0;'><span style='font-weight:bold;'><span>Product Description:</span></span></p><p style='margin:16 0 16 0;'><span><span><span>Surface water is identified from Synthetic Aperture Radar (SAR) satellite imagery and mapped at 30 m spatial resolution. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period.</span></span></span></p><p style='margin:0 0 0 0;'><span style='font-weight:bold;'><span>Caveats and Limitations:</span></span></p><p style='margin:0 0 0 0;'><span><span><span><br /></span></span></span></p><p style='margin:0 0 0 0;'><span><span><span>Detecting inundation under vegetation, in the urban perimeter, in arid environments, and along water body edges is known to be challenging. The local accuracy of the flood maps in such environments may be impacted. These results are intended to support rapid emergency response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk.</span></span></span></p><p><span style='font-weight:bold;'>Suggested Use:</span></p><p style='margin:16 0 16 0;'><span><span>The OPERA DSWx-S1 Water product classifies the Sentinel-1 (S1) input imagery into &quot;not water&quot;, &quot;open surface water&quot;, and &quot;inundated vegetation”, masks include Height Above Nearest Drainage (HAND) mask and layover/shadow mask), or no data classes.</span></span></p><p style='font-weight:bold; margin:16 0 16 0;'><span><span>Water (WTR) Layer Values:</span></span></p><p style='margin:16 0 16 0;'><span><span>File names:, OPERA_L3_DSWX-S1_V1_WTR_20220528T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220516T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220509T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220504T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220501T0015_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220427T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_mosaic.tif</span></span></p><p style='margin:16 0 16 0;'></p><ul><li><span><span>0: Not Water - an area with valid data that is not open water (class 1), inundated vegetation (class 3), height above nearest drainage masked (class 250), or layover/shadow masked (class 251) (suggested color: #ffffff)</span></span></li><li><span><span>1: Open Water - an area that is entirely water and unobstructed to the sensor, including obstructions by vegetation, terrain, and buildings. (suggested color: #0000ff)</span></span></li><li><span><span>3: Inundated vegetation - an area that is considered inundated, extracted from the high value in dual polarization ratio and the wetland class in land cover map. (suggested color: #00ff00)</span></span></li><li><span><span>250: Height Above Nearest Drainage (HAND) masked - an area where topographic height is higher than the HAND threshold (suggested color: #c8c8c8)</span></span></li><li><span><span>251: Layover/shadow masked - an area identified as layover or shadow computed from the geometry of the digital elevation model and sensor. The area is directly copied from input burst RTC-S1 products (suggested color: #808080)</span></span></li><li><span><span>255: No data (suggested color: transparent)</span></span></li></ul><p></p><p><i>Maximum Water Extent Layer Values:</i></p><p>The maximum water extent observed during the event was created by aggregating OPERA DSWx-S1 water products.</p><p style='margin:16 0 16 0;'><span><span>File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220601T0007_max_extent.tif</span></span></p><p style='margin:16 0 16 0;'></p><ul><li><span><span>0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff)</span></span></li><li><span><span>1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4)</span></span></li></ul><p></p><p><i>Water Gain Layer Values:</i></p><p>The water gain shows any location where there was a change from “not water” to “inundated vegetation”, “not water” to “open surface water”, or “inundated vegetation” to “open surface water&quot; between two OPERA DSWx-S1 products.</p><p style='margin:16 0 16 0;'><span><span>File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220504T1234_water_gain.tif</span></span></p><p style='margin:16 0 16 0;'></p><ul><li><span><span>0: No Change or Water Loss- an area that had no change (e.g., open water in both images) or water loss (e.g., open water to not water). Masked pixels are set to No data. (suggested color: #ffffff)</span></span></li><li><span><span>1: Water Gain - an area that gained water in the most recent image. This includes change from Not Water to Inundated Vegetation, Not Water to Open Water, and Inundated Vegetation to Open Water. (suggested color: #ff15e4)</span></span></li></ul><p></p><p><span style='font-weight:bold;'>Credits:</span></p><p style='margin:16 0 16 0;'><span><span>The product contains modified Copernicus Sentinel data, processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA/OPERA team. The DSWx products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory.</span></span></p><p style='margin:16 0 16 0;'><span><span>Product POCs:</span></span></p><p style='margin:16 0 16 0;'><span><span>Cole Speed (</span></span><a href='mailto:cole.speed@jpl.nasa.gov' style='text-decoration:underline;'><span style='text-decoration:underline;'><span>cole.speed@jpl.nasa.gov</span></span></a><span><span>)</span></span></p><p style='margin:16 0 16 0;'><span><span>Mary Grace Bato (</span></span><a href='mailto:bato@jpl.nasa.gov' style='text-decoration:underline;'><span style='text-decoration:underline;'><span>bato@jpl.nasa.gov</span></span></a><span><span>)</span></span></p><p style='margin:16 0 16 0;'><span><span>Emre Havazli (</span></span><a href='mailto:emre.havazli@jpl.nasa.gov' style='text-decoration:underline;'><span style='text-decoration:underline;'><span>emre.havazli@jpl.nasa.gov</span></span></a><span><span>) </span></span></p><p style='margin:16 0 16 0;'><span><span>Renato Frasson (</span></span><a href='mailto:renato.prata.de.moraes.frasson@jpl.nasa.gov' style='text-decoration:underline;'><span style='text-decoration:underline;'><span>renato.prata.de.moraes.frasson@jpl.nasa.gov</span></span></a><span><span>) </span></span></p><p style='margin:16 0 16 0;'><span><span>Alexander Handwerger (</span></span><a href='mailto:alexander.handwerger@jpl.nasa.gov' style='text-decoration:underline;'><span style='text-decoration:underline;'><span>alexander.handwerger@jpl.nasa.gov</span></span></a><span><span> )</span></span></p><p><span style='font-weight:bold;'>Esri REST Endpoint:</span></p><p><span>See URL on the right.</span></p><p><span style='font-weight:bold;'>WMS Endpoint:</span></p><p><a href='https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_s1/MapServer/WMSServer' target='_blank'>https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_s1/MapServer/WMSServer</a></p><p><span></span></p></div>

Map Name: dswx_s1

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Layers: Description: Dates of Images:20220422T1234, 20220427T1242, 20220501T0015, 20220504T1234, 20220509T1242, 20220516T1234, 20220528T1234 (GMT) (YYYYMMDD: HHMM)Summary:The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at the Jet Propulsion Laboratory, California Institute of Technology produced flood mapping products using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) dataset. These products provide a rapid assessment of surface water extent to support emergency response and situational awareness during flood events.The dataset provided includes three products:Surface Water Extent maps on individual datesWater Gain maps, showing areas where water increased between two datesMaximum Surface Water Extent maps, showing the full extent of water observed over a defined time periodDates and Input Data:Pre-event image: April 22, 2022 Flood images: April 27, 2022, May 01, 2022, May 05, 2022, May 16, 2022, May 28, 2022Products are generated from OPERA DSWx-S1 satellite imagery and mosaicked across tiles to provide continuous coverage.Product Description:Surface water is identified from Synthetic Aperture Radar (SAR) satellite imagery and mapped at 30 m spatial resolution. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period.Caveats and Limitations:Detecting inundation under vegetation, in the urban perimeter, in arid environments, and along water body edges is known to be challenging. The local accuracy of the flood maps in such environments may be impacted. These results are intended to support rapid emergency response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk.Suggested Use:The OPERA DSWx-S1 Water product classifies the Sentinel-1 (S1) input imagery into &quot;not water&quot;, &quot;open surface water&quot;, and &quot;inundated vegetation”, masks include Height Above Nearest Drainage (HAND) mask and layover/shadow mask), or no data classes.Water (WTR) Layer Values:File names:, OPERA_L3_DSWX-S1_V1_WTR_20220528T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220516T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220509T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220504T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220501T0015_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220427T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_mosaic.tif0: Not Water - an area with valid data that is not open water (class 1), inundated vegetation (class 3), height above nearest drainage masked (class 250), or layover/shadow masked (class 251) (suggested color: #ffffff)1: Open Water - an area that is entirely water and unobstructed to the sensor, including obstructions by vegetation, terrain, and buildings. (suggested color: #0000ff)3: Inundated vegetation - an area that is considered inundated, extracted from the high value in dual polarization ratio and the wetland class in land cover map. (suggested color: #00ff00)250: Height Above Nearest Drainage (HAND) masked - an area where topographic height is higher than the HAND threshold (suggested color: #c8c8c8)251: Layover/shadow masked - an area identified as layover or shadow computed from the geometry of the digital elevation model and sensor. The area is directly copied from input burst RTC-S1 products (suggested color: #808080)255: No data (suggested color: transparent)Maximum Water Extent Layer Values:The maximum water extent observed during the event was created by aggregating OPERA DSWx-S1 water products.File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220601T0007_max_extent.tif0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff)1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4)Water Gain Layer Values:The water gain shows any location where there was a change from “not water” to “inundated vegetation”, “not water” to “open surface water”, or “inundated vegetation” to “open surface water&quot; between two OPERA DSWx-S1 products.File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220504T1234_water_gain.tif0: No Change or Water Loss- an area that had no change (e.g., open water in both images) or water loss (e.g., open water to not water). Masked pixels are set to No data. (suggested color: #ffffff)1: Water Gain - an area that gained water in the most recent image. This includes change from Not Water to Inundated Vegetation, Not Water to Open Water, and Inundated Vegetation to Open Water. (suggested color: #ff15e4)Credits:The product contains modified Copernicus Sentinel data, processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA/OPERA team. The DSWx products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory.Product POCs:Cole Speed (cole.speed@jpl.nasa.gov)Mary Grace Bato (bato@jpl.nasa.gov)Emre Havazli (emre.havazli@jpl.nasa.gov) Renato Frasson (renato.prata.de.moraes.frasson@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov )Esri REST Endpoint:See URL on the right.WMS Endpoint:https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_s1/MapServer/WMSServer

Service Item Id: 18cdffa5d7ce4d8183870831a30e4b8a

Copyright Text: NASA-JPL/Caltech ARIA/OPERA team, Copernicus Sentinel Data, Landsat, NASA Disasters

Spatial Reference: 32614  (32614)  LatestVCSWkid(0)


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Initial Extent: Full Extent: Units: esriMeters

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Document Info: Supports Dynamic Layers: true

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MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

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Supports Datum Transformation: true



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