DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx

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Service Description: <div style='text-align:Left;'>Dates of Images:20220427T1719, 20220505T1728, 20220507T1719, 20220510T1709, 20220515T1727, 20220522T1718, 20220524T1721, 20220527T1719 (GMT) (YYYYMMDDTHHMM) SummaryThe 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 Harmonized Landsat Sentinel-2 (DSWx-HLS) 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:<ol><li>Surface Water Extent maps on individual dates</li><li>Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period</li></ol>Dates and Input Data:<ul><li>Flood images: April 27, 2022, May 05, 2022, May 07, 2022, May 10, 2022, May 15, 2022, May 22, 2022, May 24, 2022, May 27, 2022 </li><li>Products are generated from OPERA DSWx-HLS satellite imagery and mosaicked across tiles to provide continuous coverage.</li></ul>Product Description:Surface water is identified from optical satellite imagery and mapped at 30 m spatial resolution. Water Gain maps highlight newly inundated areas by comparing pre- and flood-event conditions. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period.Caveats and Limitations:We note the HLS snow/ice mask often misclassifies sediment rich water as snow/ice. 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. The OPERA DSWx-HLS product from 27 April 2022 was likely impacted by unmitigated aerosol effects on the western edge of the image, potentially causing false detections limited to approximately 10 km measured from the western edge into the image. The granule is provided but caution should be taken when interpreting the affected area.Suggested Use:The OPERA DSWx-HLS Water product classifies the Harmonized Landsat Sentinel-2 (HLS) input imagery into "not water", "open surface water", and “partial surface water”. The "HLS cloud/cloud shadow" and "HLS snow/ice" layers are direct inputs from the HLS Fmask.Water (WTR) Layer Values:File names: OPERA_L3_DSWX-HLS_V1_WTR_20220427T1719_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220505T1728_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220507T1719_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220510T1709_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220515T1727_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220522T1718_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220524T1721_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220527T1719_mosaic.tif<ul><li>0: Not Water - an area with valid reflectance data that is not open water (class 1), partial surface water (class 2), snow/ice (class 252), cloud/cloud shadow (class 253), or ocean masked (class 254). Masking can result in a not water (class 0) where land cover masking is applied. (suggested color: #ffffff)</li><li>1: Open Water - an area that is entirely water and unobstructed to the sensor, including obstructions by vegetation, terrain, and buildings. (suggested color: #0000ff)</li><li>2: Partial Surface Water - 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: #b4d5f4)</li><li>252: Snow/Ice - an area identified as snow/ice according to input HLS Fmask quality assurance (QA) data (suggested color: #00ffff)</li><li>253: Cloud/Cloud Shadow - an area identified as cloud or cloud shadow or adjacent to cloud/cloud shadow according to input HLS Fmask quality assurance (QA) data (suggested color: #afafaf)</li><li>254: Ocean Masked - an area identified as ocean using a shoreline database with an added margin (suggested color: #00007f)</li><li>255: No data (suggested color: transparent)</li></ul>Maximum Water Extent Layer Values:The maximum water extent observed during the event was created by aggregating OPERA DSWx-HLS water products.. File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20220505T1728_20220527T1719_max_extent.tif<ul><li>0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff)</li><li>1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4)</li></ul>Satellite/Sensor/Resolution:Harmonized Landsat Sentinel-2 (HLS) derived from MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B/2C satellites and Operational Land Imager 2 (OLI-2) on NASA/USGS Landsat 8/9 satellites.Spatial Resolution: 30 metersTemporal Resolution: Sub-weeklyCredits: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 (<a href='mailto:cole.speed@jpl.nasa.gov' style='text-decoration:underline;'>cole.speed@jpl.nasa.gov</a>)Mary Grace Bato (<a href='mailto:bato@jpl.nasa.gov' style='text-decoration:underline;'>bato@jpl.nasa.gov</a>)Emre Havazli (<a href='mailto:emre.havazli@jpl.nasa.gov' style='text-decoration:underline;'>emre.havazli@jpl.nasa.gov</a>) Renato Frasson (<a href='mailto:renato.prata.de.moraes.frasson@jpl.nasa.gov' style='text-decoration:underline;'>renato.prata.de.moraes.frasson@jpl.nasa.gov</a>) Alexander Handwerger (<a href='mailto:alexander.handwerger@jpl.nasa.gov' style='text-decoration:underline;'>alexander.handwerger@jpl.nasa.gov</a> )Esri REST Endpoint: See URL to the right. WMS Endpoint: <a href='https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls/MapServer/WMSServer' target='_blank'>https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls/MapServer/WMSServer</a></div>

Map Name: dswx-hls

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Description: Dates of Images:20220427T1719, 20220505T1728, 20220507T1719, 20220510T1709, 20220515T1727, 20220522T1718, 20220524T1721, 20220527T1719 (GMT) (YYYYMMDDTHHMM)SummaryThe 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 Harmonized Landsat Sentinel-2 (DSWx-HLS) 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 datesMaximum Surface Water Extent maps, showing the full extent of water observed over a defined time periodDates and Input Data:Flood images: April 27, 2022, May 05, 2022, May 07, 2022, May 10, 2022, May 15, 2022, May 22, 2022, May 24, 2022, May 27, 2022 Products are generated from OPERA DSWx-HLS satellite imagery and mosaicked across tiles to provide continuous coverage.Product Description:Surface water is identified from optical satellite imagery and mapped at 30 m spatial resolution. Water Gain maps highlight newly inundated areas by comparing pre- and flood-event conditions. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period.Caveats and Limitations:We note the HLS snow/ice mask often misclassifies sediment rich water as snow/ice. 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. The OPERA DSWx-HLS product from 27 April 2022 was likely impacted by unmitigated aerosol effects on the western edge of the image, potentially causing false detections limited to approximately 10 km measured from the western edge into the image. The granule is provided but caution should be taken when interpreting the affected area.Suggested Use:The OPERA DSWx-HLS Water product classifies the Harmonized Landsat Sentinel-2 (HLS) input imagery into "not water", "open surface water", and “partial surface water”. The "HLS cloud/cloud shadow" and "HLS snow/ice" layers are direct inputs from the HLS Fmask.Water (WTR) Layer Values:File names: OPERA_L3_DSWX-HLS_V1_WTR_20220427T1719_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220505T1728_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220507T1719_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220510T1709_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220515T1727_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220522T1718_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220524T1721_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20220527T1719_mosaic.tif0: Not Water - an area with valid reflectance data that is not open water (class 1), partial surface water (class 2), snow/ice (class 252), cloud/cloud shadow (class 253), or ocean masked (class 254). Masking can result in a not water (class 0) where land cover masking is applied. (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)2: Partial Surface Water - 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: #b4d5f4)252: Snow/Ice - an area identified as snow/ice according to input HLS Fmask quality assurance (QA) data (suggested color: #00ffff)253: Cloud/Cloud Shadow - an area identified as cloud or cloud shadow or adjacent to cloud/cloud shadow according to input HLS Fmask quality assurance (QA) data (suggested color: #afafaf)254: Ocean Masked - an area identified as ocean using a shoreline database with an added margin (suggested color: #00007f)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-HLS water products.. File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20220505T1728_20220527T1719_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)Satellite/Sensor/Resolution:Harmonized Landsat Sentinel-2 (HLS) derived from MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B/2C satellites and Operational Land Imager 2 (OLI-2) on NASA/USGS Landsat 8/9 satellites.Spatial Resolution: 30 metersTemporal Resolution: Sub-weeklyCredits: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 to the right.WMS Endpoint:https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls/MapServer/WMSServer

Service Item Id: 59d435680999437a91ac1d7eff7ddeef

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

Spatial Reference: 4326 (4326) LatestVCSWkid(0)

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DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls (MapServer)