DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx

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Service Description: <div style='text-align:Left;'>Dates of Images:20240421T1331, 20240506T1329 (GMT) (YYYYMMDDTHHMM)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 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>Water Gain maps, showing areas where water increased between two 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>Pre-event image: April 21, 2024 </li><li>Flood image: May 6, 2024 </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. 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_20240421T1331_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20240506T1329_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 inundated area that is at least 20% and less than 100% open water. This may be referred to as “subpixel inundation” when referring to a pixel’s area. Examples include wetlands, water bodies with emergent vegetation, and pixels bisected by coastlines. (suggested color: #b4d5f4)</li><li>252: Snow/Ice/Sediment Rich Water - 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>Water Gain Layer Values:The water gain shows any location where there was a change from “not water” to “partial surface water”, “not water” to “open surface water”, or “partial surface water” to “open surface water" between two OPERA DSWx-HLS products.File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20240421T1331_20240506T1329_water_gain<ul><li>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)</li><li>1: Water Gain - an area that gained water in the most recent image. This includes change from Not Water to Partial Surface Water, Not Water to Open Water, and Partial Surface Water to Open Water. (suggested color: #ff15e4)</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_20240421T1340_20240506T1329_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:Satellite/Sensor: 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 bottom right.WMS Endpoint:<a href='https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_hls/MapServer/WMSServer' target='_blank'>https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_hls/MapServer/WMSServer</a></div>

Map Name: opera_dswx_hls

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Layers:

Water Extent (0)
- Water Extent (April 21, 2024) (1)
- Water Extent (May 6, 2024) (2)
Water Gain Map (April 21, 2024-May 6, 2024) (3)
Max Extent (April 21, 2024-May 6, 2024) (4)

Description: Dates of Images:20240421T1331, 20240506T1329 (GMT) (YYYYMMDDTHHMM)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 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 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 21, 2024 Flood image: May 6, 2024 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. 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_20240421T1331_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20240506T1329_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 inundated area that is at least 20% and less than 100% open water. This may be referred to as “subpixel inundation” when referring to a pixel’s area. Examples include wetlands, water bodies with emergent vegetation, and pixels bisected by coastlines. (suggested color: #b4d5f4)252: Snow/Ice/Sediment Rich Water - 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)Water Gain Layer Values:The water gain shows any location where there was a change from “not water” to “partial surface water”, “not water” to “open surface water”, or “partial surface water” to “open surface water" between two OPERA DSWx-HLS products.File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20240421T1331_20240506T1329_water_gain0: 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 Partial Surface Water, Not Water to Open Water, and Partial Surface Water to Open Water. (suggested color: #ff15e4)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_20240421T1340_20240506T1329_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:Satellite/Sensor: 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 bottom right.WMS Endpoint:https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_hls/MapServer/WMSServer

Service Item Id: 17b115eb5e5a41ceb5aced7387f6644d

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

Spatial Reference: 32622 (32622) LatestVCSWkid(0)

Single Fused Map Cache: false

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MaxSelectionCount: 2000

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MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

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Supports Datum Transformation: true

Child Resources: Info Dynamic Layer

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DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_hls (MapServer)