OPERA Dynamic Surface Water Extent from NASA Harmonized Landsat Sentinel-2 product (DSWx-HLS) for the Alaska Floods October 2025

NOTE: The Disasters Team is currently revising the legend on this dataset. Visualization properties are not finalized. Please consult the metadata on this page for reference. Date of Images Pre-event: 2025-10-08, 2025-10-10 Co and Post-event: 2025-10-12, 2025-10-13, 2025-10-15 Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory (JPL) and the California Institute of Technology produced maps showing areas affected by flooding in western Alaska in October 2025 using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) product. The flooding was triggered by the remnants of Typhoon Halong, which brought hurricane-force winds and record-breaking storm surge to the Yukon-Kuskokwim Delta region. The event caused catastrophic damage across multiple Alaska Native coastal villages, including Kipnuk and Kwigillingok, where floodwaters swept homes from their foundations, destroyed infrastructure, and disrupted access to essential services. These maps provide an initial view of the surface water extent observed following the flood event. The results presented here are preliminary and unvalidated, intended primarily to support situational awareness and field response efforts. The ARIA-Share platform emphasizes rapid dissemination of satellite-based products for disaster response. All information is provisional and should be used under emergency response guidelines. These data are provided without warranty of any kind. Use at your own risk. OPERA DSWx-S1 The OPERA DSWx-S1 was used to identify surface water for the flooding event. The images provided are a mosaic of OPERA DSWx-S1 products, producing a composite image for each date. The mosaicking applied prioritized pixels classified as open surface water to preserve water pixels in region of product granule overlap. The images are provided as GeoTIFF files. Water (WTR) Layer Description: Masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water and inundated vegetation), masks (HAND mask and layover/shadow mask), or no data classes. Water (WTR) Layer Values: 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). Masking can result in "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) 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) Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A satellite. Resolution: 30 meters OPERA DSWx-S1 data availability The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20251012_Alaska_Floods/DSWx-S1/. The OPERA DSWx-S1 products have been in production since September 2024, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite. For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov. For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/. REST Endpoint: See URL on the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202510_FLOOD_AK/202510_opera_dswx_s1/ImageServer/WMSServer Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (mary.grace.p.bato@jpl.nasa.gov) Ines Fenni (ines.fenni@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov) Renato Frasson (renato.prata.de.moraes.frasson@jpl.nasa.gov) Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2025), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The 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. NASA JPL-Caltech ARIA/OPERA Team ==================

Dates of Images: May 24, 2026 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 provides: Surface Water Extent maps on individual dates Dates and Input Data: Flood images: May 24, 2026 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. 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_BWTR_20260524T1609_mosaic.tif, Values: 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) 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) 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 meters Temporal Resolution: Sub-weekly Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_opera_dswx_hls/MapServer/WMSServer

Dates of Images: 20180914T1609, 20180917T1553, 20180918T1549, 20180919T1540, 20180920T1539 (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 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 two products: Surface Water Extent maps on individual dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Flood images: September 14, 2018, September 17, 2018, September 18, 2018, September 19, 2018, September 20, 2018 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. 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_20180914T1609_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180917T1553_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180918T1549_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180919T1540_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180920T1539_mosaic.tif Values: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) 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) Maximum Water Extent Layer Values: File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20180830T1604_20180920T1539_max_extent.tif 0: 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 meters Temporal Resolution: Sub-weekly Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_opera_dswx_hls/MapServer/WMSServer

Date of Images Co and Post-event: 2025-10-30; 2025-11-02; 2025-11-04 Pre-event: 2025-10-15, 2025-10-17, 2025-10-18, 2025-10-20, 2025-10-23 Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory and California Institute of Technology created maps of surface water extent impacted by the flooding caused by Hurricane Melissa in Jamaica on October 28, 2025 using the OPERA Dynamic Surface Water Extent (DSWx) from NASA Harmonized Landsat Sentinel-2 (HLS) product.  The results posted here are preliminary and unvalidated results, primarily intended to aid the field response and people who wanted to have a rough first look at the inundation extent. The ARIA-share website has always focused on posting preliminary results as fast as possible for disaster 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. OPERA DSWx-HLS The OPERA DSWx-HLS was used to identify surface water for the flooding event. The images provided are a mosaic of OPERA DSWx-HLS products, producing a composite image for each date. The mosaicking applied prioritized pixels classified as open surface water to preserve water pixels in region of product granule overlap. The images are provided as GeoTIFF files.  Note: Cloud/cloud shadow and snow/ice layers are derived from HLS Fmask quality assurance (QA) data, which sometimes misclassifies sediment-rich water as snow/ice. Snow/ice pixels were reclassified to open water to capture the full innundated extent. Water (WTR) Layer Description: Masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water, and partial surface water), snow/ice, cloud/cloud shadow and adjacent to cloud/cloud shadow, ocean masked, or no data classes as a result of processing the diagnostic (DIAG) layer through all intermediate steps/layers (WTR-1, and WTR-2). Water (WTR) Layer Values: 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 “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) Binary Water (BWTR) Layer Description: The binary water layer is derived from the WTR layer as a union of water classes (open water and partial surface water) into a binary map indicating areas with and without water. This layer is meant to provide users with a quick view for  water/no-water. Invalid data classes (snow/ice, cloud/cloud shadow along with adjacent to cloud/cloud shadow, ocean masked, and fill value) are also provided to indicate areas in which the binary classification does not provide water/no-water classification. Binary Water (BWTR) Layer Values: 0: Not Water - an area with valid reflectance data that is not water (class 1) and not snow/ice (class 252), cloud/cloud shadow  (class 253), or ocean masked (class 254) (suggested color: #ffffff) 1: Water - an area classified as open water or partial surface water (suggested color: #0000ff) 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) Satellite/Sensor: Multi Spectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/B/C satellites and Operational Land Imager 2 (OLI-2) on NASA's Landsat 8 satellite. Resolution: 30 meters OPERA DSWx-HLS data availability The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20251028_Hurricane_Melissa/DSWx-HLS/. The OPERA DSWx-HLS products have been in production since April 2023, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite.  For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov.  For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/.   REST Endpoint: See the URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202510_HURRICANE_MELISSA/ARIA_DSWxHLS/MapServer/WMSServer Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (bato@jpl.nasa.gov) Ines Fenni (ines.fenni@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov) Renato Frasson (renato.prata.de.moraes.frasson@jpl.nasa.gov) Credits: HLS data was accessed through NASA EarthData Search. The product contains modified Copernicus Sentinel data (2025), processed by the European Space Agency, NASA/USGS Landsat 8/9 data, and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The 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 Jet Propulsion Laboratory. NASA JPL-Caltech ARIA/OPERA Team ================== Last Update 29 Oct 2025

Dates of Images: 20220427T1719, 20220505T1728, 20220507T1719, 20220510T1709, 20220515T1727, 20220522T1718, 20220524T1721, 20220527T1719 (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 dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates 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.tif 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) 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.tif 0: 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 meters Temporal Resolution: Sub-weekly 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 to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls/MapServer/WMSServer

Dates of Images: 20220427T1719, 20220505T1728, 20220507T1719, 20220510T1709, 20220515T1727, 20220522T1718, 20220524T1721, 20220527T1719 (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 dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates 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.tif 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) 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.tif 0: 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 meters Temporal Resolution: Sub-weekly 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 to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_hls/MapServer/WMSServer