OPERA Dynamic Surface Water Extent-HLS, Confidence January 2023 - Present (Daily)

A representation of the confidence associated with the WTR classification that is based on a combination of Diagnostic Layer (DIAG) results and quality assurance information provided with the input HLS data. For example, the Open water class of the WTR layer is split into two classes: High Confidence and Moderate Confidence while WTR Partial surface water Class pixels of WTR are flagged as either Partial surface water Conservative or Partial surface water Aggressive, with the latter exhibiting less certainty. As in the WTR layers, pixels for which water retrievals are difficult or impossible due to HLS snow/ice, HLS cloud/shadow, or fill values are also noted in the CONF layer. This dataset contains Level-3 Dynamic OPERA surface water extent product version 1. The data are validated surface water extent observations beginning January 2023. Known issues and caveats on usage are described in the Product Documentation. The input dataset for generating each product is the Harmonized Landsat-8 and Sentinel-2A/B/C (HLS) product version 2.0. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B/C satellite. The surface water extent products are distributed over projected map coordinates using the Universal Transverse Mercator (UTM) projection. Each UTM tile covers an area of 109.8 km × 109.8 km. This area is divided into 3,660 rows and 3,660 columns at 30-m pixel spacing. This EGIS service offers access to the confidence data layer. More information about the dataset is available at https://www.earthdata.nasa.gov/data/catalog/pocloud-opera-l3-dswx-hls-v1-1.0 OPERA was informed by the Satellite Needs Working Group (SNWG), an interagency effort of the U.S. Government dedicated to identifying and addressing Earth observation needs across U.S. civilian federal agencies. If you have feedback on this service, please provide them via this form. For questions about this service, please contact podaac@podaac.jpl.nasa.gov For tutorials on using this service, please visit the PO.DAAC Cookbook. Disclaimer: If opening with the MapViewer in the browser, due to the size of the underlying data, it can take a few minutes for the data to render on the map. Tips: zoom into your area of interest on the map; and/or change time slider settings - see the PODAAC Cookbook tutorial. Fields objectid: The unique, internal database ID for the specific image. name: The granule/filename of the scene. minps, maxps, lowps, highps: "Pixel Spacing (ps)" metrics used by the ArcGIS server's backend to decide at what zoom levels the image should be visible on a map. category: A backend GIS tag indicating the type of raster (1 for primary data/source raster & 2 for overviews). centerx & centery: The precise center point (Longitude and Latitude) of the image footprint. shape: The geographic footprint of the image. processingdate: The date and time the image was uploaded and processed into the image service. tileid: The specific tile identifier of the product, which is also the tile ID of the input HLS product in the Military Grid Reference System (MGRS). (e.g., T11SPA or T12STF). datetime: The acquisition date and time derived from the input HLS granule name. productgenerationdatetime: The date and time at which the product was generated by OPERA. cloud_coverage: The percentage of pixels that is obscured by clouds.  spacecraft_name: The name of the sensor platform (e.g., Landsat-8, Sentinel-2A, Sentinel-2B).  downloadurl: The direct web link to download the individual data file (requires NASA Earthdata authentication). urldisplay: A secondary URL field sometimes used by web maps to generate clickable links in pop-up windows. Colormap

Overview: OPERA Level-3 Dynamic Surface Water Extent (DSWx) product from Harmonized Landsat-8/9 and Sentinel-2A/B/C (HLS), processed and developed by OPERA (JPL/USGS). Values for B01 WTR are a masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water, and partial surface water), HLS snow/ice, HLS cloud/cloud shadow and adjacent to cloud/cloud shadow, or no data classes.   This dataset contains Level-3 Dynamic OPERA surface water extent product version 1. The data are validated surface water extent observations beginning April 2023. Known issues and caveats on usage are described in the Product Documentation. The input dataset for generating each product is the Harmonized Landsat-8 and Sentinel-2A/B/C (HLS) product version 2.0. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B/C satellite. This EGIS service offers access to the water classification data layer.   More information about the dataset is available at https://www.earthdata.nasa.gov/data/catalog/pocloud-opera-l3-dswx-hls-v1-1.0 OPERA was informed by the Satellite Needs Working Group (SNWG), an interagency effort of the U.S. Government dedicated to identifying and addressing Earth observation needs across U.S. civilian federal agencies. Specifications: Temporal coverage: January 1, 2023 – Present Version: 1.0 Spatial Resolution: 3,660 rows and 3,660 columns at 30-m pixel spacing Processing Level: 3 Spatial coverage/reference: Near Global (N: 84 S: -84 E: 180 W: -180) coverage distributed over a projected map coordinate using the Universal Transverse Mercator (UTM) projection (109.8 km × 109.8 km) (EPSG:3857). Sensor: The input dataset for generating each product is the Harmonized Landsat-8 and Sentinel-2A/B/C (HLS) product version 2.0. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B/C satellite. Time interval: Daily Time standard: Coordinated Universal Time (UTC) Update frequency: Updated daily (based on ~3-day satellite acquisition latency)   Fields  objectid: The unique, internal database ID for the specific image. name: The granule/filename of the scene. minps, maxps, lowps, highps: "Pixel Spacing (ps)" metrics used by the ArcGIS server's backend to decide at what zoom levels the image should be visible on a map. category: A backend GIS tag indicating the type of raster (1 for primary data/source raster & 2 for overviews). centerx & centery: The precise center point (Longitude and Latitude) of the image footprint. shape: The geographic footprint of the image. processingdate: The date and time the image was uploaded and processed into the image service. tileid: The specific tile identifier of the product, which is also the tile ID of the input HLS product in the Military Grid Reference System (MGRS). (e.g., T11SPA or T12STF). datetime: The acquisition date and time derived from the input HLS granule name. productgenerationdatetime: The date and time at which the product was generated by OPERA. cloud_coverage: The percentage of pixels that is obscured by clouds. spacecraft_name: The name of the sensor platform (e.g., Landsat-8, Sentinel-2A, Sentinel-2B). downloadurl: The direct web link to download the individual data file (requires NASA Earthdata authentication). urldisplay: A secondary URL field sometimes used by web maps to generate clickable links in pop-up windows. Colormap: Values for the B01 WTR layer are a masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water, and partial surface water), HLS snow/ice, HLS cloud/cloud shadow and adjacent to cloud/cloud shadow, or no data classes.  Intended Use: This service provides the ability to perform temporal trend analysis, zonal statistics, and to track dynamic water volume/extent changes over time.    Limitations of Use: If opening with the MapViewer in the browser, due to the size of the underlying data, it can take a few minutes for the data to render on the map. Tips: zoom into your area of interest on the map; and/or change time slider settings - see the PODAAC Cookbook tutorial.  Known issues and caveats on usage are described in the Product Documentation. Contact: If you have feedback on this service, please provide them via this form. For questions about this service, please contact podaac@podaac.jpl.nasa.gov For tutorials on using this service, please visit the PO.DAAC Cookbook.

OPERA Level-3 Dynamic Surface Water Extent (DSWx) product from Harmonized Landsat-8/9 and Sentinel-2A/B/C (HLS), processed and developed by OPERA (JPL/USGS). Values for B01 WTR are a masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water, and partial surface water), HLS snow/ice, HLS cloud/cloud shadow and adjacent to cloud/cloud shadow, or no data classes. This dataset contains Level-3 Dynamic OPERA surface water extent product version 1. The data are validated surface water extent observations beginning April 2023. Known issues and caveats on usage are described in the Product Documentation. The input dataset for generating each product is the Harmonized Landsat-8 and Sentinel-2A/B/C (HLS) product version 2.0. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B/C satellite. The surface water extent products are distributed over projected map coordinates using the Universal Transverse Mercator (UTM) projection. Each UTM tile covers an area of 109.8 km × 109.8 km. This area is divided into 3,660 rows and 3,660 columns at 30-m pixel spacing. This EGIS service offers access to the water classification data layer. More information about the dataset is available at https://www.earthdata.nasa.gov/data/catalog/pocloud-opera-l3-dswx-hls-v1-1.0 OPERA was informed by the Satellite Needs Working Group (SNWG), an interagency effort of the U.S. Government dedicated to identifying and addressing Earth observation needs across U.S. civilian federal agencies. If you have feedback on this service, please provide them via this form. For questions about this service, please contact podaac@podaac.jpl.nasa.gov For tutorials on using this service, please visit the PO.DAAC Cookbook. Disclaimer: If opening with the MapViewer in the browser, due to the size of the underlying data, it can take a few minutes for the data to render on the map. Tips: zoom into your area of interest on the map; and/or change time slider settings - see the PODAAC Cookbook tutorial. Fields objectid: The unique, internal database ID for the specific image. name: The granule/filename of the scene. minps, maxps, lowps, highps: "Pixel Spacing (ps)" metrics used by the ArcGIS server's backend to decide at what zoom levels the image should be visible on a map. category: A backend GIS tag indicating the type of raster (1 for primary data/source raster & 2 for overviews). centerx & centery: The precise center point (Longitude and Latitude) of the image footprint. shape: The geographic footprint of the image. processingdate: The date and time the image was uploaded and processed into the image service. tileid: The specific tile identifier of the product, which is also the tile ID of the input HLS product in the Military Grid Reference System (MGRS). (e.g., T11SPA or T12STF). datetime: The acquisition date and time derived from the input HLS granule name. productgenerationdatetime: The date and time at which the product was generated by OPERA. cloud_coverage: The percentage of pixels that is obscured by clouds.  spacecraft_name: The name of the sensor platform (e.g., Landsat-8, Sentinel-2A, Sentinel-2B).  downloadurl: The direct web link to download the individual data file (requires NASA Earthdata authentication). urldisplay: A secondary URL field sometimes used by web maps to generate clickable links in pop-up windows. Colormap

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

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