202511_opera_dswx_hls

Date of Images Co and Post-event: 2025-10-30; 2025-11-02 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