United States of America water data
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Data from the FEMA National Flood Hazard Layer (NFHL) https://www.fema.gov/flood-maps/national-flood-hazard-layer
FLOOD HAZARD INFORMATION - FEDERAL EMERGENCY MANAGEMENT AGENCY
Date of Images: Syn-Event: 2024-09-26 23:38:04 (UTC) or 7:38 PM EDT Pre-Event: 2024-09-14 23:37:54 (UTC) or 7:38 PM EDT 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 derived the surface water extent maps using the OPERA Dynamic Surface Water eXtent from Sentinel-1 (DSWx-S1) products. The results posted here are preliminary and unvalidated results, primarily intended to aid the field response and people who want to have a rough first look at the water extent. The ARIA-share website has always focused on posting preliminary results as fast as possible for disaster response. OPERA DSWx-S1 The OPERA DSWx-S1 data identifies surface water and inundated vegetation. We provide the Water (WTR) and the Binary Water (BWTR) layers. Images are provided from 1) September 14, 2024 and 2) September 26, 2024. Each image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file. ARIA/OPERA water change map derived from OPERA DSWx-S1 The ARIA/OPERA water change map is derived from two OPERA DSWx-S1 Binary Water (BWTR) images taken on September 14, 2024 and September 26, 2024. The BTWR combines inundated vegetation and open water into a single water class.These maps depict areas of new water detection (or loss). The change map includes values of: (0) indicate no change between images, (1) absence of water pre-event, presence of water syn-event, and (-1) presence of water pre-event, absence of water syn-event. Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A satellite was used for both the September 14 and September 26 images. Resolution: 30 meters The DSWx-S1 products have these flags: 250 (light gray) and 251 (dark gray) represent HAND and layover/shadow masks, respectively. HAND mask (light gray, value 250) delineates regions where the terrain's elevation exceeds a specified threshold relative to the height above the nearest drainage point, indicating areas less likely to be subject to direct inundation. Layover/shadow mask (dark gray, value 251) identifies zones that are either occluded by topographic features taller than the surrounding landscape (layover) or are not illuminated by the radar signal due to obstruction by these elevated features (shadow), leading to potential data voids in SAR imagery. OPERA DSWx-S1 data availability The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20240926-Hurricane_Helene/DSWx/. 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 OPERA project and other products, visit https://www.jpl.nasa.gov/go/opera. 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/ Suggested Use DSWx-S1 The OPERA DSWx-S1 products classifies the OPERA Radiometric Terrain Corrected SAR backscatter from Sentinel-1 (RTC-S1) input imagery into: not water, water, and inundated vegetation with the masks such as layover/shadow mask and HAND mask. The WTR layer includes all classes. The BWTR layer merges water and inundated vegetation into a single water layer. Open water and inundated vegetation are represented in blue and green in WTR and blue in BWTR. Areas with masks are gray. The masks include the layover/shadow mask and HAND mask. Areas with no water detected are transparent. DSWx-S1 change map The ARIA/OPERA water extent change map classifies water extent into change/no change. Increased in water represented in blue, no change in water represented in transparent, decrease in water represented in red. RTC-S1 OPERA Radiometric Terrain Corrected SAR backscatter from Sentinel-1 (RTC-S1) image was converted to a false color image. In this color scale, vegetated areas appear green, urban areas appear white/pink, calm water appears black, and rough water appears purple or magenta.” Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2024), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. NASA JPL-Caltech ARIA/OPERA Team ================== Files: 20240914_DSWx-S1_BWTR.tif: The September 14, 2024 binary water map is derived from the WTR layer as a union of water classes (open water and inundated vegetation) into a binary map indicating areas with and without water. 20240926_DSWx-S1_BWTR.tif: The September 26, 2024 binary water map. 20240926_DSWx-S1_WTR.tif: 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. OPERA_DSWx-S1_BWTR_ChngMap_20240926-20240914_v2.tif: The ARIA/OPERA flood change map is derived from two OPERA DSWx-HLS images taken on September 14, 2024 and September 26, 2024. These maps depict areas of new water detection that is interpreted as flood. Track121_Florida_DSWx-S1-overview.png: An overview of the 20240926_DSWx-S1_WTR product with a satellite image background. These files have the same GeoTIFF format as the OPERA DSWx-S1 images described above and are in the UTM Zone 16N.
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The layers in this web service depict ecosystem services at the census block group level for all EnviroAtlas communities. These layers illustrate the ecosystems and natural resources that are associated with clean air, clean and plentiful water, natural hazard mitigation, climate stabilization, recreation, culture, and aesthetics, and biodiversity conservation, and factors that place stress on those resources. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Date of Images: 5/5/2024 Date of Next Image: Unknown Summary: The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted by the event. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space and may show damage caused by severe weather. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. The Short Wave Infrared (SWIR) RGB is a product that can provides value in flood detection. Areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta, snow will appear as a bright blue/cyan, and bare soils being multicolor dependent on their makeup. Compare pre-event imagery to post-event imagery to identify potential flooding. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: True Color RGB: 10 meters Color Infrared RGB: 10 meters Shortwave Infrared RGB: 20 meters Credits: NASA/MSFC, USGS, ESA Copernicus Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=34b74048c81c437bb316969d639adad8 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_TX/2408_sentinel2/ImageServer/WMSServer
geoconnex.us reference dams linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
NPDES Facilities that Discharge to Water linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
geoconnex.us reference gages linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The EnviroAtlas Potentially Restorable Wetlands on Agricultural Land (PRW-Ag) dataset shows potentially restorable wetlands at 30-meter resolution. Beginning two centuries ago, many wetlands were turned into farm fields or urban areas, yet wetlands play an important role in removing water pollution, regulating water storage and flows, and providing habitat for wildlife. Wetland restoration could help restore these benefits. Potentially restorable wetlands, as developed for this map, are lands currently in agriculture that naturally accumulate water due to topography and have historically had poorly or very poorly draining soils. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
HUC12 Pour Points NHDPlusV2 linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
This map service was created to support the National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management’s (OCM) Coastal Flood Exposure Mapper. The purpose of the online mapping tool is to provide coastal managers, planners, and stakeholders a preliminary look at exposures to coastal flooding hazards. The Mapper is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help communities initiate resilience planning efforts. Currently the extent of this map service and the Coastal Flood Exposure Mapper is limited to U.S. coastal counties along the Gulf of Mexico and Atlantic Ocean. The purpose of this map service is to depict high-risk V zones and A zones (1% annual chance, or 100-year floodplain) and moderate-risk shaded X zones (0.2% annual chance, or 500-year floodplain) designated by the Federal Emergency Management Agency (FEMA). Data in this map service represent a composite of best available National Flood Hazard Layer (NFHL) and digital Q3 data, as of October 2018. Visit FEMA’s Map Service Center to access NFHL products. This is a cached map service. Tiles have been cached down to Level ID 15 (1:18,055). The dataset should be used only as a screening-level tool for management decisions. As with all remotely sensed data, all features should be verified with a site visit. The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes. For more information, visit the Coastal Flood Exposure Mapper (https://coast.noaa.gov/floodexposure). Send questions or comments to the NOAA Office for Coastal Management (coastal.info@noaa.gov).
NHDPlus comid linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Selected GRAND Reservoirs linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Date of Images Post-event: 2026-06-21 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 Louisiana using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) product. 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) and Binary Water (BWTR) 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. 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 (2026), 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: Post-Event: 5/24/2022 Pre-Event: 5/16/2022 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_landsat_mndwi/ImageServer/WMSServer
Date of Images: Pre-Landfall: HLS: 9/27/2024 - 10/7/2024 Sentinel-1: 10/3/2024, 10/8/2024 Post-Landfall: Sentinel-1: 10/10/2024, 10/11/2024 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 derived the surface water extent maps from the OPERA Dynamic Surface Water Extent (DSWx) from NASA Harmonized Landsat Sentinel-2 (HLS) and Sentinel-1 (DSWx-S1) products. 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. OPERA DSWx-S1 The OPERA DSWx-S1 data identifies surface water and inundated vegetation. We provide the Water (WTR) layers. Images are provided from 1) October 3, 2024, 2) October 8, 2024, 3) October 10, 2024, and 4) October 11, 2024. Each image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file. ARIA/OPERA water change map derived from OPERA DSWx-S1 The ARIA/OPERA water change map is derived from two OPERA DSWx-S1 Binary Water (BWTR) images. Change maps are made for images taken on October 3, 2024 and October 11, 2024 and for October 8, 2024, and October 11, 2024. The BWTR combines inundated vegetation and open water into a single water class. These maps depict areas of new water detection (or loss). The change map includes values of: (0) indicate no change between images, (1) absence of water pre-event, presence of water during-event, and (-1) presence of water pre-event, absence of water during-event. OPERA DSWx-HLS The OPERA DSWx-HLS was used to identify surface water using the WTR layer. 378 images were examined from 2024-09-27 to 2024-10-07, prioritizing pixels classified as open surface water. Pixels flagged as snow/ice in the HLS Fmask were reclassified to water. The mosaic image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file. Suggested Use: OPERA DSWx-S1 The OPERA DSWx-S1 products classifies the OPERA Radiometric Terrain Corrected SAR backscatter from Sentinel-1 (RTC-S1) input imagery into: not water, water, and inundated vegetation with the masks such as layover/shadow mask and HAND mask. The WTR layer includes all classes. Open water and inundated vegetation are represented in blue and green in WTR. Areas with masks are gray. The masks include the layover/shadow mask and HAND mask. Areas with no water detected are transparent. Transparent: Not Water Blue: Water Green: Inundated Vegetation Gray: Layover/Shadow/Hand Masks ARIA/OPERA water change map derived from OPERA DSWx-S1 The ARIA/OPERA water extent change map classifies water extent into change/no change. Transparent (0): No Change Red (1): increased water extent Gray (-1): decreased water extent OPERA DSWx-HLS-WTR 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. Transparent (0): No Water Blue (1): Open Water Light Blue (2): Partial Surface Water Gray (253): HLS Cloud/Cloud Shadow This layer is meant to provide users with a quick view for water/no-water. Invalid data classes (snow/ice and cloud/cloud shadow along with adjacent to cloud/cloud shadow) are also provided to indicate areas in which the water classification does not provide water/no-water classification. Note: Sediment rich water is sometimes misclassified as snow/ice by the HLS Fmask. As such, we have reclassified any of the snow/ice pixels to water for these images. For more information about how the OPERA DSWx-HLS Water product classifies data: https://d2pn8kiwq2w21t.cloudfront.net/documents/ProductSpec_DSWX_URS309746.pdf Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A satellite Harmonized Landsat Sentinel-2 (HLS): MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites and Operational Land Imager (OLI) on the NASA/USGS Landsat 8 satellite Resolution: 30 meters The DSWx-S1 products have these flags: 250 (light gray) and 251 (dark gray) represent HAND and layover/shadow masks, respectively. HAND mask (light gray, value 250) delineates regions where the terrain's elevation exceeds a specified threshold relative to the height above the nearest drainage point, indicating areas less likely to be subject to direct inundation. Layover/shadow mask (dark gray, value 251) identifies zones that are either occluded by topographic features taller than the surrounding landscape (layover) or are not illuminated by the radar signal due to obstruction by these elevated features (shadow), leading to potential data voids in SAR imagery. Credits: NASA JPL-Caltech ARIA/OPERA Team Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2024), 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. HLS data was accessed through NASA EarthData Search. The product contains modified Copernicus Sentinel data (2024), processed by the European Space Agency, NASA/USGS Landsat 8 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's Jet Propulsion Laboratory. The OPERA DSWx 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. Data Download: https://aria-share.jpl.nasa.gov/20241010-Hurricane_Milton/DSWx/ Esri REST Endpoint:
Date of Images: June 23, 2025; June 26, 2025; June 28, 2025 Date of Next Image: Unknown 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 in a region of eastern/central New Mexico impacted by floods between June 20-28, 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 three distinct dates (June 23, 2025; June 26, 2025; June 28, 2025) during a period of flooding in eastern and central New Mexico. The images provided are a mosaic of OPERA DSWx-HLS products from 9 individual granules, 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. Suggested Use: 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 8/9 satellite. Resolution: 30 meters OPERA DSWx-HLS data availability: The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20250630_NewMexico_Floods/. 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/. Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (mary.grace.p.bato@jpl.nasa.gov) Alexander L. Handwerger (alexander.handwerger@jpl.nasa.gov) Steven Chan (steventsz.k.chan@jpl.nasa.gov) David Bekaert (david.bekaert@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's Jet Propulsion Laboratory. NASA JPL-Caltech ARIA/OPERA Team ================== Service URL: WMS Endpoint: Data Download: OPERA_DSWx-HLS_V1_BWTR_2025-06-23.tif: DSWx-HLS mosaic image of binary water classification layer (BWTR) from data acquired on June 23, 2025. OPERA_DSWx-HLS_V1_BWTR_2025-06-26.tif: DSWx-HLS mosaic image of binary water classification layer (BWTR) from data acquired on June 26, 2025. OPERA_DSWx-HLS_V1_BWTR_2025-06-28.tif: DSWx-HLS mosaic image of binary water classification layer (BWTR) from data acquired on June 28, 2025. Last Update 30 June 2025
2020 Census Block - NHDPlusV2 Catchment Intersections linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
EPA National Rivers and Streams Assessment linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Vigil Network Data linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Water Quality Portal linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (http://EnviroAtlas.epa.gov). The EnviroAtlas Potential Wetland Areas (PWA) dataset shows potential wetland areas at 30-meter resolution. Beginning two centuries ago, many wetlands were turned into farm fields or urban areas, yet wetlands play an important role in removing water pollution, regulating water storage and flows, and providing habitat for wildlife. Wetland restoration could help restore these benefits. Potential wetland areas, as developed for this map, are lands that naturally accumulate water due to topography and have historically had poorly or very poorly draining soils. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
The FEMA National Flood Hazard Layer (NFHL), published by FEMA.
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This web service includes layers depicting NHD Plus Version 2 hydrologic unit boundaries and labels at the Subregion (HUC-4), Subbasin (HUC-8), and Subwatershed (HUC-12) levels. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This web service includes layers depicting NHD Plus Version 2 hydrologic unit boundaries and labels at the Subregion (HUC-4), Subbasin (HUC-8), and Subwatershed (HUC-12) levels. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This web service includes layers depicting NHD Plus Version 2 hydrologic unit boundaries and labels at the Subregion (HUC-4), Subbasin (HUC-8), and Subwatershed (HUC-12) levels. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This web service includes layers depicting NHD Plus Version 2 hydrologic unit boundaries and labels at the Subregion (HUC-4), Subbasin (HUC-8), and Subwatershed (HUC-12) levels. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This web service includes layers depicting NHD Plus Version 2 hydrologic unit boundaries and labels at the Subregion (HUC-4), Subbasin (HUC-8), and Subwatershed (HUC-12) levels. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
USGS Geospatial Fabric V1.1 Points of Interest linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
HUC12 Pour Points circa 10-2020 linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.
Primary ambient monitoring stations have ongoing water quality monitoring that oftentime extend for decades, making these stations ideal for studying water quality trends over time. The contributing basins are necessary to determine yields and understand land cover and uses that impact water quality. Contributing basins were derived using the StreamStats (USGS, 2017) web application . These data also include nutrient (total nitrogen and total phosphorus) loads and yields data for the basins included in the study, Nutrient Loads and Yields in Kentucky: 2005-2017, and the Update to the 2019 Nutrient Loads and Yields in Kentucky Study, with a study period of 2005-2019.
Rasters/PotentialWetlandAreasOnCropland
Date of Image(s): Post-Event: April 7,2025; April 8, 2025 Date of Next Image: Unknown Summary: This is an experimental product. Some areas are affected by cloud cover. Water maps use a beta PlanetScope Flood Mapping system created in partnership between NASA GSFC and the Dartmouth Flood Observatory at the University of Colorado. This product distinguishes water covered pixels from non-water covered pixels, using an adaptive NDWI dynamic thresholding approach. Details are in a pending publication. Processed water map raster data include clouds (1), areas not covered by water (2), and water (3). Suggested Use: This product shows water that is detected by the sensor with different colors indicating different land cover/land use classifications Satellite/Sensor: PlanetScope. This product includes copyrighted material of Planet Labs PBC. All rights reserved. Resolution: 3 meters Credits: NASA Disasters Program, Dartmouth Flood Observatory at the University of Colorado, NASA GSFC. NASA-GSFC Principle Investigator (PI): Frederick Policelli PlanetScope: Includes copyrighted material of Planet Labs PBC. All rights reserved. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=7bdfbe8aec794a59ba94d079cd97188c WMS: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202504_SEVEREWX_SOUTHEASTUS/2505_planet_water/ImageServer/WMSServer
Dates of Images: Post-Event: 5/24/2022 Pre-Event: 5/16/2022 Summary: True Color: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Color Infrared: The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted from the fires. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Suggested Use: True Color: provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. Color Infrared: depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page
Water Data Exchange Water Rights linked to the NHDPlus river network through the USGS Network-Linked Data Index (NLDI), which navigates upstream and downstream along rivers to find connected monitoring sites, basins and features.