We present a preliminary point inventory of landslides triggered by Hurricane Helene, which impacted southern Appalachia between September 25–27, 2024. This inventory is a result of a rapid response mapping effort led by the U.S. Geological Survey’s Landslide Assessments, Situational Awareness, and Event Response Research (LASER) project. LASER collaborated with state surveys and landslide researchers to identify landslides and their impacts for situational awareness and emergency response. The area of interest (AOI) for this effort was informed by a preliminary landslide hazard map created for the event (Martinez et al., 2024), and encompasses western North Carolina as well as parts of Tennessee, Virginia, Georgia, and South Carolina. This point inventory contains the following attributes: ‘Source’ and ‘Impact’. The ‘Source’ attribute identifies the data source(s) used to map each landslide. Note that the data sources listed in this attribute refer only to those used for mapping a given landslide; this does not imply that the landslide is absent or undocumented in other unlisted sources. We do not provide any specific information or metadata (e.g., footprint ID, imagery date, hyperlinks, etc.) for the listed source(s) used to map a landslide. The sources used for mapping landslides in this inventory are listed in Table 1. We relied heavily on Sentinel-2 satellite data during the mapping phase and exclusively during the review phase. While Sentinel-2 has a lower spatial resolution (10m) compared to other satellite and aerial sources (ranging from 0.15 to 3m), it is the only dataset with complete mapping AOI coverage and pre- and post-event multi-spectral imagery. The primary Sentinel-2 images used were acquired on August 26, 2024, and September 22, 2024 (pre-event), as well as October 2, 5, 7, 10, and 12, 2024 (post-event). To assist in rapid landslide detection, we derived Normalized Difference Vegetation Index (NDVI) change products using various combinations of the pre- and post-event Sentinel-2 data. NDVI change analysis was instrumental in identifying areas where vegetation loss or damage occurred, thus helping to pinpoint potential landslide activity in this heavily vegetated region. Additionally, red-green-blue (RGB) composite imagery from both pre- and post-event acquisitions was used to validate that NDVI changes were indeed indicative of landslides. Details on these data sources and analysis methods area can be found in Burgi et al. (2024). The data sources listed in the ‘Source’ attribute listed in alphabetical order. The ‘Impact’ attribute indicates the primary impact of a landslide. The options for the impact attribute are listed in Table 2. A landslide is deemed to have an impact if it appears to intersect with river(s) (including streams and creeks), road(s), building(s), or other human-modified land or infrastructure (e.g., bridges, railroads, powerlines, trails, agricultural fields, lawns, etc.) Impact was determined to the best of a mapper’s ability with the available data and at the time that the imagery was acquired. Many landslides had multiple impacts; however, in most cases, a primary impact could be identified. For example, many landslides appeared to severely impact a road and continue to fail into a nearby river, with no visible impact on the river. In this case, the primary impact would be “road”. If a landslide appeared to have multiple and equally significant impacts, it was classified as “various”. We do not report the number of impacts; for example, a landslide with a “building” Impact may have impacted more than one building. Emergency response landslide mapping efforts took place between September 28 to October 23, 2024. All landslides were mapped with a single point, irrespective of size or impact. Given the urgency of providing situational awareness for emergency response, landslide points were placed at the location of greatest visible impact, such as buildings, roads, and rivers, rather than at the headscarp. In cases where there was no visible impact, the landslide point was placed at the headscarp. Following the emergency mapping phase, all points underwent a basic review process to refine attributes, remove duplicate/low confidence points, add points for multi-source failures that coalesced into a single failure, and, where possible, adjust point locations from impact zones to the landslide headscarp(s). Reviewers utilized only Sentinel-2 NDVI and RGB imagery (pre- and post-event) for reference during the review process, relying most heavily on the 9/22 pre-event and 10/12 post-event products. Impactful landslides that are not clearly visible in the Sentinel-2 data (likely mapped using higher resolution data) were not repositioned to a headscarp and may remain at the impact location. Due to the rapid and extensive nature of this mapping effort, a formal and systematic assessment of the positional accuracy of the mapped points has not yet been conducted. As a result, there may be some degree of uncertainty in the location and classification of landslides within this inventory. We estimate our accuracy of most landslide headscarp points to be within tens of meters of their correct location. However, in some cases, dense vegetation and imaging geometry may obscure the true headscarp location, further decreasing the accuracy of some mapped landslide points. Furthermore, field or high-resolution validation was not possible for every landslide, therefore some mapped points may not correspond to actual landslide events. In particular, distinguishing landslides from severe tree blowdowns or areas of recently human-modified land cover (e.g., clearcutting or construction activities) sometimes proved challenging. It is possible that a small number of points mistakenly represent these features instead of genuine landslides. Finally, it is important to note that this inventory is preliminary and does not capture the full extent of landslides triggered by Hurricane Helene. Factors such as the rapid response nature of the mapping effort, limitations in imagery resolution, and dense forest canopy that obstructed the overhead (i.e., aerial and satellite) view of smaller or non-catastrophic landslides may contribute to underrepresentation of the total landslide count. References Burgi, P.M., Collins, E.A., Allstadt, K.E., Einbund, M.M., 2024, Normalized Difference Vegetation Index (NDVI) Change Map between 9/22/2024 and 10/12/2024, Southern Appalachian Mountains: 2024 USGS provisional data release. https://doi.org/10.5066/P14KDUKK Martinez, S.N., Stanley, T., Allstadt, K.E., Baxstrom, K.W., Mirus, B.B., Einbund, M.M., Bedinger, E.C., 2024, Preliminary Landslide Hazard Models for the 2024 Hurricane Helene Landslide Emergency Response: 2024 USGS Provisional Data Release. https://doi.org/10.5066/P134ERB9

This map displays Hurricane Helene 2024 estimated rainfall totals for FEMA region 4.NOTE: The data provided are preliminary. They are subject to updates and corrections as appropriate.The National Hurricane Center is responsible for conducting the official post-analysis of all tropical cyclones. Once compiled, the Tropical Cyclone Report is posted here: https://www.nhc.noaa.gov/data/tcr/index.php . For current official data and information, go to weather.gov.

Preliminary water levels taken from Post Tropical Cyclone reports issued by Florida WFOs. All data is considered preliminary and may contain errors/unofficial observations.

This dataset supports the analysis conducted in the study "Did Official Flood Maps Work in Hurricane Helene? Systematic Evaluation of Official Flood Maps with Ground-truth Observations." It includes: (1) camera-based ground-truth flood extent data from Hurricane Helene in Pinellas County, Florida; (2) official flood maps from FEMA, FDEM, and Fathom; (3) population exposure and flood map performance metrics at the census block group level; (4) auxiliary datasets such as land cover and high-resolution population grids; and (5) Python scripts for calculating the Social Vulnerability Index (SoVI). The data enable spatial validation of flood risk models and investigation of socio-spatial disparities in flood map accuracy.

Aerial imagery was acquired following Hurricane Helene. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired using a Digital Sensor System (DSS) version 6.

Date of Images:Syn-Event: 2024-09-26 23:38:04 (UTC) or 7:38 PM EDTPre-Event: 2024-09-14 23:37:54 (UTC) or 7:38 PM EDTSummary: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-S1The 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-S1The 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 metersThe 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 availabilityThe 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-suiteFor more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.govFor more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/Suggested UseDSWx-S1The 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 mapThe 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-S1OPERA 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.

The Experimental Binary NDVI change product is highlighting areas that experienced change (of any kind) since the pre-event Copernicus Sentinel-2 pass (22 September 2024) used in the analysis. The product is further filters to reduce noise and focus the identification on the more pronounced areas of change in an effort to identify areas that may have experienced damage during Hurricane Helene's passage and associated water and wind impacts. Usage: This binary mask layer is designed to overlaid with post event imagery (pre if it is available as well). The True color imagery or the Color IR RGB should be used to orient the user to areas that match the type of change being investigated. Color IR RGB uses infrared channels to isolate areas of high vegetation (and greenness) in red from areas that are not, such as cities, rivers, which will appear in shades of green/teal. Clouds are white while cloud shadows tend to be black (or close to it) Caveats: The include cloud mask is not capturing all of the clouds and is causing some areas to be falsely identified as change in the product. This is why it is recommended to use the product with the True Color and Color Infrared RGB. Some areas of open water were flagged as change and this is most likely due to changes of sediment and debris in these open water areas. Many areas of changed were flagged within areas of rugged terrain. Some of these area are actual changed as result of damaging winds and water. Others may be related to clouds and cloud shadows. Using the this product with the RGB imagery should be help support interpretation. Satellite/Sensor:Copernicus Sentinel-2 Resolution:10 metersEsri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/hurricane_helene_2024/Experimental_Binary_NDVI_Change_Product/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/NDVIchange/

Date of Image:Pre-Event: August 2024Post-Event: October 1, 2024, October 3, 2024, October 6, 2024, October 10, 2024Summary:These Black Marble High-Definition (BMHD) images were created by the NASA Black Marble Science team, with directed funding the NASA-Google Partnership program. The images map the impact of Hurricane Helene on electric grids. The baseline image is from August 2024, a cloud-free, moon-free composite, and the “after" image is from October 1-October 10. There is a layer to display where clouds are present in the "after" images. This comparison between the images is meant as a visual assessment of outage impacts from the extreme heat to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery.Suggested Use:NOTE: Black Marble HD images are downscaled from NASA’s Black Marble nighttime lights product (VNP46), and as such are a “modelled” or “best guess” estimate of how lights are distributed at a 30m resolution. These images should be used for visualization purposes, not for quantitative analysis.The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights.Satellite/Sensor:The primary data source, NASA’s Black Marble nighttime lights product suite (VNP46), utilized to generate this product is derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP) along with high resolution base layers - Landsat derived normalized index products (NDVI and NDWI) and OpenStreetMap (OSM) derived road layerResolution:Scaled resolution of 30 metersCredits:NASA Black Marble Science teamPlease cite the following two references when using this dataRomán MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883.Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43.Point of Contact:Ranjay ShresthaNASA Goddard Space Flight CenterE-mail: ranjay.m.shrestha@nasa.govAdditional Links:NASA’s Black Marble Product SuiteRomán, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6).Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143.Esri REST Endpoint:See URL section on right side of page.WMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/hurricane_helene_2024/Black_Marble_High_Definition_Hurricane_Helene_2024/MapServer/WMSServer

Date of Image:9/28/2024, 10/3/2024, 10/5/2024, 10/10/2024, 10/15/2024, 10/17/2024Date of Next Image:UnknownSummary:NASA used a Sentinel-1 SAR backscatter change approach developed in GEE (Handwerger et al., 2022) to detect areas with high landslide density. This approach detects potential landslides by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach. False positives such as backscatter change due to flooding, agriculture, and more, are removed by using threshold-based masks made from the topographic slope from the 1 arcsec (∼30 m) resolution NASADEM (NASA JPL, 2020). Using stacks of SAR data reduces noise, and furthermore, the pre-event stack provides backscatter data that is more representative of the pre-event ground surface properties. Finally, to detect landslide areas, the backscatter change raster was thresholded using the 99th percentile to highlight strong signals, and the heatmap was calculated.Pre-event time frame: 2024-01-10 to 2024-09-26Post-event time frame: 2024-09-28 to 2024-10-17This map should be used as a guidance to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual corrections to remove false positives.Suggested Use:The red and yellow areas indicate potential zones of dense landsliding.Disclaimer: not verified in field and optical imagery has clouds preventing verification.Satellite/Sensor:Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)Resolution:10 metersCredits:NASA GSFC Landslides Team, Copernicus Sentinel-1 dataHandwerger AL, Huang M-H, Jones SY, Amatya P, Kerner HR, Kirschbaum DB. 2022. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine. Nat. Hazards Earth Syst. Sci. Copernicus Publications, 22(3): 753–773. https://doi.org/10.5194/nhess-22-753-2022.Esri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/hurricane_helene_2024/Landslide_Proxy_Heat_Map_S1_on_Sept_28_2024_for_Hurricane_Helene/MapServer/WMSServerData Download:N/A

Dates of Images:Post-Event: October 12, October 10, October 7, October 5, October 2, September 27Pre-Event: September 20, September 22Date of Next Image:UnknownSummary: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.The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument.The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue.Suggested Use:The True Color RGB 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.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.A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred.Satellite/Sensor:MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellitesResolution:True Color: 10 metersCredits:NASA/MSFC, USGS, ESA CopernicusEsri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/sentinel2/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/sentinel2/

Data from October 12th onwards can be found here for Hurricane Milton: https://maps.disasters.nasa.gov/arcgis/home/item.html?id=93d2cb2403684275af7c47d468a7be5bDate of Image:Pre-Event: August 2024, September 18, 2024 - September 26, 2024Post-Event: September 27, 2024 - October 11, 2024Summary:These Black Marble Day-Night Band (BRDF-Corrected) images were created by the NASA Black Marble Science team. The images corrected for atmospheric, terrain, lunar BRDF, and straylight effects, and directly measures light intensity on the ground in units of nanowatts/(steradian centimeter squared). The images are scaled from 0 - 30, and show the impact of Hurricane Helene on electric grids in the Southeast US. The baseline image is from August 2024, generated from all daily atmospheric and lunar-corrected data from that month, with additional baselines from September 18-25, 2024, and the “after" image from September 27, 2024. There is a layer to display where clouds are present. This comparison between the images is meant as a visual assessment of outage impacts from Francine to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery.Suggested Use:NASA's Black Marble Nighttime Light product suite is a state-of-the-art daily global collection of standard products for monitoring nighttime lights (NTL). Utilizing the Visible Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) aboard the Suomi-NPP, NOAA-20, and NOAA-21 satellites.The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights. Grey represents cloud cover.Satellite/Sensor:Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP), NOAA-20, and NOAA-21SNPP: August 2024 composite, September 18 - 24, 2024, October 1, 2024, October 10, 2024 - October 11, 2024NOAA-20: September 25 - September 30, 2024, October 2, 2024 - October 9, 2024Resolution:500 metersCredits:NASA Black Marble Science teamPlease cite the following two references when using this data:Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883.Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43.Point of Contact:Ranjay ShresthaNASA Goddard Space Flight CenterE-mail: ranjay.m.shrestha@nasa.govAdditional Links:NASA’s Black Marble Product SuiteRomán, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6).Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143.Esri REST Endpoint:See URL section on right side of page.WMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/Black_Marble_BRDF_Corrected_for_Hurricane_Helene_September_2024/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/blackmarble/

Visualization OverviewThis visualization represents a "false color" band combination (Red = DNB, Green = DNB, Blue = Inverted M15) of data collected by the VIIRS instrument on the joint NASA/NOAA Joint Polar Satellite System NOAA-20 and SNPP satellites. The imagery is most useful for identifying nighttime lights from cities, fires, boats, and other phenomena. At its highest resolution, this visualization represents the underlying data scaled to a resolution of 500m per pixel at the equator.The algorithm to combine the VIIRS DNB and M15 bands into an RGB composite was originally designed by the Naval Research Lab and was subsequently incorporated into NASA research and applications efforts. As you will see, nighttime city lights appear in shades of yellow, while clouds appear in shades of blue to yellow/white as the illumination from the moon changes over the lunar month. Hence, this visualization is colloquially referred to as a "blue-yellow RGB."The following guidelines will aid in understanding this visualization.Interpretation of both the presence and relative brightness of the city lights will be affected by the lunar cycle. This composite offers a qualitative assessment of the light conditions and should not be used as the sole source of information concerning power outages. During bright moonlight conditions, moonlight reflected from cloud tops and the land surface may also provide a yellow hue to those features. Comparisons of cloud-free conditions before and after a period of significant change, such as new city growth, disasters, fires, or other factors, may exhibit a change in emitted light (yellows) from those features over time.Multi-Spectral BandsAt its highest resolution, this visualization represents the underlying data scaled from its native 750m per pixel resolution to 500m per pixel at the equator. The following table lists the VIIRS bands that are utilized to create this visualization. See here for a full description of all VIIRS bands.BandDescriptionWavelength (µm)Resolution (m)DNBVisible (reflective)0.5 - 0.9750DNBVisible (reflective)0.5 - 0.9750M15 (Inverted)Longwave IR10.26 - 11.26750Temporal CoverageBy default, this layer will display the imagery currently available for today’s date. This imagery is a "daily composite" that is assembled from hundreds of individual data files. When viewing imagery for “today,” you may notice that only a portion of the map has imagery. This is because the visualization is continually updated as the satellite collects more data. To view imagery over time, you can update the layer properties to enable time animation and configure time settings. NASA Global Imagery Browse Services (GIBS), NASA Worldview, & NASA LANCEThis visualization is provided through the NASA Global Imagery Browse Services (GIBS), which are a set of standard services to deliver global, full-resolution satellite imagery for hundreds of NASA Earth science datasets and science parameters. Through its services, and the NASA Worldview client, GIBS enables interactive exploration of NASA's Earth imagery for a broad range of users. The data and imagery are generated within 3 hours of acquisition through the NASA LANCE capability.Esri and NASA Collaborative ServicesThis visualization is made available through an ArcGIS image service hosted on Esri servers and facilitates access to a NASA GIBS service endpoint.

Aerial imagery was acquired following Hurricane Helene. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired using a Digital Sensor System (DSS) version 6.Credit the National Oceanic and Atmospheric Administration (NOAA) when you use these photos in a report, publication, or presentation.This imagery was acquired by the NOAA Remote Sensing Division to support NOAA national security and emergency response requirements. This aerial imagery will primarily support NOAA interests including safety of navigation, HAZMAT and marine debris impacts, as well as impacts to coastal zone management interests. It is not intended for mapping, charting or navigation. In addition, it will be used for ongoing research efforts for testing and developing standards for airborne digital imagery.The ground sample distance (GSD) for each image is 15 cm to 30 cm. All imagery acquired to support an emergency response is made available online through the online viewer and AWS.In an effort to acquire imagery in a timely manner after the event, clouds may be present in the imagery. Be advised that the bounding coordinates reflect the extents of the images acquired for this event and do not imply full image coverage of the area.Source:HereMetadata:Here

Date of Images:10/2/2024 at 16:11 UTC (12:11 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 disturbance maps using the OPERA Disturbance Alert from Harmonized Landsat Sentinel-2 (DIST-ALERT-HLS) 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 surface disturbance extent. The ARIA-share website has always focused on posting preliminary results as fast as possible for disaster response.OPERA DIST-ALERT-HLSThe Disturbance product (DIST) maps per pixel vegetation disturbance (specifically, vegetation cover loss) from the Harmonized Landsat Sentinel-2 (HLS) scenes. We provide the vegetation disturbance status (VEG-DIST-STATUS) and the maximum vegetation anomaly value (VEG-ANOM-MAX) layers. Images are provided from October 2, 2024. Each image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file.VEG-DIST-STATUSIndication of vegetation cover loss (vegetation disturbance). The status label is based on the maximum anomaly value, confidence level, and whether it is ongoing or finished. "First" means the pixel has had an anomaly detection but no subsequent observations whether anomalous or not. "Provisional" means there have been two consecutive disturbance detections but not yet high confidence. "Confirmed" means that vegetation disturbance is detected with high confidence. The label "finished" is applied to confirmed disturbances that have had two consecutive no-anomaly observations or one 15 days or more after the last anomaly detection. If a new disturbance is detected, it will overwrite those in a "finished" state. These labels are reported for both above and below the 50% disturbance threshold based on the maximum anomaly value.VEG-ANOM-MAXDifference between historical and current year observed vegetation cover at the date of maximum decrease (vegetation loss of 0-100%). This layer can be used to threshold vegetation disturbance per a given sensitivity (e.g. disturbance of >20% vegetation cover loss). The sum of the historical percent vegetation and the anomaly value will be the vegetation cover estimate for the current year.The DIST-ALERT HLS products have these flags:255 represents No Data and is based on the Fmask layer of the source HLS granule.Suggested Use:VEG-ANOM-MAX0-100: Maximum loss of percent vegetation 255: No data VEG-DIST-STATUS:0: No disturbance 1: first <50% 2: provisional <50% 3: confirmed <50% 4: first >50% 5: provisional >50% 6: confirmed >50% 7: confirmed <50%, finished 8: confirmed >50%, finished 255: No data Satellite/Sensor:MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A satellitesResolution:30 metersCredits:NASA JPL-Caltech ARIA/OPERA TeamThe product contains modified Copernicus Sentinel data (2024) and is produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group. Managed by NASA's Jet Propulsion Laboratory, OPERA funds and manages the DIST-ALERT-HLS product developed and produced by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland.Additional Information:OPERA DIST-ALERT-HLS data availabilityThe post-processed products are available to download at https://aria-share.jpl.nasa.gov/20240926-Hurricane_Helene/DIST. The OPERA DIST-HLS products have been in production since January 2022, are freely distributed to the public via NASA's Land Processes Distributed Active Archive Center (LP DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Surface Disturbance product suite, please refer to the DIST Product page: https://www.jpl.nasa.gov/go/opera/products/dist-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/20240926-Hurricane_Helene/DIST. Esri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/aria_dist/MapServer/WMSServer

Map displaying Hurricane Helene 2024 estimated max wind gust data for FEMA4. NOTE: The data provided are preliminary. They are subject to updates and corrections as appropriate.The National Hurricane Center is responsible for conducting the official post-analysis of all tropical cyclones. Once compiled, the Tropical Cyclone Report is posted here: https://www.nhc.noaa.gov/data/tcr/index.php . For current official data and information, go to weather.gov.

Dates of Images:Post-Event: 10/1/2024 (Landsat 8), 10/2/2024 (Landsat 9), 10/9/2024 (Landsat 9)Pre-Event: 8/30/2024 (Landsat 8)Date of Next Image:UnknownSummary:Natural Color: The Natural Color RGB provides a false composite look at the surface. This RGB uses a shortwave, the near-infrared, and red channels from the 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.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.Suggested Use:Natural Color: areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta.Color Infrared: depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred.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.Satellite/Sensor:Landsat 8 and Landsat 9 Operational Land Imagers (OLI)Resolution:30 metersCredits:NASA/MSFC, USGSEsri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/landsat8/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/landsat/

Dates of Images:Post-Event: October 12, October 10, October 7, October 5, October 2, September 27Pre-Event: September 20, September 22Date of Next Image:UnknownSummary: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.The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument.The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue.Suggested Use:The True Color RGB 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.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.A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred.Satellite/Sensor:MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellitesResolution:True Color: 10 metersCredits:NASA/MSFC, USGS, ESA CopernicusEsri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/sentinel2/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/sentinel2/

Dates of Images:Pre-Event: 9/14, 9/16, 9/19, 9/21Post-Event: 9/26, 9/28Date of Next Image:Varies by region, typically 12 days since previous pass. Set time slider to most recent interval and click on area of interest to identify date of last pass.Summary:The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composites and surface water extent products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event.Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas).Suggested Use:In this image, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas.Post-event data is classified from the above imagery shows water that is detected by the sensor with different colors indicating different land cover/land use classifications from CDL that appear to have water and are potentially flooded.Blue (1): Known WaterRed (2): Flooded DevelopedGreen (3): Flooded VegetationOrange (4): Flooded Cropland/GrasslandGray (5): Clouds/Cloud Shadow(0): No DataSatellite/Sensor:Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A/B satelliteNOTE: Sentinel-1B is no longer acquiring data and is only available into December 2021Resolution:20 metersEsri REST Endpoint:See URL on the right.RGB Product:https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RGB/ImageServerRTC Product:VV - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VV/ImageServerVH - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VH/ImageServerSurface Water Extent Product:https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_WM/ImageServerWMS:https://maps.disasters.nasa.gov/ags04/services/hurricane_helene_2024/sentinel1/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2024/hurricane_helene_202409/sentinel1/

This layer features tropical storm (hurricanes, typhoons, cyclones) tracks, positions, and observed wind swaths from the past hurricane season for the Atlantic, Pacific, and Indian Basins. These are products from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC). They are part of an archive of tropical storm data maintained in the International Best Track Archive for Climate Stewardship (IBTrACS) database by the NOAA National Centers for Environmental Information.Data SourceNOAA National Hurricane Center tropical cyclone best track archive.Update FrequencyWe automatically check these products for updates every 15 minutes from the NHC GIS Data page.The NHC shapefiles are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.Area CoveredWorldWhat can you do with this layer?Customize the display of each attribute by using the ‘Change Style’ option for any layer.Run a filter to query the layer and display only specific types of storms or areas.Add to your map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools like ‘Enrich Data’ on the Observed Wind Swath layer to determine the impact of cyclone events on populations.Visualize data in ArcGIS Insights or Operations Dashboards.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources for official guidance.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

Aerial imagery was acquired following Hurricane Helene. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired using a Digital Sensor System (DSS) version 6.Credit the National Oceanic and Atmospheric Administration (NOAA) when you use these photos in a report, publication, or presentation.This imagery was acquired by the NOAA Remote Sensing Division to support NOAA national security and emergency response requirements. This aerial imagery will primarily support NOAA interests including safety of navigation, HAZMAT and marine debris impacts, as well as impacts to coastal zone management interests. It is not intended for mapping, charting or navigation. In addition, it will be used for ongoing research efforts for testing and developing standards for airborne digital imagery.The ground sample distance (GSD) for each image is 15 cm to 30 cm. All imagery acquired to support an emergency response is made available online through the online viewer and AWS.In an effort to acquire imagery in a timely manner after the event, clouds may be present in the imagery. Be advised that the bounding coordinates reflect the extents of the images acquired for this event and do not imply full image coverage of the area.Source:HereMetadata:Here