The United States has an average elevation of roughly 2,500 feet (763m) above sea level, however there is a stark contrast in elevations across the country. Highest states Colorado is the highest state in the United States, with an average elevation of 6,800 feet (2,074m) above sea level. The 10 states with the highest average elevation are all in the western region of the country, as this is, by far, the most mountainous region in the country. The largest mountain ranges in the contiguous western states are the Rocky Mountains, Sierra Nevada, and Cascade Range, while the Appalachian Mountains is the longest range in the east - however, the highest point in the U.S. is Denali (Mount McKinley), found in Alaska. Lowest states At just 60 feet above sea level, Delaware is the state with the lowest elevation. Delaware is the second smallest state, behind Rhode Island, and is located on the east coast. Larger states with relatively low elevations are found in the southern region of the country - both Florida and Louisiana have an average elevation of just 100 feet (31m) above sea level, and large sections of these states are extremely vulnerable to flooding and rising sea levels, as well as intermittent tropical storms.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).

IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.

The Wind Integration National Dataset (WIND) Toolkit, developed by the National Renewable Energy Laboratory (NREL), provides modeled wind speeds at multiple elevations. Instantaneous wind measurements were analyzed from more than 126,000 sites in the continental United States for the years 2007–2013. The model results were mapped on a 2-km grid. A subset of the contiguous United States data for 2012 is shown here. Offshore data is shown to 50 nautical miles.Time Extent: Annual 2012Units: m/sCell Size: 2 kmSource Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection:  WGS 1984 Web MercatorExtent: Contiguous United StatesSource: NREL Wind Integration National Dataset v1.1WIND is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies.Accessing Elevation InformationEach of the 9 elevation slices can be accessed, visualized, and analyzed. In ArcGIS Pro, go to the Multidimensional Ribbon and use the Elevation pull-down menu. In ArcGIS Online, it is best to use Web Map Viewer Classic where the elevation slider will automatically appear on the righthand side. The elevation slider will be available in the new Map Viewer in an upcoming release. What can you do with this layer?This layer may be added to maps to visualize and quickly interrogate each pixel value. The pop-up provides the pixel’s wind speed value.This analytical imagery tile layer can be used in analysis. For example, the layer may be added to ArcGIS Pro and proposed wind turbine locations can be used to Sample the layer at multiple elevation to determine the optimal hub height. Source data can be accessed on Amazon Web ServicesUsers of the WIND Toolkit should use the following citations:Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory.Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. "The Wind Integration National Dataset (WIND) Toolkit." Applied Energy 151: 355366.King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results. This was done for each of the emissions scenarios (Lower Emissions = 2022 Intermediate SLR Scenario Higher Emissions = 2022 Intermediate High SLR Scenario) at each of the mapped time intervals (Early Century - Year 2030, Middle Century - Year 2050, and Late Century - Year 2090). The resulting maps are displayed in the CMRA Assessment Tool. County, tract, and tribal geographies summaries of percentage SLR inundation were also calculated using Zonal Statistics tools. The Sea Level Rise Scenario year 2020 is considered “baseline” and the impacts are calculated by subtracting the baseline value from each of the near-term, mid-term and long-term timeframes. General Disclaimer The data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided 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. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes. SLR visualizations and statistics are not available in CMRA for Hawaii, Alaska, or U.S. territories at this time. Levees Disclaimer Enclosed levee areas are displayed as gray areas on the maps. Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database. Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences. Citations 2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.Data can be downloaded here: Geodatabase or ShapefileThese files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico. These integrated bathymetric-topographic DEMs were developed for NOAA Coastal Survey Development Laboratory (CSDL) through the American Recovery and Reinvestment Act (ARRA) of 2009 to evaluate the utility of the Vertical Datum Transformation tool (VDatum), developed jointly by NOAA's Office of Coast Survey (OCS), National Geodetic Survey (NGS), and Center for Operational Oceanographic Products and Services (CO-OPS). Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. Coastal Services Center (CSC), the U.S. Office of Coast Survey (OCS), the U.S. Army Corps of Engineers (USACE), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of North American Vertical Datum of 1988 (NAVD 88), Mean High Water (MHW) or Mean Lower Low Water (MLLW) and horizontal datum of North American Datum of 1983 (NAD 83). Cell size ranges from 1/3 arc-second (~10 meters) to 1 arc-second (~30 meters). The NOAA VDatum DEM Project was funded by the American Recovery and Reinvestment Act (ARRA) of 2009 (http://www.recovery.gov/).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).This is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), with vertical units referenced to mean high water (NAVD88). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service provides data from many individual DEMs combined together as a mosaic. By default, the rasters are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Alternatively, a single DEM or group of DEMs can be isolated using a filter/definition query or using the 'Lock Raster 'mosaic method in ArcMap. This is one of three services displaying collections of DEMs that are referenced to common vertical datums: North American Vertical Datum of 1988 (NAVD88): http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042, Mean High Water (MHW): http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799, and Mean Higher High Water: http://noaa.maps.arcgis.com/home/item.html?id=9471f8d4f43e48109de6275522856696. In addition, the DEM Global Mosaic is a general-purpose global, seamless bathymetry/topography mosaic containing all the DEMs together. Two services are available: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff Elevation Values: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff and Color Shaded Relief: http://noaa.maps.arcgis.com/home/item.html?id=feb3c625dc094112bb5281c17679c769. Please see the corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. This service has several server-side functions available. These can be selected in the ArcGIS Online layer using 'Image Display ', or in ArcMap under 'Processing Templates '. None: The default. Provides elevation/depth values in meters relative to the NAVD88 vertical datum. ColorHillshade: An elevation-tinted hillshade visualization. The depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png. GrayscaleHillshade: A simple grayscale hillshade visualization. SlopeMapRGB: Slope in degrees, visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/SlopeMapLegend_V7b.png. SlopeNumericValues: Slope in degrees, returning the actual numeric values. AspectMapRGB: Orientation of the terrain (0-360 degrees), visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/AspectMapLegendPie_V7b.png. AspectNumericValues: Aspect in degrees, returning the actual numeric values.

The following dataset includes "Active Benchmarks," which are provided to facilitate the identification of City-managed standard benchmarks. Standard benchmarks are for public and private use in establishing a point in space. Note: The benchmarks are referenced to the Chicago City Datum = 0.00, (CCD = 579.88 feet above mean tide New York). The City of Chicago Department of Water Management’s (DWM) Topographic Benchmark is the source of the benchmark information contained in this online database. The information contained in the index card system was compiled by scanning the original cards, then transcribing some of this information to prepare a table and map. Over time, the DWM will contract services to field verify the data and update the index card system and this online database.This dataset was last updated September 2011. Coordinates are estimated. To view map, go to https://data.cityofchicago.org/Buildings/Elevation-Benchmarks-Map/kmt9-pg57 or for PDF map, go to http://cityofchicago.org/content/dam/city/depts/water/supp_info/Benchmarks/BMMap.pdf. Please read the Terms of Use: http://www.cityofchicago.org/city/en/narr/foia/data_disclaimer.html.

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results.Scenario: For each of the 5 GMSL scenarios (identified by the rise amounts in meters by 2100--0.3 m , 0.5 m. 1.0 m, 1.5 m and 2.0 m), there is a low, medium (med) and high value, corresponding to the 17th, 50th, and 83rd percentiles. Scenarios (15 total): 0.3 - MED, 0.3 - LOW, 0.3 - HIGH, 0.5 - MED, 0.5 - LOW, 0.5 - HIGH, 1.0 - MED, 1.0 - LOW, 1.0 - HIGH, 1.5 - MED, 1.5 - LOW, 1.5 - HIGH, 2.0 - MED, 2.0 - LOW, and 2.0 - HIGH Years (15 total): 2005, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100, 2110, 2120, 2130, 2140, and 2150Report Website: https://oceanservice.noaa.gov/hazards/sealevelrise/sealevelrise-tech-report.htmlGeneral DisclaimerThe data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided 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. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes.SLR data are not available for Hawaii, Alaska, or U.S. territories at this time.Levees DisclaimerEnclosed levee areas are displayed as gray areas on the maps.Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database.Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences.Citations2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results. This was done for each of the emissions scenarios (Lower Emissions = 2022 Intermediate SLR Scenario Higher Emissions = 2022 Intermediate High SLR Scenario) at each of the mapped time intervals (Early Century - Year 2030, Middle Century - Year 2050, and Late Century - Year 2090). The resulting maps are displayed in the CMRA Assessment Tool. County, tract, and tribal geographies summaries of percentage SLR inundation were also calculated using Zonal Statistics tools. The Sea Level Rise Scenario year 2020 is considered “baseline” and the impacts are calculated by subtracting the baseline value from each of the near-term, mid-term and long-term timeframes. General Disclaimer The data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided 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. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes. SLR visualizations and statistics are not available in CMRA for Hawaii, Alaska, or U.S. territories at this time. Levees Disclaimer Enclosed levee areas are displayed as gray areas on the maps. Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database. Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences. Citations 2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

The inundation areas depicted in the Sea Level Rise dataset are not as precise as they may appear. Levels of confidence are depicted on this map. Blue areas denote a high confidence of inundation, orange areas denote a high degree of uncertainty, and unshaded areas denote a high confidence that these areas will be dry given the chosen water level. In this application 80% is considered a high degree of confidence such that, for example, the blue areas denote locations that may be correctly mapped as 'inundated' more than 8 out of 10 times. Areas with a high degree of uncertainty represent locations that may be mapped correctly (either as inundated or dry) less than 8 out of 10 times. There are many unknowns when mapping future conditions, including natural evolution of the coastal landforms (e.g., barrier island overwash and migration), as well as the data used to predict the changes. The presentation of confidence in these maps only represents the known error in the elevation data and tidal corrections. Inundation Uncertainty Associated with Elevation Data and Tidal Datum Conversion for Current Mean Higher High Water. This dataset was created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer depicting potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer 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 gauge trends and prioritize actions for different scenarios. The purpose of this dataset is to depict errors that are directly related to elevation and water height data. These errors can be used to begin defining areas with mapped inundation that do not have the same level of confidence as other areas. For a detailed explanation of mapping methods, see http://www.coast.noaa.gov/slr/assets/pdfs/Elevation_Mapping_Confidence_Methods.pdf. 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. Tiles have been cached down to Level ID 15 (1:18,055). For more information visit the Sea Level Rise Impacts Viewer (http://coast.noaa.gov/slr).View Dataset on the Gateway

Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.Data can be downloaded here: Geodatabase or ShapefileThese files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.

A bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using triangulated irregular network (TIN) processing of the ground point returns. Hydro-flattened Bare Earth DEMs represent water bodies in a cartographically and aesthetically pleasing manner, and are not intended to accurately map water surface elevations. In a Hydro-flattened DEM, water surfaces are flat and level for lakes with a greater area than two acres, and gradated for rivers or other long impoundments (e.g., reservoirs) that are wider than 100 feet, and tidal areas. Any existing island larger than one acre was be delineated. Water surface edge elevations were at or below the immediately surrounding terrain. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average elevation for that area. The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet for horizontal, and vertical units are NAVD88 (12A) US Survey Feet. The dataset encompasses a portion of Sonoma County. WSI collected the LiDAR and created this data set for the Sonoma County Vegetation Mapping and LiDAR Consortium.

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Catalina Mountains by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

A bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using triangulated irregular network (TIN) processing of the ground point returns. Hydro-flattened Bare Earth DEMs represent water bodies in a cartographically and aesthetically pleasing manner, and are not intended to accurately map water surface elevations. In a Hydro-flattened DEM, water surfaces are flat and level for lakes with a greater area than two acres, and gradated for rivers or other long impoundments (e.g., reservoirs) that are wider than 100 feet, and tidal areas. Any existing island larger than one acre was be delineated. Water surface edge elevations were at or below the immediately surrounding terrain. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average elevation for that area. The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet for horizontal, and vertical units are NAVD88 (12A) US Survey Feet. The dataset encompasses all of Sonoma County and parts of Mendocino County. WSI collected the LiDAR and created this data set for the Sonoma County Vegetation Mapping and LiDAR Program.Data hosted by Sonoma County Information Systems Department (ISD).

1950 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1950. In 2002, NOAA published digitized shorelines for T-sheet (T-9393), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted.

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results. This was done for each of the emissions scenarios (Lower Emissions = 2022 Intermediate SLR Scenario Higher Emissions = 2022 Intermediate High SLR Scenario) at each of the mapped time intervals (Early Century - Year 2030, Middle Century - Year 2050, and Late Century - Year 2090). The resulting maps are displayed in the CMRA Assessment Tool. County, tract, and tribal geographies summaries of percentage SLR inundation were also calculated using Zonal Statistics tools. The Sea Level Rise Scenario year 2020 is considered “baseline” and the impacts are calculated by subtracting the baseline value from each of the near-term, mid-term and long-term timeframes. General Disclaimer The data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided 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. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes. SLR visualizations and statistics are not available in CMRA for Hawaii, Alaska, or U.S. territories at this time. Levees Disclaimer Enclosed levee areas are displayed as gray areas on the maps. Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database. Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences. Citations 2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

A high resolution LiDAR derived hillshade facilitates the visualization of the topography of a landscape at a variety of scales. This hillshade which was created from a LiDAR derived hydro-flattened bare earth digital elevation model shows the signal returns without any vegetation or human-made structures. In addition to that, bodies of water have been smoothed. This layer may be used on its own or in conjunction with other data.The Sonoma County Vegetation Mapping and LiDAR Program. and the University of Maryland (under grant NNX13AP69G from NASA’s Carbon Monitoring System, Dr. Ralph Dubayah, PI) contracted LiDAR and orthophoto data collection for all of Sonoma County in late 2013. Also included in the data collection were two areas in Mendocino County - the Soda Spring Creek-Dry Creek Watershed and Lake Mendocino. This fine scale data will help provide an accurate, up-to-date inventory of the county’s landscape features, ecological communities and habitats. Project funders include: NASA, the University of Maryland, the Sonoma County Agricultural Preservation and Open Space District, the Sonoma County Water Agency, the California Department of Fish and Wildlife, the United States Geological Survey, the Sonoma County Information Systems Department, the Sonoma County Transportation and Public Works Department, the Nature Conservancy, and the City of Petaluma.The hillshade is a greyscale image showing topography in the landscape. In this case it is created from a LiDAR derived hydro-flattened bare earth digital elevation model illuminated by hypothetical light source shining from the north west. A hydro flattened bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. In addition bodies of waters 2acres or larger have been smoothed.The DEM used to create this hillshade is described as a bare earth digital elevation model (DEM) representing the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using triangulated irregular network (TIN) processing of the ground point returns. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average elevation for that area.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and modeling efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of Mean High Water (MHW) and horizontal datum of World Geodetic System 1984 (WGS84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).This is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), with vertical units referenced to mean high water (MHW). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service provides data from many individual DEMs combined together as a mosaic. By default, the rasters are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Alternatively, a single DEM or group of DEMs can be isolated using a filter/definition query or using the 'Lock Raster 'mosaic method in ArcMap. This is one of three services displaying collections of DEMs that are referenced to common vertical datums: North American Vertical Datum of 1988 (NAVD88): http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042, Mean High Water (MHW): http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799, and Mean Higher High Water: http://noaa.maps.arcgis.com/home/item.html?id=9471f8d4f43e48109de6275522856696. In addition, the DEM Global Mosaic is a general-purpose global, seamless bathymetry/topography mosaic containing all the DEMs together. Two services are available: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff Elevation Values: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff and Color Shaded Relief: http://noaa.maps.arcgis.com/home/item.html?id=feb3c625dc094112bb5281c17679c769. Please see the corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. This service has several server-side functions available. These can be selected in the ArcGIS Online layer using 'Image Display ', or in ArcMap under 'Processing Templates '. None: The default. Provides elevation/depth values in meters relative to the NAVD88 vertical datum. ColorHillshade: An elevation-tinted hillshade visualization. The depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png. GrayscaleHillshade: A simple grayscale hillshade visualization. SlopeMapRGB: Slope in degrees, visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/SlopeMapLegend_V7b.png. SlopeNumericValues: Slope in degrees, returning the actual numeric values. AspectMapRGB: Orientation of the terrain (0-360 degrees), visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/AspectMapLegendPie_V7b.png. AspectNumericValues: Aspect in degrees, returning the actual numeric values.

This map represents Flood Insurance Rate Map (FIRM) data important for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). The National Flood Hazard Layer (NFHL) data present the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The NFHL database is a subset of the information created for the Flood Insurance Studies (FIS) and serves as a means to archive a portion of the information collected during the FIS. The NFHL data incorporates Digital Flood Insurance Rate Map (DFIRM) databases published by Federal Emergency Management Agency (FEMA). The 100-year flood is referred to as the 1% annual exceedance probability flood, since it is a flood that has a 1% chance of being equaled or exceeded in any single year. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The 1% annual chance (base flood) is the flood that has a 1% chance of being equaled or exceeded in any year. The Special Flood Hazard area is the area subject to flooding by the 1% annual chance flood. Areas of Special Flood Hazard include Zones A, AE, AH, AO, AR, A99, D, V, VE, and X. These flood zones are explained below and reflects the severity or type of flooding in the area. A - Zone A is the flood insurance rate zone that corresponds to the 1-percent annual chance floodplains that are determined in the Flood Insurance Study by approximate methods of analysis. Because detailed hydraulic analyses are not performed for such areas, no Base Flood Elevations or depths are shown within this zone. Mandatory flood insurance purchase requirements apply. AE and A1-A30 - Zones AE and A1-A30 are the flood insurance rate zones that correspond to the 1-percent annual chance floodplains that are determined in the Flood Insurance Study by detailed methods of analysis. In most instances, Base Flood Elevations derived from the detailed hydraulic analyses are shown at selected intervals within this zone. Mandatory flood insurance purchase requirements apply. AH - Zone AH is the flood insurance rate zone that corresponds to the areas of 1-percent annual chance shallow flooding with a constant water-surface elevation (usually areas of ponding) where average depths are between 1 and 3 feet. The Base Flood Elevations derived from the detailed hydraulic analyses are shown at selected intervals within this zone. Mandatory flood insurance purchase requirements apply. AO - Zone AO is the flood insurance rate zone that corresponds to the areas of 1-percent shallow flooding (usually sheet flow on sloping terrain) where average depths are between 1 and 3 feet. Average flood depths derived from the detailed hydraulic analyses are shown within this zone. In addition, alluvial fan flood hazards are shown as Zone AO on the Flood Insurance Rate Map. Mandatory flood insurance purchase requirements apply. AR - Zone AR is the flood insurance rate zone used to depict areas protected from flood hazards by flood control structures, such as a levee, that are being restored. FEMA will consider using the Zone AR designation for a community if the flood protection system has been deemed restorable by a Federal agency in consultation with a local project sponsor; a minimum level of flood protection is still provided to the community by the system; and restoration of the flood protection system is scheduled to begin within a designated time period and in accordance with a progress plan negotiated between the community and FEMA. Mandatory purchase requirements for flood insurance will apply in Zone AR, but the rate will not exceed the rate for an unnumbered Zone A if the structure is built in compliance with Zone AR floodplain management regulations. A99 - Zone A99 is the flood insurance rate zone that corresponds to areas within the 1-percent annual chance floodplain that will be protected by a Federal flood protection system where construction has reached specified statutory milestones. No Base Flood Elevations or depths are shown within this zone. Mandatory flood insurance purchase requirements apply. D - Zone D designation is used for areas where there are possible but undetermined flood hazards. In areas designated as Zone D, no analysis of flood hazards has been conducted. Mandatory flood insurance purchase requirements do not apply, but coverage is available. The flood insurance rates for properties in Zone D are commensurate with the uncertainty of the flood risk. V - Zone V is the flood insurance rate zone that corresponds to areas within the 1-percent annual chance coastal floodplains that have additional hazards associated with storm waves. Because approximate hydraulic analyses are performed for such areas, no Base Flood Elevations are shown within this zone. Mandatory flood insurance purchase requirements apply. VE - Zone VE is the flood insurance rate zone that corresponds to areas within the 1-percent annual chance coastal floodplain that have additional hazards associated with storm waves. Base Flood Elevations derived from the detailed hydraulic analyses are shown at selected intervals within this zone. Mandatory flood insurance purchase requirements apply. X - Zone X is the flood insurance rate zones that correspond to areas outside the 1-percent annual chance floodplain – Areas protected from the 1-percent annual chance flood by levees. No Base Flood Elevations or depths are shown within this zone. Insurance purchase is not required in these zones. More information about the flood zones can be found here. The NFHL data are derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data where available. The NFHL data is available at State level. The data is updated on monthly basis and FEMA is in the process of mapping all the flood zones and so some counties do not have complete data. For better visualization, it’s recommended to display the service with 50% transparency. The map service has a county layer that helps differentiate between the counties that have flood data available and those that do not. The flood data is scale dependent and is set to show from 1:3,000,000. This data is as of March 2011.