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).

Graph and download economic data for High School Graduate or Higher (5-year estimate) in Yakutat City and Borough, AK (HC01ESTVC1602282) from 2010 to 2023 about Yakutat City and Borough, AK; AK; secondary schooling; secondary; educational attainment; education; 5-year; and USA.

A nationwide listing of known publicly available high-accuracy topographic and bathymetric source elevation data for the United States and its territories. The inventory provides a single resource for information about all known completed and in-progress broad-area public domain elevation data. The information provided for each elevation dataset includes many attributes such as vertical accurac...

Graph and download economic data for High School Graduate or Higher (5-year estimate) in Staunton city, VA (HC01ESTVC1651790) from 2010 to 2023 about Staunton City, VA; secondary schooling; secondary; educational attainment; VA; education; 5-year; and USA.

Snow and ice-covered Mount Baker in northern Washington, is the highest peak in the North Cascades (3,286 meters or 10,781 feet) and the northernmost volcano in the conterminous United States. It is the only U.S. volcano in the Cascade Range that has been affected by both alpine and continental glaciation. The stratovolcano is composed mainly of andesite lava flows and breccias formed prior to the most recent major glaciation (Fraser Glaciation), which occurred between about 25,000 and 10,000 years ago. The most recent major eruption at Mount Baker (6,700 years ago) was accompanied by a major flank-collapse event that caused lahars to rush down the Nooksack River and then eastward into Baker Lake. In 1975-76, Sherman Crater immediately south of the summit, exhibited signs of renewed volcanic activity as a result of magma intruding into the volcano but not erupting. The DEM (digital elevation model) of Mount Baker covers approximately 201 square miles and is the product of high-precision airborne lidar (Light Detection and Ranging) surveys performed between 08/26/15 and 09/27/15 by Quantum Spatial under contract with the USGS. The DEM, represents the ground surface beneath forest cover. This release includes two raster datasets in .tif format, (1) a DEM dataset (mt_baker_dem.zip, 1.40 GB), and (2) a hillshade raster (mt_baker_hillshade.zip, 573 MB).

This data release provides access to a low-altitude, aeromagnetic survey of a part of central Washington centered approximately 22 km west-southwest of Ellensburg. The survey includes the cities of Ellensburg, Cle Elum, and Yakima and is referred to as the Cle Elum aeromagnetic survey. The Cle Elum aeromagnetic survey extends from the Columbia Plateau westward to the eastern Cascade Range and illuminates magnetic anomalies associated with folds and faults of the Yakima folds, including the Umtanum Ridge, Saddle Mountains, and Frenchman Hills anticlines. These data were acquired during August and September, 2008, by Firefly Aviation, Ltd., working under contract to the U.S. Geological Survey. Total magnetic field values were acquired using a fixed-wing aircraft flown at a target elevation 150 m above terrain. The nominal flying height was based on a best fit, pre-planned, three-dimensional draped surface 155 m above terrain, subject to aircraft climb and descent limitations. Flight lines were spaced 400 m apart and directed east-west. Tie lines were spaced 4000 m apart, and directed north-south. A total of 26,680 line-kilometers were acquired. The details of the Cle Elum aeromagnetic survey are described in the document, CleElem_Tech_report.pdf available for download in this data release.

This digital spatial data set consists of the aquifer base elevation contours (50-foot contour interval) for part of the High Plains aquifer in the central United States. This subset of the High Plains aquifer covers the Republican River Basin in Nebraska, Kansas, and Colorado upstream from the streamflow station on the Republican River near Hardy, Nebraska, near the Kansas/Nebraska border. In Nebraska, the digitized contours extend to the South Platte, Platte, and Little Blue Rivers. In Colorado and Kansas, the digital contours extend to the edge of the High Plains aquifer. These boundaries were chosen to simplify boundary conditions for a computer simulation model being used for a hydrologic study of the Republican River Basin.

The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the coastal zone vertically from -12 meters (m) to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for four decades (the 2020s, 2030s, 2050s and 2080s). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of current sea-level forecasts, vertical land movement rates, and current elevation data. Coastal response type predictions incorporate adjusted elevation predictions with land cover data and expert knowledge to determine the likelihood that an area will be able to accommodate or adapt to water level increases and maintain its initial land class state or transition to a new non-submerged state (dynamic) or become submerged (static). Intended users of these data include scientific researchers, coastal planners, and natural resource management communities.

These GIS layers provide the probability of observing the forecast of adjusted land elevation (PAE) with respect to predicted sea-level rise or the Northeastern U.S. for the 2020s, 2030s, 2050s and 2080s. These data are based on the following inputs: sea-level rise, vertical land movement rates due to glacial isostatic adjustment and elevation data. The output displays the highest probability among the five adjusted elevation ranges (-12 to -1, -1 to 0, 0 to 1, 1 to 5, and 5 to 10 m) to be observed for the forecast year as defined by a probabilistic framework (a Bayesian network), and should be used concurrently with the adjusted land elevation layer (AE), also available from http://woodshole.er.usgs.gov/project-pages/coastal_response/, which provides users with the forecast elevation range occurring when compared with the four other elevation ranges. These data layers primarily show the distribution of adjusted elevation range probabilities over a large spatial scale and should therefore be used qualitatively.

The U.S. Interagency Elevation Inventory displays high-accuracy topographic and bathymetric data for the United States and its territories. The project is a collaborative effort between NOAA, the U.S. Geological Survey, the Federal Emergency Management Agency, the U.S. Department of Agriculture, the U.S. Forest Service, the National Park Service and the U.S. Army Corps of Engineers. This resource is a comprehensive, nationwide listing of known high-accuracy topographic data, including lidar and IfSAR, and bathymetric data,including NOAA hydrographic surveys, multibeam data, and bathymetric lidar. The following data layers are updated quarterly: topographic lidar, topobathy shoreline lidar, IfSAR data, and bathymetric lidar. The NOAA hydrographic surveys, the multibeam and trackline bathymetry shown are provided via a service that is available from the NOAA National Centers for Environmental Information (NCEI). Access the bathymetric data directly from the NCEI at: http://maps.ngdc.noaa.gov/viewers/bathymetry/ The US Army Corps of Engineers (USACE) hydrographic surveys are provided via a service that is available from the USACE. The information provided for each elevation dataset includes many attributes such as vertical accuracy, point spacing, and date of collection. A direct link to access the data or information about the contact organization is also available through the inventory.

United States US: Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 0.980 % in 2010. This stayed constant from the previous number of 0.980 % for 2000. United States US: Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 0.980 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.980 % in 2010 and a record low of 0.980 % in 2010. United States US: Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Land Use, Protected Areas and National Wealth. Rural land area below 5m is the percentage of total land where the rural land elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted average;

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 seamless, three-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the +20-m elevation contour.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

A revision to the hydrogeologic framework of the Virginia coastal plain southwest of the James River was developed by USGS during 2019-2021. This revision includes modifications to existing understanding of the groundwater system in Prince George, Surry, Sussex, Isle of Wight, and Southampton counties and the cities of Franklin and Suffolk in southeast Virginia. This USGS data release contains a csv file of interpreted borehole hydrogeologic-unit top-surface altitudes, a shapefile of the study area extent, a shapefile of faults within the study area, shapefiles of altitude contours for 12 hydrogeologic-unit top surfaces, shapefiles of hydrogeologic-unit margins for 10 hydrogeologic-units in the coastal plain of Virginia southwest of the James River. This data supports the following publication Caldwell, S. H., and McFarland, E. R., 2022 , Revision to the Virginia Coastal Plain Hydrogeologic Framework Southwest of the James River: U.S. Geological Survey Scientific Investigations ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Graph and download economic data for High School Graduate or Higher (5-year estimate) in San Francisco County/city, CA (HC01ESTVC1606075) from 2010 to 2023 about San Francisco County/City, CA; San Francisco; secondary schooling; secondary; educational attainment; education; CA; 5-year; and USA.

United States Alabama: Gen Exp: Education: Higher Education data was reported at 4,863,337.000 USD th in 2015. This records an increase from the previous number of 4,706,215.000 USD th for 2014. United States Alabama: Gen Exp: Education: Higher Education data is updated yearly, averaging 934,447.000 USD th from Sep 1957 (Median) to 2015, with 57 observations. The data reached an all-time high of 4,977,347.000 USD th in 2013 and a record low of 28,828.000 USD th in 1957. United States Alabama: Gen Exp: Education: Higher Education data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.F009: Revenue & Expenditure: State and Local Government: Alabama.

This data set represents geologic structure contours for the Madison Limestone, Black Hills, South Dakota.

Graph and download economic data for High School Graduate or Higher (5-year estimate) in Charles City County, VA (HC01ESTVC1651036) from 2010 to 2023 about Charles City County, VA; Richmond; secondary schooling; secondary; educational attainment; VA; education; 5-year; and USA.

Graph and download economic data for High School Graduate or Higher (5-year estimate) in Salem city, VA (HC01ESTVC1651775) from 2010 to 2023 about Salem City, VA; Roanoke; secondary schooling; secondary; educational attainment; VA; education; 5-year; and USA.