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.

This dataset contains average elevation data at 1-degree resolution for the globe, and at 5-minute resolution for Europe, parts of North Africa, and most of North America.

This statistic shows a ranking of the estimated average elevation of the land area in 2020 in Latin America, differentiated by country.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

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 U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light detection and ranging (lidar)-derived data acquired in 2002 (Brock and others, 2006, 2007) to calculate historical seafloor elevation changes in the Upper Florida Keys (UFK) (Yates and others, 2017). Using those changes in seafloor elevation, annual rates of elevation change were calculated for 13 habitat types found in the UFK reef tract. The annual rate of mean elevation change for each habitat type was applied to a digital elevation model (DEM) extending from Deerfield Beach to Homestead, FL that was modified from the NOAA National Centers for Environmental Information (NCEI) Miami coastal DEM (NOAA, 2015) to project future seafloor elevation (from 2014) along the Miami section of the Florida Reef Tract. Grid resolution for the DEM is 1/3 arc second (approximately 10 meters).

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.

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 DEM ranges from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).

This tabular data set represents average depth to water table relative to the land surface(meters) compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for average depth to water table from the land surface was produced by Ying Fan and others (written communication, Rutgers University, 2007). Units are meters from land surface. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

The USGS and the NGA have collaborated on the development of a notably enhanced global elevation model named the GMTED2010 that replaces GTOPO30 as the elevation dataset of choice for global and continental scale applications. The new model has been generated at three separate resolutions (horizontal post spacing) of 30 arc-seconds (about 1 kilometer), 15 arc-seconds (about 500 meters), and 7.5 arc-seconds (about 250 meters). This new product suite provides global coverage of all land areas from latitude 84 degrees N to 56 degrees S for most products, and coverage from 84 degrees N to 90 degrees S for several products. Some areas, namely Greenland and Antarctica, do not have data available at the 15- and 7.5-arc-second resolutions because the input source data do not support that level of detail. An additional advantage of the new multi-resolution global model over GTOPO30 is that seven new raster elevation products are available at each resolution. The new elevation products have been produced using the following aggregation methods: minimum elevation, maximum elevation, mean elevation, median elevation, standard deviation of elevation, systematic subsample, and breakline emphasis. The systematic subsample product is defined using a nearest neighbor resampling function, whereby an actual elevation value is extracted from the input source at the center of a processing window. Most vertical heights in GMTED2010 are referenced to the Earth Gravitational Model 1996 (EGM 96) geoid (NGA, 2010). In addition to the elevation products, detailed spatially referenced metadata containing attribute fields such as coordinates, projection information, and raw source elevation statistics have been generated on a tile-by-tile basis for all the input datasets that constitute the global elevation model. GMTED2010 is based on data derived from 11 raster-based elevation sources.

United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data was reported at 2.264 % in 2010. This records an increase from the previous number of 2.246 % for 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data is updated yearly, averaging 2.264 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 2.329 % in 1990 and a record low of 2.246 % in 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Urban population below 5m is the percentage of the total population, living in areas where the 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;

Ce modèle numérique d'altitude (MNT) a été créé à partir du jeu de données de terrain principal (MTD) de Hakai au moyen de l'outil « MNT to raster » dans ArcGIS for Desktop d'ESRI à l'aide d'une méthode d'échantillonnage Natural Neighbour. Le DEM a été créé en mode natif à une résolution de 3 m. Ce DEM a été fixé à une zone tampon à 10 m du rivage. Une combinaison de différentes altitudes autour de l'île a été utilisée pour créer le rivage.

Le MNT qui en résulte est un modèle d'élévation hydroaplati en terre nue et donc considéré comme « topographiquement complet ». Chaque pixel représente l'altitude en mètres au-dessus du niveau moyen de la mer de la terre nue à cet endroit. Le système de référence vertical est le « Système de référence géodésique vertical canadien 1928 » (CGVD28).

Hakai a produit des DEM à différentes résolutions de manière native directement à partir du MTD des données LiDAR. Pour vos recherches, veuillez utiliser le produit de résolution approprié parmi ceux produits par Hakai. Afin de maintenir l'homogénéité, il n'est pas recommandé de procéder à un suréchantillonnage ou à une mise à l'échelle supérieure à partir de produits de résolution supérieure car cela pourrait introduire et propager des erreurs de différentes grandeurs dans les analyses en cours ; veuillez utiliser des produits déjà disponibles, et si vous avez besoin d'une résolution non disponible, contactez data@hakai.org afin d'obtenir un DEM produit directement à partir du MTD.

Les DEM topographiquement complets suivants ont été produits en mode natif à partir du DTM par Hakai :

MNE topographiquement complète de 3 m. Ce produit a été utilisé pour produire les ensembles de données hydrologiques de Hakai (cours d'eau et bassins versants) DEM Topographiquement complet de 20 m. Compatible avec les mesures du couvert végétal de Hakai et les rasters associés. MNT topographiquement complet de 25 m. Compatible avec les produits de données TRIM BCGov. DEM Topographiquement complet de 30 m. Compatible avec les produits STRM.

Création du jeu de données de terrain principal

Nuages de points LiDAR issus de missions effectuées en 2012 et 2014 au-dessus de l'île Calvert où ils ont été chargés (XYZ uniquement) dans une classe d'entités ponctuelles d'une géodatabase ESRI.

Seul le sol (classe 2) renvoie l'endroit où il est chargé dans la géodatabase.

Le « jeu de données de MNT » ESRI a été créé dans la même géodatabase à l'aide des points LiDAR en tant que points de masse intégrés.

Les lacs et les étangs TEM Plus avec des valeurs d'altitude moyennes au-dessus des miroirs des plans d'eau ont été utilisés comme lignes de rupture de remplacement dur pour obtenir un hydroaplatissement.

La géométrie d'emprise minimale de toutes les étendues de fichiers LAS contigus a été utilisée comme masque de découpe souple lors de la création du jeu de données de MNT en tant que limite de projet.

Le système de coordonnées horizontales et le datum utilisés pour le jeu de données de MNT sont : UTM Zone 9 NAD1983 ; le système de référence vertical a été défini sur CGVD28. Les deux systèmes de référence correspondent au système de référence natif des nuages de points LiDAR.

L'espacement minimal des points défini pendant la création du jeu de données de MNT a été défini sur 1.

The Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) provides a new level of detail in global topographic data. Previously, the best available global DEM was GTOPO30 with a horizontal grid spacing of 30 arc-seconds. The GMTED2010 product suite contains seven new raster elevation products for each of the 30-, 15-, and 7.5-arc-second spatial resolutions and incorporates the current best available global elevation data. The new elevation products have been produced using the following aggregation methods: minimum elevation, maximum elevation, mean elevation, median elevation, standard deviation of elevation, systematic subsample, and breakline emphasis. Metadata have also been produced to identify the source and attributes of all the input elevation data used to derive the output products. Many of these products will be suitable for various regional continental-scale land cover mapping, extraction of drainage features for hydrologic modeling, and geometric and radiometric correction of medium and coarse resolution satellite image data. The global aggregated vertical accuracy of GMTED2010 can be summarized in terms of the resolution and RMSE of the products with respect to a global set of control points (estimated global accuracy of 6 m RMSE) provided by the National Geospatial-Intelligence Agency (NGA). At 30 arc-seconds, the GMTED2010 RMSE range is between 25 and 42 meters; at 15 arc-seconds, the RMSE range is between 29 and 32 meters; and at 7.5 arc-seconds, the RMSE range is between 26 and 30 meters. GMTED2010 is a major improvement in consistency and vertical accuracy over GTOPO30, which has a 66 m RMSE globally compared to the same NGA control points. In areas where new sources of higher resolution data were available, the GMTED2010 products are substantially better than the aggregated global statistics; however, large areas still exist, particularly above 60 degrees North latitude, that lack good elevation data. As new data become available, especially in areas that have poor coverage in the current model, it is hoped that new versions of GMTED2010 might be generated and thus gradually improve the global model.

description: A digital elevation model (DEM) of a portion of the Potato Creek watershed in Georgia was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 27, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .; abstract: A digital elevation model (DEM) of a portion of the Potato Creek watershed in Georgia was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 27, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

DEM is the English abbreviation of Digital Elevation Model, which is the important original data of watershed topography and feature recognition.DEM is based on the principle that the watershed is divided into cells of m rows and n columns, the average elevation of each quadrilateral is calculated, and then the elevation is stored in a two-dimensional matrix.Since DEM data can reflect local topographic features with a certain resolution, a large amount of surface morphology information can be extracted through DEM, which includes slope, slope direction and relationship between cells of watershed grid cells, etc..At the same time, the surface flow path, river network and watershed boundary can be determined according to certain algorithm.Therefore, to extract watershed features from DEM, a good watershed structure pattern is the premise and key of the design algorithm. Elevation data map 1km data formed according to 1:250,000 contour lines and elevation points in China, including DEM, hillshade, Slope and Aspect maps. Data set projection: Two projection methods: Equal Area projection Albers Conical Equal Area (105, 25, 47) Geodetic coordinates WGS84 coordinate system

Elevation Derivatives for National Applications (EDNA) is a seamless, nationwide, multi-layered three-dimensional (3D) hydrologic database derived from a version of the National Elevation Dataset. EDNA's 3D hydrologic layers are vertically consistent by their very nature, meaning that hydrologic drainage always flows from a higher elevation to a lower elevation and that reach catchment boundaries always follow the elevation drainage divide. This consistency allows for transfer of valuable information from digital elevation models onto EDNA-derived drainage lines and watersheds, including stream gradient, minimum and maximum elevation within a watershed, average watershed slope, and elevation.

The National Ecological Framework for Canada's "Elevation by Ecodistrict” dataset provides elevation information for ecodistrict framework polygons, in meters. It includes codes and descriptions for minimum elevation, maximum elevation, mean elevation and the difference in elevation.

Bathymetry for Mobile Bay was derived from twenty-three surveys containing 173,661 soundings. Older, overlapping, less accurate surveys were deleted. The average separation between surveys was 79 meters. The surveys used dated from 1960 to 1962. The range of soundings for the surveys was 0.6 meters to -32.9 meters at mean low water. Mean high water values between 0.3 and 0.5 meters were assigned to the shoreline. Nine points were found that were not consistent with the surrounding data. These were removed prior to tinning. DEM grid values outside the shoreline (on land) were assigned null values (-32676). Mobile Bay has eighteen 7.5 minute DEMs and two one degree DEMs. The 1 degree DEMs were generated from the higher resolution 7.5 minute DEMs which covered the estuary. A Digital Elevation Model (DEM) contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A- record), followed by a series of profile records (B- records) each of which include a short B-record header followed by a series of ASCII integer elevations (typically in units of 1 centimeter) per each profile. The last physical record of the DEM is an accuracy record (C-record). The 7.5-minute DEM (30- by 30-m data spacing) is cast on the Universal Transverse Mercator (UTM) projection. It provides coverage in 7.5- by 7.5-minute blocks. Each product provides the same coverage as a standard USGS 7.5-minute quadrangle but the DEM contains over edge data. Coverage is available for many estuaries of the contiguous United States but is not complete.

Ce MNT a été créé à partir du jeu de données de terrain principal (MTD) de Hakai à l'aide de l'outil « MNT to raster » dans ArcGIS for Desktop d'ESRI à l'aide d'une méthode d'échantillonnage Natural Neighbour. Le DEM a été créé nativement à une résolution de 20 m. Ce MNE a été coupé sur le littoral de l'île. Une combinaison de différentes altitudes autour de l'île a été utilisée pour créer le rivage.

La grille de ce MNT est alignée ou « accrochée » à la grille raster des mesures de la canopée de végétation et des rasters associés.

Le MNT qui en résulte est un modèle d'élévation hydro-aplati à terre nue et donc considéré comme « topographiquement complet ». Chaque pixel représente l'altitude en mètres au-dessus du niveau moyen de la mer de la terre nue à cet endroit. Le système de référence vertical est « Canadian Geodetic Vertical Datum 1928 » (CGVD28).

Hakai a produit des DEM à différentes résolutions nativement à partir du MTD de données LiDAR. Veuillez utiliser le produit de résolution approprié de ceux produits par Hakai à des fins de recherche. Afin de maintenir l'homogénéité, il n'est pas recommandé d'échantillonnager/augmenter à partir de produits à haute résolution, car il peut introduire et propager des erreurs de grandeur variable dans les analyses en cours ; veuillez utiliser des produits déjà disponibles, et si vous avez besoin d'une résolution non disponible, contactez data@hakai.org afin d'obtenir un MNT produit directement à partir du MTD.

Les DEM topographiquement complets suivants ont été produits nativement à partir du DTM par Hakai :

MNT topographiquement complet de 3 m. Ce produit a été utilisé pour produire les jeux de données hydrologiques de Hakai (Streams and Watersheds) MNE topographiquement complet de 20 m. Compatible avec les mesures de la canopée de végétation de Hakai et les rasters associés. MNT topographiquement complet de 25 m Compatible avec les produits de données BCGov TRIM. MNE topographiquement complet de 30 m. Compatible avec les produits STRM.

Création d'un jeu de données de MNT principal :

Clouds de points LiDAR provenant de missions effectuées en 2012 et 2014 au-dessus de Calvert Island où ils sont chargés (XYZ uniquement) dans une classe d'entités ponctuelles dans une géodatabase ESRI.

Seul ground (classe 2) renvoie lorsqu'il est chargé sur la géodatabase.

Le « jeu de données de MNT » ESRI a été créé dans la même géodatabase à l'aide des points LiDAR comme points de masse intégrés.

Les lacs et étangs TEM Plus ayant des valeurs d'altitude moyennes au-dessus des miroirs des plans d'eau ont été utilisés comme lignes de fracture de remplacement dur pour obtenir un aplatissement hydro-aplati.

La géométrie limite minimale de tous les blocs de fichiers LAS contigus a été utilisée comme masque de clip souple lors de la création du jeu de données de MNT en tant que limite de projet.

Le système de coordonnées horizontales et la référence utilisés pour le jeu de données de MNT sont : UTM Zone 9 NAD1983 ; le système de référence vertical a été défini sur CGVD28. Les deux systèmes de référence correspondent au système de référence natif des nuages de points LiDAR.

L'espacement minimal des points défini lors de la création du jeu de données de MNT a été défini sur 1.

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.