12 datasets found
  1. Cities with the highest altitudes in the world

    • statista.com
    Updated Jan 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Cities with the highest altitudes in the world [Dataset]. https://www.statista.com/statistics/509341/highest-cities-in-the-world/
    Explore at:
    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    World
    Description

    The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits 3,869 meters above sea level, and is more than 1,000 meters higher than the second ranked city - Quito. La Paz is also higher than Mt. Fuji in Japan, which has a height of 3,776 meters. Many of the world's highest cities are located in South America. The only city in North America that makes the top 20 list is Denver, Colorado, which has an altitude of 1,673 meters.

  2. Global elevation spans by select country

    • statista.com
    Updated Feb 16, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Global elevation spans by select country [Dataset]. https://www.statista.com/statistics/935722/highest-and-lowest-elevation-points-worldwide-by-select-country/
    Explore at:
    Dataset updated
    Feb 16, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    World
    Description

    This statistic displays the countries with the greatest range between their highest and lowest elevation points. China and Nepal share the highest elevation point worldwide, which ascends to an amount of 8848 meters above sea level. Near the city Turpan Pendi, Xinjiang, China's elevation reaches 154 meters below sea level.

  3. a

    Surging Seas: Risk Zone Map

    • amerigeo.org
    • data.amerigeoss.org
    Updated Feb 18, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    AmeriGEOSS (2019). Surging Seas: Risk Zone Map [Dataset]. https://www.amerigeo.org/datasets/8a4ffc7b7ab3404a8cd4e4576fae7c1d
    Explore at:
    Dataset updated
    Feb 18, 2019
    Dataset authored and provided by
    AmeriGEOSS
    Description

    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.

  4. o

    Geonames - All Cities with a population > 1000

    • public.opendatasoft.com
    • data.smartidf.services
    • +3more
    csv, excel, geojson +1
    Updated Mar 10, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Geonames - All Cities with a population > 1000 [Dataset]. https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/
    Explore at:
    csv, json, geojson, excelAvailable download formats
    Dataset updated
    Mar 10, 2024
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

  5. United States: highest point in each state or territory

    • statista.com
    Updated Aug 8, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). United States: highest point in each state or territory [Dataset]. https://www.statista.com/statistics/203932/highest-points-in-the-united-states-by-state/
    Explore at:
    Dataset updated
    Aug 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005
    Area covered
    United States
    Description

    At 20,310 feet (6.2km) above sea level, the highest point in the United States is Denali, Alaska (formerly known as Mount McKinley). The highest point in the contiguous United States is Mount Whitney, in the Sierra Nevada mountain range in California; followed by Mount Elbert, Colorado - the highest point in the Rocky Mountains. When looking at the highest point in each state, the 13 tallest peaks are all found in the western region of the country, while there is much more diversity across the other regions and territories.

    Despite being approximately 6,500 feet lower than Denali, Hawaii's Mauna Kea is sometimes considered the tallest mountain (and volcano) on earth. This is because its base is well below sea level - the mountain has a total height of 33,474 feet, which is almost 4,500 feet higher than Mount Everest.

  6. United States: lowest point in each state or territory as of 2005

    • statista.com
    Updated Aug 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). United States: lowest point in each state or territory as of 2005 [Dataset]. https://www.statista.com/statistics/1325443/lowest-points-united-states-state/
    Explore at:
    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005
    Area covered
    United States
    Description

    At 282 feet below sea level, Death Valley in the Mojave Desert, California is the lowest point of elevation in the United States (and North America). Coincidentally, Death Valley is less than 85 miles from Mount Whitney, the highest point of elevation in the mainland United States. Death Valley is one of the hottest places on earth, and in 1913 it was the location of the highest naturally occurring temperature ever recorded on Earth (although some meteorologists doubt its legitimacy). New Orleans Louisiana is the only other state where the lowest point of elevation was below sea level. This is in the city of New Orleans, on the Mississippi River Delta. Over half of the city (up to two-thirds) is located below sea level, and recent studies suggest that the city is sinking further - man-made efforts to prevent water damage or flooding are cited as one reason for the city's continued subsidence, as they prevent new sediment from naturally reinforcing the ground upon which the city is built. These factors were one reason why New Orleans was so severely impacted by Hurricane Katrina in 2005 - the hurricane itself was one of the deadliest in history, and it destroyed many of the levee systems in place to prevent flooding, and the elevation exacerbated the damage caused. Highest low points The lowest point in five states is over 1,000 feet above sea level. Colorado's lowest point, at 3,315 feet, is still higher than the highest point in 22 states or territories. For all states whose lowest points are found above sea level, these points are located in rivers, streams, or bodies of water.

  7. Crescent City, California 1/3 arc-second MHW Coastal Digital Elevation Model...

    • datadiscoverystudio.org
    • s.cnmilf.com
    • +3more
    netcdf v.4 classic
    Updated Jul 14, 2010
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce (2010). Crescent City, California 1/3 arc-second MHW Coastal Digital Elevation Model [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/ea34f9b507b54fe2a60a2065543561c8/html
    Explore at:
    netcdf v.4 classicAvailable download formats
    Dataset updated
    Jul 14, 2010
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Environmental Satellite, Data, and Information Service
    Authors
    DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce
    Area covered
    Description

    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 warning 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 a variety of vertical datums and horizontal datum of World Geodetic System of 1984 (WGS84). Cell size for the DEMs ranges 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.

  8. Football stadiums located in the highest altitude worldwide 2020

    • statista.com
    Updated Feb 8, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Football stadiums located in the highest altitude worldwide 2020 [Dataset]. https://www.statista.com/statistics/1185193/highest-altitude-football-stadiums-worldwide/
    Explore at:
    Dataset updated
    Feb 8, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    World
    Description

    South America was home to the world's highest altitude soccer stadiums in 2020. At the top of the list was Daniel Alcides Carrión stadium, located at 4,380 meters above sea level (MASL), in the Peruvian city of Cerro del Pasco. It hosts matches during the Copa Perú, a regional football tournament. Also surpassing the four thousand meters of altitude, the municipal stadium of El Alto ranked second that year, followed by Víctor Agustín stadium, at 3,960 MASL. Both of these stadiums are located in Bolivia, which is also home to the highest altitude soccer stadium in a capital city &#8211 Hernando Siles stadium, in La Paz.

  9. a

    World Elevation Terrain

    • bangladesh-gis-hub-unhcr.hub.arcgis.com
    • hub.arcgis.com
    Updated May 27, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    krolikie@unhcr.org_unhcr (2019). World Elevation Terrain [Dataset]. https://bangladesh-gis-hub-unhcr.hub.arcgis.com/datasets/d31dde17965741f2999de4506b9dde53
    Explore at:
    Dataset updated
    May 27, 2019
    Dataset authored and provided by
    krolikie@unhcr.org_unhcr
    Area covered
    Description

    This dynamic World Elevation Terrain service provides numeric values representing ground surface heights, based on a digital terrain model (DTM). The ground heights are based on multiple sources. Heights are orthometric (sea level = 0), and water bodies that are above sea level have approximated nominal water heights.What can you do with this layer?Use for Visualization: This layer is generally not optimal for direct visualization. By default, 32 bit floating point values are returned, resulting in higher bandwidth requirements. Therefore, usage should be limited to applications requiring elevation data values. Alternatively, client applications can select from numerous additional functions, applied on the server, that return rendered data. For visualizations such as multi-directional hillshade, hillshade, elevation tinted hillshade, and slope, consider using the appropriate server-side function defined on this service.Use for Analysis: Yes. This layer provides data as floating point elevation values suitable for use in analysis.NOTE: The image services combine data from different sources and resample the data dynamically to the requested projection, extent and pixel size. For analyses requiring the highest accuracy, when using ArcGIS Desktop, you will need to use native coordinates and specify the native resolutions (refer to the table under Data Sources) as the cell size geoprocessing environment setting and ensure that the request is aligned with the source pixels.Server Functions: This layer has server functions defined for the following elevation derivatives:Slope DegreesSlope PercentageAspectEllipsoidal heightHillshadeMulti-Directional HillshadeDark Multi-Directional Hillshade (BETA)Pre-symbolized Elevation Tinted HillshadePre-symbolized Slope DegreesPre-symbolized AspectData Sources: The data for this layer comes from the multiple sources listed below, with original source data in its native coordinate system. Depending on the scale being viewed; data from one of these datasets will be returned:

    Source Data

    Source Native Pixel Size

    Approximate Pixel Size (m)

    Primary Sources

    Grand Geneva 50cm

    0.5 meters

    0.5

    SITG

    Canton of Basel-Landschaft 25cm

    0.25 meters

    0.25

    Geoinformation Kanton Basel-Landschaft

    Canton of Solothurn 50cm

    0.5 meters

    0.5

    Geoinformation Kanton Solothurn

    Canton of Aargau 50cm

    0.5 meters

    0.5

    Aargauische Geografische Informationssystem

    Canton of Zurich 50cm

    0.5 meters

    0.5

    Geoinformation Kanton Zürich

    Estonia 1m

    1 meter

    1

    Estonian Land Board

    Estonia 5m

    5 meters

    5

    Estonian Land Board

    Estonia 10m

    10 meters

    10

    Estonian Land Board

    England 2m

    2 meters

    2

    Environment Agency

    Wales 2m

    2 meters

    2

    Natural Resources Wales

    Scotland 1m

    1 meter

    1

    Scottish Government et.al

    Netherlands 3m

    3 meters

    3

    Rijkswaterstaat

    Nordrhein-Westfalen 1m

    1 meter

    1

    Land NRW

    Vienna City 1m

    1 meter

    1

    City of Vienna

    Upper Austria 50cm

    0.5 meters

    0.5

    Land Oberosterreich

    Salzburg 5m

    5 meters

    5

    Land Salzburg

    Vorarlberg 5m

    5 meters

    5

    Land Vorarlberg

    Tyrol 5m

    5 meters

    5

    Land Tyrol

    Carinthia 5m

    5 meters

    5

    Land Carinthia

    Austria 10m

    10 meters

    10

    Geoland

    Denmark 3m

    3.2 meters

    3

    Geodatastyrelsen

    Denmark 10m

    10 meters

    10

    Geodatastyrelsen

    Finland 3m

    3 meters

    3

    NLS

    Finland 10m

    10 meters

    10

    NLS

    Japan DEM5A, DEM5B

    0.000055555555 degrees

    5

    GSI

    Japan DEM10B

    0.00011111111 degrees

    10

    GSI

    Madrid City 1m

    1 meter

    1

    Ayuntamiento de Madrid

    Spain 5m

    5 meters

    5

    IGN

    Spain 10m

    10 meters

    10

    IGN

    Norway 10m

    10 meters

    10

    NMA

    OS Terrain 50

    50 meters

    50

    Ordnance Survey

    FEMA LiDAR DTM

    3 meters

    3

    FEMA

    NRCS 1m

    1 meter

    1

    NRCS USDA

    3DEP 1m

    1 meter

    1

    USGS

    NED 1/9 arc second

    0.000030864197530866 degrees

    3

    USGS

    NED 1/3 arc second

    0.000092592592593 degrees

    10

    USGS

    NED 1 arc second

    0.0002777777777779 degrees

    31

    USGS

    NED 2 arc second

    0.000555555555556 degrees

    62

    USGS

    WorldDEM4Ortho

    0.00022222222 degrees

    24

    Airbus Defense and Space GmbH

    SRTM 1 arc second

    0.0002777777777779 degrees

    31

    NASA

    SRTM 1 arc second DEM-S

    0.0002777777777779 degrees

    31

    Geoscience Australia

    SRTM v4.1

    0.00083333333333333 degrees

    93

    CGIAR-CSI

    EarthEnv-DEM90

    0.00083333333333333 degrees

    93

    N Robinson,NCEAS

    GMTED2010 7.5 arc second

    0.00208333333333333 degrees

    232

    USGS

    GMTED2010 15 arc second

    0.00416666666666666 degrees

    464

    USGS

    GMTED2010 30 arc second

    0.0083333333333333 degrees

    928

    USGS

    Mosaic Method: This image service uses a default mosaic method of "By Attribute”, using Field 'Best' and target of 0. Each of the rasters has been attributed with ‘Best’ field value that is generally a function of the pixel size such that higher resolution datasets are displayed at higher priority. Other mosaic methods can be set, but care should be taken as the order of the rasters may change. Where required, queries can also be set to display only specific datasets such as only NED or the lock raster mosaic rule used to lock to a specific dataset.Data Coverage: To see the coverage of various datasets comprising this service, click here.Accuracy: The accuracy of these services will vary as a function of location and data source. Please refer to the metadata available in the services, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes.This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single request.This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

  10. d

    Ocean City, Maryland Coastal Digital Elevation Model.

    • datadiscoverystudio.org
    • data.wu.ac.at
    html, nc
    Updated Feb 8, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2018). Ocean City, Maryland Coastal Digital Elevation Model. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/eeeceb51eebe45659b37212569a8ad42/html
    Explore at:
    nc, htmlAvailable download formats
    Dataset updated
    Feb 8, 2018
    Description

    description: 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 warning 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 (WGS 84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).; abstract: 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 warning 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 (WGS 84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).

  11. Z

    Identifying environmentally-comparable cities across the globe for urban...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Feb 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cristian Roman (2023). Identifying environmentally-comparable cities across the globe for urban ecology studies [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_7586607
    Explore at:
    Dataset updated
    Feb 2, 2023
    Dataset provided by
    Kyle Arechiga
    Cristian Roman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Defining a comprehensive and quantitative framework for comparing urban areas is a priority for conducting research in urban ecology and related fields. In this study, we use unsupervised learning on a matrix of climate- and human-related features to estimate the number of groups explaining the characteristics of ~6,000 cities across the globe. Using estimates of city-level stability within clusters, we estimate that cities can be clustered in 5–7 clusters, with 6 being the most likely and stable number of groups. Groups of cities are primarily defined by climatic and geographical features (e.g. elevation), with population-level and land use parameters being less relevant for structuring cities. City clusters generally correspond with a continental-based partitioning. However, geographic distances between cities do not necessarily reflect their position in the examined multivariate space. The analytical framework presented in this paper can be extended to accounting for alternative features to describing cities and their characteristics. We implement an online web application for comparing cities across the globe based on the results presented in this study. This application is expected to inform decisions on where to sample populations or species in cities with either similar or divergent climatic conditions.

  12. Lowest elevations on earth

    • statista.com
    Updated Jan 19, 2016
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2016). Lowest elevations on earth [Dataset]. https://www.statista.com/statistics/504443/the-lowest-places-on-earth/
    Explore at:
    Dataset updated
    Jan 19, 2016
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2016
    Area covered
    World
    Description

    This statistic shows a ranking of the ten lowest places on earth based on elevation below sea level. The world's lowest place on earth is the Dead Sea located in Jordan and Israel, with an elevation amounting to approximately 414 meters below sea level.

  13. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Cities with the highest altitudes in the world [Dataset]. https://www.statista.com/statistics/509341/highest-cities-in-the-world/
Organization logo

Cities with the highest altitudes in the world

Explore at:
Dataset updated
Jan 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2020
Area covered
World
Description

The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits 3,869 meters above sea level, and is more than 1,000 meters higher than the second ranked city - Quito. La Paz is also higher than Mt. Fuji in Japan, which has a height of 3,776 meters. Many of the world's highest cities are located in South America. The only city in North America that makes the top 20 list is Denver, Colorado, which has an altitude of 1,673 meters.

Search
Clear search
Close search
Google apps
Main menu