16 datasets found
  1. United States: lowest point in each state or territory as of 2005

    • statista.com
    Updated Aug 9, 2024
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    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/
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    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.

  2. U.S. population at risk of rising sea levels by city 2060-2100

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). U.S. population at risk of rising sea levels by city 2060-2100 [Dataset]. https://www.statista.com/statistics/1110480/flood-risk-population-sea-level-rise/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In Miami Beach, Florida, around ****** residents live in homes at risk to being flooded by 2060 due to rising sea levels. Florida has many cities that may be lost to coastal erosion as a result of sea level rise, as well as storm surges. The significance of sea level rise is particularly great for the many cities with high values of assets that are under threat.

  3. United States: average elevation in each state or territory as of 2005

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). United States: average elevation in each state or territory as of 2005 [Dataset]. https://www.statista.com/statistics/1325529/lowest-points-united-states-state/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005
    Area covered
    United States
    Description

    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.

  4. A

    Surging Seas: Risk Zone Map

    • data.amerigeoss.org
    Updated Feb 18, 2019
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    AmeriGEOSS (2019). Surging Seas: Risk Zone Map [Dataset]. https://data.amerigeoss.org/dataset/surging-seas-risk-zone-map2
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    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Feb 18, 2019
    Dataset provided by
    AmeriGEOSS
    Description

    Introduction

    Climate 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 top


    Methods and Qualifiers

    This 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 Alaska
    Elevation 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

  5. a

    Sea Level Rise Model for 2030 for the United States

    • hub.arcgis.com
    Updated Sep 12, 2023
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    MapMaker (2023). Sea Level Rise Model for 2030 for the United States [Dataset]. https://hub.arcgis.com/maps/123e28ee1e87448885a41b974efadf1f
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    Dataset updated
    Sep 12, 2023
    Dataset authored and provided by
    MapMaker
    License

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

    Area covered
    Description

    The average level of the ocean has been rising since we started measuring and recording this data. According to the National Aeronautics and Space Agency (NASA), since 1900 the global mean sea level has risen more than 200 millimeters (nearly 8 inches) and nearly half of that increase has occurred since 1993 in a concerning change in rate of rise.Sea level rise is one of the many effects of global warming. Scientists attribute sea level rise to two things, melting ice and increased ocean water temperatures. Increasing air temperatures, particularly in the polar regions, has encouraged the melting of land-based ice reserves such as glaciers, ice sheets, and permafrost. Historically, warm season ice melt was balanced by replenishment during the cold season but warming temperatures have created conditions where melting exceeds the buildup of ice. This water flows through rivers and streams to the ocean in quantities sufficient to contribute to sea level rise.Oceans are also massive heat sinks. They pull large quantities of atmospheric heat and greenhouse gases such as carbon dioxide and store it in the ocean. The sea changes temperature much more slowly than the air and over time ocean temperatures have continued to build. As the ocean water warms it expands causing the sea levels to rise.Sea levels are not rising equally across Earth. Some areas are already experiencing significant impacts due to the rising water levels while others have seen minimal changes. This is due to a variety of reasons. First, despite how it is typically illustrated Earth is not perfectly round so the height of the ocean at any given point varies. This can be due to the Earth’s rotation, ocean currents, or prevailing wind speed and direction.Experts consider sea level rise and urgent climatic threat. Many low-lying places such as islands and coastal areas are already experiencing high waters. Higher waters also make storms such as hurricanes more dangerous due to higher storm surges and flooding. As coastlines could lose key infrastructure, land will become uninhabitable, and many people could lose their livelihoods. It is estimated 10 percent of the world’s population could be impacted as the waters rise. Many of the approximately 770 million people could be forced to migrate to higher ground, or in the case of island countries, such as Kiribati, to new countries once theirs sinks below the sea.This map was created with data from the National Oceanic and Atmospheric Administration (NOAA), NASA, and the United States Geological Survey. Experts used an elevation data and the NOAA model Scenarios of Future Mean Seal Level to illustrate the scale of potential coastal flooding. The mapmaker chose to remove levees from the data, so the areas flooded include places, particularly in the states of Texas and Louisiana, that are presently protected by this infrastructure. It is important to note that these are possible outcomes. This model does not include possible erosion, subsidence, or construction that may occur between 2022 when this data was created and 2030, 2050, or 2090 respectively. While models are powerful tools it is difficult to calculate every aspect that shapes our environment.Learn more about how coastal communities are impacted by sea level rise with this StoryMap by NOAA’s Office for Coastal Management, The King Tides Project: Snap the shore, See the Future.

  6. a

    Sea Level Rise Model for 2050 for the United States

    • impactmap-smudallas.hub.arcgis.com
    • hub.arcgis.com
    Updated Mar 18, 2024
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    SMU (2024). Sea Level Rise Model for 2050 for the United States [Dataset]. https://impactmap-smudallas.hub.arcgis.com/maps/94da4a7229bc4dce921b7971f3dd1f7c
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    Dataset updated
    Mar 18, 2024
    Dataset authored and provided by
    SMU
    Area covered
    Description

    The average level of the ocean has been rising since we started measuring and recording this data. According to the National Aeronautics and Space Agency (NASA), since 1900 the global mean sea level has risen more than 200 millimeters (nearly 8 inches) and nearly half of that increase has occurred since 1993 in a concerning change in rate of rise.Sea level rise is one of the many effects of global warming. Scientists attribute sea level rise to two things, melting ice and increased ocean water temperatures. Increasing air temperatures, particularly in the polar regions, has encouraged the melting of land-based ice reserves such as glaciers, ice sheets, and permafrost. Historically, warm season ice melt was balanced by replenishment during the cold season but warming temperatures have created conditions where melting exceeds the buildup of ice. This water flows through rivers and streams to the ocean in quantities sufficient to contribute to sea level rise.Oceans are also massive heat sinks. They pull large quantities of atmospheric heat and greenhouse gases such as carbon dioxide and store it in the ocean. The sea changes temperature much more slowly than the air and over time ocean temperatures have continued to build. As the ocean water warms it expands causing the sea levels to rise.Sea levels are not rising equally across Earth. Some areas are already experiencing significant impacts due to the rising water levels while others have seen minimal changes. This is due to a variety of reasons. First, despite how it is typically illustrated Earth is not perfectly round so the height of the ocean at any given point varies. This can be due to the Earth’s rotation, ocean currents, or prevailing wind speed and direction.Experts consider sea level rise and urgent climatic threat. Many low-lying places such as islands and coastal areas are already experiencing high waters. Higher waters also make storms such as hurricanes more dangerous due to higher storm surges and flooding. As coastlines could lose key infrastructure, land will become uninhabitable, and many people could lose their livelihoods. It is estimated 10 percent of the world’s population could be impacted as the waters rise. Many of the approximately 770 million people could be forced to migrate to higher ground, or in the case of island countries, such as Kiribati, to new countries once theirs sinks below the sea.This map was created with data from the National Oceanic and Atmospheric Administration (NOAA), NASA, and the United States Geological Survey. Experts used an elevation data and the NOAA model Scenarios of Future Mean Seal Level to illustrate the scale of potential coastal flooding. The mapmaker chose to remove levees from the data, so the areas flooded include places, particularly in the states of Texas and Louisiana, that are presently protected by this infrastructure. It is important to note that these are possible outcomes. This model does not include possible erosion, subsidence, or construction that may occur between 2022 when this data was created and 2030, 2050, or 2090 respectively. While models are powerful tools it is difficult to calculate every aspect that shapes our environment.Learn more about how coastal communities are impacted by sea level rise with this StoryMap by NOAA’s Office for Coastal Management, The King Tides Project: Snap the shore, See the Future.

  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
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    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
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    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. United States: highest point in each state or territory

    • statista.com
    Updated Aug 8, 2024
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    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/
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    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.

  9. Panama City, Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    • datadiscoverystudio.org
    • datasets.ai
    • +4more
    netcdf v.3.6.2
    Updated Jul 1, 2010
    + more versions
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    DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce (2010). Panama City, Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/f76d11507bec4c9f835e66197d8d2f8f/html
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    netcdf v.3.6.2Available download formats
    Dataset updated
    Jul 1, 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 in the Gulf of Mexico. These integrated bathymetric-topographic DEMs were developed for NOAA Coast Survey Development Laboratory (CSDL) through the American Recovery and Reinvestment Act (ARRA) of 2009 to evaluate the utility of the Vertical Datum Transformation tool (VDatum), developed jointly by NOAA's Office of Coast Survey (OCS), National Geodetic Survey (NGS), and Center for Operational Oceanographic Products and Services (CO-OPS). Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. Coastal Services Center (CSC), the U.S. Office of Coast Survey (OCS), the U.S. Army Corps of Engineers (USACE), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of North American Vertical Datum of 1988 (NAVD 88) or Mean High Water (MHW) and horizontal datum of North American Datum of 1983 (NAD 83). Grid spacings for both DEMs are 1/3 arc-second (~10 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 (NAVD88). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service provides data from many individual DEMs combined together as a mosaic. By default, the rasters are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Alternatively, a single DEM or group of DEMs can be isolated using a filter/definition query or using the 'Lock Raster 'mosaic method in ArcMap. This is one of three services displaying collections of DEMs that are referenced to common vertical datums: North American Vertical Datum of 1988 (NAVD88): http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042, Mean High Water (MHW): http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799, and Mean Higher High Water: http://noaa.maps.arcgis.com/home/item.html?id=9471f8d4f43e48109de6275522856696. In addition, the DEM Global Mosaic is a general-purpose global, seamless bathymetry/topography mosaic containing all the DEMs together. Two services are available: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff Elevation Values: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff and Color Shaded Relief: http://noaa.maps.arcgis.com/home/item.html?id=feb3c625dc094112bb5281c17679c769. Please see the corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. This service has several server-side functions available. These can be selected in the ArcGIS Online layer using 'Image Display ', or in ArcMap under 'Processing Templates '. None: The default. Provides elevation/depth values in meters relative to the NAVD88 vertical datum. ColorHillshade: An elevation-tinted hillshade visualization. The depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png. GrayscaleHillshade: A simple grayscale hillshade visualization. SlopeMapRGB: Slope in degrees, visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/SlopeMapLegend_V7b.png. SlopeNumericValues: Slope in degrees, returning the actual numeric values. AspectMapRGB: Orientation of the terrain (0-360 degrees), visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/AspectMapLegendPie_V7b.png. AspectNumericValues: Aspect in degrees, returning the actual numeric values.

  10. d

    1 foot Digital Elevation Model (DEM) Integer Raster

    • catalog.data.gov
    • data.cityofnewyork.us
    • +2more
    Updated Nov 1, 2024
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    data.cityofnewyork.us (2024). 1 foot Digital Elevation Model (DEM) Integer Raster [Dataset]. https://catalog.data.gov/dataset/1-foot-digital-elevation-model-dem-integer-raster
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    Dataset updated
    Nov 1, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    A bare-earth, hydro-flattened, digital-elevation surface model derived from 2010 Light Detection and Ranging (LiDAR) data. Surface models are raster representations derived by interpolating the LiDAR point data to produce a seamless gridded elevation data set. A Digital Elevation Model (DEM) is a surface model generated from the LiDAR returns that correspond to the ground with all buildings, trees and other above ground features removed. The cell values represent the elevation of the ground relative to sea level. The DEM was generated by interpolating the LiDAR ground points to create a 1 foot resolution seamless surface. Cell values correspond to the ground elevation value (feet) above sea level. A proprietary approach to surface model generation was developed that reduced spurious elevation values in areas where there were no LiDAR returns, primarily beneath buildings and over water. This was combined with a detailed manual QA/QC process, with emphasis on accurate representation of docks and bare-earth within 2000ft of the water bodies surrounding each of the five boroughs.

  11. d

    1 foot Digital Elevation Model (DEM)

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +4more
    Updated Nov 1, 2024
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    data.cityofnewyork.us (2024). 1 foot Digital Elevation Model (DEM) [Dataset]. https://catalog.data.gov/dataset/1-foot-digital-elevation-model-dem
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    Dataset updated
    Nov 1, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    NYC 1foot Digital Elevation Model: A bare-earth, hydro-flattened, digital-elevation surface model derived from 2010 Light Detection and Ranging (LiDAR) data. Surface models are raster representations derived by interpolating the LiDAR point data to produce a seamless gridded elevation data set. A Digital Elevation Model (DEM) is a surface model generated from the LiDAR returns that correspond to the ground with all buildings, trees and other above ground features removed. The cell values represent the elevation of the ground relative to sea level. The DEM was generated by interpolating the LiDAR ground points to create a 1 foot resolution seamless surface. Cell values correspond to the ground elevation value (feet) above sea level. A proprietary approach to surface model generation was developed that reduced spurious elevation values in areas where there were no LiDAR returns, primarily beneath buildings and over water. This was combined with a detailed manual QA/QC process, with emphasis on accurate representation of docks and bare-earth within 2000ft of the water bodies surrounding each of the five boroughs. Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_DigitalElevationModel.md

  12. d

    NYC Stormwater Flood Maps

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Oct 19, 2024
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    data.cityofnewyork.us (2024). NYC Stormwater Flood Maps [Dataset]. https://catalog.data.gov/dataset/nyc-stormwater-flood-maps
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    Dataset updated
    Oct 19, 2024
    Dataset provided by
    data.cityofnewyork.us
    Area covered
    New York
    Description

    A collection of citywide Geographic Information System (GIS) layers that show areas of potential flooding scenarios under varying sea level rise conditions. Please see the New York City Stormwater Resiliency Plan for more information about the methodology applied to develop the maps. Please direct questions or comments to StormwaterResiliency@cityhall.nyc.gov. This collection contains the following NYC Stormwater Flood Maps: NYC Stormwater Flood Map - Extreme Flood (3.66 inches/hr) with 2080 Sea Level Rise NYC Stormwater Flood Map - Moderate Flood (2.13 inches/hr) with 2050 Sea Level Rise NYC Stormwater Flood Map - Moderate Flood (2.13 inches/hr) with Current Sea Levels NYC Stormwater Flood Map - Limited Flood (1.77 inches/hr) with Current Sea Levels https://www1.nyc.gov/assets/orr/pdf/publications/stormwater-resiliency-plan.pdf Source Data: http://nyc.gov/stormwater-map

  13. d

    Elevation of the regional transgressive unconformity underlying the inner...

    • search.dataone.org
    • s.cnmilf.com
    • +2more
    Updated Mar 30, 2017
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    U.S. Geological Survey (2017). Elevation of the regional transgressive unconformity underlying the inner shelf of Long Bay (Grid; transgr_grd) [Dataset]. https://search.dataone.org/view/16151ed6-ba01-4d47-b489-9afe372b609f
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    Dataset updated
    Mar 30, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Time period covered
    Jan 1, 1999 - Jan 1, 2003
    Area covered
    Description

    In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this geologic framework and identifying the transport pathways and sinks of sediment, geoscientists are developing conceptual models of the present-day physical processes shaping the South Carolina coast. The primary objectives of this research effort are: 1) to provide a regional synthesis of the shallow geologic framework underlying the coastal upland, shoreface and inner continental shelf, and define its role in coastal evolution and modern beach behavior; 2) to identify and model the physical processes affecting coastal ocean circulation and sediment transport, and to define their role in shaping the modern shoreline; and 3) to identify sediment sources and transport pathways; leading to construction of a regional sediment budget. This data set contains a surface depicting the elevation of the regional transgressive unconformity underlying the inner shelf of Long Bay, offshore of the South Carolina Grand Strand. Chirp seismic data collected with Benthos SIS-1000 and Edgetech SB-512 acquisition systems were processed using SIOSEIS (Scripps Institute of Oceanography) and Seismic Unix (Colorado School of Mines) to produce segy files and jpg images of the profiles. Data were then imported into Landmark SeisWorks, a digital seismic interpretation package, where the sea floor and underlying transgressive surface were interpreted and digitized. The isopach between these horizons was exported at every 50th shot as xyz points, and imported to ArcGIS for interpolation into a 10-m raster grid. The isopach grid was then subtracted from a seafloor bathymetry grid (bathy_grd) to approximate the proper elevation of the transgressive unconformity beneath the sea floor.

  14. c

    State of Colorado Basemap

    • geodata.colorado.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Mar 1, 2023
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    State of Colorado (2023). State of Colorado Basemap [Dataset]. https://geodata.colorado.gov/maps/62f677708c5040399e490cc58505cdec
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    Dataset updated
    Mar 1, 2023
    Dataset authored and provided by
    State of Colorado
    Area covered
    Description

    This web map created by the Colorado Governor's Office of Information Technology GIS team, serves as a basemap specific to the state of Colorado. The basemap includes general layers such as counties, municipalities, roads, waterbodies, state parks, national forests, national wilderness areas, and trails.Layers:Layer descriptions and sources can be found below. Layers have been modified to only represent features within Colorado and are not up to date. Layers last updated February 23, 2023. Colorado State Extent: Description: “This layer provides generalized boundaries for the 50 States and the District of Columbia.” Notes: This layer was filtered to only include the State of ColoradoSource: Esri Living Atlas USA States Generalized Boundaries Feature LayerState Wildlife Areas:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state wildlife areas layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer hosted in ArcGIS Online Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerMunicipal Boundaries:Description: "Boundaries data from the State Demography Office of Colorado Municipalities provided by the Department of Local Affairs (DOLA)"Source: Colorado Information Marketplace Municipal Boundaries in ColoradoCounties:Description: “This layer presents the USA 2020 Census County (or County Equivalent) boundaries of the United States in the 50 states and the District of Columbia. It is updated annually as County (or County Equivalent) boundaries change. The geography is sources from US Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrology to add a detailed coastline for cartographic purposes. Geography last updated May 2022.” Notes: This layer was filtered to only include counties in the State of ColoradoSource: Esri USA Census Counties Feature LayerInterstates:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: Interstates are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointU.S. Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: U.S. Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointState Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: State Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointMajor Roads:Description: Authoritative data from the Colorado Department of Transportation representing major roads Source: Colorado Department of Transportation Major Roads REST EndpointLocal Roads:Description: Authoritative data from the Colorado Department of Transportation representing local roads Source: Colorado Department of Transportation Local Roads REST EndpointRail Lines:Description: Authoritative data from the Colorado Department of Transportation representing rail lines Source: Colorado Department of Transportation Rail Lines REST EndpointCOTREX Trails:Description: “The Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently their are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments). Responsibility for accuracy of the data rests with the source.These data were last updated on 2/5/2019” Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerNHD Waterbodies:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include waterbodies in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerNHD Flowlines:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include flowline features in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerState Parks:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state parks layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerDenver Parks:Description: "This dataset should be used as a reference to locate parks, golf courses, and recreation centers managed by the Department of Parks and Recreation in the City and County of Denver. Data is based on parcel ownership and does not include other areas maintained by the department such as medians and parkways. The data should be used for planning and design purposes and cartographic purposes only."Source: City and County of Denver Parks REST EndpointNational Wilderness Areas:Description: “A parcel of Forest Service land congressionally designated as wilderness such as National Wilderness Area.”Notes: This layer was filtered to only include National Wilderness Areas in the State of ColoradoSource: United States Department of Agriculture National Wilderness Areas REST EndpointNational Forests: Description: “A depiction of the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with subsequent Executive Orders, Proclamations, Public Laws, Public Land Orders, Secretary of Agriculture Orders, and Secretary of Interior Orders creating modifications thereto, along with lands added to the NFS which have taken on the status of 'reserved from the public domain' under the General Exchange Act. The following area types are included: National Forest, Experimental Area, Experimental Forest, Experimental Range, Land Utilization Project, National Grassland, Purchase Unit, and Special Management Area.”Notes: This layer was filtered to only include National Forests in the State of ColoradoSource: United States Department of Agriculture Original Proclaimed National Forests REST Endpoint

  15. d

    Future WRMA's Land Use Dataset

    • search.dataone.org
    • hydroshare.org
    Updated Dec 5, 2021
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    Enjie Li (2021). Future WRMA's Land Use Dataset [Dataset]. https://search.dataone.org/view/sha256%3A6c0c3a0847cd26c741eb52e32fc606b7d1c15bcdebc1a6b96c19a5a5f8a45695
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    Dataset updated
    Dec 5, 2021
    Dataset provided by
    Hydroshare
    Authors
    Enjie Li
    Time period covered
    Jan 1, 2014 - Dec 31, 2040
    Area covered
    Description

    This dataset contains the urban growth simulation results of future land use in 2040 of the Wasatch Range Metropolitan Area (WRMA) .In this study, we defined the WRMA as a broad, ten-county region that surrounds the Wasatch Mountain Range east of the Great Salt Lake and Salt Lake City in Utah. This region encompasses four Wasatch Front counties west of the mountain range (Weber County, Davis County, Salt Lake County, and Utah County), three Wasatch Back counties east of the mountain range (Morgan County, Summit County, and Wasatch County), and three counties neighboring the Wasatch Front (Cache County, Box Elder County, and Tooele County).

    SLEUTH-3r urban growth simulation model is used to generate this dataset. Detailed SLEUTH model protocol can be found at: http://www.ncgia.ucsb.edu/projects/gig/index.html. The data used to run the SLEUTH-3r model include National Land Cover Database 2001, 2006, and 2011, US Census TIGER/Line shapefile for 2000 and 2011, United States Geological Survey 7.5 min elevation model, and Utah Landownership map from Utah Automated Geographic Reference Center.

    Three alternative scenarios were developed to explore how conserving Utah’s agriculturale land and maintaining healthy watersheds would affect the patterns and trajectories of urban development: 1) The first scenario is a “Business as Usual” scenario. In this scenario, federal, state, and local parks, conservation easement areas, and surface water bodies, were completely excluded (value = 100) from development, and all the remaining lands are were naively assumed as developable (value = 0). This is the same excluded layer that was also used during model calibration. Under this scenario, we hypothesized that future urban grow will occur following the historical growth behaviors and trajectories and no changes in land designation or policies to restrict future growth will be implemented. 2) The second scenario is an “Agricultural Conservation” scenario. Within the developable areas that we identified earlier, we then identified places that are classified by the United States Department of Agriculture (USDA) as prime farmland, unique farmland, farmland of statewide importance, farmland of local importance, prime farmland if irrigated, and prime farmland if irrigated and drained. Each of these classes were assigned with an exclusion value from urban development of 100, 80, 70, 60, 50, and 40 respectively. These exclusion values reflect the relative importance of each farmland classification and preservation priorities. By doing so, the model discourages but does not totally eliminate growth from occurring on agricultural lands, which reflects a general policy position to conserve agricultural landscapes while respecting landowners’ rights to sell private property. 3) A “Healthy Watershed” scenario aims to direct urban growth away from areas prone to flooding and areas critical for maintaining healthy watersheds. First, we made a 200-meter buffer around existing surface water bodies and wetlands and assigned these areas an exclusion value of 100 to keep growth from occurring there. In addition, we assigned areas that have frequent, occasional, rare and no-recorded flooding events with exclusion values of 100, 70, 40 and 0 accordingly. We also incorporated the critical watershed restoration areas identified by the Watershed Restoration Initiative of Utah Division of Wildlife Resources (https://wri.utah.gov/wri/) into this scenario. These watershed restoration areas are priority places for improving water quality and yield, reducing catastrophic wildfires, restoring the structure and function of watersheds following wildfire, and increasing habitat for wildlife populations and forage for sustainable agriculture. However, there are not yet legal provisions for protecting them from urbanization, so we assigned these areas a value of 70 to explore the potential urban expansion outcomes if growth were encouraged elsewhere.

    Future land use projections of 2040 are in GIF format, which can be reprojected and georeferenced in ArcGIS or QGIS, or be read directly as a picture.

  16. Global water-stress scores by major city 2018

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Global water-stress scores by major city 2018 [Dataset]. https://www.statista.com/statistics/1040184/water-stress-score-city-globally/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    Worldwide
    Description

    The city of Chennai, located in India, was the megacity with highest water-stress score in 2018, with 3.48 out of five points. In the same year, Los Angeles was the only city from the United States among the list of cities with the highest water-stress score globally, with a score of 2.85 out of five.

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

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

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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.

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