The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits ***** 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 largest 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 ***** meters.

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

This 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 *** meters below sea level.

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

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

As of 2020, Ifrane was the highest city in Morocco, with an altitude of ***** meters. Midelt and Errachidia followed, as they were ***** meters and ***** meters above sea level, respectively. In contrast, the areas of Tétouan and Kénitra each recorded the lowest altitude in the country.

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 (WGS84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).

To illustrate and evaluate the impact of the higher 100-year coastal floods in the future, we produced a dataset representing stillwater flood elevations over land for flood heights of seven-and-one-half-feet above mean higher high water (MHHW, the average of the higher high water elevation of each tidal day.) The data includes horizontal spatial extent of seven-and-one-half-foot coastal floods above mean higher high water in the City of Boston.

The High Accuracy Elevation Data Project collected elevation data (meters) on a 400 meter topographic grid with a vertical accuracy of +/- 15 centimeters to define the topography in South Florida. The data are referenced to the horizontal datum North American Datum 1983 (NAD 83) and the vertical datum North American Vertical Datum 1988 (NAVD 88). In some areas, the surveying was accomplished using airboats. Because access was a logistical problem with airboats, the USGS developed a helicopter-based instrument known as the Airborne Height Finder (AHF). All subsequent data collection used the AHF. Data were collected from the Loxahatchee National Wildlife Refuge, south through the Water Conservation Areas (1A, 2A, 2B, 3A, and 3B), Big Cypress National Park, the Everglades National Park, to the Florida Bay. The data are available for the areas shown on the USGS High Accuracy Elevation Data graphic at http://sofia.usgs.gov/exchange/desmond/desmondelev.html. The work was performed for Everglades ecosystem restoration purposes.

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

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.

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

These GIS layers provide the probability of observing a static vs. dynamic coastal response (CR) with respect to predicted sea-level rise for the Northeastern U.S. for the 2020s, 2030s, 2050s and 2080s. These data are based on the following inputs: sea-level rise, vertical land movement rates due to glacial isostatic adjustment, elevation data, and land cover data. The output displays a probability based on binary end members for the forecast year as defined by a probabilistic framework (a Bayesian network). Because the static vs dynamic coastal response is a binary relationship, the dynamic (i.e. landform or landscape change) coastal response can be derived by subtracting the static response from 1 (and vice versa). These data layers primarily show the distribution of likely coastal response types over a large spatial scale and should therefore be used qualitatively.

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).

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

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).

[From GeoData Center Home Page descriptions, "http://www.gi.alaska.edu/alaska-satellite-facility/geodata-center"]

 The GeoData Center is the browse facility for the state copy of the AHAP
 collection, which covers approximately 95% of the State of Alaska in 1:60,000
 color infrared (CIR) and 1:120,000 black and white (B&W) photography. The data
 reside in 10" film format. Approximately 70,000 frames of photography were
 acquired between 1978 and 1986.

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

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.