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.

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.

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.

United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 1.168 % in 2010. This stayed constant from the previous number of 1.168 % for 2000. United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 1.168 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 1.168 % in 2010 and a record low of 1.168 % in 2010. United States US: Land Area Where Elevation is Below 5 Meters: % of Total Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Land area below 5m is the percentage of total land where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

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.

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rovers. The GCPs can be used as constraints during photogrammetric processing. Transect points were collected by using the same RTK-GNSS system; these can be used to evaluate photogrammetric products. This data release includes georeferenced images, image-location files, GCPs, and transect points. Collection of these data was supported by the U.S. Geological Survey Coastal/Marine Hazards and Resources Program and conducted under U.S. Geological Survey field activity numbers 2016-013-FA, 2016-043-FA, 2016-053-FA, 2016-054-FA and 2016-055-FA.

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.

This component of IFR Enroute Aeronautical Chart series is designed to meet the needs of users who require a low altitude digital version chart for the U.S. This version is in PDF format.

The sea level rise (SLR) coastal inundation layers were created using existing federal products: the (1) NOAA Coastal Digital Elevation Models (DEMs) and (2) 2022 Interagency Sea Level Rise Technical Report Data Files. The DEMs for the Continental United States (CONUS) are provided in North American Vertical Datum 1988 (NAVD 88) and were converted to Mean Higher High Water (MHHW) using the NOAA VDatum conversion surfaces; the elevation values are in meters (m). The NOAA Scenarios of Future Mean Sea Level are provided in centimeters (cm). The MHHW DEMs for CONUS were merged and converted to cm and Scenarios of Future Mean Sea Level were subtracted from the merged DEM. Values below 0 represent areas that are below sea level and are “remapped” to 1, all values above 0 are remapped to “No Data”, creating a map that shows only areas impacted by SLR. Areas protected by levees in Louisiana and Texas were then masked or removed from the results.Scenario: For each of the 5 GMSL scenarios (identified by the rise amounts in meters by 2100--0.3 m , 0.5 m. 1.0 m, 1.5 m and 2.0 m), there is a low, medium (med) and high value, corresponding to the 17th, 50th, and 83rd percentiles. Scenarios (15 total): 0.3 - MED, 0.3 - LOW, 0.3 - HIGH, 0.5 - MED, 0.5 - LOW, 0.5 - HIGH, 1.0 - MED, 1.0 - LOW, 1.0 - HIGH, 1.5 - MED, 1.5 - LOW, 1.5 - HIGH, 2.0 - MED, 2.0 - LOW, and 2.0 - HIGH Years (15 total): 2005, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100, 2110, 2120, 2130, 2140, and 2150Report Website: https://oceanservice.noaa.gov/hazards/sealevelrise/sealevelrise-tech-report.htmlGeneral DisclaimerThe data and maps in this tool illustrate the scale of potential flooding, not the exact location, and do not account for erosion, subsidence, or future construction. Water levels are relative to Mean Higher High Water (MHHW) (excludes wind driven tides). The data, maps, and information provided should be used only as a screening-level tool for management decisions. As with all remotely sensed data, all features should be verified with a site visit. Hydroconnectivity was not considered in the mapping process. The data and maps in this tool are provided “as is,” without warranty to their performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of these data is assumed by the user. This tool should be used strictly as a planning reference tool and not for navigation, permitting, or other legal purposes.SLR data are not available for Hawaii, Alaska, or U.S. territories at this time.Levees DisclaimerEnclosed levee areas are displayed as gray areas on the maps.Major federal leveed areas were assumed high enough and strong enough to protect against inundation depicted in this viewer, and therefore no inundation was mapped in these regions. Major federal leveed areas were taken from the National Levee Database.Minor (nonfederal) leveed areas were mapped using the best available elevation data that capture leveed features. In some cases, however, breaks in elevation occur along leveed areas because of flood control features being removed from elevation data, limitations of the horizontal and vertical resolution of the elevation data, the occurrence of levee drainage features, and so forth. Flooding behind levees is only depicted if breaks in elevation data occur or if the levee elevations are overtopped by the water surface. At some flood levels, alternate pathways around—not through—levees, walls, dams, and flood gates may exist that allow water to flow into areas protected at lower levels. In general, imperfect levee and elevation data make assessing protection difficult, and small data errors can have large consequences.Citations2022 Sea Level Rise Technical Report - Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak, 2022: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nostechrpt01-global-regional-SLR-scenarios-US.pdf

This statistic shows a ranking of the estimated average elevation of the land area in 2020 in Latin America, differentiated by country.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

Severe drought across the Western United States has caused water levels at Lake Mead in Nevada to drop in recent decades. Since 1970, the lowest end of month water level of Lake Mead at Hoover Dam was recorded in July 2022, at 1,040 feet above sea level. This was also the lowest level since the 1930s when the lake was formed by the Hoover Dam. Seven of the 10 lowest water levels recorded since 1970 were in 2022, while three were recorded in 2023. Lake Mead is considered at full capacity when water levels reach 1,220 feet above sea level, but it’s able to hold a maximum of 1,229 feet of water. The last time the lake approached this capacity was in the summer of 1983.

Lake Mead, the largest artificial reservoir by volume in the United States, generates electricity and supplies drinking water to California, Arizona, Nevada, and parts of Mexico.

This dataset was created to represent the land surface elevation at 1:24,000 scale for Florida. The elevation contour lines representing the land surface elevation were digitized from United States Geological survey 1:24,000 (7.5 minute) quadrangles and were compiled by South Florida, South West Florida, St. Johns River and Suwannee River Water Management Districts and FDEP. QA and corrections to the data were supplied by the Florida Department of Environmental Protection's Florida Geological Survey and the Division of Water Resource Management. This data, representing over 1,000 USGS topographic maps, spans a variety of contour intervals including 1 and 2 meter and 5 and 10 foot. The elevation values have been normalized to feet in the final data layer. Attributes for closed topographic depressions were also captured where closed (hautchered) features were identified and the lowest elevation determined using the closest contour line minus one-half the contour interval. This data was derived from the USGS 1:24,000 topographic map series. The data is more than 20 years old and is likely out-of-date in areas of high human activity.

Increased frequency and intensity of storms, saltwater intrusion, sea level rise, and warming temperatures are affecting forests along the mid-Atlantic, Southeastern, and Gulf coasts of the US. However, we still lack a clear understanding of how the structure of coastal forests is being altered by climate change drivers. Here, we used data from the Forest Inventory and Analyses program of the United States Forest Service to examine structure and biomass change in forests along the mid-Atlantic, Southeastern, and Gulf coasts of the US. We selected plots that have been resampled at low (5 m) and mid (30-50 m) elevations in coastal areas of states from Texas to New Jersey, allowing us to determine change in live trees, standing dead wood, and downed dead wood biomass (and carbon) stocks across a decade. We estimated forest attributes at the county level for each elevational class. Forest area increased by 1.9% in low elevation counties and by 0.3% in mid elevation counties. Live tree biomass density increased by 13% in low elevation counties, and by 16% in mid elevation counties. Standing dead biomass decreased in low elevation counties by 9.2% and by 2.8% in mid elevation counties. On average, downed dead wood increased by 22% in low elevation counties and decreased by 50% in mid elevation counties. Changes in the stock of C in standing and downed dead wood (0.45 to 9.1 Tg C) are similar to soil marsh C loss (9.54 Tg C). Annualized growth and harvest were both higher (16% and 58% respectively) in mid elevation counties than low elevation counties, while annualized mortality was 25% higher in low elevation counties. Annualized growth in low elevation counties was negatively correlated to sea level rise rates, and positively correlated to number of storms, illustrating tradeoffs associated with different climate change drivers. Overall, our results illustrate the vulnerability of US southeastern coastal low and mid elevation forests to climate change and sea level rise with indications that the complexity and rate of change in associated ecosystem functions (e.g., growth, mortality, and carbon storage) within the greater social environment (e.g., agricultural abandonment) may increase. Methods We used data from the National Forest Inventory and Analysis (FIA) program which, administered by the USDA Forest Service, provides a comprehensive statistical inventory and associated database of forests across the United States. The program applies standardized techniques to measure forest characteristics across a national plot sampling network of approximately one plot per 2,428 ha, with plot locations determined using a hexagonal sampling framework designed to be as spatially balanced as possible. The plot location within each 2,428 ha hexagon was visited by field crews if remotely sensed data indicated it was in forest land use (having ≥ 10% tree canopy cover, or evidence of such cover) that was at least 0.4 ha in area and 37 m wide. We focused on data for the mid-Atlantic and Southeast coast of the US, from Texas to New Jersey. We selected information from forested plots located in low (~5m) and mid elevation (30-50 m) areas with slopes less than 15%, and had either hydric conditions, or were near a water feature, which are indicative of forested wetlands. We used the FIA methodologies to estimate forest resources attributes from plot level to the county level. We looked at changes in live trees (biomass and C), standing dead wood (SD, biomass and C), and downed dead wood (biomass and C, DD). The systematic FIA sample design further allowed for statistical population-level estimates of various forest attributes, such as the area of a low-elevation forest in a county, using an “expansion factor” assigned to each plot condition. Using a design-based approach to population inference, expansion factors can be summed across plots in a population to provide an estimate of the total area within that population. Similarly, the FIA sample design allows individual trees inventoried on plots to be scaled via an expansion factor to estimate the total C of trees within an area. In this case, we calculated the area and biomass (from standing live, standing dead, and downed dead) of low-elevation and mid-elevation forests in low-elevation and mid-elevation counties, respectively, and within each state. Field crews collected a wide variety of data using standardized protocols from each FIA plot, which covered 0.067 hectares within four 7.31-m radius subplots arranged at the vertices and center of a triangle. This included the diameter, height, and species for every live and dead tree with a diameter at breast height (DBH) ≥ 12.7 cm. All trees with DBH ≥ 2.54 cm but < 12.7 cm were measured in a single 2.07-m-radius microplot within each of the plot’s four subplots. Using the component ratio method, the FIA program estimates the aboveground dry biomass of each tree with DBH ≥ 2.54 cm in pounds. Biomass and C densities were calculated by scaling plot-level data to per hectare estimates for the counties. We estimated change in the stocks of different pools by subtracting time 2 from time 1. We also looked at changes in different size classes and decay classes (for dead wood). We used data from the two latest survey evaluation periods, spanning a decade of change (Table 1). We estimated forest biomass standing stocks and change among key structural components using data from 1700 plots in low elevation counties and 3200 plots in mid elevation counties. We estimated population level values for 126 low elevation counties and 179 mid elevation counties (Fig 1). We excluded counties for which there were less than three plots in any survey year. To examine potential climate change drivers of forest dynamics we used publicly available datasets. We obtained sea level rise rates for 43 of the National Oceanic and Atmospheric Administration (NOAA) tide gauges from the Permanent Service for Mean Sea Level (PSMSL, Supplementary Table 1). We used the website to estimate rates of sea level rise from 2010-2020 to match the FIA dataset, given reports of accelerating rates of sea level rise in the Southeastern US. We calculated mean annual temperature and mean annual precipitation from the GridMet dataset (4 km2 spatial resolution), accessed through the Climate Engine portal (https://app.climateengine.org/climateEngine) for the period 2010-2020, to roughly match the FIA measurements. We also estimated change in temperature and precipitation by estimating the sen slope of each factor over the same time period using the Climate Engine portal. We used the NOAA National Hurricane Center Atlantic Hurricane Catalog (HURDAT2), accessed through Google Earth Engine, to count the number of tropical cyclones that passed through a 100 km radius buffer of the NOAA tide gauges for the same period. On average, low elevation counties were located 22.4 ± 2.6 km, while mid elevation counties were 108 ± 5.9 km from the NOAA tide gauges.

Lake Mead's water elevation at the end of February 2025 was 1,068.18 feet above sea level, a small increase in comparison to the previous month. In July 2022, the reservoir reached the lowest monthly water level recorded since Lake Mead was first formed by the Hoover Dam in the 1930s. At full capacity, Lake Mead has a water level of 1,229 feet above sea level. Lake Mead nearing dead pool status Situated on the border of Arizona and Nevada, Lake Mead is the largest reservoir in the United States. It is a crucial water source that provides drinking water to tens of millions of people in the states of Arizona, California, and Nevada. However, experts have warned that if the lake continues to recede due to the severe droughts across the Southwestern United States, it will become a dead pool. This means that there will not be enough water for the Hoover Dam to produce hydropower or deliver water downstream to metropolitan centers. U.S. water resources are depleting With large swathes of western U.S. recently suffering from a megadrought, which is a period of prolonged drought that spans more than two decades, many other lakes have been severely depleted in recent years. Water levels of major reservoirs in California have fallen to all-time lows in recent years. California’s two largest reservoirs, Shasta Lake and Oroville Lake, were at less than half capacity in July 2022.

Nadir videos shot from a GoPro Hero3 Black Edition (focal length 2.77 mm) of the arctic landscape during low altitude transects at the rate of 60 frames per second. Transects were conducted from small aircraft over the National Park Service’s Bering Land Bridge National Preserve and the U.S. Fish and Wildlife Service’s Selawik National Wildlife Refuge in northwest Alaska.

Oblique videos shot from a Panasonic Lumix DMC-FZ200 (24x superzoom with variable focal length) and a Panasonic Lumix DMC-SZ7 (10x superzoom with variable focal length)) of the arctic landscape during low altitude transects. Transects were conducted from small aircraft over the National Park Service’s Arctic Network (Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park, and Noatak National Preserve) and the U.S. Fish and Wildlife Service’s Selawik National Wildlife Refuge in northwest Alaska.

The low-altitude communication network service market is projected to reach $XXX million by 2033, exhibiting a CAGR of XX% from 2025 to 2033. The increasing application of low-altitude communication networks in transportation, culture and tourism, agriculture, medical, and other sectors is a significant factor driving the market growth. Additionally, the need for efficient and reliable communication in airspace supervision networks is further bolstering the demand for low-altitude communication services. Major players operating in the low-altitude communication network service market include China Mobile Communications, China United Network Communications, ZTE, and China Telecommunications. The market is segmented by application, type, and region. Key regions include North America, South America, Europe, Middle East & Africa, and Asia Pacific. The Asia Pacific region is expected to dominate the market due to the increasing adoption of low-altitude communication networks in China, India, and Japan. North America and Europe are also expected to witness significant growth due to the presence of leading technology providers and the growing demand for smart city applications.

Oblique images snapped from a Canon Rebel 3Ti with a Sigma zoom lens (18-200mm focal length), a Panasonic Lumix DMC-FZ200 (24x superzoom with variable focal length) and a Panasonic Lumix DMC-SZ7 (10x superzoom with variable focal length) of the arctic landscape during low altitude transects. Transects were conducted from small aircraft over the National Park Service’s Arctic Network (Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park, and Noatak National Preserve) and the U.S. Fish and Wildlife Service’s Selawik National Wildlife Refuge in northwest Alaska.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Coweeta (CWT) contains soil temperature at 5 cm depth (mean) measurements in celsius units and were aggregated to a yearly timescale.

description: Maps portraying the flight paths for low altitude transects conducted from small aircraft over the National Park Service s Arctic Network (Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park, and Noatak National Preserve) and the U.S. Fish and Wildlife Service s Selawik National Wildlife Refuge in northwest Alaska.; abstract: Maps portraying the flight paths for low altitude transects conducted from small aircraft over the National Park Service s Arctic Network (Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park, and Noatak National Preserve) and the U.S. Fish and Wildlife Service s Selawik National Wildlife Refuge in northwest Alaska.