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

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.

United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data was reported at 2.264 % in 2010. This records an increase from the previous number of 2.246 % for 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data is updated yearly, averaging 2.264 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 2.329 % in 1990 and a record low of 2.246 % in 2000. United States US: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Urban population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

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

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

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

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;

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).

The Wind Integration National Dataset (WIND) Toolkit, developed by the National Renewable Energy Laboratory (NREL), provides modeled wind speeds at multiple elevations. Instantaneous wind measurements were analyzed from more than 126,000 sites in the continental United States for the years 2007–2013. The model results were mapped on a 2-km grid. A subset of the contiguous United States data for 2012 is shown here. Offshore data is shown to 50 nautical miles.Time Extent: Annual 2012Units: m/sCell Size: 2 kmSource Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection:  WGS 1984 Web MercatorExtent: Contiguous United StatesSource: NREL Wind Integration National Dataset v1.1WIND is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies.Accessing Elevation InformationEach of the 9 elevation slices can be accessed, visualized, and analyzed. In ArcGIS Pro, go to the Multidimensional Ribbon and use the Elevation pull-down menu. In ArcGIS Online, it is best to use Web Map Viewer Classic where the elevation slider will automatically appear on the righthand side. The elevation slider will be available in the new Map Viewer in an upcoming release. What can you do with this layer?This layer may be added to maps to visualize and quickly interrogate each pixel value. The pop-up provides the pixel’s wind speed value.This analytical imagery tile layer can be used in analysis. For example, the layer may be added to ArcGIS Pro and proposed wind turbine locations can be used to Sample the layer at multiple elevation to determine the optimal hub height. Source data can be accessed on Amazon Web ServicesUsers of the WIND Toolkit should use the following citations:Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory.Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. "The Wind Integration National Dataset (WIND) Toolkit." Applied Energy 151: 355366.King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and modeling efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of Mean High Water (MHW) and horizontal datum of World Geodetic System 1984 (WGS84). Grid spacings for the DEM ranges from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).

The single value tidal water surface of mean higher high water (MHHW) modeled at the Honolulu tide gauge is used to represent present-day sea level for the urban corridor stretching from Honolulu International Airport to Waikiki and Diamond Head along the south shore of Oahu in the state of Hawaii. Water levels are shown as they would appear during the highest high tides (excluding wind-driven tides). Land elevation was derived using a National Geospatial Agency (NGA)-provided digital elevation model (DEM) based on LiDAR data of the Honolulu area collected in 2009. This "bare earth" DEM (vegetation and structures removed) was used to represent the current topography of the study area above zero elevation. The accuracy of the DEM was validated using a selection of 16 Tidal Benchmarks located within the study area. Data produced in 2014 by Dr. Charles "Chip" Fletcher of the department of Geology & Geophysics (G&G) in the School of Ocean and Earth Science and Technology (SOEST) of the University of Hawaii at Manoa. Supported in part by the NOAA Coastal Storms Program (CSP) and the University of Hawaii Sea Grant College Program. These data should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.

These airborne lidar data were gathered by the Instituto Nacional de Estadistica y Geografia of Mexico as part of a regional mapping activity in northwestern Mexico. They span the area that ruptured in the April 2010 M7.2 El Mayor Cucupah earthquake which was laser scanned and for which data are available in OpenTopography's holdings. Alejandro Hinojosa of CICESE is the contact person for these data. This version of the data has been empirically corrected by Craig Glennie and colleagues at the University of Houston. Details for the data corrections as follows: Rather than trying to correct the whole dataset, we just concentrated on the portion that overlaps with the post-event data. Here is a brief summary of what we did: (1) Pre-Event Data was given in ITRF 1992 (1988.0 epoch) and post-event NCALM data was processed in ITRF2000 (Epoch 2010.627). NGS software package HTDP was used to compute a coordinate shift between these two reference frames (-0.900 m East, 0.429 m North, 0.004 m Up). To correct the 2006 data to the same datum as the NCALM data, we added the vector (-0.900,0.429,0.004) to all of the pre-event data points. (2) Original dataset contained all scan data out to +/- 28 degree scan angle. There are significant problems at the outer edge of the scan, so all scan lines were cropped to +/-24 degrees. This results in minimal overlap between scan lines, but doesn't create any data gaps between flight lines. (3)Dataset was then re-boresighted. We determined a roll and pitch offset for each flight line individually, plus a global mirror scale factor. (4) Finally, we determined an individual delta "z" correction for each flightline. Note that for all of the above adjustments, none of the post-earthquake data was used. We purposely sequestered the two datasets so as not to inadvertently remove differences caused by the earthquake. To give an idea of the magnitude of the improvement, on the pre-event dataset (as delivered to me) in the overlap, we were seeing average elevation differences of 95 cm (1 sigma). After cropping the data to 24 degrees, the average elevation differences were 70 cm (1 sigma) After steps (3) and (4) above, the average elevation differences were reduced to 52 cm (1 sigma). So overall, it appears we were able to reduce the vertical errors by almost a factor of two.

Q: What was the average temperature for the month? A: Colors show the average monthly temperature across the contiguous United States. White and very light areas had average temperatures near 50°F. Blue areas on the map were cooler than 50°F; the darker the blue, the cooler the average temperature. Orange to red areas were warmer than 50°F; the darker the shade, the warmer the monthly average temperature. Q: Where do these measurements come from? A: Daily temperature readings come from weather stations in the Global Historical Climatology Network (GHCN-D). Volunteer observers or automated instruments collect the highest and lowest temperature of the day at each station over the entire month, and submit them to the National Centers for Environmental Information (NCEI). After scientists check the quality of the data to omit any systematic errors, they calculate each station’s monthly average of daily mean temperatures, then plot it on a 5x5 km gridded map. To fill in the grid at locations without stations, a computer program interpolates (or estimates) values, accounting for the distribution of stations and various physical relationships, such as the way temperature changes with elevation. The resulting product is the NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid). Q: What do the colors mean? A: Shades of blue show areas that had monthly average temperatures below 50°F. The darker the shade of blue, the lower the average temperature. Areas shown in shades of orange and red had average temperatures above 50°F. The darker the shade of orange or red, the higher the average temperature. White or very light colors show areas where the average temperature was near 50°F. Q: Why do these data matter? A: The 5x5km NClimGrid data allow scientists to report on recent temperature conditions and track long-term trends at a variety of spatial scales. The gridded cells are used to create statewide, regional and national snapshots of climate conditions. Energy companies use this information to estimate demand for heating and air conditioning. Agricultural businesses also use these data to optimize timing of planting, harvesting, and putting livestock to pasture. Q: How did you produce these snapshots? A: Data Snapshots are derivatives of existing data products; to meet the needs of a broad audience, we present the source data in a simplified visual style. This set of snapshots is based on NClimGrid climate data produced by and available from the National Centers for Environmental Information (NCEI). To produce our images, we invoke a set of scripts that access the source data and represent them according to our selected color ramps on our base maps. Additional information The data used in these snapshots can be downloaded from different places and in different formats. We used these specific data sources: NClimGrid Average Temperature References NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) NOAA Monthly U.S. Climate Divisional Database (NClimDiv) Improved Historical Temperature and Precipitation Time Series for U.S. Climate Divisions) NCEI Monthly National Analysis) Climate at a Glance - Data Information) NCEI Climate Monitoring - All Products Source: https://www.climate.gov/maps-data/data-snapshots/data-source/temperature-us-monthly-averageThis upload includes two additional files:* Temperature - US Monthly Average _NOAA Climate.gov.pdf is a screenshot of the main Climate.gov site for these snapshots.* Cimate_gov_ Data Snapshots.pdf is a screenshot of the data download page for the full-resolution files.

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United States US: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 2.513 % in 2010. This records an increase from the previous number of 2.502 % for 2000. United States US: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 2.513 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 2.575 % in 1990 and a record low of 2.502 % in 2000. United States US: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Population below 5m is the percentage of the total population living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

United States US: Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 0.980 % in 2010. This stayed constant from the previous number of 0.980 % for 2000. United States US: Rural Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 0.980 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.980 % in 2010 and a record low of 0.980 % in 2010. United States US: Rural 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 United States – Table US.World Bank.WDI: Land Use, Protected Areas and National Wealth. Rural land area below 5m is the percentage of total land where the rural land 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;

United States US: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 0.187 % in 2010. This stayed constant from the previous number of 0.187 % for 2000. United States US: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 0.187 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.187 % in 2010 and a record low of 0.187 % in 2010. United States US: Urban 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. Urban land area below 5m is the percentage of total land where the urban land 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;

United States US: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 0.249 % in 2010. This records a decrease from the previous number of 0.256 % for 2000. United States US: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 0.249 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.256 % in 2000 and a record low of 0.246 % in 1990. United States US: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Land Use, Protected Areas and National Wealth. Rural population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

This data set represents the average monthly maximum temperature in Celsius multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster dataset produced by the Spatial Climate Analysis Service at Oregon State University.

The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique ...