Property:Extended data description
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H
The HydroLAKES database was designed as a digital map repository to include all lakes with a surface area of at least 10 ha. Version 1 comprises the shoreline polygons of 1,427,688 individual lakes. HydroLAKES aims to be as comprehensive and consistent as possible at a global scale and contains both freshwater and saline lakes, including the Caspian Sea, as well as human-made reservoirs and regulated lakes. The HydroLAKES database was created by compiling, correcting, and unifying several near-global and regional datasets, foremost the SRTM Water Body Data (SWBD; Slater et al., 2006) for regions from 56˚S to 60˚N, and CanVec (Natural Resources Canada, 2013) for most North American lakes. Map generalization methods were applied and some polygon outlines were smoothed during the mapping process to ensure spatial consistency of the data. The resulting map scale is estimated to be between 1:100,000 and 1:250,000 for most lakes globally, with some coarser ones at 1:1 million. +
I
The ICE-5G (VM2) model mathematically analyses glacio-isostatic adjustment processes and provides model data on global ice sheet coverage, ice thickness and paleotopography at 10 min spatial resolution for 21ka and 0ka, and at 1degree spatial resolution for intervals in between these snapshots. These are NETCDF files. +
N
The Indian National River Linking Project (NRLP), or Indian Rivers Interlinking project (IRI), proposes a major redistribution of water resources over the Indian subcontinent. A large engineering effort is proposed to redistribute monsoonal water from the Himalayas and foothills, store water in reservoirs, and route it via canals ("links") to the drier regions of Southern India. A total of 29 links and 43 dams and barrages are proposed as part of the project.
The plan would provide water resources for agriculture, drinking water and industrial use to a growing population in central and southern India, while potentially improving flood control in the northern and mountainous areas. The project would also result in a major reorganization of watersheds, with possible impacts on ecosystems and the environment. There would be impacts on trans-boundary rivers.
Here provided are two databases: (1) the dams database, with locations, operating specifications, sources, and notes on population expected to be displaced; and (2) the canals database, with locations, operating specifications, and further notes. The databases are available as shapefiles for GIS visualization - click a feature to see its database information. A "rivers" shapefile is also available for help in generating visualizations. Note that the rivers are not currently labeled in the shapefile. Raw txt/csv format is also available for the canals and dams databases. An annotated reference list is included to give specifics on the sources from which each number was obtained and/or calculated.
The databases are constructed from hundreds of government reports, geo-referenced maps, planning and design documents and Open Street Map data. For full methodology and calculations regarding displaced populations, see the accompanying manuscript: Higgins et al., 2017. For the graph database tool used to calculate basin connectivity changes and water discharge changes for given river mouths, see the github page: https://github.com/sahiggin/NRLP .
M
The MERIT DEM was developed by removing multiple error components (absolute bias, stripe noise, speckle noise, and tree height bias) from the existing spaceborne DEMs (SRTM3 and AW3D). It represents the terrain elevations at a 3sec resolution (~90m at the equator), and covers land areas between 90N-60S. The data is freely available for research and education purpose. +
N
The Multi-Resolution Land Characteristics Consortium (MRLC) has completed the National Land Cover Database (NLCD) 2001 products for the conterminous United States, Hawaii, Alaska and Puerto Rico at 30 m cell resolution. The NLCD 2001 products (land cover, impervious surface and canopy density) were generated from a standardized set of data layers mosaicked by mapping zone. Typical zonal layers included multi-season Landsat 5 and Landsat 7 imagery centered on a nominal collection year of 2001, and Digital Elevation Model based derivatives at 30 meters spatial resolution. NLCD 2001 used an improved classification algorithm from NLCD 1992, resulting in a more precise rendering of spatial boundaries between 16 classes of land cover (additional classes are available in coastal areas and Alaska only). +
The National Elevation Dataset (NED) is the primary elevation data product of the USGS. The NED is a seamless dataset with the best available raster elevation data of the conterminous United States, Alaska, Hawaii, and territorial islands. The NED is updated on a nominal two month cycle to integrate newly available, improved elevation source data. All NED data are public domain. The NED is derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. NED data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the conterminous United States, are referenced to the North American Vertical Datum of 1988 (NAVD 88). The vertical reference will vary in other areas. NED data are available nationally (except for Alaska) at resolutions of 1 arc-second (about 30 meters) and 1/3 arc-second (about 10 meters), and in limited areas at 1/9 arc-second (about 3 meters). In most of Alaska, only lower resolution source data are available. As a result, most NED data for Alaska are at 2-arc-second (about 60 meters) grid spacing. Part of Alaska is available at the 1- and 1/3-arc-second resolution, and plans are in development for a significant improvement in elevation data coverage of the state. +
The National Hydrography Dataset (NHD) is the surface-water component of The National Map. The NHD is a comprehensive set of digital spatial data that represents the surface water of the United States using common features such as lakes, ponds, streams, rivers, canals, streamgages, and dams. Polygons are used to represent area features such as lakes, ponds, and rivers; lines are used to represent linear features such as streams and smaller rivers; and points are used to represent point features such as streamgages and dams. Lines also are used to show the water flow through area features such as the flow of water through a lake. The combination of lines is used to create a network of water and transported material flow to allow users of the data to trace movement in downstream and upstream directions. +
The National Ocean Service (NOS) Hydrographic Data Base (NOSHDB), maintained by NGDC in conjunction with NOS, provides extensive survey coverage of the coastal waters and Exclusive Economic Zone (EEZ) of the United States and its territories. The NOSHDB contains data digitized from smooth sheets of hydrographic surveys completed between 1851 and 1965, and from survey data acquired digitally on NOS survey vessels since 1965.
Over 76 million soundings from over 6600 surveys are now included in the NOSHDB. These data may be searched and downloaded online using the Hydrographic Survey Data Map Service (an interactive map and data discovery tool at NGDC; http://map.ngdc.noaa.gov/website/mgg/nos_hydro/viewer.htm). The NOSHDB data with search and retrieval software are also available on a DVD-ROM or CD-ROM set.
Data products from NOS surveys, including BAG files, descriptive reports (DRs), smooth sheet images, survey data images, textual gridded data, and sidescan sonar mosaics, are available for download from NGDC using the Hydrographic Survey Data Map Service. +
S
The Natural Resources Conservation Service (NRCS) - National Cartography and Geospatial Center (NCGC) previously archived and distributed the State Soil Geographic (STATSGO) Database. The STATSGO spatial and tabular data were revised and updated in 2006. STATSGO has been renamed to the U.S. General Soil Map (STATSGO2). It is available for download from the Soil Data Mart (http://soildatamart.nrcs.usda.gov/).
The dataset was created by generalizing more detailed soil survey maps. Where more detailed soil survey maps were not available, data on geology, topography, vegetation, and climate were assembled, together with Land Remote Sensing Satellite (LANDSAT) images. Soils of like areas were studied, and the probable classification and extent of the soils were determined.
Map unit composition was determined by transecting or sampling areas on the more detailed maps and expanding the data statistically to characterize the whole map unit.
This dataset consists of geo-referenced vector and tabular digital data. The map data were collected in 1- by 2-degree topographic quadrangle units and merged into a seamless national dataset. It is distributed in state/territory and national extents. The soil map units are linked to attributes in the tabular data, which give the proportionate extent of the component soils and their properties.
The tabular data contain estimated data on the physical and chemical soil properties, soil interpretations, and static and dynamic metadata. Most tabular data exist in the database as a range of soil properties, depicting the range for the geographic extent of the map unit. In addition to low and high values for most data, a representative value is also included for these soil properties. +
P
The PSMSL was established in 1933, and is the global data bank for long term sea level change information from tide gauges. The PSMSL collect data from several hundred gauges situated all over the globe. As of December 2006, the database of the PSMSL contains over 55000 station-years of monthly and annual mean values of sea level from almost 2000 tide gauge stations around the world received from almost 200 national authorities. On average, approximately 2000 station-years of data are entered into the database each year. +
S
The SRTM Water Body Data files are a by-product of the data editing performed by the National Geospatial-Intelligence Agency (NGA) to produce the finished SRTM Digital Terrain Elevation Data Level 2 (DTED® 2). In accordance with the DTED® 2 specification, the terrain elevation data have been edited to portray water bodies that meet minimum capture criteria. Ocean, lake and river shorelines were identified and delineated. Lake elevations were set to a constant value. Ocean elevations were set to zero. Rivers were stepped down monotonically to maintain proper flow. After this processing was done, the shorelines from the one arc second (approx. 30-meter) DTED® 2 were saved as vectors in ESRI 3-D Shapefile format.
In most cases, two orthorectified image mosaics (one for ascending passes and one for descending passes) at a one arc second resolution were available for identifying water bodies and delineating shorelines in each 1 x1 cell. These were used as the primary source for water body editing. The guiding principle for this editing was that water must be depicted as it was in February 2000 at the time of the shuttle flight. A Landcover water layer and medium-scale maps and charts were used as supplemental data sources, generally as supporting evidence for water identified in the image mosaics. Since the Landcover water layer was derived mostly from Landsat 5 data collected a decade earlier than the Shuttle mission and the map sources had similar currency problems, there were significant seasonal and temporal differences between the depiction of water in the ancillary sources and the actual extent of water bodies in February 2000 in many instances. In rare cases, where the SRTM image mosaics were missing or unusable, Landcover was used to delineate the water in the SRTM cells. The DTED® header records for those cells are documented accordingly. +
The SSURGO database contains information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS. The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. The maps outline areas called map units. The map units describe soils and other components that have unique properties, interpretations, and productivity. The information was collected at scales ranging from 1:12,000 to 1:63,360. More details were gathered at a scale of 1:12,000 than at a scale of 1:63,360. The mapping is intended for natural resource planning and management by landowners, townships, and counties. Some knowledge of soils data and map scale is necessary to avoid misunderstandings. +
The Shuttle Radar Topography Mission (SRTM) obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of Earth between 56 degrees south and 60 degrees north latitude. SRTM consisted of a specially modified radar system that flew onboard the Space Shuttle Endeavour during an 11-day mission in February of 2000.
NASA has released version 2 of the Shuttle Radar Topography Mission digital topographic data (also known as the "finished" version). Version 2 is the result of a substantial editing effort by the National Geospatial Intelligence Agency and exhibits well-defined water bodies and coastlines and the absence of spikes and wells (single pixel errors), although some areas of missing data ('voids') are still present. The Version 2 directory also contains the vector coastline mask derived by NGA during the editing, called the SRTM Water Body Data (SWBD), in ESRI Shapefile format.
Version 2.1 is a recalculation of the SRTM3 (nominal 90 meter sample spacing) version made by 3x3 averaging of the full resolution edited data. Version 2 had been generated by masking in edited samples from the lower-resolution publicly released by the NGA, and contained occasional artifacts, and in particular a slight vertical “banding” in databeyond 50° latitude. These have been eliminated in Version 2.1
SRTM data are distributed in two levels: SRTM1 (for the U.S. and its territories
and possessions) with data sampled at one arc-second intervals in latitude and
longitude, and SRTM3 (for the world) sampled at three arc-seconds. Three arc-second data are generated by three by three averaging of the one arc-second samples. +
The Southern Alaska Coastal Relief Model is a 24 arc-second digital elevation model ranging from 170° to 230° and 48.5° to 66.5° N. It integrates bathymetry and topography to represent Earth's surface and spans over the Gulf of Alaska, Bering Sea, Aleutian Islands, and Alaska's largest communities: Anchorage, Fairbanks, and Juneau. The relief model was built from a variety of source datasets acquired from the National Geophysical Data Center, National Ocean Service, United States Geological Survey, National Aeronautics and Space Administration, and other U.S. and international agencies.
The CRM provides a framework to enable scientists to model tsunami propagation and ocean circulation. In addition, it may be useful for benthic habitat research, weather forecasting, and environmental stewardship. +
R
The U.S. Geological Survey Real-Time Permafrost and Climate Monitoring Network in Arctic Alaska is a collaborative effort with BLM, U.S. Fish and Wildlife Service, private organizations and universities, all managed by USGS.
The network was established to provide high quality real-time environmental data to aid in land management decision making.
This real-time network is a subset of a larger U.S. Geological Survey permafrost and climate monitoring research network. Many of the stations are co-located with deep boreholes, thus forming the basis for comprehensive permafrost monitoring observatories. The objectives of the larger network include climate change detection, monitoring how permafrost and vegetation respond to climate change, and acquiring improved data for current permafrost characterization and impact assessment models. +
N
The United States Geological Survey (USGS) has collected water-resources data at approximately 1.5 million sites across the United States, Puerto Rico, and Guam.
The types of data collected are varied, but generally fit into the broad categories of surface water and ground water. Surface-water data, such as gage height (stage) and streamflow (discharge), are collected at major rivers, lakes, and reservoirs. Ground-water data, such as water level, are collected at wells and springs.
Water-quality data are available for both surface water and ground water. Examples of water-quality data collected are temperature, specific conductance, pH, nutrients, pesticides, and volatile organic compounds.
This web site serves current and historical data. Data are retrieved by category of data, such as surface water, ground water, or water quality, and by geographic area. Subsequent pages allow further refinement by selecting specific information and by defining the output desired.
Real-time data typically are recorded at 15-60 minute intervals, stored onsite, and then transmitted to USGS offices every 1 to 4 hours, depending on the data relay technique used. Recording and transmission times may be more frequent during critical events. Data from real-time sites are relayed to USGS offices via satellite, telephone, and/or radio and are available for viewing within minutes of arrival. (Note that all real-time data are provisional and subject to revision). +
W
The World Glacier Inventory contains information for over 100,000 glaciers through out the world. Parameters within the inventory include geographic location, area, length, orientation, elevation,and classification of morphological type and moraines. The inventory entries are based upon a single observation in time and can be viewed as a 'snapshot' of the glacier at this time. The core of this collection is data from the World Glacier Monitoring Service, Zurich. The development of the data product was funded through NOAA's Environmental Services Data and Information Management (ESDIM) program. +
The World Ocean Atlas 2001 (WOA01) contains ASCII data of statistics and objectively analyzed fields for one-degree and five-degree squares generated from World Ocean Database 2001 observed and standard level flagged data.
The ocean variables included in the atlas are: in-situ temperature, salinity, dissolved oxygen, apparent oxygen utilization, percent oxygen saturation, dissolved inorganic nutrients (phosphate, nitrate, and silicate), chlorophyll at standard depth levels, and plankton biomass sampled from 0 - 200 meters. +
The World Vector Shoreline (WVS) is a digital data file at a nominal scale of 1:250000, containing the shorelines, international boundaries and country names of the world. The World Vector Shoreline is a standard US Defense Mapping Agency (DMA) product that has been designed for use in many applications. The WVS is divided into ten ocean basin area files. Together the ten files form a seamless world, with the exception of Central America, where there is an overlap between the Western North Atlantic file and the Eastern North Pacific File.
The main source material for the WVS was the DMA's Digital Landmass Blanking (DLMB) data which was derived primarily from the Joint Operations Graphics and coastal nautical charts produced by DMA. The DLMB data consists of a land/water flag file on a 3 by 3 arc-second interval grid. This raster data set was converted into vector form to create the WVS. For areas of the world not covered by the DLMB data (e.g. the Arctic and Antarctic), the shoreline was taken from the best available hard copy sources at a preferred scale of 1:250000. The WVS data are stored in chain-node format, and include tags to indicate the landside/waterside of the shoreline. +
G
The basic concept adopted to develop this database is to integrate the best land cover data available, from local to global, into one single database using international standards; this task requires the harmonization among different layers and legends to create a consistent product.
Here are criteria and steps for the harmonization:
* absorb, overcome and minimize the thematic and spatio-temporal differences between individual databases;
* create an efficient and practical mechanism to harmonize various datasets using the land cover elements;
* use data fusion techniques to overcome some of the harmonization issues;
identify agreement/disagreement between a limited number of global dataset at pixel level;
* create land cover database;
* validate land cover database;
* develop a fully automated “procedure” to update the database when new datasets may become available. +
