Property:Extended data description
From CSDMS
This is a property of type Text.
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. +
The fully-standardised 26 geomorphometric variables consist of layers that describe the (i) rate of change across the elevation gradient, using first and second derivatives, (ii) ruggedness, and (iii) geomorphological forms. The Geomorpho90m variables are available at 3 (~90 m) and 7.5 arc-second (~250 m) resolutions under the WGS84 geodetic datum, and 100 m spatial resolution under the Equi7 projection. They are useful for modelling applications in fields such as geomorphology, geology, hydrology, ecology and biogeography. +
M
The global Mixed Layer Depth (MLD) Climatologies available here are computed from more than 5 million individual profiles obtained from the National Oceanographic Data Center (NODC), from the World Ocean Circulation Experiment (WOCE) database, and from the ARGO program. Those are all the high vertical resolution data available since 1941 until 2008, including mechanical bathythermograph (MBT), expendable bathythermograph (XBT), conductivity-temperature-depth probes (CTD), and profiling floats (PFL).
The MLDs are estimated directly on individual profiles with data at observed levels. The MLD is defined through the threshold method with a finite difference criterion from a near-surface reference value. A linear interpolation between levels is then used to estimate the exact depth at wich the difference criterion is reached. The reference depth is set at 10 m to avoid a large part of the strong diurnal cycle in the top few meters of the ocean. The optimal temperature criterion is found to be 0.2 °C absolute difference from surface. The optimal one in density is 0.03 kg/m3 difference from surface.
Reduction of the data is done on a regular 2° by 2° grid for every month, by taking the median of all MLDs in each grid mesh. A slight smoothing is then applied to take account of the noisy nature of ship observations. The last step consisted into an optimal prediction of the missing data using ordinary kriging method. This interpolation was limited to a 1000 km radius disk containing at least 5 grid point values, leaving regions without values instead of filled by a doubtful interpolation. The advantage of kriging is that it is an exact interpolator, and an estimation error in the form of the kriging standard deviation, an analogy to the statistical standard deviation, is also provided. +
D
The global drainage direction map DDM30 is a raster map which describes the drainage directions of surface water with a spatial resolution of 30’ longitude by 30’ latitude. 66896 individual grid cells, covering the entire land surface of the globe (without Antarctica), are connected to each other by their respective drainage direction and are thus organized into drainage basins. Each cell can drain only into one of the eight neighboring cells.
DDM30 is based on
# the digital drainage direction map with a resolution of 5’ of Graham et al. (1999) for South America, Australia, Asia and Greenland,
# the HYDRO1k digital drainage direction map (as flow accumulation map) with a resolution of 1 km (USGS, 1999) for North America, Europe, Africa and Oceania (without Australia).
Both given base maps were up scaled to a resolution of 30’. +
O
The mission of the OpenTopography Facility is to:
-Democratize online access to high-resolution (meter to sub-meter scale), Earth science-oriented, topography data acquired with LiDAR and other technologies.
-Harness cutting edge cyberinfrastructure to provide Web service-based data access, processing, and analysis capabilities that are scalable, extensible, and innovative.
-Promote discovery of data and software tools through community populated metadata catalogs.
-Partner with public domain data holders to leverage OpenTopography infrastructure for data discovery, hosting and processing.
-Provide professional training and expert guidance in data management, processing, and analysis.
-Foster interaction and knowledge exchange in the Earth science LiDAR user community.
The OpenTopography Facility is based at the San Diego Supercomputer Center at the University of California, San Diego and is operated in collaboration with colleagues at UNAVCO and in the School of Earth and Space Exploration at Arizona State University. Core operational support for OpenTopography comes from the National Science Foundation Earth Sciences: Instrumentation and Facilities Program (EAR/IF) and the Office of Cyberinfrastructure. In addition, we receive funding from the NSF and NASA to support various OpenTopography related research and development activities. OpenTopography was initially developed as a proof of concept cyberinfrastructure in the Earth sciences project as part of the NSF Information and Technology Research (ITR) program-funded Geoscience Network (GEON) project. +
3
The overall objective of the project is to combine radar and lidar remote sensing to characterize the forested landscapes in 3D. The science products generated by Simard and collaborators have four main components:
1 Global scale mapping of canopy height and biomass at 1km spatial resolution.
2 Improving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS).
3 High spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR.
4 Mapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change. +
R
This comprehensive river discharge database covers the entire pan-Arctic drainage system. The collection comprises data from 9138 gauges and contains monthly river discharge data extending from the 1890s (for four Canadian and five Russian gauges) through the early 1990s, but the majority of data was collected between 1960 and 2001. The pan-Arctic drainage region covers a land area of approximately 21 million km2 and drains into the Arctic Ocean as well as Hudson Bay, James Bay, and the Northern Bering Strait. The collection also includes the Yukon and Anadyr River basins. Most of the drainage basins in the database are greater than 15,000 km2; however, the collection includes all available gauge data from Canada and Russia. Data from gauges measuring large drainage areas are of greatest interest to the regional, continental, and global-scale scientific community for modeling purposes. Individual station data are accessible through a graphical interface, or as tab-delimited ASCII text. Tab-delimited ASCII data are also compiled by hydrological region and as a single file for the complete data set. +
N
This data portal, operated by the National Oceanic and Atmospheric Administration (NOAA) and the National Climatic Data Center (NCDC), contains archives of weather radar data (Doppler radar: NEXRAD), satellite coverage, and additional surface and marine data. These additional surface and marine data comprise historical forecasts and analyses, as well as the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) that covers three centuries of global ocean-atmosphere data, including 2x2 and (since 1960) 1x1 degree gridded data sets.
A tutorial for retrieving radar data is here:
http://www.ncdc.noaa.gov/oa/radar/nxhastutorial.html +
S
This data set is generated from brightness temperature data derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and Defense Meteorological Satellite Program (DMSP) -F8, -F11 and -F13 Special Sensor Microwave/Imager (SSM/I) radiances at a grid cell size of 25 x 25 km. The data are provided in the polar stereographic projection.
This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) spanning the coverage of several passive microwave instruments. To aid in this goal, sea ice algorithm coefficients are changed to reduce differences in sea ice extent and area as estimated using the SMMR and SSM/I sensors. The data are generated using the NASA Team algorithm developed by the Oceans and Ice Branch, Laboratory for Hydrospheric Processes at NASA Goddard Space Flight Center (GSFC).
These data include gridded daily (every other day for SMMR data) and monthly averaged sea ice concentrations for both the north and south polar regions. Two types of data are provided: final data and preliminary data. Final data are produced at GSFC about once per year, with roughly a one-year latency, and include data since 26 October 1978. Final data are produced from SMMR brightness temperature data processed at NASA GSFC and SSM/I brightness temperature data processed at the National Snow and Ice Data Center (NSIDC). Preliminary data are produced at NSIDC approximately every three months (quarterly), using SSM/I data acquired from Remote Sensing Systems, Inc. (RSS), and include roughly the most recent three to twelve months of processed data.
Data are scaled and stored as one-byte integers in flat binary arrays. +
