This data is part of the series of maps that covers the whole of Australia at a scale of 1:250 000 (1cm on a map represents 2.5km on the ground) and comprises 513 maps. This is the largest scale at which published topographic maps cover the entire continent. Data is downloadable in various distribution formats.

All available bathymetry and related information for Mitchell Lake were collected and hard copy maps digitized where necessary. The data were validated against more recent data (Shuttle Radar Topography Mission 'SRTM' imagery and Indian Remote Sensing 'IRS' imagery) and corrected where necessary. The published data set contains the lake bathymetry formatted as an Arc ascii grid. Bathymetric contours and the boundary polygon are available as shapefiles.

The Flood Risk Review Meeting for Baker, Grady, and Mitchell Counties was held on November 15, 2023. This meeting was coordinated by the Georgia Flood MAP Program as part of the Lower Flint Risk MAP Project.

All available bathymetry and related information for Mitchell Lake were collected and hard copy maps digitized where necessary. The data were validated against more recent data (Shuttle Radar Topography Mission 'SRTM' imagery and Indian Remote Sensing 'IRS' imagery) and corrected where necessary. The published data set contains the lake bathymetry formatted as an Arc ascii grid. Bathymetric contours and the boundary polygon are available as shapefiles.

From the site: “The Geologic Atlas of the United States is a set of 227 folios published by the U.S. Geological Survey between 1894 and 1945. Each folio includes both topographic and geologic maps for each quad represented in that folio, as well as description of the basic and economic geology of the area. The Geologic Atlas collection is maintained by the Map & GIS Library. The repository interface with integrated Yahoo! Maps was developed by the Digital Initiatives -- Research & Technology group within the TAMU Libraries using the Manakin interface framework on top of the DSpace digital repository software. Additional files of each map are available for download for use in GIS or Google Earth. A tutorial is provided which describes how to download theses files.”

The Kickoff Meeting for Baker, Decatur, Grady, Miller, and Mitchell Counties was held on October 8, 2020. This meeting was coordinated by the Georgia Flood MAP Program as part of the Lower Flint Watershed Risk MAP Project.

This Zoning feature class is an element of the Oregon GIS Framework statewide, Zoning spatial data. This version is authorized for public use. Attributes include zoning districts that have been generalized to state classes. As of June 30, 2023, this feature class contains zoning data from 229 local jurisdictions. DLCD plans to continue adding to and updating this statewide zoning dataset as they receive zoning information from the local jurisdictions. Jurisdictions included in the latest version of the statewide zoning geodatabase: Cities: Adams, Adrian, Albany, Amity, Antelope, Ashland, Astoria, Athena, Aurora, Banks, Barlow, Bay City, Beaverton, Bend, Boardman, Bonanza, Brookings, Brownsville, Burns, Butte Falls, Canby, Cannon Beach, Carlton, Cascade Locks, Cave Junction, Central Point, Chiloquin, Coburg, Columbia City, Coos Bay, Cornelius, Corvallis, Cottage Grove, Creswell, Culver, Dayton, Detroit, Donald, Drain, Dufur, Dundee, Dunes City, Durham, Eagle Point, Echo, Enterprise, Estacada, Eugene, Fairview, Falls City, Florence, Forest Grove, Fossil, Garibaldi, Gaston, Gates, Gearhart, Gervais, Gladstone, Gold Beach, Gold Hill, Grants Pass, Grass Valley, Gresham, Halsey, Happy Valley, Harrisburg, Helix, Hermiston, Hillsboro, Hines, Hood River, Hubbard, Idanha, Independence, Jacksonville, Jefferson, Johnson City, Jordan Valley, Junction City, Keizer, King City, Klamath Falls, La Grande, La Pine, Lafayette, Lake Oswego, Lebanon, Lincoln City, Lowell, Lyons, Madras, Malin, Manzanita, Maupin, Maywood Park, McMinnville, Medford, Merrill, Metolius, Mill City, Millersburg, Milton-Freewater, Milwaukie, Mitchell, Molalla, Monmouth, Moro, Mosier, Mount Angel, Myrtle Creek, Myrtle Point, Nehalem, Newberg, Newport, North Bend, North Plains, Nyssa, Oakridge, Ontario, Oregon City, Pendleton, Philomath, Phoenix, Pilot Rock, Port Orford, Portland, Prescott, Prineville, Rainier, Redmond, Reedsport, Rivergrove, Rockaway Beach, Rogue River, Roseburg, Rufus, Saint Helens, Salem, Sandy, Scappoose, Scio, Scotts Mills, Seaside, Shady Cove, Shaniko, Sheridan, Sherwood, Silverton, Sisters, Sodaville, Spray, Springfield, Stanfield, Stayton, Sublimity, Sutherlin, Sweet Home, Talent, Tangent, The Dalles, Tigard, Tillamook, Toledo, Troutdale, Tualatin, Turner, Ukiah, Umatilla, Vale, Veneta, Vernonia, Warrenton, Wasco, Waterloo, West Linn, Westfir, Weston, Wheeler, Willamina, Wilsonville, Winston, Wood Village, Woodburn, Yamhill. Counties: Baker County, Benton County, Clackamas County, Clatsop County, Columbia County, Coos County, Crook County, Curry County, Deschutes County, Douglas County, Harney County, Hood River County, Jackson County, Jefferson County, Josephine County, Klamath County, Lane County, Lincoln County, Linn County, Malheur County, Marion County, Multnomah County, Polk County, Sherman County, Tillamook County, Umatilla County, Union County, Wasco County, Washington County, Wheeler County, Yamhill County. R emaining jurisdictions either chose not to share data to incorporate into the public, statewide dataset or did not respond to DLCD’s request for data. These jurisdictions’ attributes are designated “not shared” in the orZDesc field and “NS” in the orZCode field.

The "add on" project area surveyed depths between the 27 and 175 meter depths around St. George Island and St Paul Island in the Central Bering Sea. Full bottom coverage, consisting of 100% multibeam data was achieved within the limits of hydrography for this survey. One hundred percent backscatter data was acquired and stored by TerraSond, Ltd to be processed by the client. The data were collected from the R/V Mount Mitchell by Terrasond, Inc using a Simrad EM710 multibeam echosounder.

The purpose of this project is to map wetland areas near the Great Salt Lake and display the changes that these areas have seen during drought conditions.

The global intelligent SF6 dew point meter market is experiencing robust growth, driven by increasing demand for reliable and efficient gas-insulated switchgear (GIS) in power substations and other industrial applications. The market's expansion is fueled by stringent regulations regarding SF6 gas handling and environmental concerns surrounding its potent greenhouse gas effect. The need for precise and continuous monitoring of SF6 gas purity, particularly its dew point, is paramount for maintaining optimal equipment performance and preventing costly breakdowns. This demand is further amplified by the growing adoption of smart grids and the digitalization of power systems, requiring advanced monitoring and control technologies. The market is segmented by application (substations, chemical industry, scientific research, others) and type (desktop, portable), with substations holding the largest market share due to the widespread use of SF6-insulated equipment in power transmission and distribution. Portable devices are gaining traction due to their convenience and ease of use in various field applications. While the initial investment in intelligent SF6 dew point meters can be relatively high, the long-term benefits of preventing equipment failures, reducing downtime, and minimizing environmental impact outweigh the costs. Key players in this market are actively investing in research and development to enhance the accuracy, reliability, and functionality of their products, contributing to the market’s continued growth. The market is expected to witness considerable expansion over the forecast period (2025-2033), propelled by technological advancements such as improved sensors, data analytics capabilities, and remote monitoring features. While the global economic climate and potential supply chain disruptions pose challenges, the increasing adoption of sustainable and environmentally friendly alternatives to SF6 gas, along with stricter regulatory compliance, is expected to drive innovation and stimulate the demand for advanced monitoring solutions. Competitive landscape analysis reveals a mix of established players and emerging companies, with ongoing competition focused on innovation, cost-effectiveness, and market penetration. Regional variations exist, with North America and Europe currently holding significant market shares due to well-established power grids and a focus on environmental regulations. However, rapid industrialization and infrastructure development in Asia-Pacific are expected to drive significant growth in this region over the coming years.

Legacy product - no abstract available

In response to Executive Order 13817 of December 20, 2017, the U.S. Geological Survey (USGS) coordinated with the Bureau of Land Management (BLM) to identify 35 nonfuel minerals or mineral materials considered critical to the economic and national security of the United States (U.S.) (https://pubs.usgs.gov/of/2018/1021/ofr20181021.pdf). Acquiring information on possible domestic sources of these critical minerals is the rationale for the USGS Earth Mapping Resources Initiative (Earth MRI). The program, which partners the USGS with State Geological Surveys, Federal agencies, and the private sector, aims to collect new geological, geophysical, and topographic (lidar) data in key areas of the U.S. to stimulate mineral exploration and production of critical minerals. Phase 1 - rare earth elements (REE) - https://pubs.er.usgs.gov/publication/ofr20191023A. Phase 2 - aluminum, cobalt, graphite, lithium, niobium, platinum group elements (PGE), rare earth elements, tantalum, tin, titanium, ...

This database includes surficial geology, contacts, fault, and marker bed layers providing the legend for the surficial geology layer. Original data from 1940's-1960's. Data is from the Kansas Geological Survey - Cartographic Services and its predecessors. The surficial geology layers display attributed polygons representing intervals in the stratigraphic sequence identified and mapped at the surface of the county. In the contacts layers of the database, contacts corresponding to the boundaries between adjacent geologic polygons on the map are represented by attributed line features. Marker bed layers include distinctive beds of rock strata that are easily distinguishable and observable over large horizontal distances. The surface expression of structural geologic features such as faults or the axis of a fold, syncline, or anticline are represented by attributed line features in the faults layers. Not all counties will have layers for all these features. Counties included are: Allen, Barton, Brown, Cheyenne, Clay, Cloud, Cowley, Decatur, Ellsworth, Franklin, Gove, Graham, Grant, Greeley, Harper, Haskell, Jackson, Kingman, Kiowa, Lane, Lincoln, Linn, Logan, Marshall, Meade, Miami, Mitchell, Nemaha, Ottawa, Pratt, Rawlins, Reno, Rice, Rush, Scott, Seward, Sheridan, Sherman, Stanton, Stevens, Sumner, Thomas, Trego, Wallace, Wichita

Feature layer service of The Woodlands Parks & Recreation Department trails linear feature data layer within George Mitchell Nature Preserve (GMNP) and adjacent areas including Spring Creek Nature Trail (SCNT).

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

A GIS data set created from a map, first published by BMR in 1983, that depicts the distribution of metamorphic facies in Australia. The original map was compiled between 1972 and 1983 by T.G. Vallance, G.W. DAddario, A.J. Stewart, J.E. Mitchell, J.F. Stirzaker, and A.S.Mikolajczak using data supplied by BMR, State and Territory Geological Surveys, Universities and the Geological Society of Australia.

As a digital data set the attributes have been revised to allow relational analysis of the data within. Two formats of GIS data are provided: ArcView shape files and Mapinfo TAB files.

The best fit model variables from OLS exploratory regression and their related VIF values.

Independent variables and the dependent variable and their classification index levels.

Last Revised: February 2016

Map Information

This nowCOAST™ time-enabled map service provides maps depicting the latest global forecast guidance of water currents, water temperature, and salinity at forecast projections: 0, 12, 24, 36, 48, 60, 72, 84, and 96-hours from the NWS/NCEP Global Real-Time Ocean Forecast System (GRTOFS). The surface water currents velocity maps display the direction using white or black streaklets. The magnitude of the current is indicated by the length and width of the streaklet. The maps of the GRTOFS surface forecast guidance are updated on the nowCOAST™ map service once per day. For more detailed information about layer update frequency and timing, please reference the
nowCOAST™ Dataset Update Schedule.

Background Information

GRTOFS is based on the Hybrid Coordinates Ocean Model (HYCOM), an eddy resolving, hybrid coordinate numerical ocean prediction model. GRTOFS has global coverge and a horizontal resolution of 1/12 degree and 32 hybrid vertical layers. It has one forecast cycle per day (i.e. 0000 UTC) which generates forecast guidance out to 144 hours (6 days). However, nowCOAST™ only provides guidance out to 96 hours (4 days). The forecast cycle uses 3-hourly momentum and radiation fluxes along with precipitation predictions from the NCEP Global Forecast System (GFS). Each forecast cycle is preceded with a 48-hr long nowcast cycle. The nowcast cycle uses daily initial 3-D fields from the NAVOCEANO operational HYCOM-based forecast system which assimilates situ profiles of temperature and salinity from a variety of sources and remotely sensed SST, SSH and sea-ice concentrations. GRTOFS was developed by NCEP/EMC/Marine Modeling and Analysis Branch. GRTOFS is run once per day (0000 UTC forecast cycle) on the NOAA Weather and Climate Operational Supercomputer System (WCOSS) operated by NWS/NCEP Central Operations.

The maps are generated using a visualization technique developed by the Data Visualization Research Lab at The University of New Hampshire's Center for Coastal and Ocean Mapping (http://www.ccom.unh.edu/vislab/). The method combines two techniques. First, equally spaced streamlines are computed in the flow field using Jobard and Lefer's (1977) algorithm. Second, a series of "streaklets" are rendered head to tail along each streamline to show the direction of flow. Each of these varies along its length in size, color and transparency using a method developed by Fowler and Ware (1989), and later refined by Mr. Pete Mitchell and Dr. Colin Ware (Mitchell, 2007).

Time Information

This map service is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.

In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.

This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.

This service is configured with time coverage support, meaning that the service will always return the most relevant available data, if any, to the specified time value. For example, if the service contains data valid today at 12:00 and 12:10 UTC, but a map request specifies a time value of today at 12:07 UTC, the data valid at 12:10 UTC will be returned to the user. This behavior allows more flexibility for users, especially when displaying multiple time-enabled layers together despite slight differences in temporal resolution or update frequency.

When interacting with this time-enabled service, only a single instantaneous time value should be specified in each request. If instead a time range is specified in a request (i.e. separate start time and end time values are given), the data returned may be different than what was intended.

Care must be taken to ensure the time value specified in each request falls within the current time coverage of the service. Because this service is frequently updated as new data becomes available, the user must periodically determine the service's time extent. However, due to software limitations, the time extent of the service and map layers as advertised by ArcGIS Server does not always provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time extent of the service:

  Issue a returnUpdates=true request (ArcGIS REST protocol only)
  for an individual layer or for the service itself, which will return
  the current start and end times of available data, in epoch time format
  (milliseconds since 00:00 January 1, 1970). To see an example, click on
  the "Return Updates" link at the bottom of the REST Service page under
  "Supported Operations". Refer to the
  ArcGIS REST API Map Service Documentation
  for more information.


  Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against
  the proper layer corresponding with the target dataset. For raster
  data, this would be the "Image Footprints with Time Attributes" layer
  in the same group as the target "Image" layer being displayed. For
  vector (point, line, or polygon) data, the target layer can be queried
  directly. In either case, the attributes returned for the matching
  raster(s) or vector feature(s) will include the following:


      validtime: Valid timestamp.


      starttime: Display start time.


      endtime: Display end time.


      reftime: Reference time (sometimes referred to as
      issuance time, cycle time, or initialization time).


      projmins: Number of minutes from reference time to valid
      time.


      desigreftime: Designated reference time; used as a
      common reference time for all items when individual reference
      times do not match.


      desigprojmins: Number of minutes from designated
      reference time to valid time.




  Query the nowCOAST™ LayerInfo web service, which has been created to
  provide additional information about each data layer in a service,
  including a list of all available "time stops" (i.e. "valid times"),
  individual timestamps, or the valid time of a layer's latest available
  data (i.e. "Product Time"). For more information about the LayerInfo
  web service, including examples of various types of requests, refer to
  the 
  nowCOAST™ LayerInfo Help Documentation

References

Fowler, D. and C. Ware, 1989: Strokes for Representing Vector Field Maps. Proceedings: Graphics Interface '98 249-253. Jobard, B and W. Lefer,1977: Creating evenly spaced streamlines of arbitrary density. Proceedings: Eurographics workshop on Visualization in Scientific Computing. 43-55. Mitchell, P.W., 2007: The Perceptual optimization of 2D Flow Visualizations Using Human in the Loop Local Hill Climbing. University of New Hampshire Masters Thesis. Department of Computer Science. NWS, 2013: About Global RTOFS, NCEP/EMC/MMAB, College Park, MD (Available at http://polar.ncep.noaa.gov/global/about/). Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M. Smedstad, J. Cummings, G.R. Halliwell, R. Bleck, R. Baraille, A.J. Wallcraft, C. Lozano, H.L. Tolman, A. Srinivasan, S. Hankin, P. Cornillon, R. Weisberg, A. Barth, R. He, F. Werner, and J. Wilkin, 2009: U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM). Oceanography, 22(2), 64-75. Mehra, A, I. Rivin, H. Tolman, T. Spindler, and B. Balasubramaniyan, 2011: A Real-Time Operational Global Ocean Forecast System, Poster, GODAE OceanView –GSOP-CLIVAR Workshop in Observing System Evaluation and Intercomparisons, Santa Cruz, CA.

A map created by DHM Design locating areas of potential on-the-ground action to enhance ecological conditions at North Star Nature Preserve. Associated GIS files of some restoration opportunity locations included.