The Digital Geomorphic-GIS Map of Cumberland Island National Seashore, Georgia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (cuis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (cuis_geomorphology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (cuis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (cuis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (cuis_geomorphology_metadata_faq.pdf). Please read the cuis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: RWParkinson Inc. and MDA Information Systems, Inc. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (cuis_geomorphology_metadata.txt or cuis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:60,000 and United States National Map Accuracy Standards features are within (horizontally) 30.5 meters or 100 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Access National Hydrography ProductsThe National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach.Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close.The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reach codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/NHD%201999%20Draft%20Standards%20-%20Capture%20conditions.PDF.Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

The National Weather Service (NWS) Storm Prediction Center (SPC) routinely collects reports of severe weather and compiles them with public access from the database called SeverePlot (Hart and Janish 1999) with a Graphic Information System (GIS). The composite SVRGIS information is made available to the public primarily in .zip files of approximately 50MB size. The files located at the access point have organized severe weather data by County Warning Area (CWA). A CWA is a grouping of counties for which severe weather information is distributed. Although available to all, the data provided may be of particular value to weather professionals and students of meteorological sciences. An instructional manual is provided on how to build and develop a basic severe weather report GIS database in ArcGis and is located at the technical documentation site contained in this metadata catalog.

The Graphic Parcellar Registry (GPR) is a geographic information system for the identification of agricultural parcels, managed by the ASP (Service and Payment Agency). An anonymous version of the graphical data of the RPG associated with some of the data reported by the operators shall be disseminated. These data provide detailed information on land use and land structures. For the 2007 to 2014 versions of the RPG, the data released includes only the islands. From the 2015 version of the GPR, the data disseminated shall include islets and agricultural parcels: information on land use and type of crop goes down to the level of the plot, information on land structures disappears. The ASP now entrusts the IGN with the dissemination of the anonymised data of the RPG. The dataset presented here has been processed. Two fields have been added “cult_txt” and “grp_txt” which respectively translate into text the codings of the fields “code_cultu” and “code_group”.

Access National Hydrography ProductsThe National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach.Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close.The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reach codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/NHD%201999%20Draft%20Standards%20-%20Capture%20conditions.PDF.Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map.

Figures to support communication and broader understanding of data products developed by the Marine-life Data and Analysis Team (MDAT).

Access National Hydrography ProductsThe National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach.Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close.The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reach codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/NHD%201999%20Draft%20Standards%20-%20Capture%20conditions.PDF.Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map.

NOTE: This file includes data for all 5 boroughs and has a size of 4.60 GB. Individual borough files are available for download from the metadata attachments section. Citywide Geographic Information System (GIS) land cover layer that displays land cover classification, plus pervious and impervious area and percentage at the parcel level, separated into 5 geodatabases, one per borough. DEP hosted a webinar on this study on June 23, 2020. A recording of the webinar, plus a PDF of the webinar presentation, accompany this dataset and are available for download. Please direct questions and comments to DEP at imperviousmap@dep.nyc.gov. This citywide parcel-level impervious area GIS layer was developed by the City of New York to support stormwater-related planning, and is provided solely for informational purposes. The accuracy of the data should be independently verified for any other purpose. The City disclaims any liability for errors and makes no warranties express or implied, including, but not limited to, implied warranties of merchantability and fitness for a particular purpose as to the quality, content, accuracy or completeness of the information, text graphics, links and other items contained in this GIS layer.

The Digital Geologic-GIS Map of Big Cypress National Preserve and Vicinity, Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (bicy_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (bicy_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (bicy_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (bicy_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (bicy_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (bicy_geology_metadata_faq.pdf). Please read the bicy_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Florida Geological Survey, U.S. Geological Survey and Earthfx Incorporated/BEM Systems Inc.. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (bicy_geology_metadata.txt or bicy_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:675,000 and United States National Map Accuracy Standards features are within (horizontally) 342.9 meters or 1125 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

In an effort to clean up the most polluted areas in the Great Lakes, the United States and Canada committed to working with State and Provincial governments to develop Remedial Action Plans for designated Areas of Concern (AOC) in the Great Lakes Basin. Currently there are 26 AOCs wholly within the United States and five that are shared by both the United States and Canada. This shapefile provides a polygon boundary for the St. Louis River Area of Concern and the Expanded Study Area surrounding Duluth, Minnesota, and Superior, Wisconsin. In developing the polygon boundary, the description of each AOC provided by EPA was used as a starting point for collecting basemap information to aid in the delineation of each boundary. Using Digital Orthophotography, Digital Raster Graphics, and Geographic Information Systems (GIS) layers such as watersheds, and water bodies where available, each polygon was then digitized and reviewed by representatives of both EPA, the Minnesota Department of Natural Resources, and the Wisconsin Department of Natural Resources for agreement. Sources of digital information used in the development of the AOCs include the USGS, the Microsoft Corporation Terraserver ( http://terraserver.homeadvisor.msn.com/default.aspx ), the Minnesota Department of Natural Resources GIS Data Deli ( http://deli.dnr.state.mn.us/ ), and the Wisconsin Department of Natural Resources ( http://www.dnr.state.wi.us/ ).

US Geologic Service (USGS) Digital Raster Graphics (1:24000 scale) for the State of Georgia, combined with a hillshade visualization of a 10 meter Digital Elevation Model (DEM). A DRG is an image of a USGS standard series topographic map scanned at a minimum resolution of 250 dots per inch, and georeferenced to the Universal Transverse Mercator (UTM) projection. Each 7.5-minute DRG provides coverage for an area of land measuring 7.5-minutes of latitude by 7.5-minutes longitude. The horizontal positional accuracy and datum of the DRG matches that of the source map. The National Elevation Dataset (NED) is produced and distributed by the USGS. The NED is derived from diverse sources and processed to a common coordinate system and unit of vertical measure. NED data are in geographic coordinates (decimal degree units) and conform with the North American Datum of 1983. Elevation values are in meters, and referenced to the North American Vertical Datum of 1988 over the conterminous US. Although these data have been processed successfully on a computer system at the Georgia GIS Data Clearinghouse, no warranty expressed or implied is made by Georgia GIS Data Clearinghouse regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty.

The National Weather Service (NWS) maintains historical Atlantic Ocean hurricane weather data in a format that can be exploited by Graphic Information System (GIS) software. Using KML/KMZ formats, it takes the numbers and words from the rows and columns in databases and spreadsheets and puts them on a map. This data file contains information about named and unnamed Altantic tropical storms and hurricanes from 1851 to 2006. Once downloaded, the file can be decompiled by decade and by year in a a KML/KMZ GIS viewer.

The National Weather Service (NWS) maintains historical Eastern Pacific Ocean hurricane weather data in a format that can be exploited by Graphic Information System (GIS) software. Using KML/KMZ formats, it takes the numbers and words from the rows and columns in databases and spreadsheets and puts them on a map. This data file contains information about named and unnamed Eastern Pacific Ocean tropical storms and hurricanes from 1949 to 2006. Once downloaded, the file can be decompiled by decade and by year in a a KML/KMZ GIS viewer.

US Geologic Service (USGS) Digital Raster Graphics (1:24000 scale) covering the State of Georgia. A DRG is an image of a USGS standard series topographic map scanned at a minimum resolution of 250 dots per inch, and georeferenced to the Universal Transverse Mercator (UTM) projection. Each 7.5-minute DRG provides coverage for an area of land measuring 7.5-minutes of latitude by 7.5-minutes longitude. The horizontal positional accuracy and datum of the DRG matches that of the source map. Although these data have been processed successfully on a computer system at the Georgia GIS Data Clearinghouse, no warranty expressed or implied is made by Georgia GIS Data Clearinghouse regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty.

Total-Other-Income-Expense-Net Time Series for Argo Graphics Inc. ARGO GRAPHICS Inc. provides technical solutions in Japan. The company provides PLM solutions that simulates the feasibility of all elements relating to product development; HPC solutions to process technical calculations through system design/construction; and virtualization of server/client, server/storage consolidation, and IT infrastructure. It also provides a range of services to support its clients, including consulting for improving operations; system development for process construction; system realization/construction; and training/operational support. In addition, the company offers CAE analysis, analysis tool development, engineering experimentation and measurement, 3D CAD modeling, engineer education, and customer support services; and system development, IT hardware sales and consulting, and IT services. Further, it engages in the develops and sells scientific software, DTP software, system integration solution, quality management software, and document management software, as well as implementation of information sharing system; architecture and sale of the system for scientific computation; computer cluster sale and development support; and sale and support of 2D CAD software and 3D visual environment construction. Additionally, the company is involved in the development and sale of support software for power semiconductor and liquid crystal panel development; PDM software development, sale, and construction support; and provision of development support for IT infrastructure, and manufacturing processes and related services, as well as sales and support services of CAD/CAM software. Furthermore, it engages in the sale and support of electro magnetic software engineering; mechanical designing of powertrain multi-body systems; system programming design and consulting; advanced composite material modeling; and analysis support and consulting activities services. ARGO GRAPHICS Inc. was incorporated in 1971 and is headquartered in Tokyo, Japan.

Graphic data of Town Planning Board (TPB) Planning Guidelines No. 13G for Application for Open Storage and Port Back-up Uses under Section 16 of the Town Planning Ordinance, including all geographical information system (GIS) data, data dictionary and guidelines on using the GIS data, provided by the TPB is available for download. Please note that in using the data, you have agreed to be bound unconditionally by the Terms and Conditions of Use of the digital planning data enclosed in the downloaded data. Please read carefully the Terms and Conditions of Use. Please click https://www.info.gov.hk/tpb/en/forms/Guidelines/TPB_PG_13G_e.pdf to download the TPB Planning Guidelines No.13G. For details of the graphic data, please refer to Statutory Planning Portal 3 website (http://www.ozp.tpb.gov.hk). The multiple file formats are available for dataset download in API.

The graphics processor (GPU) market is experiencing robust growth, driven by increasing demand across diverse sectors. A compound annual growth rate (CAGR) of 33.35% from 2019 to 2024 suggests a significant expansion, which is expected to continue into the forecast period (2025-2033). Key drivers include the proliferation of high-resolution displays, the rise of artificial intelligence (AI) and machine learning (ML) applications demanding significant processing power, and the growing popularity of gaming and virtual/augmented reality (VR/AR) technologies. The market is segmented by type (dedicated, integrated, hybrid), deployment (on-premise, cloud), and application (smartphones, tablets, notebooks, workstations, gaming PCs, media & entertainment, automotive). The dedicated graphics card segment currently dominates, fueled by the gaming and professional workstation markets. However, integrated graphics solutions are gaining traction in budget-friendly devices and embedded systems. Cloud deployment is emerging as a significant growth area, driven by the increasing adoption of cloud-based gaming and AI services. Geographical distribution reveals a strong presence in North America and Asia-Pacific, with Europe and other regions showing promising growth potential. Leading companies like NVIDIA, AMD, Intel, and Qualcomm are actively investing in R&D to maintain their market positions and capitalize on emerging technologies. The restraints include supply chain disruptions, the high cost of advanced GPUs, and potential energy consumption concerns associated with high-performance computing. The future of the GPU market hinges on technological advancements such as ray tracing, advanced AI acceleration, and the development of more energy-efficient architectures. The automotive sector presents a significant growth opportunity, driven by the increasing adoption of advanced driver-assistance systems (ADAS) and autonomous driving technologies. The continued expansion of the gaming and media & entertainment industries will also bolster demand. Competition is fierce, with established players and emerging companies vying for market share. Strategic partnerships, mergers and acquisitions, and continuous innovation will be crucial for success in this dynamic market. Accurate market sizing requires further data, but based on the provided CAGR and industry trends, a reasonable estimate suggests a considerable market value by 2033. Furthermore, the shift towards high-performance computing for scientific research and data centers will create new growth avenues. Recent developments include: July 2022: The first 16-gigabit (Gb) Graphics Double Data Rate 6 (GDDR6) DRAM with processing speeds of 24 gigabits per second (Gbps) was launched by Samsung Electronics. The new memory, which is built using extreme ultraviolet (EUV) technology and Samsung's third-generation 10-nanometer-class (1z) process, is intended to significantly improve graphics performance for next-generation graphics cards (Video Graphics Arrays), laptops, game consoles, artificial intelligence-based applications, and high-performance computing (HPC) systems., November 2022: Qualcomm Technologies, Inc launched the Snapdragon 8 Gen 2 premium mobile platform. The Snapdragon 8 Gen 2 Mobile Platform, strategically developed with ground-breaking AI on every level to allow amazing experiences, will set a new benchmark for connected computing. Snapdragon 8 Gen 2 launched new Snapdragon Elite Gaming capabilities, such as real-time hardware-accelerated ray tracing, which gives mobile games realistic lighting, reflections, and illuminations. Users may enjoy champion-level gaming with longer battery life thanks to the updated Qualcomm Adreno GPU's up to 25% faster performance and the Qualcomm Kryo CPU's up to 40% greater power efficiency.. Key drivers for this market are: Increasing Demand for Graphic Applications, Rise of Geographic Information Systems (GIS) and Immersive Multimedia. Potential restraints include: Increasing Demand for Graphic Applications, Rise of Geographic Information Systems (GIS) and Immersive Multimedia. Notable trends are: Gaming Industry to Augment Market Growth.

Broadcast Graphics Systems Market Outlook

According to our latest research, the global broadcast graphics systems market size in 2024 stands at USD 1.85 billion, demonstrating robust momentum driven by technological advancements and the surging demand for high-quality visual content in broadcasting. The market is expected to expand at a CAGR of 8.7% from 2025 to 2033, reaching a projected value of USD 3.92 billion by the end of the forecast period. This growth is underpinned by the rapid adoption of digital broadcasting solutions, increasing investments in live event production, and the ongoing transition to high-definition and ultra-high-definition formats across the globe.

A primary driver for the broadcast graphics systems market is the escalating demand for immersive and engaging visual experiences in news, sports, and entertainment broadcasting. As consumer expectations evolve, broadcasters are compelled to deliver visually rich content that not only informs but also captivates audiences. This trend is further amplified by the proliferation of digital platforms and the need for real-time, interactive graphics that enhance viewer engagement. The integration of augmented reality (AR) and virtual reality (VR) into broadcast graphics systems is another significant growth factor, allowing broadcasters to create more dynamic and compelling visual narratives. Additionally, the shift towards remote production workflows, accelerated by the global pandemic, has necessitated the deployment of advanced graphics solutions that can be operated seamlessly from decentralized locations.

Technological innovation remains at the heart of the broadcast graphics systems marketÂ’s expansion. The adoption of cloud-based solutions is transforming the way graphics are generated, managed, and distributed, offering broadcasters unprecedented scalability and flexibility. These cloud-based systems enable real-time collaboration among geographically dispersed teams, streamline production workflows, and reduce infrastructure costs. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) into broadcast graphics is facilitating automated content creation, personalized viewer experiences, and efficient data visualization. As broadcasters strive to maintain a competitive edge, investments in cutting-edge graphics technologies are expected to intensify, further fueling market growth over the forecast period.

Another key growth factor is the increasing demand for live sports and event broadcasting, which requires sophisticated graphics systems to deliver real-time statistics, analysis, and augmented visual elements. Sports channels and production houses are leveraging advanced graphics solutions to enhance storytelling, provide instant replays, and offer interactive features that deepen audience engagement. The rise of e-sports and virtual events has also contributed to market expansion, as organizers seek to replicate the excitement of live sports through visually rich digital experiences. Furthermore, regulatory mandates for accessibility, such as closed captioning and multilingual graphics, are driving the adoption of versatile broadcast graphics systems across diverse end-user segments.

In the realm of sports broadcasting, Scorebug Systems have become an indispensable tool for delivering real-time information to viewers. These systems provide a seamless way to display scores, time, and other essential game statistics, enhancing the viewer's experience by keeping them informed without distracting from the action on screen. The integration of Scorebug Systems with advanced graphics solutions allows broadcasters to offer dynamic and interactive features, such as player stats and instant replays, further enriching the audience's engagement. As the demand for live sports coverage continues to grow, the role of Scorebug Systems in providing accurate and timely updates is more critical than ever, making them a vital component of modern broadcast graphics systems.

From a regional perspective, North America currently dominates the broadcast graphics systems market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of major broadcasters, rapid technological adoption, and significant investments in media infrastructure are key factors supporting North Am