The Digital Geologic Units of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina consists of geologic units mapped as area (polygon) features. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). The data were captured, grouped and attributed as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: https://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The data layer is available as a feature class in a 9.1 personal geodatabase (grsm_geology.mdb). Attributed geologic contact lines that define the geologic unit polygons are present within the Geologic Contacts (GRSMGLGA) data layer. The Geologic Units (GRSMGLG) GIS data layer is also available as a coverage export (.E00) file (GRSMGLG.E00), and as a shapefile (.SHP) file (GRSMGLG.SHP). Each GIS data format has an ArcGIS 9.1 layer (.LYR) file (GRSMGLG_GDB.LYR (geodatabase feature class), GRSMGLG_COV.LYR (coverage), GRSMGLG_SHP.LYR (shapefile) with map symbology that is included with the GIS data. See the Distribution Information section for additional information on data acquisition. The GIS data projection is NAD83, UTM Zone 17N. That data is within the area of interest of Great Smoky Mountains National Park. This dataset is just one component of the Digital Geologic Map of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina. The data layers (feature classes) that comprise the Digital Geologic Map of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina include: GRSMAML (Alteration and Metamorphic Lines), GRSMATD (Geologic Attitude and Observation Points), GRSMFLD (Folds), GRSMFLT (Faults), GRSMGLG (Geologic Units), GRSMGLGA (Geologic Contacts), GRSMGPT (Point Geologic Features), GRSMGSL (Geologic Sample Localities), GRSMMIN (Mine Point Features), GRSMSEC (Cross Section Lines), GRSMSUR (Surficial Geologic Units), GRSMSURA (Surficial Contacts) and GRSMSYM (Fault Symbology). There are three additional ancillary map components, the Geologic Unit Information (GRSMGLG1) Table, the Source Map Information (GRSMMAP) Table and the Map Help File (GRSM_GEOLOGY.HLP). Refer to the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1 (available at: https://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm) for detailed data layer (feature class) and table specifications including attribute field parameters, definitions and domains, and implemented topology rules and relationship classes.The corresponding Integration of Resource Management Applications (IRMA) NPS Data Store reference is Great Smoky Mountains National Park Geology.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. To produce a USNVC association-level vegetation map that satisfied the standards of the USGS/NPS Vegetation Mapping Program, the alliance-level vegetation map developed by Agius was edited and refined onscreen in ArcGIS 9.1. The Agius (2003b) vegetation map was not developed following the USGS/NPS Vegetation Mapping Program standards and therefore could not be used as the final vegetation classification map. Polygons that represented vegetation were readily attributed to existing associations in the U.S. National Vegetation Classification. Polygons that represented intensive land uses were attributed with names modified from the Anderson Level II categories.. Because Saugus Iron Works National Historic Park is a small park with only 21 polygons, the mapping did not rely entirely on aerial photograph interpretation, but also incorporated lines sketched onto a hard-copy map on site. Using ArcGIS 9.1, polygon boundaries were drawn onscreen based on the plot data and additional field observations. Each polygon was attributed with the name of an USNVC association or an Anderson Level II (modified) land use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. The shapefile was projected in Universal Transverse Mercator Zone 19 North, North American Datum 1983, meters, in ArcGIS 9.1.

The Digital Geologic Cross Section Lines of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina consists of cross section lines mapped as line (arc) features. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). The data were captured, grouped and attributed as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The data layer is available as a feature class in a 9.1 personal geodatabase (grsm_geology.mdb). The Geologic Cross Section Lines (GRSMSEC) GIS data layer is also available as a coverage export (.E00) file (GRSMSEC.E00), and as a shapefile (.SHP) file (GRSMSEC.SHP). Each GIS data format has an ArcGIS 9.1 layer (.LYR) file (GRSMSEC_GDB.LYR (geodatabase feature class), GRSMSEC_COV.LYR (coverage), GRSMSEC_SHP.LYR (shapefile) with map symbology that is included with the GIS data. See the Distribution Information section for additional information on data acquisition. The GIS data projection is NAD83, UTM Zone 17N. The data is within the area of interest of Great Smoky Mountains National Park.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. After the field sampling was complete, aerial photograph signatures were verified for all of the associations using the classification plot data, Bell et al. (2002), and Elliman (2004) and (2005) data. These signatures were extrapolated to other areas within the park boundary that were not sampled. Using ARCGIS 9.1, polygon boundaries in the preliminary vegetation map were further edited and refined to develop a draft association-level vegetation map. Polygons were updated with USNVC association names and codes based on the classification plot data. Polygons that were attributed with land use - land cover categories in the preliminary vegetation map retained their attributes. The aerial photointerpretation key was updated. The thematic accuracy of this 2006 draft association-level vegetation association and land use map was then assessed for accuracy.

This personal geodatabase contains land and water masks (as rasters and polygons) for the remotely sensed data. It also contains a polygon feature class named: Spatial_Extent_Remote_Sensing_Data, which denotes the outer boundaries of all of the remote sensing data. All of these masks were derived directly from the remotely sensed imagery using geoprocessing functionality in ArcGIS 9.1.

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

The Digital Point Geologic Units of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina consists of geologic units mapped as point features. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). The data were captured, grouped and attributed as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The data layer is available as a feature class in a 9.1 personal geodatabase (grsm_geology.mdb). The Point Geologic Units (GRSMGPT) GIS data layer is also available as a coverage export (.E00) file (GRSMGPT.E00), and as a shapefile (.SHP) file (GRSMGPT.SHP). Each GIS data format has an ArcGIS 9.1 layer (.LYR) file (GRSMGPT_GDB.LYR (geodatabase feature class), GRSMGPT_COV.LYR (coverage), GRSMGPT_SHP.LYR (shapefile) with map symbology that is included with the GIS data. See the Distribution Information section for additional information on data acquisition. The GIS data projection is NAD83, UTM Zone 17N. The data is within the area of interest of Great Smoky Mountains National Park.

NOAA's ENC Direct to GIS web portal provides comprehensive access to display, query, and download all available large scale NOAA ENC data in a variety of GIS/CAD formats for non-navigational purposes using Internet mapping service technology. A defined (and possibly named) administrative area. Note: The following data layers were downloaded from the NOAA ENC web site by Massachusetts Coastal Zone Management (CZM) on July 18, 2006: TRAFFIC SEPARATION SCHEME and PRECAUTIONARY AREA. These layers were converted to the ESRI shapefile format and reprojected from their native projection into North American Datum 1983 (NAD83) / Massachusetts State Plane coordinate system, Mainland Zone (Fipszone 2001) meters. All three shapefiles were merged in ArcGIS 9.1. Edits to fix topologic and geographic errors were made on August 18, 2006.

The Digital Folds of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina consists of folds mapped as line (arc) features. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). The data were captured, grouped and attributed as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The data layer is available as a feature class in a 9.1 personal geodatabase (grsm_geology.mdb). The Folds (GRSMFLD) GIS data layer is also available as a coverage export (.E00) file (GRSMFLD.E00), and as a shapefile (.SHP) file (GRSMFLD.SHP). Each GIS data format has an ArcGIS 9.1 layer (.LYR) file (GRSMFLD_GDB.LYR (geodatabase feature class), GRSMFLD_COV.LYR (coverage), GRSMFLD_SHP.LYR (shapefile) with map symbology that is included with the GIS data. See the Distribution Information section for additional information on data acquisition. The GIS data projection is NAD83, UTM Zone 17N. The data is within the area of interest of Great Smoky Mountains National Park.

The GEOCR500 dataset was processed completely digitally in ArcGIS 9.1 and integrated within a regional geographic information system.

Global GIS Controller Market was valued at USD 9.1 Billion in 2024 and is expected to reach USD 18.22 Billion in 2030 and project robust growth in the forecast period with a CAGR of 12.1% through 2030.

This feature layer represents road freight (tonnes carried) by region of origin. The layer has been developed as a proxy to represent SDG 9.1.2 'Passenger and Freight Volumes, by Mode of Transport' for Ireland. The layer was created using data produced by the Central Statistics Office (CSO) as part of the Road Freight Transport Survey 2016 and NUTS 3 boundary data produced by Tailte Éireann.Note that the NUTS 3 boundary refers to the former Regional Authorities established under the NUTS Regulation (Regulation (EU) 1059/2003). These boundaries were subsequently revised in 2016 through Commission Regulation (EU) 2016/2066 amending annexes to Regulation 1059/2003 (more info).

In 2015 UN countries adopted a set of 17 goals to end poverty, protect the planet and ensure prosperity for all as part of a new sustainable development agenda. Each goal has specific targets to help achieve the goals set out in the agenda by 2030. Governments are committed to establishing national frameworks for the achievement of the 17 Goals and to review progress using accessible quality data. With these goals in mind the CSO and Tailte Éireann are working together to link geography and statistics to produce indicators that help communicate and monitor Ireland’s performance in relation to achieving the 17 sustainable development goals.The indicator displayed supports the efforts to achieve goal number 9 which aims to build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation.

The GEOCR500 dataset was processed completely digitally in ArcGIS 9.1 and integrated within a regional geographic information system.

The Digital Geologic Map of the Lucas quadrangle, Kentucky is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcMap 9.1 layer (.LYR) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.4. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.1 personal geodatabase (luca_geology.mdb), as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 16N. That data is within the area of interest of Mammoth Cave National Park.

Bathymetric data were collected using a Lowrance Elite-5 HDI Combo sonar depth recorder along several transects throughout Lake Peters in August 2015. These data were used to create a bathymetric map using ArcGIS 9.1.

RAV Network information periodically changes with additions or removal of data and users should confirm that information is current and accurate. The RAV Network Road Tables and RAV Mapping Tool can be found on the Main Roads Western Australia website, refer Hyperlink below.https://www.mainroads.wa.gov.au/heavy-vehicles/Main Roads Open Data: Restricted Access Networkshttps://portal-mainroads.opendata.arcgis.com/pages/hvs-networksUpdate Frequency: WeeklySpatial Coverage: Western AustraliaLegalYou are accessing this data pursuant to a Creative Commons (Attribution) Licence which has a disclaimer of warranties and limitation of liability. You accept that the data provided pursuant to the Licence is subject to changes. Main Roads WA website is the official and current source of RAV Network data.Pursuant to section 3 of the Licence you are provided with the following notice to be included when you Share the Licenced Material and when you Share your Adapted Material: The Commissioner of Main Roads is the creator and owner of the data and Licenced Material, which is accessed pursuant to a Creative Commons (Attribution) Licence, which has a disclaimer of warranties and limitation of liability. Main Roads WA website is the official and current source of RAV Network data.Licensinghttps://creativecommons.org/licenses/by/4.0/legalcode

Series Name: Passenger volume (passenger kilometres) by mode of transportSeries Code: IS_RDP_PFVOLRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 9.1.2: Passenger and freight volumes, by mode of transportTarget 9.1: Develop quality, reliable, sustainable and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for allGoal 9: Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovationFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

The Digital Surficial Units of Great Smoky Mountains National Park and Vicinity, Tennessee and North Carolina consists of surficial units mapped as area (polygon) features. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). The data were captured, grouped and attributed as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The data layer is available as a feature class in a 9.1 personal geodatabase (grsm_geology.mdb). Attributed surficial contact lines that define the surficial unit polygons are present within the Surficial Contacts (GRSMSURA) data layer. The Surficial Units (GRSMSUR) GIS data layer is also available as a coverage export (.E00) file (GRSMSUR.E00), and as a shapefile (.SHP) file (GRSMSUR.SHP). Each GIS data format has an ArcGIS 9.1 layer (.LYR) file (GRSMSUR_GDB.LYR (geodatabase feature class), GRSMSUR_COV.LYR (coverage), GRSMSUR_SHP.LYR (shapefile) with map symbology that is included with the GIS data. See the Distribution Information section for additional information on data acquisition. The GIS data projection is NAD83, UTM Zone 17N. The data is within the area of interest of Great Smoky Mountains National Park.

The Digital Geologic Map of the Guinea Quadrangle, Virginia is comprised of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata, ArcMap 9.1 layer (.LYR) files, and an ArcMap 9.1 map document (.MXD) file. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.3.1 (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.htm). The GIS data is available as an 9.1 personal geodatabase (guin_geology.mdb), as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 18N. That data is within the area of interest of Fredericksburg and Spotsylvania County Battlefields Memorial National Military Park.

Mean depth was calculated from the bathymetry surface for each cell using the ArcGIS Spatial Analyst Focal Statistics "Mean" parameter. Mean depth represents the average depth value (in meters) within a square 3x3 cell window. The 2x2 meter resolution mean depth GeoTIFF was exported and added as a new map layer to aid in benthic habitat classification. Acoustic imagery was acquired for the VICRNM on two separate missions onboard the NOAA ship, Nancy Foster. The first mission took place from 2/18/04 to 3/5/04. The second mission took place from 2/1/05 to 2/12/05. On both missions, seafloor depths between 14 to 55 m were mapped using a RESON SeaBat 8101 ER (240 kHz) MBES sensor. This pole-mounted system measured water depths across a 150 degree swath consisting of 101 individual 1.5 degree x 1.5 degree beams. The beams to the port and starboard of nadir (i.e., directly underneath the ship) overlapped adjacent survey lines by approximately 10 m. The vessel survey speed was between 5 and 8 kn. In 2004, the ship's _location was determined by a Trimble DSM 132 DGPS system, which provided a RTCM differential data stream from the U.S. Coast Guard Continually Operating Reference Station (CORS) at Port Isabel, Puerto Rico. Gyro, heave, pitch and roll correctors were acquired using an Ixsea Octans gyrocompass. In 2005, the ship's positioning and orientation were determined by the Applanix POS/MV 320 V4, which is a GPS aided Inertial Motion Unit (IMU) providing measurements of roll, pitch and heading. The POS/MV obtained its positions from two dual frequency Trimble Zephyr GPS antennae. An auxiliary Trimble DSM 132 DGPS system provided a RTCM differential data stream from the U.S. Coast Guard CORS at Port Isabel, Puerto Rico. For both years, CTD (conductivity, temperature and depth) measurements were taken approximately every 4 hours using a Seabird Electronics SBE-19 to correct for the changing sound velocities in the water column. In 2004, raw data were logged in .xtf (extended triton format) using Triton ISIS software 6.2. In 2005, raw data were logged in .gsf (generic sensor format) using SAIC ISS 2000 software. Data from 2004 were referenced to the WGS84 UTM 20 N horizontal coordinate system, and data from 2005 were referenced to the NAD83 UTM 20 N horizontal coordinate system. Data from both projects were referenced to the Mean Lower Low Water (MLLW) vertical tidal coordinate system. The 2004 and 2005 MBES bathymetric data were both corrected for sensor offsets, latency, roll, pitch, yaw, static draft, the changing speed of sound in the water column and the influence of tides in CARIS Hips & Sips 5.3 and 5.4, respectively. The 2004 data was then binned to create a 1 x 1 m raster surface, and the 2005 data was binned to a create 2 x 2 m raster surface. After these final surfaces were created, the datum for the 2004 bathymetric surfaces was transformed from WGS84 to NAD83 using the "Project Raster" function in ArcGIS 9.1. The 2004 surface was transformed so that it would have the same datum as the 2005 surface. The 2004 bathymetric surface was then down sampled from 1 x 1 to 2 x 2 m using the "Resample" function in ArcGIS 9.1. The 2004 surface was resampled so it would have the same spatial resolution as the 2005 surface. Having the same coordinate systems and spatial resolutions, the final 2004 and 2005 bathymetry rasters were then merged using the Raster Calculator function "Merge" in ArcGIS's Spatial Analyst Extension to create a seamless bathymetry surface for the entire VICRNM area south of St. John. For a complete description of the data acquisition and processing parameters, please see the data acquisition and processing reports (DAPRs) for projects: NF-04-06-VI and NF-05-05-VI (Monaco & Rooney, 2004; Battista & Lazar, 2005).