Sheboygan's custom projection file used with aerial imagery downloads.

The goal of this project is to create a map of the planet Mars, by using ESRI software. For this, a 3D project was developed using ArcGIS Pro, considering a global scene, to be published in an online platform. All the various data from Mars will be available in a single website, where everyone can visualize and interact. The Red Planet has been studied for many decades and this year marks the launch of a new rover, Mars2020, which will happen on the 17th of July. This new rover will be continuing the on-going work of the Curiosity Rover, launched in 2012. The main objective for these rovers is to determine if Mars could have supported life, by studying its water, climate and geology. Currently, the only operational rover in Mars is Curiosity and with that in mind, this project will have a strong focus on the path taken by this rover, during almost 8 years of exploration. In the web application, the user will be able to see the course taken by Curiosity in Mars’ Gale Crater, from its landing until January 2020. The map highlights several points of interest, such as the location after each year passed on MarsEarth year and every kilometer, which can be interacted with as well as browse through photos taken at each of the locations, through a pop-up window. Additionally, the application also supports global data of Mars. The two main pieces, used as basemaps, are the global imagery, with a pixel size of 925 meters and the Digital Elevation Model (DEM), with 200 meters per pixel. The DEM represents the topography of Mars and was also used to develop Relief and Slope Maps. Furthermore, the application also includes data regarding the geology of the planet and nomenclature to identify regions, areas of interest and craters of Mars. This project wouldn’t have been possible without NASA’s open-source philosophy, working alongside other entities, such as the European Space Agency, the International Astronomical Union and the Working Group for Planetary System Nomenclature. All the data related to Imagery, DEM raster files, Mars geology and nomenclature was obtained on USGS Astrogeology Science Center database. Finally, the data related to the Curiosity Rover was obtained on the portal of The Planetary Society. Working with global datasets means working with very large files, so selecting the right approach is crucial and there isn’t much margin for experiments. In fact, a wrong step means losing several hours of computing time. All the data that was downloaded came in Mars Coordinate Reference Systems (CRS) and luckily, ESRI handles that format well. This not only allowed the development of accurate analysis of the planet, but also modelling the data around a globe. One limitation, however, is that ESRI only has the celestial body for planet Earth, so this meant that the Mars imagery and elevation was wrapped around Earth. ArcGIS Pro allows CRS transformation on the fly, but rendering times were not efficient, so the workaround was to project all data into WGS84. The slope map and respective reclassification and hillshading was developed in the original CRS. This process was done twice: one globally and another considering the Gale Crater. The results show that the crater’s slope characteristics are quite different from the global panorama of Mars. The crater has a depression that is approximately 5000 meters deep, but at the top it’s possible to identify an elevation of 750 meters, according to the altitude system of Mars. These discrepancies in a relatively small area result in very high slope values. Globally, 88% of the area has slopes less than 2 degrees, while in the Gale Crater this value is only 36%. Slopes between 2 and 10 degrees represent almost 60% of the area of the crater. On the other hand, they only represent 10% of the area globally. A considerable area with more than 10 degrees of slope can also be found within the crater, but globally the value is less than 1%. By combining Curiosity’s track path with the DEM, a profile graph of the path was obtained. It is possible to observe that Curiosity landed in a flat area and has been exploring in a “steady path”. However, in the last few years (since the 12th km), the rover has been more adventurous and is starting to climb the crater. In the last 10 km of its journey, Curiosity “climbed” around 300 meters, whereas in the first 11 km it never went above 100 meters. With the data processed in the WGS84 system, all was ready to start modelling Mars, which was firstly done in ArcGIS Pro. When the data was loaded, symbology and pop-ups configured, the project was exported to ArcGIS Online. Both the imagery and elevation layer were exported as “hosted tile service”. This was a key step, since keeping the same level of detail online and offline would have a steep increase in imagery size, to hundreds of Terabytes, thus a lot of work was put into balancing tile cache size and the intended quality of imagery. For the remaining data, it was a straight-forward step, exporting these files as vectors. Once all the data was in the Online Portal, a Global Web Scene was developed. This is an on-going project with an outlook to develop the global scene into an application with ESRI’s AppBuilder, allowing the addition of more information. In the future, there is also interest to increment the displayed data, like adding the paths taken by other rovers in the past, alongside detailed imagery of other areas beyond the Gale Crater. Finally, with 2021 being the year when the new rover Mars2020 will land on the Red Planet, we might be looking into adding it to this project.https://arcg.is/KuS4r

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. We converted the photointerpreted data into a GIS-usable format employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM) projection, Zone 16, using North American Datum of 1983 (NAD83). To produce a polygon vector layer for use in ArcGIS, we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format using ArcGIS (Version 9.2, © 2006 Environmental Systems Research Institute, Redlands, California). In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map attribute codes (both map class codes and physiognomic modifier codes) to the polygons, and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer of INDU and immediate environs. At this stage, the map layer has only map attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map class names, physiognomic definitions, link to NVC association and alliance codes), we produced a feature class table along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature class layers produced from this project, including vegetation sample plots, accuracy assessment sites, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

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. GIS Database 2002-2005: Project Size = 1,898 acres Fort Larned National Historic Site (including the Rut Site) = 705 acres 16 Map Classes 11 Vegetated 5 Non-vegetated Minimum Mapping Unit = ½ hectare is the program standard but this was modified at FOLS to ¼ acre. Total Size = 229 Polygons Average Polygon Size = 8.3 acres Overall Thematic Accuracy = 92% To produce the digital map, a combination of 1:8,500-scale (0.75 meter pixels) color infrared digital ortho-imagery acquired on October 26, 2005 by the Kansas Applied Remote Sensing Program and 1:12,000-scale true color ortho-rectified imagery acquired in 2005 by the U.S. Department of Agriculture - Farm Service Agency’s Aerial Photography Field Office, and all of the GPS referenced ground data were used to interpret the complex patterns of vegetation and land-use. In the end, 16 map units (11 vegetated and 5 land-use) were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. One hundred and six accuracy assessment (AA) data points were collected in 2006 by KNSHI and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 92%.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

New project plans are no longer accepted. Project Plan amendments are the only form of Project Plan that is still reviewed. Before submitting an application, applicants must meet with planning staff and receive an amendment checklist that outlines the required submission items. A Project Plan sets the development density, height limit, and public amenities for optional method projects in the CBD zones under the 2004 Zoning Ordinance. For further details: https://montgomeryplanning.org/development/development-applications/project-plan/ For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and 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 (guis_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 map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.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 (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_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 (guis_geomorphology_metadata_faq.pdf). Please read the guis_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: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_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 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 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).

This layer presents the Universal Transverse Mercator (UTM) zones of the world. The layer symbolizes the 6-degree wide zones employed for UTM projection.To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to World UTM Zones Grid.

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. James W. Sewall Company developed a complete GIS coverage for the park and revised the preliminary vegetation map classes to better match the results from the cluster analysis and NMS ordination. Polygons representing vegetation stands were digitized on-screen in ArcGIS 8.3, and later in ArcMap 9.1 and 9.2, using lines drawn on the acetate overlays, base layers of 1:8,000 CIR aerial photography, orthorectified photo composite image, and plot location and data. The minimum map unit used was 0.5 ha (1.24 ac). Stereo pairs were used to double check stand signatures during the digitizing process. Photo interpretation and polygon digitization extended outside the NPS boundary, especially where vegetation units were arbitrarily truncated by the boundary. Each polygon was attributed with the name of a vegetation map class or an Anderson Level II land use category based on plot data, field observations, aerial photography signatures, and topographic maps. Data fields identifying the USNVC association inclusions within the vegetation map class were attributed to the vegetation polygons in the shapefile. The GIS coverages and shapefiles were projected to Universal Transverse Mercator (UTM) Zone 19 North American Datum 1983 (NAD83). FGDC compliant metadata (FGDC 1998a) were created with the NPS-MP ESRI extension and included with the vegetation map shapefile. A photointerpretation key to the map classes for the 2006 draft vegetation map is included as Appendix A. The composite vegetation coverage was clipped to the NPS 2002 MIMA boundary shapefile for accuracy assessment (AA). After the 2006 vegetation map was completed, the thematic accuracy of this map was assessed.

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology and structural framework map. The maps were done in ArcGIS 9.3.1 and the data stored in file geodatabases, topology created and validated. This provides greater data quality by performing topological validation on the feature's spatial relationships. For the purposes of the DVD, shapefiles were created from the file geodatabases and for MapInfo users MapInfo .tab and .wor files. The shapefiles on the DVD are a revision of the 1975 Queensland geology data, and are both are available for display, query and download on the department's online GIS application. The Queensland geology map is a digital representation of the distribution or extent of geological units within Queensland. In the GIS, polygons have a range of attributes including unit name, type of unit, age, lithological description, dominant rock type, and an abbreviated symbol for use in labelling the polygons. The lines in this dataset are a digital representation of the position of the boundaries of geological units and other linear features such as faults and folds. The lines are attributed with a description of the type of line represented. Approximately 2000 rock units were grouped into the 250 map units in this data set. The digital data was generalised and simplified from the Department's detailed geological data and was captured at 1:500 000 scale for output at 1:2 000 000 scale. In the ESRI version, a layer file is provided which presents the units in the colours and patterns used on the printed hard copy map. For Map Info users, a simplified colour palette is provided without patterns. However a georeferenced image of the hard copy map is included and can be displayed as a background in both Arc Map and Map Info. The geological framework of Queensland is classified by structural or tectonic unit (provinces and basins) in which the rocks formed. These are referred to as basins (or in some cases troughs and depressions) where the original form and structure are still apparent. Provinces (and subprovinces) are generally older basins that have been strongly tectonised and/or metamorphosed so that the original basin extent and form are no longer preserved. Note that intrusive and some related volcanic rocks that overlap these provinces and basins have not been included in this classification. The map was compiled using boundaries modified and generalised from the 1:2 000 000 Queensland Geology map (2012). Outlines of subsurface basins are also shown and these are based on data and published interpretations from petroleum exploration and geophysical surveys (seismic, gravity and magnetics). For the structural framework dataset, two versions are provided. In QLD_STRUCTURAL_FRAMEWORK, polygons are tagged with the name of the surface structural unit, and names of underlying units are imbedded in a text string in the HIERARCHY field. In QLD_STRUCTURAL_FRAMEWORK_MULTI_POLYS, the data is structured into a series of overlapping, multi-part polygons, one for each structural unit. Two layer files are provided with the ESRI data, one where units are symbolised by name. Because the dataset has been designed for units display in the order of superposition, this layer file assigns colours to the units that occur at the surface with concealed units being left uncoloured. Another layer file symbolises them by the orogen of which they are part. A similar set of palettes has been provided for Map Info. Dataset History Details on the source data can be found in the xml file associated with data layer. Data in this release *ESRI.shp and MapInfo .tab files of rock unit polygons and lines with associated layer attributes of Queensland geology *ESRI.shp and MapInfo .tab files of structural unit polygons and lines with associated layer attributes of structural framework *ArcMap .mxd and .lyr files and MapInfo .wor files containing symbology *Georeferenced Queensland geology map, gravity and magnetic images *Queensland geology map, structural framework and schematic diagram PDF files *Data supplied in geographical coordinates (latitude/longitude) based on Geocentric Datum of Australia - GDA94 Accessing the data Programs exist for the viewing and manipulation of the digital spatial data contained on this DVD. Accessing the digital datasets will require GIS software. The following GIS viewers can be downloaded from the internet. ESRI ArcExplorer can be found by a search of www.esriaustralia.com.au and MapInfo ProViewer by a search on www.pbinsight.com.au collectively ("the websites"). Metadata Metadata is contained in .htm files placed in the root folder of each vector data folder. For ArcMap users metadata for viewing in ArcCatalog is held in an .xml file with each shapefile within the ESRI Shapefile folders. Disclaimer The State of Queensland is not responsible for the privacy practices or the content of the websites and makes no statements, representations, or warranties about the content or accuracy or completeness of, any information or products contained on the websites. Despite our best efforts, the State of Queensland makes no warranties that the information or products available on the websites are free from infection by computer viruses or other contamination. The State of Queensland disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages and costs you might incur as a result of accessing the websites or using the products available on the websites in any way, and for any reason. The State of Queensland has included the websites in this document as an information source only. The State of Queensland does not promote or endorse the websites or the programs contained on them in any way. WARNING: The Queensland Government and the Department of Natural Resources and Mines accept no liability for and give no undertakings, guarantees or warranties concerning the accuracy, completeness or fitness for the purposes of the information provided. The consumer must take all responsible steps to protect the data from unauthorised use, reproduction, distribution or publication by other parties. Please view the 'readme.html' and 'licence.html' file for further, more complete information Dataset Citation Geological Survey of Queensland (2012) Queensland geology and structural framework - GIS data July 2012. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/69da6301-04c1-4993-93c1-4673f3e22762.

The Columbia River Light Detection and Ranging (LiDAR) survey project was a collaborative effort to develop detailed high density LiDAR terrain data for the US Army Corps of Engineers (USACE). The LiDAR will be used to support hydraulic modeling work associated with proposed 2014 Columbia River treaty negotiations. The dataset encompasses approximately 2836 square miles of territory in portions of Oregon, Washington, Idaho and Montana within the Columbia River drainage. This survey was under the jurisdiction of three Corps districts: Portland (CENWP), Seattle (CENWS), and Walla Walla (CENWW). CENWP was the project lead and primary contracting organization. Bare earth point data are classified as either ground (2), model key point (8) or water (9) and represent the earth's surface with all vegetation and human-made structures removed. Model key points were generated to represent the bare earth surface within a 0.07 m tolerance. Ground points (class 2) are the remaining ground points not classed as model key. Both ground and model key classes are needed for display of all bare earth points. Water classification was used for those bare earth/ground classified points that fell inside a water boundary as determined using softcopy photogrammetry with stereograms generated from LiDAR intensities. All remaining points received the default classification (1). In some areas of heavy vegetation or forest cover, there may be relatively few ground points in the LiDAR data. The RMSE of the data for open, hard-packed surfaces is 0.046 meters as assessed from 40,266 ground survey (real time kinematic) points taken on hard-packed road surfaces. This value is representative of anticipated accuracies in open, evenly sloped or flat terrain where maximum point densities were achieved. The project was completed for the US Army Corps of Engineers, Portland District, to support hydraulic modeling related to the ACOE Columbia River Treaty project. Data acquisition, bare earth processing, and development of final tiled LiDAR deliverables and DEM's was performed by Watershed Sciences, Inc. Overall project management, photogrammetric quality control review using LiDAR stereograms, water delineation and breakline development was performed by David C. Smith & Associates, Inc. Professional Surveyor oversight of ground control data, ground control data processing and ground control publication was performed by David Evans and Associates, Inc. Final quality control review in ArcGIS of all final deliverables, including preparation of point density rasters and reach based geo-databases incorporating all deliverables, was performed by CC Patterson and Associates. NOTE ON DATUM ISSUES: All ground control and subsequent LiDAR data deliverables were developed and delivered at NAD '83 CORS 96 horizontal and NAVD '88 Geoid '09 vertical datums as processed in OPUS-DB. Due to limitations in the transformations supported by ESRI, NAD '83 and NAVD '88 datums were temporarily assigned to the ESRI deliverables and ESRI .prj file even though the actual coordinate values in the data files are at the original NAD '83 CORS 96 and NAVD '88 Geoid '09 datums. In many instances, a temporary assignment of NAD '83 HARN or HPGN may better approximate local conditions. Plain NAD '83 was used for the primary deliverable in order to avoid any implication of higher precision; however, the user may want to evaluate other approximations for specific applications. At such time as ESRI includes support for NAD '83 CORS '96, the temporary NAD '83 assignment in the .prj file should be replaced with NAD '83 CORS '96 without further reprojection. The NOAA Coastal Services Center has converted the data to ellipsoid heights (using Geoid09) and NAD 83 geographic coordinates for data storage and Digital Coast provisioning purposes.

Includes country boundaries that existed in 1998 as well as 1992, administrative unit boundaries, cities, gazetteer points, including places and airports, lakes and rivers. Demographic and geographic attributes.The ArcView project world.apr displays most of the dataset, however it expects the data files to bepresent on CD in another directory structure.

Updated July 2nd 2020 to adopt Pro 2.6 release and create Pro locators.This sample contains an ArcGIS Pro 2.6 Toolbox file containing five Spatial ETL Tools:ImportPSV2 - imports pipe separated source text files into a new (or existing, optionally to be overwritten) File Geodatabase.ImportStatePSV2 - the same as ImportPSV2 except includes a filter for a target state.MakeAllLocalityAliases - makes a city or locality alias table used in locator creation.MakeAddress2 - makes a point feature class ADDRESS with the schema similar to the ADDRESS_VIEW example in the PSMA documentation.MakeReferenceAddress - creates a point feature class REFERENCEADDRESS from the ADDRESS features, having expanded house number ranges and house number and subaddress details in suitable fields. This is the primary role data for the locator.The download also includes FME workbench FMW files (2020) for use in that product and ArcGIS Pro.You must re-source the Spatial ETL tools in the download toolbox to point to the FMW files in the download and you must re-path the data sources in each Spatial ETL tool to suit your project workspace.A model CreateGNAFLocator is in the download toolbox, use this to create your locator. A sample locator for the ACT is included.The sample locator and ones you create will support subaddress inputs, like flats and units.ImportPSV2 takes 19 hours to process 104M features on my machine. You might like to process a state at a time.If you add intermediate data to a map or leave an output geodatabase expanded in the Catalog pane you may get an error when writing output because of file locking. It is recommended you do not open an output workspace in Pro until app processing is complete.MakeAddress2 and MakeReferenceAddress take 4 hours to run for all Australia.The schema expected is as per February 2021, it may change each release, read the source documentation for change notices, this sample may not be maintained. The primary and foreign key fields according to PSMA's data model are indexed.G-NAF download site is: https://data.gov.au/dataset/geocoded-national-address-file-g-naf

Any geological exploration of the Earth ultimately requires understanding its structure and crustal geometry and composition - its architecture - whether we are searching for battery minerals, metals, water, hydrocarbons, carbon storage reservoirs, or geothermal. Although regional and local databases are available, especially in the commercial world, there is no systematic, global suite of databases for crustal architecture and structure accessible by the entire scientific community. This is why we have built Reclus. The Reclus suite includes databases of the following: (1) structural elements, which define the three-dimensional geometry of the rock volume, including folds and faults; (2) 'crustal' facies describing the geometry and composition/rheology of the lithosphere; (3) igneous features; and (4) geodynamics, representing the dominant thermo-mechanical processes acting on the lithosphere. The datasets provided here are for East Africa and are described in detail in Markwick et al., (Accepted for publication). Interpretations were made between 2017-2021 using a range of primary and secondary sources. These input datasets include gravity and magnetic data, Landsat imagery, radar data, published well and seismic information, geological maps and published papers, MSc and Ph.d. theses, and reports. The databases are compiled and managed using ESRI's ArcGIS software and are underpinned by a comprehensive data management system and systematic attribution. In this resource, the databases are provided as ESRI shapefiles. Shapefiles are the ESRI data format that can be used most widely, including the following: different versions of ArcGIS; QGIS, Schlumberger's Petrel; and Google Earth. Reclus enables commercial explorationists to place their internal data and expertise within a systematically built, regional context. For students and academics, Reclus is designed to provide a starting point for further research - it is so much easier to take an existing resource, question it, disagree with it, change it, and improve it. Reclus is named after the French geographer Jacques Élisée Reclus”, who in the late 19th century compiled and analyzed physical and human geographic data for every continent. This was published in his 19 volume work, La Nouvelle Géographie Universelle, la Terre et Les Hommes, which included some of the first maps illustrating the global distribution of volcanoes and mountains. File descriptions: A single zip file, Reclus_East_Africa_DataSet_S1.zip, that contains the following:Five ESRI shapefiles1. Reclus2021_Structural_Elements_EAfrica2. Reclus2021_Crustal_Facies_EAfrica3. Reclus2021_Igneous_Features_EAfrica4. Reclus2021_Igneous_Features_lines_EAfrica5. Reclus2021_Geodynamics_EAfricaEach shapefile comprises 8 separate files with the following suffixes: .cpg, .dbf, .prj, .sbn, .sbx, .shp, .shp.xml, .shx.Five ESRI layer files (.lyr). One for each shapefile. Layer files store information on the symbology used and link to their respective shapefile. The layer files should automatically link to the relevant shapefile. However, if this does not happen, then the users may need to manually relink each shapefile. This is explained on the ESRI website at https://desktop.arcgis.com/en/arcmap/10.3/map/working-with-layers/repairing-broken-data-links.htm1. Reclus2021_Structural_Elements_EAfrica.lyr2. Reclus2021_Crustal_Facies_EAfrica.lyr3. Reclus2021_Igneous_Features_EAfrica.lyr4. Reclus2021_Igneous_Features_lines_EAfrica.lyr5. Reclus2021_Geodynamics_EAfrica.lyrFurther information on each database is provided in the related paper: Markwick et al (Accepted) Reclus: A new database for investigating the tectonics of the Earth: the East African margin and hinterland. Geochemistry, Geophysics, Geosystems.

Geostrat Report – The Sequence Stratigraphy and Sandstone Play Fairways of the Late Jurassic Humber Group of the UK Central Graben

This non-exclusive report was purchased by the NSTA from Geostrat as part of the Data Purchase tender process (TRN097012017) that was carried out during Q1 2017. The contents do not necessarily reflect the technical view of the NSTA but the report is being published in the interests of making additional sources of data and interpretation available for use by the wider industry and academic communities.

The Geostrat report provides stratigraphic analyses and interpretations of data from the Late Jurassic to Early Cretaceous Humber Group across the UK Central Graben and includes a series of depositional sequence maps for eight stratigraphic intervals. Stratigraphic interpretations and tops from 189 wells (up to Release 91) are also included in the report.

The outputs as published here include a full PDF report, ODM/IC .dat format sequence maps, and all stratigraphic tops (lithostratigraphy, ages, sequence stratigraphy) in .csv format for import into different interpretation platforms.

In addition, the NSTA has undertaken to provide the well tops, stratigraphic interpretations and sequence maps in shapefile format that is intended to facilitate the integration of these data into projects and data storage systems held by individual organisations who are using non-ESRI ArcGIS GIS software. As part of this process, the Geostrat well names have been matched as far as possible to the NSTA well names from the NSTA Offshore Wells shapefile (as provided on the NSTA’s Open Data website) and the original polygon files have been incorporated into an ArcGIS project. All the files within the GIS folder of this delivery have been created by the NSTA.

An ESRI ArcGIS version of this delivery, including geodatabases, layer files and map documents for well tops, stratigraphic interpretations and sequence maps is available on the NSTA’s Open Data website and is recommended for use with ArcGIS. All releases included in the Data Purchase tender process that have been made openly available are summarised in a mapping application available from the NSTA website. The application includes an area of interest outline for each of the products and an overview of which wellbores have been included in the products.

Proportional change in effective area of similar ecological environments for Reptiles as a function of land clearing and change in long term (30 year average) climates between the present (1990 …Show full descriptionProportional change in effective area of similar ecological environments for Reptiles as a function of land clearing and change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the combined effects of climate change and land clearing on the area of similar environments to each grid cell as a proportion. Each cell is compared with a sample of 60,000 points in both the present uncleared landscape and an alternative scenario (either present with clearing, or future with clearing), and the pairwise similarities summed (e.g. a completely similar cell will contribute 1, a dissimilar cell 0, with a range of values in between). Only cells which are flagged as uncleared contribute. For each time point, this describes the area of similar environments, which will be low for rare environments and high for widely distributed environments. By dividing the test area by the current area, we are able to quantify the reduction in area as a function of land use/climate change. Values less than one indicate a reduction, values of 1 no change, and values greater than 1 (rare cases in the north) show an increase in similar environments. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: Zipped ESRI float grids: Binary float grids (.flt) with associated ESRI header files (.hdr) and projection files (.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. ArcGIS layer package (.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: Mammals, M: mammals, R: reptiles and V: vascular plants The metadata and files (if any) are available to the public.

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. The MANZ spatial database and map layer was produced by CTI from 2010 imagery using 21 map units that were directly cross-walked or matched to their corresponding rUSNVC plant association/alliance or land cover types. The final map layer was assessed for thematic accuracy by creating contingency tables and the final overall accuracy of the map layer was determined to be 96% with a Kappa value of 95%. The vegetation mapping was conducted at MANZ in two phases. The first phase conducted by the USGS Fort Collins Science Center created the primary vegetation and associated spatial data layers using the 2005 NAIP Manzanar NE DOQQ imagery (acquired on September 3, 2005 from the Cal-Atlas Geospatial Clearinghouse at http://atlas.ca.gov/). Preliminary mapping was conducted by the USGS through a semi-automated process using a combination of the ENVI Feature Extraction Module (ITT Visual Information Systems, 2008) and ArcGIS software (ESRI, 2008).

ESRI ArcMap project containing of the Quaternary geology of the Providence/East Providence Quadrangle, scale and explanation. Contains the feature class coverage of Quaternary geologic map units, as well as the topomap basemap.