Map Tiles is a reference dataset used to identify the spatial location of DWG contour data delivered to TLCGIS by Merrick. The attributes contained in the PAGE field in Map Tiles can be used to reference the name of the the individual DWG contour files.The individual DWG contour files are bundled into 4 quadrants for Leon County: NE, NW, SE, & SW. You may download these quadrants to use in conjuction with the Map Tiles data.

The 5m DEM is derived from the LiDAR2019B dataset (consisting of the 2018, 2019A and 2019B datasets). The 5m DEM has a vertical accuracy of 30cm. The height reference used is the SA Land Levelling Datum and the SAGEOID2010 was employed.The City of Cape Town Ground Level Map 2019 is defined in the City of Cape Town Municipal Planning Amendment By-law, 2019 as: “‘City of Cape Town Ground Level Map’ means a map approved in terms of the development management scheme, indicating the existing ground level based on floating point raster’s and a contour dataset from LiDAR information available to the City”. The Ground Level Map was approved by the City Council on the 27th July 2023.All Raster Image Services (REST):https://cityimg.capetown.gov.za/erdas-iws/esri/GeoSpatial%20Datasets/rest/services/All Raster Image Services (WMS):Use URL below to add WMS Server Connection in ArcGIS Desktop, ArcPro, QGIS, AutoCAD, etc.https://cityimg.capetown.gov.za/erdas-iws/ogc/wms/GeoSpatial Datasets?service=WMS&request=getcapabilities&For a copy or subset of this dataset, please contact the City Maps Office: city.maps@capetown.gov.zaCCT Ground Level Map: ‘How to Access’ Guide – External Users: CCT Ground Level Map: ‘How to Access’ Guide – External Users | Open Data Portal (arcgis.com)Geomatics Ground Level Map Explainer: Geomatics Ground Level Map Explainer | Open Data Portal (arcgis.com)Land Use Management Ground Level Map Explainer: Land Use Management Ground Level Map Explainer | Open Data Portal (arcgis.com)

This dataset provides an initial version of the generalized physical boundaries of New Mexico State Parks, in polygonal form with limited attributes, compiled using available data from a variety of sources. The boundaries have been digitized from AutoCAD drawings and/or from legal descriptions, supplemented by digital orthophotography cross-checking, and adjusted to the GCDB when possible. The dataset will be refined in the future to include other attributes and provide better accuracy.

This data set contains a database of infectious diseases, vaccine uptake, congenital anomalies, population data sets, social classification, unemployment and medical card details.

The original photography flown was at 2500 feet. Vectors were validated using standard Sysdeco vector validation. Sysdeco GIS is a technical member of ISO/TC211 and the Open GIS Consortium (OGC).

Supply format of the data include ASCII, DXF, DWG (AutoCAD v12,v13 & v14) NTF (BS 7567), UNDLST or TIFF raster structure. Paradigm Technologies provide a service for translating the proprietary SYSCAN DST Unload format into the .shp ArcView files. View Padadigm Contact Details. Supply media include 3.5" Floppy, CD-ROM, 100MB Zip Disk 4mm DAT Data Cartridge, 8mm Exabyte, Q150 ¼" Cartridge.

Available as partial data sets defined either by urban area, property address, user defined extent or selected attributes. Paper plots available in 800m by 600m areas. Option of site centre plots available.

For data access, please contact the data center.

[Summary provided by Geo-ID]

Unfortunately, the provided README for the ckanext-dwgviewer extension lacks specific details about its functionality and features. Based on the name, it is likely that this extension enables CKAN to preview and handle DWG (drawing) files, a common file format for CAD (Computer-Aided Design) drawings. This would enhance CKAN's ability to manage and share geospatial and engineering data. Key Features (Inferred): DWG File Preview: The extension probably renders a preview of DWG files directly within the CKAN interface. DWG Metadata Extraction: Metadata, such as author, creation date, or layers, could be extracted from DWG files upon upload and stored as part of the dataset metadata. Format Support: Supports DWG files, and potentially related CAD formats. Integration with existing viewers Integration with open-source libraries or viewers enabling DWG file viewing Use Cases (Inferred): Engineering and Construction: Agencies involved in civil engineering, infrastructure projects, or construction can share design and as-built drawings through CKAN. Geospatial Data Management: Organizations dealing with maps, GIS data, or urban planning can publish and share DWG-based spatial information. Data Publishing for CAD: Institutions managing CAD datasets can support visualization and metadata browsing through a CKAN deployment. Technical Integration (Based on Standard CKAN Extension Practices): The ckanext-dwgviewer plugin is installed like a normal CKAN extension; by adding the plugin it is assumed the extension will integrate by automatically interpreting available resources with the appropriate file type, or by providing upload fields to load the file type and relevant metadata. This requires installation by following the given instructions, including installation of dependencies, activating the plugin and adding to the CKAN configuration file settings. Benefits & Impact (Inferred): Using the ckanext-dwgviewer can make CKAN more useful for organizations that manage geospatial, engineering, or CAD data. Users can discover, preview, and download DWG files directly from the CKAN interface, improving data accessibility and collaboration.

Queensland's spatial cadastre datasets are changing! From a planned date of 1 July 2025 the current Digital Cadastral Database (DCDB) will be migrated to an entirely new operating environment, and there will be some changes to the data provided. Visit our Spatial Applications Support page (https://spatial-qld-support.atlassian.net/wiki/spaces/QSUITE/pages/1067515932/Cadastre+and+Address+Modernisation+CAM) for more information.The Digital Cadastre is the spatial representation of every current parcel of land in Queensland, and its legal Lot on Plan description and relevant attributes. It provides the map base for systems dealing with land-related information. The Digital Cadastre is considered to be the point of truth for the graphical representation of property boundaries. It is not the point of truth for the legal property boundary or related attribute information, this will always be the plan of survey or the related titling information and administrative data sets. This data is updated weekly on Sunday.Data dictionary https://www.publications.qld.gov.au/dataset/queensland-digital-cadastral-database-supporting-documents/resource/b59bb1a1-3818-4754-8dc4-3669f0ec3f8b Spatial cadastre accuracy map https://www.publications.qld.gov.au/dataset/queensland-digital-cadastral-database-supporting-documents/resource/d6f029ad-b3a4-428b-bcf1-2f7c7326132b

Last Rev. 01/24/08 - E.Foster, P.E. - FSU/BSRCThe Historic Shoreline Database on the Web contains many directories of related types of information about beach changes in Florida over the past 150 or so years. The historic shoreline map images (see the Drawings directory) show precision-digitized approximate mean high water (mhw) shorelines, from the US government coastal topographic maps listed in the associated map bibliography files (see the Sourcebibs directory). These generally show data extending from the mid to late 1800’s to the mid to late 1970’s. The mhw positions have been extracted and tabulated (see the MWHfiles directory) relative to fixed reference “R” points along the beach, spaced approximately 1000 feet (300 meters) apart. Reference points not actually corresponding to actual “in the ground” survey markers are virtual “V” points. Mean high water positions have been and continue to be extracted from FDEP beach profile surveys from the 1970’s through the present and added to the tables. The beach profile data files from which mhw data have been extracted and added into the mhw tables can be found in the ProfileData directory and visually (for many areas) in the ClickOnProfiles directory. The beach profile files include elevation information along the entire length of the profiles. This profile data set has undergone up to fifteen additional quality control checks to ensure accuracy, reliability, and consistency with the historic database coordinate and bearing set. Note that any data deeper than wading depth have not yet undergone any extra quality control checks. Note also that there are *.cod text files of notes associated with the review of the profile data files.The digital historic shoreline map image files are given in a DWG autocad-based format, which should be usable on most versions, as well as many GIS systems. The Florida State Plane 1927/79-adjusted and 1983/90 horizontal coordinate systems are used. These are not metric systems, but with the proper software can be converted to whatever systems you may need. Each map image DWG file contains many layers, documented in an ASCII layer list archived with the DWG file.The database has been maintained and greatly expanded by E. Foster since approximately 1987 and by N. Nguyen since 1995. The initial map digitizing effort was done for FDEP at Florida State University, primarily by S. Demirpolat. Final processing and editing of the original map files to make them user-friendly was performed by N. Nguyen and E. Foster in 1995-7. Extensive quality control and update work has been performed by E. Foster since 1987, and by N. Nguyen since 1995. Field profile surveys have been performed by the FDEP Coastal Data Acquisition section since the early 1970’s, and by a number of commercial surveyors in recent years.The formats of the mhw tables and profile files are explained in text files included in the respective directories.Note that the digitized map image files were originally created in the UTM coordinate system on Intergraph equipment. The translation from UTM to the State Plane coordinate systems has resulted in some minor textual and other visual shifts in the northwest Florida area map image files.The dates in the map legends in the map images are generally composite dates. It is necessary to use the mhw data tables and map bibliographies for accurate dates for any specific location. The date ranges in the data tables relate to specific information given in the map bibliography files.2Generally it may be assumed that the historic shorelines have been digitized as carefully as possible from the source maps. If a historic shoreline does not contain a systematic position error and is feasible in a physical sense, the accuracy of the mhw position is estimated at plus or minus 15 to 50 feet (5 to 15 m), depending on the source and scale. This is as a position in time, NOT as an average mhw position. Data added from field surveys are estimated at plus or minus 10 feet (3 m) or better.It is to be noted that from the 1920’s onward, aerial photographs have usually been the basis of the US government’s coastal topographic maps. Prior to that, the method was plane table surveying. Along higher wave energy coasts, especially the Florida east coast, if there was significant wave activity in the source photography, it is very possible that the mhw was mapped in a more landward location than was probably correct. Alternatively, the use of photography sets with excessive sun glare may have caused the mhw to be mapped in a more seaward location than was probably correct. These effects have been frequently observed in comparisons of close-in-time FDEP controlled aerial photography with FDEP profile surveys. The use of some photography sets containing high wave uprush or sun glare is probable within the historic data. For example, on the east coast the 1940’s series maps tend to show the mhw more seaward than expected, possibly due to sun glare, and the 1960’s series tend to show the mhw more landward than expected. In the latter case, the effect may be due to the 1960’s being a decade of frequent storms. It is recommended that the analyst be aware that some of these effects may exist in the historic data. A questionable historic shoreline is NOT necessarily one to be discarded, just considered with allowance for its’ potential limitations.Using this database, it can readily be observed that the historic trends in shoreline evolution are very consistent with behavior expected from the longshore transport equation, well known to coastal engineers. This is a non-linear equation. Shoreline change can be expected to be linear or constant only in certain situations. It is NOT recommended that any analyst arbitrarily assume constant or linear shoreline change rates over long periods of time, which is often done but not supported by the evidence. The three primary factors controlling shoreline change are sand supply, wave climate, and local geographic features. In some parts of Florida, major storms since 1995 have also become important factors.

NSW Cadastre web service is a dynamic map of cadastral features extracted from the NSW Digital Cadastral Database (DCDB). It provides access to a state wide integrated database and a component of the foundation spatial datasets within the New South Wales.

A “cadastre” is an official register of property showing boundaries. The DCDB contains current land titles only.

The cadastral feature class layers provided through this web service includes:

• Large Rural Plan Extent

• Rural Plan Extent

• Section Extent

• Plan Extent

• Lot

• Plan Extent Labels

• Section Extent Labels

• Lot Labels

The available attributes for point queries are:

• Lot/Section/Plan string

• CadID

This web service allows users to easily integrate NSW Cadastre into Open Geospatial Consortium (OGC) compliant spatial platforms and applications. The NSW Cadastral web service can be used for resource management, environmental management, land use planning, agriculture management, emergency management and recreational purposes This service can be used to aggregate information for analytical purposes.

Cadastral boundary data in combination with geo-coded address data, imagery, demographic information and agency specific business information underpins the ability to perform high quality spatial analysis.

This data includes new data delivered in 2024 by R&V. This dataset uses a new schema that was provided with the new data. Data was loaded by Smalley in March 2024. Data provided was only included for warded towns. The remainder of the towns were loaded from existing data, which the majority of the metadata is based on. For important metadata on the new data source, contact Middlesex County Office of IT. Description from source: Remington & Vernick Engineers computer-generated and currently maintains, all or in part, the ward/election maps for eleven (11) New Jersey County Boards of Election utilizing AutoCAD software and Esri ArcGIS software applications. We will utilize and reference these resources along with GIS resources available through local, county, state and federal sources, including, but not limited tax assessment parcel data. We will use these resources to create, update, maintain and verify the State-wide GIS dataset comprised of polygon shape files representing the current ward boundaries and election district boundaries for all constituent municipalities in the twenty-one (21) counties in the state of New Jersey. Description from target data.Municipal voting district boundaries 2011-2020. The segmentation of a municipality for voting purposes is based on their type of government. In Middlesex County seven municipalities are divided into Ward/Districts and the balance of eighteen are divided into Districts only. In Warded towns, the geographical area is divided into equally sized wards based on registered voters. Every 10 years, after a Census, each Ward must be examined and “re‑balanced” so that each of the Wards contains an equal amount of voters, within a certain percentage. Each Ward is sub-divided into Districts or Voting districts where each district is analyzed after 2 consecutive General elections so that the votes cast were no more than 750 votes or less than 250. If there are more, the county considers a split of a district, or if less than 250, merging with an adjacent district is considered. Based on the numbers mentioned above, the list of registered voters is reviewed and as close as possible boundaries are drawn to contain the appropriate amount of voters. Physically, boundaries can be centers of streets, fence lines, waterways, etc.