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.

Celldesigner format for atopic dermatitis and ulcerative colitis maps

CAD Base (whole city) https://maps.victoria.ca/CustomMaps/OpenData/VicBaseDWG.zip Cadastre https://maps.victoria.ca/CustomMaps/OpenData/CadastreDWG.zip Civil 3D Template Drawing https://maps.victoria.ca/CustomMaps/OpenData/AutoCAD_Civil3D_Template.zip Sewer (whole network) https://maps.victoria.ca/CustomMaps/OpenData/SewerDWG.zip Storm Drain (whole network) https://maps.victoria.ca/CustomMaps/OpenData/StormDWG.zip Water (whole utility network) https://maps.victoria.ca/CustomMaps/OpenData/WaterDWG.zip AutoCAD Legends https://maps.victoria.ca/CustomMaps/OpenData/AutoCAD_Legends.zip The "Last Updated" date shown on our Open Data Portal refers to the last time the data schema was modified in the portal, or any changes were made to this description. The AutoCAD files listed above are copied to our server every week or so, which does not trigger the "last updated" date to change.

The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

Vector polygon map data of property parcels from Parker County, Texas containing 5673 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Vector polygon map data of property parcels from Los Angeles County, California containing 2,405,987 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Select Aggregate Planimetric CAD Vectors from set of 2001-2019 Community Profile AutoCAD files - Initial release version Oct 26, 2023This is an AGOL-hosted Feature Service - hence text point labels only display horizontallySee these related Services (circa Oct 2023):DCRA Community Profile Availability and Map Sheet Outlines with PDF Maps as downloadable attachmentsDCRA Community Profile Aerial Imagery (Community Hi-Res Scale)DCRA Community Profile Aerial Imagery (Community General Area Low-Res Scale)State of Alaska Maxar RGB Satellite ImageryHigh Level Documentation as a PowerPoint Presentation in PDF form

Select Aggregate Planimetric CAD Vectors from set of 2001-2019 Community Profile AutoCAD files - Initial release version Oct 26, 2023This is an AGOL-hosted Feature Service - hence text point labels only display horizontallySee these related Services (circa Oct 2023):DCRA Community Profile Availability and Map Sheet Outlines with PDF Maps as downloadable attachmentsDCRA Community Profile Aerial Imagery (Community Hi-Res Scale)DCRA Community Profile Aerial Imagery (Community General Area Low-Res Scale)State of Alaska Maxar RGB Satellite ImageryHigh Level Documentation as a PowerPoint Presentation in PDF form

Vector polygon map data covering property parcels from Orange County, California containing 699,877 features.

Parcel map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Integrieren von Daten aus geografischen Informationssystemen und CAD für GIS und 3D-Kartografie.

The 108-year version is created by digitizing and archiving urban planning announcement data provided by the Urban Development Bureau.

Property lines mapped as parcel polygons within Langley Township. The data includes the following information: Folio, PID, and civic address of existing parcels Description The Township uses two survey systems. The first was 1859 District Lot system which still describes many properties near the Fraser River. The District Lot system was superseded in 1873 with the New Westminster Township Section system which covers the bulk of the municipality and is used to the present day. The cadastral data set originated as hand drawn township-section maps in imperial scales. The lot lines were compiled from historical community maps, registered legal plans surveyed with astronomic bearings and legal descriptions where no surveys exist.

In the late 1970’s the Township's maps were converted to metric scales and all dimension annotation was converted manually to metric. In 1982 parcels BC GAS manually digitized the hand drawn township-section maps and assembled them into a single continuous cadastral fabric encompassing the entire township. The lot line data was rubber sheeted to fit the higher accuracy mapping of neighbouring municipalities, no interior control points were used. In 1983 Langley Township obtains BC GAS Intergraph format lot line data and translated it into Terrasoft format for the Township's GIS.In 1986 the lot lines were converted to parcel polygons linked to BCAA folio numbers and Tempest. In 1987 map annotation was converted to digital. In 1999 the GIS data was converted from Terrasoft to AutoCAD Map format. In 2000 the digital base was again rubber sheeted with a township wide grid pattern of survey monuments used for control. In 2003 lot links were converted from BCAA folio numbers to Township property numbers. In 2004 GIS data is converted from AutoCAD Map format to Munsys Oracle format. In 2005 Langley Township adopts DIGITAL LEGAL SURVEY PLAN STANDARDS and new cadastral is entered directly from high accuracy UTM projected surveys. In 2009 GIS data was converted from Munsys Oracle format to ESRI ArcSDE format.

% ============================================================================== % CAD 120 Affordance Dataset % Version 1.0 % ------------------------------------------------------------------------------ % If you use the dataset please cite: % % Johann Sawatzky, Abhilash Srikantha, Juergen Gall. % Weakly Supervised Affordance Detection. % IEEE Conference on Computer Vision and Pattern Recognition (CVPR'17) % % and % % H. S. Koppula and A. Saxena. % Physically grounded spatio-temporal object affordances. % European Conference on Computer Vision (ECCV'14) % % Any bugs or questions, please email sawatzky AT iai DOT uni-bonn DOT de. % ==============================================================================

This is the CAD 120 Affordance Segmentation Dataset based on the Cornell Activity Dataset CAD 120 (see http://pr.cs.cornell.edu/humanactivities/data.php).

Content

frames/*.png: RGB frames selected from Cornell Activity Dataset. To find out the location of the frame in the original videos, see video_info.txt.

object_crop_images/*.png image crops taken from the selected frames and resized to 321*321. Each crop is a padded bounding box of an object the human interacts with in the video. Due to the padding, the crops may contain background and other objects. In each selected frame, each bounding box was processed. The bounding boxes are already given in the Cornell Activity Dataset. The 5-digit number gives the frame number, the second number gives the bounding box number within the frame.

segmentation_mat/*.mat 321*321*6 segmentation masks for the image crops. Each channel corresponds to an affordance (openabe, cuttable, pourable, containable, supportable, holdable, in this order). All pixels belonging to a particular affordance are labeled 1 in the respective channel, otherwise 0.

segmentation_png/*.png 321*321 png images, each containing the binary mask for one of the affordances.

lists/*.txt Lists containing the train and test sets for two splits. The actor split ensures that train and test images stem from different videos with different actors while the object split ensures that train and test data have no (central) object classes in common. The train sets are additionally subdivided into 3 subsets A,B and C. For the actor split, the subsets stem from different videos. For the object split, each subset contains every third crop of the train set.

crop_coordinate_info.txt Maps image crops to their coordinates in the frames.

hpose_info.txt Maps frames to 2d human pose coordinates. Hand annotated by us.

object_info.txt Maps image crops to the (central) object it contains.

visible_affordance_info.txt Maps image crops to affordances visible in this crop

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55 The crops contain the following object classes: 1.table 2.kettle 3.plate 4.bottle 5.thermal cup 6.knife 7.medicine box 8.can 9.microwave 10.paper box 11.bowl 12.mug

Affordances in our set: 1.openable 2.cuttable 3.pourable 4.containable 5.supportable 6.holdable

Note that our object affordance labeling differs from the Cornell Activity Dataset: E.g. the cap of a pizza box is considered to be supportable.

This data set was collected to create a comprehensive platform to visualize SWP owned land. The parcels were created from record parcel information displayed on Department CAD maps known as “Property Management Maps”. This CAD data was then converted to a compatible GIS source and imported as parcels. Each parcel displays the pertinent information regarding the Departments ownership rights and the time that it was acquired or granted. This data set was created to improve the efficiently of accessing and organize the departments land records.

Vector polygon map data of property parcels from Harris County, Texas containing 1,410,276 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

The San Francisco Basemap in CAD format comprised of 74 (zipped) tiled drawing files (SF00C.dwg - SF99C.dwg) refreshed weekly.

Projection and Datum · The files are referenced to the California State Plane Coordinate System, Zone III. The coordinate units are in feet. · The Datum is North American Datum 1983.

Vector polygon map data of property parcels from Nashville, Tennessee containing 268,019 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Vector polygon map data of property parcels from Contra Costa County, California containing 378,332 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Vector polygon map data of property parcels from New York State containing 2,789,211 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Additional metadata, including field descriptions, can be found at the NYS GIS Clearinghouse: http://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1300.

© Contributing counties, NYS Office of Information Technology Services GIS Program Office (GPO) and NYS Department of Taxation and Finance’s Office of Real Property Tax Services (ORPTS).

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.

Dataset contains framework layers compiled for representation on state reference map, scale 1:1.5 million. Line and polygon features only. Road, rail, waterbody and watercourse themes included. State coastline not included.

Purpose

Can be used as a framework layer for whole of state mapping or for a generalised framework for regional mapping. Not suitable for analysis.

Dataset History

Information was compiled and digitised in generalised form from 1:250 000 scale hard copy maps. The individual CAD files were combined into seamless form and converted to Lambert Conformal Conic projection, standard parallels 29 degrees and 35 degrees S, central meridian 135 degrees E. Subsequently the information was converted to GIS format and re-projected to the state standard LCC projection.

Dataset Citation

SA Department of Environment, Water and Natural Resources (2015) Topography - State Refence Map - ARC. Bioregional Assessment Source Dataset. Viewed 26 May 2016, http://data.bioregionalassessments.gov.au/dataset/b6f2d7af-7fbb-4bf5-9051-b725d51b270a.