ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
map of all SF properties with associated, zoning, permits, complaints and appeals history
See the Data Downloads section of the websites help page for links to individual DataSF datasets used to create the Property Information Map https://sfplanninggis.org/pim/help.html
Web map for City Properties and Facilities in support of the Land & Building Management System
This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. This layer contains the boundaries and IDs of the Maryland tax maps produced by Maryland Department of Planning. Tax maps - also known as assessment maps - property maps or parcel maps - are a graphic representation of real property showing and defining individual property boundaries in relationship to contiguous real property. Last Updated: Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/PlanningCadastre/MD_PropertyData/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.
This map contains property related information by parcel.This product can be found in the Municipality of Anchorage Maps and Apps Gallery.
To access parcel information:Enter an address or zoom in by using the +/- tools or your mouse scroll wheel. Parcels will draw when zoomed in.Click on a parcel to display a popup with information about that parcel.Click the "Basemap" button to display background aerial imagery.From the "Layers" button you can turn map features on and off.Complete Help (PDF)Parcel Legend:Full Map LegendAbout this ViewerThis viewer displays land property boundaries from assessor parcel maps across Massachusetts. Each parcel is linked to selected descriptive information from assessor databases. Data for all 351 cities and towns are the standardized "Level 3" tax parcels served by MassGIS. More details ...Read about and download parcel dataUpdatesV 1.1: Added 'Layers' tab. (2018)V 1.2: Reformatted popup to use HTML table for columns and made address larger. (Jan 2019)V 1.3: Added 'Download Parcel Data by City/Town' option to list of layers. This box is checked off by default but when activated a user can identify anywhere and download data for that entire city/town, except Boston. (March 14, 2019)V 1.4: Data for Boston is included in the "Level 3" standardized parcels layer. (August 10, 2020)V 1.4 MassGIS, EOTSS 2021
To access the tax lot layer you will need to contact the county Assessor's office. ORMAP is a statewide digital cadastral base map that is publicly accessible, continually maintained, supports the Oregon property tax system, supports a multi-purpose land information system, strives to comply with appropriate state and national standards, and will continue to be improved over time.
This Image Service of Maryland Property Data allows for the manipulation of the display properties of the Statewide Tax Maps dataset. This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/imap/rest/services/PlanningCadastre/MD_PropertyData/ImageServer
The data set “Matrikkelen-Property Map Teig — historical data 2019” is the annual version of “Matrikkelen-Property Map Teig”. It is only zip files that are renamed, nothing inside the files. Version 2019 is based on product specification: Matrikkelen-Property map-Teig_20180501. Excerpts from the 2019 description of Matrikkelen-Property Map Teig: The dataset contains a small extract of property information that is registered in Matrikkelen, Norway’s official register of real estate. The data set contains teiger (limited areas/soil pieces) with information about which property it belongs to. The matricle number (farm number/use number) identifies the property. Point, boundaries and level of quality information are included in the data set. Volumes of construction properties (properties above/under ground) are supplied as an area, — a plant “footprint”. The distribution is set against a distribution solution that provides some delay from the matricle system — from 30 minutes delay when downloading data in freely selected area from maps, daily for WMS and WFS, weekly for downloads of ready-made files and databases. Known errors: For some surfaces where arches are included, arc is replaced by malformed “edge section”.
These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 > 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building. More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.
description: Parcels and Land Ownership dataset current as of unknown. This data set consists of digital map files containing parcel-level cadastral information obtained from property descriptions. Cadastral features contained in the data set include real property boundary lines, rights-of-way boundaries, property dimensions.; abstract: Parcels and Land Ownership dataset current as of unknown. This data set consists of digital map files containing parcel-level cadastral information obtained from property descriptions. Cadastral features contained in the data set include real property boundary lines, rights-of-way boundaries, property dimensions.
This map highlights all the publicly owned parcels in Los Angeles by council district.
This layer contains the boundaries and IDs of the Maryland tax maps produced by Maryland Department of Planning. Tax maps, also known as assessment maps, property maps or parcel maps, are a graphic representation of real property showing and defining individual property boundaries in relationship to contiguous real property.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/PlanningCadastre/MD_PropertyData/MapServer/2
This data set contains a shapefile of a digitized map of the land parcel information of the original properties of the Uruara colonization site, Para, Brazil, acquired from the Instituto de Colonizacao e Reforma Agraria, or the Colonization and Agrarian Reform Institute (INCRA). The Uruara settlement geometry was initially designed by INCRA, and consists of mostly 100 hectare lots (400 x 2500 meters, and 500 x 2000 meters), running north and south of the Trans-Amazon Highway, as a fine network of small, narrow rectangles. The other parcels in the landscape are the so-called glebas that range up to 3,000 hectares. The map was in the form of a paper map without a projection (a spherical geographic coordinate system) in the South American 1969 datum (SAD 1969). This paper map was digitized in Environmental Science Research Institute (ESRI) ArcInfo 8.1 using a digitizing table, and the digital cadastral data were geo-referenced and projected to match the Universal Transverse Mercator projection (Zone 22 South, World Geodetic System 1984 datum) of Landsat imagery (Landsat.org). There is one compressed (*.zip) file with this data set.
Property map viewer for the State of Tennessee that covers 85 of the 95 counties in Tennessee.This application allows for searching and displaying property ownership and location information for 87 counties in Tennessee. It is designed to work in concert with the Real Estate Assessment Data site operated by the Comptroller of the Treasury. The following counties are not available in this application but can be found on their own internet sites: Bradley, Davidson (Metro Nashville), Hamilton (Chattanooga), Knox (Knoxville), Montgomery (Clarksville), Rutherford(Murfreesboro), Shelby (Memphis), Sumner, Unicoi, and Williamson.
Web App. Use the tabs provided to discover information about map features and capabilities. Link to Metadata. A variety of searches can be performed to find the parcel of interest. Use the Query Tool to build searches. Click Apply button at the bottom of the tool.Query by Name (Last First) (e.g. Bond James)Query by Address (e.g. 41 S Central)Query by Locator number (e.g. 21J411046)Search results will be listed under the Results tab. Click on a parcel in the list to zoom to that parcel. Click on the parcel in the map and scroll through the pop-up to see more information about the parcel. Click the ellipse in the Results tab or in the pop-up to view information in a table. Attribute information can be exported to CSV file. Build a custom Filter to select and map properties by opening the Parcels attribute table:1. Click the arrow tab at the bottom middle of the map to expand the attribute table window2. Click on the Parcels tab3. Check off Filter by map extent4. Open Options>Filter5. Build expressions as needed to filter by owner name or other variables6. Select the needed records from the returned list7. Click Zoom to which will zoom to the selected recordsPlease note that as the map zooms out detailed layers, such as the parcel boundaries will not display.In addition to Search capabilities, the following tools are provided:MeasureThe measure tool provides the capabilities to draw a point, line, or polygon on the map and specify the unit of measurement.DrawThe draw tool provides the capabilities to draw a point, line, or polygon on the map as graphics. PrintThe print tool exports the map to either a PDF or image file. Click Settings button to configure map or remove legend.Map navigation using mouse and keyboard:Drag to panSHIFT + CTRL + Drag to zoom outMouse Scroll Forward to zoom inMouse Scroll Backward to zoom outUse Arrow keys to pan+ key to zoom in a level- key to zoom out a levelDouble Click to Zoom inFAQsHow to select a parcel: Click on a parcel in the map, or use Query Tool to search for parcel by owner, address or parcel id.How to select more than one parcel: Go to Select Tool and choose options on Select button.How to clear selected parcel(s): Go to Select Tool and click Clear.
MassGIS' standardized assessors’ parcel mapping data set contains property (land lot) boundaries and database information from each community's assessor.The data were developed through a competitive procurement funded by MassGIS. Each community in the Commonwealth was bid on by one or more vendors and the unit of work awarded was a city or town. The specification for this work was Level 3 of the MassGIS Digital Parcel Standard.This map service contains three feature classes and one table.Feature service also available.See the datalayer page for full details.
These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 > 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building. More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.
This map compares the residency of Jersey City property owners, i.e. Jersey City versus non-Jersey City.View this map here.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Original maps and plans created by real estate firms from 1850s to mid 1900s from State Library of Queensland collection collections.
This dataset includes descriptions, geographic coordinates and links for 1259 digitised maps.
Estate maps can give information about land subdivisions, including how the land was subdivided, when it was first auctioned, who the surveyors were and who sold the land. They are useful for investigating the history of urban land areas.
The maps are predominantly from Brisbane but also cover some regional areas of Queensland such as the Gold and Sunshine Coasts.
Additional information about this collection is available at: https://www.slq.qld.gov.au/blog/real-estate-map-collection-treasure-collection-john-oxley-library
Also available in State Library’s library catalogue http://onesearch.slq.qld.gov.au
Explore State Library’s events, programs and services at https://slq.qld.gov.au
OSA web map to view State of Colorado property data
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
map of all SF properties with associated, zoning, permits, complaints and appeals history
See the Data Downloads section of the websites help page for links to individual DataSF datasets used to create the Property Information Map https://sfplanninggis.org/pim/help.html