This dataset has been published by the Office of the Real Estate Assessor of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.

Field descriptions for the James City County Parcel layer and the Data table.

This dataset is created by the Town of Cary GIS Group. It contains data from the western portion of Wake County, the eastern portion of Chatham County, and the southern portion of Durham County. It has been modified from the original sources to act as one layer for use by the Town of Cary. This file is updated once a month from the respective sources. Please refer to each Counties' data for the latest information:

Wake County

Durham County

Chatham County

This is a comprehensive collection of tax and assessment data extracted at a specific time. The data is in CSV format. A data dictionary (pdf) and the current tax rate book (pdf) are also included.

This table contains the assessed values for current tax year and prior tax year for land and building for properties in Fairfax County. There is a one to one relationship to the parcel data. Refer to this document for descriptions of the data in the table.

This file contains all assessment information for City parcels. The "ParcelNumber" field can be joined to the "ParcelNumber" field in the "Parcel Area Details" data set for mapping purposes (current parcels only).

Sales and transfer information, to include owner information is updated daily.

The assessment values are done yearly and reassessment notices go out at the end of January. The new assessment values will be reflected on the GIS viewer after reassessment notices are mailed.

Note: Active and Retired parcels are included in this data set so joining this data set to the data sets: ‘Real Estate (Base Active)’ or ‘Parcel Area Details’ will not result in all parcels matching since ‘Real Estate (Base Active)’ and ‘Parcel Area Details’ only contain currently active parcels.

This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.

This is a collection of CSV files that contain assessment data. The files in this extract are:Primary Parcel file containing primary owner and land information;Addn file containing drawing vectors for dwelling records;Additional Address file containing any additional addresses that exist for a parcel;Assessment file containing assessed value-related data;Appraisal file containing appraised value-related data;Commercial file containing primary commercial data;Commercial Apt containing commercial apartment data;Commercial Interior Exterior dataDwelling fileEntrance data containing data from appraisers' visits;Other Buildings and Yard ImprovementsSales FileTax Rate File for the current billing cycle by taxing district authority and property class; and,Tax Payments File containing tax charges and payments for current billing cycle.In addition to the CSV files, the following are included:Data Dictionary PDF; and,St Louis County Rate Book for the current tax billing cycle.

This data set includes information pertaining to the transfer (sales) history for parcels. The "ParcelNumber" field can be joined to the "ParcelNumber" field in the "Parcel Area Details" data set for mapping purposes (current parcels only).This dataset is updated on a daily basis and reflects the Real Estate system as of the previous business day.

The assessment values are done yearly and reassessment notices go out at the end of January.

The new assessment values will be reflected on the GIS viewer after reassessment notices are mailed.

This repository contains data and codes that support the findings of the study.- PPD-EPC open dataset with the enriched spatial analyses scores and UPRN.- Batch Geocoding Notebook of PPD-EPC dataset with GeoPy - Here API- PyQGIS codes for proximity, terrain, and visibility spatial analyses.- Jupyter Notebook of Machine Learning algorithms for mass property valuation.

description: The primary objective of the project is to develop an integrated ecological and socioeconomic land use evaluation model (the Ecosystem Portfolio Model, EPM) for Department of the Interior (DOI) resource managers to use to reconcile the need to maintain the ecological health of South Florida parks and refuges with increasing pressures for higher density development in the agricultural lands outside of the Urban Development Boundary in Miami-Dade County. The EPM has three major components: (1) an ecological value model based on ecological criteria relevant to National Park Service and US Fish & Wildlife Service resource management and species protection mandates; (2) a real estate market-based land value model sensitive to relevant land use/cover attributes indicative of conservation and development decisions; and (3) a set of socioeconomic indicators sensitive to land use/cover changes relevant to regional environmental and ecological planning. The current version is implemented for Miami-Dade County, with the protection of ecological values in the lands between the Everglades and Biscayne National Parks as the focus. The first two components have been implemented in the GIS web-enabled prototype interface and the third component is being developed in draft form in FY08 in consultation with the Florida Atlantic University Dept of Urban and Regional Planning.; abstract: The primary objective of the project is to develop an integrated ecological and socioeconomic land use evaluation model (the Ecosystem Portfolio Model, EPM) for Department of the Interior (DOI) resource managers to use to reconcile the need to maintain the ecological health of South Florida parks and refuges with increasing pressures for higher density development in the agricultural lands outside of the Urban Development Boundary in Miami-Dade County. The EPM has three major components: (1) an ecological value model based on ecological criteria relevant to National Park Service and US Fish & Wildlife Service resource management and species protection mandates; (2) a real estate market-based land value model sensitive to relevant land use/cover attributes indicative of conservation and development decisions; and (3) a set of socioeconomic indicators sensitive to land use/cover changes relevant to regional environmental and ecological planning. The current version is implemented for Miami-Dade County, with the protection of ecological values in the lands between the Everglades and Biscayne National Parks as the focus. The first two components have been implemented in the GIS web-enabled prototype interface and the third component is being developed in draft form in FY08 in consultation with the Florida Atlantic University Dept of Urban and Regional Planning.

This is a comprehensive collection of tax and assessment data extracted at a specific time. The data is in CSV format. A data dictionary (pdf) and the current tax rate book (pdf) are also included.

Air right lots are reflect a party’s right to construct an improvement above an existing area of land that is not owned by the constructor. They are a type of development right in real estate referring to the empty space about a property. These tax lot numbers start at 7000. There are approximately 704 air rights lots. Non-contiguous Air Rights Lots numbered in 8000 series can either be District owned Multifamily rental units or Existing Development Mixed (residential and commercial).Multifamily 8000 series lots can be proposed development projects that are inclusive of the Mayor’s Office Affordable/Public Housing Initiatives. Additionally, they can either be development sites that are owned by the District and the site is leased to developer. Due to financing and legal requirements, each set of government funded units are required to have separate parcel ID’s (SSL’s). All the units are rentals, none of the units will be for sale.Existing Development Mixed Use 8000 series lots are residential owner(s) that own both residential and commercial portions. The Lot split is done to ensure each party pays the appropriate real estate taxes assessed to each specific use. There is a master covenant lease outlining property access-rights-use between residential and commercial owner and lease holders. There is also a master lease related to the commercial space where the residential owner is the lease holder.

This is a comprehensive collection of tax and assessment data extracted at a specific time. The data is in CSV format. A data dictionary (pdf) and the current tax rate book (pdf) are also included.

Property and parcel data is a critical layer to any city or statewide data holdings. In our city's complex urban environment, this includes numerous geographies that identify federal government lands, reservations, District lands, personal property and so much more. Use this application to query and identify boundaries including,Property LotsLot DimensionsCondo DataTax AssessmentsZoningSquaresThe District's Vector Property Mapping (VPM) project works daily to capture property lot transactions so that city planners, business development leaders and residents stay current.

This dataset visualises the spatial distribution of the rental value in Amsterdam between 1647 and 1652. The source of rental value comes from the Verponding registration in Amsterdam. The verponding or the ‘Verpondings-quohieren van den 8sten penning’ was a tax in the Netherlands on the 8^th penny of the rental value of immovable property that had to be paid annually. In Amsterdam, the citywide verponding registration started in 1647 and continued into the early 19^th century. With the introduction of the cadastre system in 1810, the verponding came to an end.

The original tax registration is kept in the Amsterdam City Archives (Archief nr. 5044) and the four registration books transcribed in this dataset are Archief 5044, inventory 255, 273, 281, 284. The verponding was collected by districts (wijken). The tax collectors documented their collecting route by writing down the street or street-section names as they proceed. For each property, the collector wrote down the names of the owner and, if applicable, the renter (after ‘per’), and the estimated rental value of the property (in guilders). Next to the rental value was the tax charged (in guilders and stuivers). Below the owner/renter names and rental value were the records of tax payments by year.

This dataset digitises four registration books of the verponding between 1647 and 1652 in two ways. First, it transcribes the rental value of all real estate properties listed in the registrations. The names of the owners/renters are transcribed only selectively, focusing on the properties that exceeded an annual rental value of 300 guilders. These transcriptions can be found in Verponding1647-1652.csv. For a detailed introduction to the data, see Verponding1647-1652_data_introduction.txt.

Second, it geo-references the registrations based on the street names and the reconstruction of tax collectors’ travel routes in the verponding. The tax records are then plotted on the historical map of Amsterdam using the first cadaster of 1832 as a reference. Since the geo-reference is based on the street or street sections, the location of each record/house may not be the exact location but rather a close proximation of the possible locations based on the street names and the sequence of the records on the same street or street section. Therefore, this geo-referenced verponding can be used to visualise the rental value distribution in Amsterdam between 1647 and 1652. The preview below shows an extrapolation of rental values in Amsterdam. And for the geo-referenced GIS files, see Verponding_wijken.shp.

GIS specifications:

Coordination Reference System (CRS): Amersfoort/RD New (ESPG:28992)

Historical map tiles URL (From Amsterdam Time Machine)

NB: This verponding dataset is a provisional version. The georeferenced points and the name transcriptions might contain errors and need to be treated with caution.

Contributors

• Historical and archival research: Weixuan Li, Bart Reuvekamp
• Plotting of geo-referenced points: Bart Reuvekamp
• Spatial analysis: Weixuan Li
• Mapping software: QGIS
• Acknowledgements: Virtual Interiors project, Daan de Groot