This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes:* Clipping input datasets to the California boundary* Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc)* Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California.* Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only.* Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs)* In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD* As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources:* GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf* US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore* Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases* Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov* Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.
[Metadata] Description: Detailed Government Landownership in the State of Hawaii as of 2022: County, Federal, State, and State DHHL Lands (by TMK parcel) Sources: County of Kauai, April, 2022; City & County of Honolulu, April 27, 2022; County of Maui, April, 2022; County of Hawaii, April, 2022; State Department of Hawaiian Home Lands, October, 2022. This dataset was created using ownership information provided by the counties via tax map key parcel layers and ownership tables. Parcels were queried using the "Owner" field for state, county, and federal agency names. State GIS staff verified land ownership using the online service QPublic, the 2022 Department of Hawaiian Home Lands layer and other GIS layers and resources. Where ownership was still unclear, State GIS personnel reached out to appropriate agencies for clarification. Standardization and Summary fields "ownedby," “majorowner” and “type” were created using additional filters and queries. The parcel boundaries are intended to provide a visual reference only and do not represent legal or survey level accuracy. Attributes are for assessment purposes only and are subject to change at any time.For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/gov_own_detailed.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
Please note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.Overview of the Data:This dataset is a polygon feature layer with the boundaries of all tax parcels owned by the City of Rochester. This includes all public parks, and municipal buildings, as well as vacant land and structures currently owned by the City. The data includes fields with features about each property including property type, date of sale, land value, dimensions, and more.About City Owned Properties:The City's real estate inventory is managed by the Division of Real Estate in the Department of Neighborhood and Business Development. Properties like municipal buildings and parks are expected to be in long term ownership of the City. Properties such as vacant land and vacant structures are ones the City is actively seeking to reposition for redevelopment to increase the City's tax base and economic activity. The City acquires many of these properties through the tax foreclosure auction process when no private entity bids the minimum bid. Some of these properties stay in the City's ownership for years, while others are quickly sold to development partners. For more information please visit the City's webpage for the Division of Real Estate: https://www.cityofrochester.gov/realestate/Data Dictionary: SBL: The twenty-digit unique identifier assigned to a tax parcel. PRINTKEY: A unique identifier for a tax parcel, typically in the format of “Tax map section – Block – Lot". Street Number: The street number where the tax parcel is located. Street Name: The street name where the tax parcel is located. NAME: The street number and street name for the tax parcel. City: The city where the tax parcel is located. Property Class Code: The standardized code to identify the type and/or use of the tax parcel. For a full list of codes, view the NYS Real Property System (RPS) property classification codes guide. Property Class: The name of the property class associated with the property class code. Property Type: The type of property associated with the property class code. There are nine different types of property according to RPS: 100: Agricultural 200: Residential 300: Vacant Land 400: Commercial 500: Recreation & Entertainment 600: Community Services 700: Industrial 800: Public Services 900: Wild, forested, conservation lands and public parks First Owner Name: The name of the property owner of the vacant tax parcel. If there are multiple owners, then the first one is displayed. Postal Address: The USPS postal address for the vacant landowner. Postal City: The USPS postal city, state, and zip code for the vacant landowner. Lot Frontage: The length (in feet) of how wide the lot is across the street. Lot Depth: The length (in feet) of how far the lot goes back from the street. Stated Area: The area of the vacant tax parcel. Current Land Value: The current value (in USD) of the tax parcel. Current Total Assessed Value: The current value (in USD) assigned by a tax assessor, which takes into consideration both the land value, buildings on the land, etc. Current Taxable Value: The amount (in USD) of the assessed value that can be taxed. Tentative Land Value: The current value (in USD) of the land on the tax parcel, subject to change based on appeals, reassessments, and public review. Tentative Total Assessed Value: The preliminary estimate (in USD) of the tax parcel’s assessed value, which includes tentative land value and tentative improvement value. Tentative Taxable Value: The preliminary estimate (in USD) of the tax parcel’s value used to calculate property taxes. Sale Date: The date (MM/DD/YYYY) of when the vacant tax parcel was sold. Sale Price: The price (in USD) of what the vacant tax parcel was sold for. Book: The record book that the property deed or sale is recorded in. Page: The page in the record book where the property deed or sale is recorded in. Deed Type: The type of deed associated with the vacant tax parcel sale. RESCOM: Notes whether the vacant tax parcel is zoned for residential or commercial use. R: Residential C: Commercial BISZONING: Notes the zoning district the vacant tax parcel is in. For more information on zoning, visit the City’s Zoning District map. OWNERSHIPCODE: Code to note type of ownership (if applicable). Number of Residential Units: Notes how many residential units are available on the tax parcel (if applicable). LOW_STREET_NUM: The street number of the vacant tax parcel. HIGH_STREET_NUM: The street number of the vacant tax parcel. GISEXTDATE: The date and time when the data was last updated. SALE_DATE_datefield: The recorded date of sale of the vacant tax parcel (if available). Source: This data comes from the department of Neighborhood and Business Development, Bureau of Real Estate.
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ForestOwn_v1 is a 250-meter spatial resolution raster geospatial dataset of forest ownership of the conterminous United States (CONUS). The dataset was prepared by the Forest Inventory and Analysis (FIA) program, Northern Research Station, Forest Service, United States Department of Agriculture (USDA), and differentiates forest from non-forest land and water, public and private ownership, and the percent of private forest land in corporate ownership. The forest/non-forest land/water classification is derived from the USDA Forest Service's CONUS Forest/Nonforest dataset. Public and private land ownership class is derived from the Protected Areas Database of the United States, Version 1.1 (CBI Edition). Corporate ownership of private forest land is derived from the Forest Service's 2007 Resources Planning Act (RPA) dataset, summarized over the Environmental Protection Agency's Original Environmental Monitoring & Assessment Program (EMAP) grid 648 square kilometer hexagon dataset.The ForestOwn_v1 dataset is designed for conducting geospatial analyses and for producing cartographic products over regional to national geographic extents.A corresponding Research Map (RMAP) has been produced to cartographically portray this dataset.
Original metadata date was 02/09/2011. Minor metadata updates were made on 05/10/2013, 04/16/2014, 12/21/2016, and 02/06/2017. Additional minor metadata updates were made on 04/20/2023.
On 07/23/2020 a newer version of these data became available (Sass et al. 2020).
Title: Cotality Smart Data Platform (SDP): Owner Transfer and Mortgage
The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.
Formerly known as CoreLogic Smart Data Platform: Owner Transfer & Mortgage.
In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.
To fill researchers’ needs for uniform parcel data, Cotality collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. Cotality augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from Cotality's parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.
For more information about how the data was prepared for Redivis, please see Cotality 2024 GitLab.
The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.
The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).
The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP
, a unique identification number assigned to each property.
Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID
.
For more information about included variables, please see:
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For a count of records per FIPS code, please see cotality_sdp_owner_transfer_counts_2024.txt and cotality_sdp_mortgage_counts_2024.txt.
For more information about how the Cotality Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see 2025_Legacy_Content_Mapping.pdf.
Data access is required to view this section.
Land and Property Extents expressed as polygons as recorded through the Allerdale Land Terrier. Extents captured from OS Mastermap from legal title plans
Federal Land Ownership (Bureau of Land Management BLM, United States Forest Service USFS, Bureau of Reclamation BOR) of parcels in Trinity County derived by merging parcels by ownership type and calculating acres.
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This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.
Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.
Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.
Vacant property owned and managed by the City of Chicago Department of Planning and Development. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the LIS database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the LIS database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.
U.S. Government Workshttps://www.usa.gov/government-works
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Please read all metadata before accessing the dataset. Note that records shown here are updated at different frequencies from data in products from MDP and SDAT. Please see the full documentation at https://opendata.maryland.gov/api/views/ed4q-f8tm/files/WtRzMltUzm25OasOCYtu7PgOGUfrplWsZTalSH4Iukg?download=true&filename=Real%20Property%20Records%20Documentation.pdf and review the dedicated metadata site (https://opendata.maryland.gov/dataset/Beta-Maryland-Statewide-Real-Property-Assessments-/ed4q-f8tm/about).
Lands conveyed to the State of Alaska with a variety of cases such as general purpose, expansion of communities, University of Alaska, and recreational purposes. This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Ownership - Other State Acquired Land category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction. Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://www.dnr.state.ak.us/las/LASMenu.cfm Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.
Parcels and Land Ownership dataset current as of 2005. ParcelView-The data set is a view of the parcel polygon consisting of more than 93,000 tax parcel boundaries in Davis County. This Davis County Recorder compiled the parcel layer using GeoMeida Professional and GeoMedia Parcel Manager..
Parcels and Land Ownership dataset current as of 2009. recorder lines.
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Taiwan LR: Area: Change in Land Ownership: Transaction data was reported at 21,055.596 sq m th in Oct 2018. This records an increase from the previous number of 19,140.148 sq m th for Sep 2018. Taiwan LR: Area: Change in Land Ownership: Transaction data is updated monthly, averaging 28,343.999 sq m th from Feb 1995 (Median) to Oct 2018, with 285 observations. The data reached an all-time high of 80,713.208 sq m th in Oct 1999 and a record low of 15,676.545 sq m th in Feb 2016. Taiwan LR: Area: Change in Land Ownership: Transaction data remains active status in CEIC and is reported by Construction and Planning Agency, Ministry of the Interior. The data is categorized under Global Database’s Taiwan – Table TW.EB007: Land Registration: Area.
COUNTY_LAND_PARCELS_IDHS_IN is a polygon feature class that contains land parcels maintained by county agencies in Indiana, provided by personnel of Indiana Department of Homeland Security (IDHS) as of June 29, 2009, and subsequently updated on September 30, 2009, December 2, 2009, December 28, 2009, February 2, 2010, March 5, 2010, April 6, 2010, October 11, 2010, November 19, 2010, March 22, 2011, September 8, 2011, January 30, 2012, June 8, 2012, August 27, 2012, April 27, 2013, and November 22, 2013. This data set was provided by IDHS in ESRI feature class named "County_Parcels." This data set was compiled by IDHS as part of the IndianaMap Data Sharing Initiative between IGIC, Indiana Office of Technology (IOT), Indiana Geographic Information Office (GIO), Indiana Department of Homeland Security (IDHS), Indiana Geological Survey (IGS) and participating Indiana counties to provide the most accurate framework data (including address points, street centerlines, land parcels, and governmental boundaries) for the citizens of Indiana. More information is available at the following Web URL: http://www.igic.org/news/index.php?itemid=265
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This dataset is intended to provide a statewide depiction of land ownership in California. It includes lands owned by each federal agency, state agency, local government entities, conservation organizations, and special districts. It does not include lands that are in private ownership.
Ownership is derived from CAL FIRE's State Responsibility Area (SRA) dataset and GreenInfo Network's California Protected Areas Database (CPAD).
CAL FIRE tracks lands owned by federal agencies as part of our efforts to maintain fire protection responsibility boundaries, captured as part of our State Responsibility Areas (SRA) dataset. This effort draws on data provided by various federal agencies including USDA Forest Service, BLM, National Park Service, US Fish and Wildlife Service, and Bureau of Indian Affairs. Since SRA lands are matched to county parcel data where appropriate, often federal land boundaries are also adjusted to match parcels, and may not always exactly match the source federal data.
Federal lands from the SRA dataset are combined with ownership data for non-federal lands from CPAD, in order to capture lands owned by various state and local agencies, special districts, and conservation organizations. Data from CPAD are imported directly and not adjusted to match parcels or other features. However, CPAD features may be trimmed if they overlap federal lands from the SRA dataset.
This service represents the latest release of the dataset by FRAP, and is updated annually. As of November 2018, it represents ownership18_2.
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An area depicted as surface ownership parcels dissolved on the same ownership classification. MetadataThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.
An area depicting ownership parcels of the surface estate. Each surface ownership parcel is tied to a particular legal transaction. The same individual or organization may currently own many parcels that may or may not have been acquired through the same legal transaction. Therefore, they are captured as separate entities rather than merged together. This is in contrast to Basic Ownership, in which the surface ownership parcels having the same owner are merged together. Basic Ownership provides the general user with the Forest Service versus non-Forest Service view of land ownership within National Forest boundaries. Surface Ownership provides the land status user with a current snapshot of ownership within National Forest boundaries.
Ownership – This table contains the ownership, address, legal description, tax area and value for each parcel. There is one row of data per account. Only the primary owner is listed. For additional owners on the account, reference the SecondaryNameOwnershipList data table.Following are definitions for each of the field names:ACCOUNTNO – Account NumberNAMEADDRID – For internal useNAMETYPE – P=Primary Owner. For additional owners, see SecondaryNameOwnershipList data table.NAME – Owner NameCAREOF – In Care ofADDRESS1 – Mailing Address1ADDRESS2 – Mailing Address2CITY – City of Mailing AddressSTATE – State of Mailing AddressZIP – Zip Code of Mailing AddressPARCELNB – Parcel NumberMHSPACE – Mobile Home spacePARCELSEQ – This field no longer usedAREAID – Tax Area Identification #. See TaxAreaAuths data table for a list of taxing authorities in the area. See LevyTotals data table for the mill levy associated with this tax area.ACCTTYPE – Type of Account (Commercial, Residential, Vacant Land, etc.). For multi-use properties (i.e. Commercial and Residential), ACCTTYPE will reflect the primary use of the property.BUSINESSNAME – Business NameMAPNO – Map # (for internal use)BORDERINGCOUNTY – This field is no longer usedBACODE – For Personal Property Accounts, identifies the type of business. Contact our office for a description of what each code means.LAGENT – This field is no longer usedSTREETNO – Street # of physical locationSTREETNAME – Street Name of physical locationLANDACT – Land Actual ValueIMPACT - Improvement Actual ValueLANDASD – Land Assessed ValueIMPASD – Improvement Assessed ValueACRES – Land lot size in AcresSQFT – Total Square Feet of all ImprovementsUNITS – Land lot size in SFLEGAL – Legal Description of propertyAPRDIST – This field is no longer usedBA_OWNER_ID – This field is no longer usedBA_LOCATION – This field is no longer usedSTREETALP – Unit or Apartment Number of Physical AddressSTREETDIR – Street Direction of Physical Address (North, East, South, West)STREETSUF – Street suffix of Physical Address (Ave, Street, Court, Blvd)LOCCITY –City of physical location. Unincorporated areas will be WELD or blank.LANDSQFT – Land lot size in square feetSUBCODE – Subdivision codeSUBNAME – Subdivision nameCONDOCODE – This field no longer usedCONDONAME – This field no longer usedSALEP – Sale Price of most recent saleSALEDT – Sale Date of most recent saleDOCFEE – Doc Fee (Fee to record the deed) of most recent saleDEEDTYPE – Deed Type Code of most recent saleBLOCK – Block#LOT – Lot #CONDOUNIT – This field no longer usedBOOK – Book # of most recent sale. No longer used by Clerk and Recorder’s Office. Only populated on older sales. Use RECEPTION_NO instead.PAGE – Page # of most recent sale. No longer used by Clerk and Recorder’s Office. Only populated on older sales. Use RECEPTION_NO instead.RECEPTION_NO – Reception # of most recent sale For a complete Property Address, combine the following field names in this order:PROPERTY ADDRESS: STREETNO, STREETDIR, STREETNAME, STREETSUF, STREETALP
Parcels and Land Ownership dataset current as of 2001. 1s4w-10.
This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes:* Clipping input datasets to the California boundary* Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc)* Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California.* Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only.* Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs)* In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD* As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources:* GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf* US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore* Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases* Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov* Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.