This dataset was updated May, 2025.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.html Data 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.25_1: The CPAD Input dataset was amended to merge large gaps in certain areas of the state known to be erroneous, such as Yosemite National Park, and to eliminate overlaps from the original input. The FWS input dataset was updated in February of 2025, and the DOD input dataset was updated in October of 2024. The BIA input dataset was the same as was used for the previous ownership version.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.

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.

This ownership dataset utilizes a methodology that results in a federal ownership extent that matches the Federal Responsibility Areas (FRA) footprint from CAL FIRE's State Responsibility Areas for Fire Protection (SRA) data. FRA lands are snapped to county parcel data, thus federal ownership areas will also be snapped. Since SRA Fees were first implemented in 2011, CAL FIRE has devoted significant resources to improve the quality of SRA data. This includes comparing SRA data to data from other federal, state, and local agencies, an annual comparison to county assessor roll files, and a formal SRA review process that includes input from CAL FIRE Units. As a result, FRA lands provide a solid basis as the footprint for federal lands in California (except in the southeastern desert area). The methodology for federal lands involves:

Ownership is a commonly used base layer used in a wide range of business functions and these data are intended to provide a depiction of the land ownership within the CLM project area. ownership22_1 - California Multi-Source Land Ownership, includes lands owned by each federal agency (including USFS) state agency, local government entities, conservation organizations, and special districts. It does not include lands of private ownership.

The CDFW Owned and Operated Lands and Conservation Easements dataset is a subset of the CDFW Lands dataset. It contains lands owned (fee title), some operated (wildlife areas, ecological reserves, and public/fishing access properties that are leases/agreements with other agencies that may be publicly accessible) and conservation easements held by CDFW. CDFW Owned and Operated Lands and Conservation Easements replaces the prior dataset, DFG Owned and Operated Lands, which included only fee title lands and some operated lands (wildlife areas, ecological reserves, and public/fishing access properties that are leases/agreements with other agencies and that may be publicly accessible). This is a generalized version dataset that has a shorter attribute table than the original and also has been dissolved based on the fields included. Please note that some lands may not be accessible due to the protection of resources and habitat. It is recommended that users contact the appropriate regional office for access information and consult regulations for CDFW lands in Sections 550, 550.1, 551, 552, 630 and 702. The CDFW Lands dataset is a digitized geographical inventory of selected lands owned and/or administered by the California Department of Fish and Wildlife. Properties such as ecological reserves, wildlife areas, undesignated lands containing biological resource values, public and fishing access lands, and CDFW fish hatcheries are among those lands included in this inventory. Types of properties owned or administered by CDFW which may not be included in this dataset are parcels less than 1 acre in size, such as fishing piers, fish spawning grounds, fish barriers, and other minor parcels. Physical boundaries of individual parcels are determined by the descriptions contained in legal documents and assessor parcel maps relating to that parcel. The approximate parcel boundaries are drawn onto U.S. Geological Survey 7.5'-series topographic maps, then digitized and attributed before being added to the dataset. In some cases, assessor parcel or best available datasets are used to digitize the boundary. Using parcel data to adjust the boundaries is a work in progress and will be incorporated in the future. Township, range, and section lines were based on the U.S. Geological Survey 7.5' series topographic maps (1:24,000 - scale). In some areas, the boundaries will not align with the Bureau of Land Management's Public Lands Survey System (PLSS). See the "SOURCE" field for data used to digitize boundary.This dataset is intended to provide information on the location of lands owned and/or administered by the California Department of Fish and Wildlife (CDFW) and for general conservation planning within the state. This dataset is not intended for navigational use. Users should contact the CDFW, Wildlife Branch, Lands Program or CDFW Regional offices for access information to a particular property. These datasets do not provide legal determination of parcel acreages or boundaries. Legal parcel acreages are based on County Assessor records. Users should contact the Wildlife Branch, Lands Program for this information and related data. When labeling or displaying properties on any map, use the provided field named "MAPLABEL" or use a generic label such as "conservation lands", "restricted lands", or some other similiar generalized label. All conservation easements are closed to public access.This dataset is not a surveyed product and is not a legal record of original survey measurements. They are representations or reproductions of information using various sources, scales, and precision of boundary data. As such, the data do not carry legal authority to determine a boundary, the location of fixed works nor is it suitable for navigational purposes. The California Department of Fish and Wildlife shall not be held liable for any use or misuse of the data. Users are responsible for ensuring the appropriate use of the data . It is strongly recommended that users acquire this dataset directly from the California Department of Fish and Wildlife and not indirectly through other sources which may have outdated or misinterpreted information.

The following data is provided as a public service, for informational purposes only. This data should not be construed as legal advice. Users of this data should independently verify its determinations prior to taking any action under the California Environmental Quality Act (CEQA) or any other law. The State of California makes no warranties as to accuracy of this data. General plan land use element data was collected from 532 of California's 539 jurisdictions. An effort was made to contact each jurisdiction in the state and request general plan data in whatever form available. In the event that general plan maps were not available in a GIS format, those maps were converted from PDF or image maps using geo-referencing techniques and then transposing map information to parcel geometries sourced from county assessor data. Collection efforts began in late 2021 and were mostly finished in late 2022. Some data has been updated in 2023. Sources and dates are documented in the "Source" and "Date" columns with more detail available in the accompanying sources table. Data from a CNRA funded project, performed at UC Davis was used for 7 jurisdictions that had no current general plan land use maps available. Information about that CNRA funded project is available here: https://databasin.org/datasets/8d5da7200f4c4c2e927dafb8931fe75dIndividual general plan maps were combined for this statewide dataset. As part of the aggregation process, contiguous areas with identical use designations, within jurisdictions, were merged or dissolved. Some features representing roads with right-of-way or Null zone designations were removed from this data. Features less than 4 square meters in area were also removed.

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300 data sources in total
2. 20 data sources in California
3. 14,500,000 properties in California
4. 4 billion records (listed in the "data types" block above) in total
5. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

All property addresses for City of Kitchener, which includes business names.All addresses are provided and only addresses not covered under MFIPPA are shown. MFIPPA is Ontario Municipal Freedom of Information and Protection of Privacy Act - The Act requires that local government institutions protect the privacy of an individual's personal information existing in government records. Only the owner of a business (or number company) or government agency can be shown, and all other addresses are marked as private.

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels which comprise the spatial features of CPAD, generally corresponding to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. •The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1.CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6.Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7.These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.10. PAD-US is a principal data source for understanding the spatial distribution of GAP coded lands, but it is national in scope, and may not always be the most current source of data with respect to California holdings. GreenInfo Network, which develops and maintains the CPAD and CCED datasets, has taken a lead role in establishing communication with land stewards across California in order to make GAP attribution of these lands as current and accurate as possible. The tabular attribution of these datasets is analyzed in addition to PAD-US in order to understand whether a holding may be considered conserved. Tracking Conserved Areas The total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review.The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

The SMA implementation is comprised of one feature dataset, with several polygon feature classes, rather than a single feature class. SurfaceManagementAgency: The Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency's surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. This layer is also updated whenever BLM is notified that Lands have been acquired by other Federal Agencies. For additional information regarding an acquisition search the Bureau's LR2000 system: The LND_SurfaceEstate data is edited and maintained in a single polygon feature class. Whenever possible, BLM lands are constructed from the Public Land Survey System (PLSS), also available to the public (PublicLandSurvey.gdb). Alignment of BLM data with the PLSS is a continual process, as the accuracy and density of PLSS data continues to improve and develop. Issues of misalignment with the PLSS are more common with non-BLM management areas. These discrepancies are being addressed at the BLM California State office based on U.S. Department of Interior priorities throughout the State of California

This layer can be used for watershed analysis and planning in the Russian River region of California.

This dataset contains all properties in the City of Los Angeles owned by the following public entities: Federal GSD, State of California, Los Angeles County, City of Los Angeles, LAUSD, and Metro.

This data on property ownership was derived from the data made available by the Los Angeles County Assessor's Office, here: https://data.lacounty.gov/Parcel-/Assessor-Publicly-Owned-Parcels-Listing/a9jw-tqfp/data

"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"SCAG has developed and maintained its regional geospatial dataset of land use information at parcel-level—approximately five million parcels in the SCAG Region. The parcel-based land use dataset is developed (1) to aid in SCAG’s regional transportation planning, scenario planning and growth forecasting, (2) facilitate policy discussion on various planning issues, and (3) enhance information database to better serve SCAG member jurisdictions, research institutes, universities, developers, general public, etc. After the successful release of SCAG’s 2016 regional land use dataset for the development of the Connect SoCal (the 2020 RTP/SCS), SCAG has initiated a process to annually update its regional land use information at the parcel-level (the Annual Land Use Update). For the Annual Land Use Update process, SCAG collected county assessor’s tax roll records (including parcel polygons and property information) from county assessor’s offices, plus other reference layers including California Protected Areas Database (CPAD), California School Campus Database (CSCD), Farmland Mapping and Monitoring Program (FMMP)'s Important Farmland, U.S. Department of Defense's Military Installations, Ranges, and Training Areas (MIRTA) as well as SCAG's regional geospatial datasets, such as airport polygons and water body polygons.Note: This dataset is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Users should consult with each local jurisdiction directly to obtain the official land use information.Data DescriptionFIELD_NAMEDESCRIPTIONPID202020 SCAG's unique parcel identifierAPN202020 Assessor Parcel NumberAPN20_P2020 Assessor Parcel Number - Parent Parcel (if applicable)COUNTYCounty nameCOUNTY_IDCounty FIPS codeCITYCity nameCITY_IDCity FIPS codeMULTIPARTMultipart feature (the number of multipart polygons; '1' = singlepart feature)STACKDuplicate geometry (the number of stacked polygons; '1' = no duplicate polygons)ACRESParcel area (in acres)SLOPESlope information1GEOID202020 Census Block GEOIDAPN_DUPDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIORatio of improvements assessed value to land assessed valueALU202020 Existing Land UseALU20_SRC2020 Existing Land Use Source2GP19_CITY2019 Jurisdiction’s general plan land use designationGP19_SCAG2019 SCAG general plan land use codeSP19_CITY2019 Jurisdiction’s specific plan land use designationSP19_SCAG2019 SCAG specific plan land use codeZN19_CITY2019 Jurisdiction’s zoning codeZN19_SCAG2019 SCAG zoning codeSP19_INDEX2019 Specific Plan Index ('0' = outside specific plan area; '1' = inside specific plan area)DC_BLTDecade built of existing structure (example: year built between 1960-1969 is '1960s')3BF_SQFT Building footprint area (in square feet)4PUB_OWNPublic-owned land index ('1' = owned by public agency)PUB_TYPEType of public agency5ADU_STATEThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)6, (1 = ADU eligible parcel, 0 = Not ADU eligible parcel)SF_UNBUILTDifference between parcel land area and building footprint area expressed in square feetFLOODParcel intersects with flood areas delineated by the Federal Emergency Management Agency (FEMA), obtained from the Digital Flood Insurance Rate Map from FEMA in August 2017. FIREParcel intersects with CalFire State Responsibility Areas Fire Hazard Severity zones (high and very high severity), dated 9/29/2023 and implemented 4/1/2024. WUIParcel intersects with Wildland-Urban Interface or Intermix zones, utilized from CAL FIRE’s Fire and Resource Assessment Program (FRAP), Wildland-Urban Interface (WUI) and Wildland-Urban Intermix (2020). See CAL FIRE for details. SEARISE36Parcel intersects with USGS Coastal Storm Modeling System (CoSMos) One-Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2, 2018)WETLANDParcel intersects a wetland or deepwater habitat, obtained from the US Fish and Wildlife Services National Wetlands Inventory Data (2020)HABITATParcel intersects with habitat connectivity corridors. Data is obtained from the California Department of Fish and Wildlife Habitat Essential Connectivity Project (2010).CONSERVParcel intersects with Areas of Conservation Emphasis (ACEIIv2), obtained from California Department of Fish and Wildlife Areas of Conservation Emphasis (2015)SOARParcel intersects with publicly owned open space identified by the County of Ventura Save Our Agricultural Resources (SOAR, 2017), which consist of a series of voter initiatives that require a majority vote of the people before agricultural land or open space areas can be rezoned for developmentCPADParcel intersects with publicly owned protected open space lands in the State of California through fee ownership as identified in the 2021 California Protected Areas Database (CPAD)CCEDParcel intersects with lands protected under conservation easements as identified in the 2021 California Conservation Easement Database (CCED)TRIBALParcel intersects with the tribal lands for the 16 Federally Recognized Tribal entities in the SCAG region, obtained from the American Indian Reservations/ Federally Recognized Tribal Entities dataset (2021)MILITARYParcel intersects with military lands managed by the US Department of Defense as of 2018FARMLANDParcel intersects with farmlands as identified in the Farmland Mapping and Monitoring Program (FMMP) in the Division of Land Resource Protection in the California Department of Conservation (2018)GRRA_INDEXThe number of Green Region Rresource Areas (GRRAs) that the parcel intersects with. GRRAs are areas where climate hazard zones, environmental sensitivities, and administrative areas where growth would generally not advance SB 375 objectives. See Connect SoCal 2024 Land Use & Communities Technical Report for details. UAZParcel centroid lies within Caltrans 2020 Adjusted Urbanized Area TCAC_2024The opportunity/resource level in the 2024 CTCAC/HCD Opportunity Map SB535_INDEXField takes a value of 1 if parcel intersects with SB 535 Disadvantaged Communities. See Connect SoCal 2024 Equity Analysis Technical Report for details. PEC_INDEXField takes a value of 1 if parcel's block falls within Priority Equity Communities. See Connect SoCal 2024 Equity Analysis Technical Report for details. PDA_INDEXThe number of Priority Development Areas (PDAs) that the parcel's largest overlapping area falls in. PDAs in Connect SoCal 2024 include Neighborhood Mobility Areas (NMAs), Transit Priority Areas (TPAs), Livable Corridors and Spheres of Influence (SOIs) (in unincorporated areas only). See Connect SoCal 2024 for details. PDA_NMAField takes a value of 1 if the parcel's largest overlapping area falls within Neighborhood Mobility Areas. See Connect SoCal 2024 for details. PDA_LCField takes a value of 1 if the parcel's largest overlapping area falls within Livable Corridors. See Connect SoCal 2024 for details. PDA_SOIField takes a value of 1 if the parcel's largest overlapping area falls within Spheres of Influence (SOIs) (in unincorporated areas only). See Connect SoCal 2024 for details. PDA_TPAField takes a value of 1 if the parcel's largest overlapping area falls within Transit Priority Areas. See Connect SoCal 2024 for details. APPAREL1MIThe number of apparel stores within a 1-mile drive7EDUC1MIThe number of educational institutions within a 1-mile drive7GROCERY1MIThe number of grocery stores within a 1-mile drive7HOSPIT1MIThe number of hospitals within a 1-mile drive7RESTAUR1MIThe number of restaurants within a 1-mile drive7JOBS_30MINThe number of the region's jobs accessible within a 30-minute commute by car during morning peak hour (6-9am) in 2050 based on Connect SoCal 2024 travel demand modeling. See Equity Technical Report for details. VMT_TOTAverage daily vehicle miles traveled (VMT) per average resident in the parcel’s transportation analysis zone (TAZ) in 2019, rounded to the nearest mile. This field contains results derived from Connect SoCal 2024’s activity-based travel demand model and do not reflect survey data, do not reflect VMT in any particular parcel within a TAZ, and are not validated at the TAZ-level. SCAG assumes no liability arising from the use of this data.8VMT_WORKAverage daily vehicle miles traveled (VMT) per average resident for work purposes in the parcel’s transportation analysis zone (TAZ) in 2019, rounded to the nearest mile. This field contains results derived from Connect SoCal 2024’s activity-based travel demand model and do not reflect survey data, do not reflect VMT in any particular parcel within a TAZ, and are not validated at the TAZ-level. SCAG assumes no liability arising from the use of this data.8JURIS_PLUSSub-jurisdictional geography in Los Angeles City (Community Plan Areas) and unincorporated areas of Los Angeles County (Planning Areas)YEARDataset YearShape_LengthLength of feature in internal unitsShape_AreaArea of feature in internal units squared1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. ASSESSOR- Assessor's 2020 tax roll records; CPAD- California Protected Areas Database (version 2020b; released in December 2020); CSCD- California School Campus Database (version 2021; released in March 2020); FMMP- Farmland Mapping and

In 2025, about ** percent of foreign buyers of residential real estate in California were from the Asia/Oceania region. Buyers of Latin American/Caribbean origin were the second largest group, with 18 percent of buyers.

Statewide Property Inventory started in 1989 per legislation 11011.15, to begin a pro-active approach to managing the State’s Real Property assets in a computerized format. Having the information in an electronic format makes it available to top level decision-makers considering options for the best use of these assets. The Statewide Property Inventory is mandated to capture detailed information on the following: land owned and leased by the state, structures owned and leased by the state, property the state leases to the private sector. Statewide Property Inventory was established in 1988 by legislative mandate. Leases were added in 2004 by executive order. Data is updated annually by the agencies. Point of Contact: Any questions should be referred to the SPIWeb@dgs.ca.gov

The table below showcases the total number of homes sold for each city in Los Angeles County, California. It's important to understand that the number of homes sold can vary greatly and can change yearly.

"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"This is SCAG's 2019 Annual Land Use (ALU v. 2019.1) at the parcel-level, updated as of February 2021. This dataset has been modified to include additional attributes in order to feed SCAG's Housing Element Parcel Tool (HELPR), version 2.0. The dataset will be further reviewed and updated as additional information is released. Please refer to the tables below for data dictionary and SCAG’s land use classification.Field NameData TypeField DescriptionPID19Text2019 SCAG’s parcel unique IDAPN19Text2019 Assessor’s parcel numberCOUNTYTextCounty name (based on 2016 county boundary)COUNTY_IDDoubleCounty FIPS code (based on 2016 county boundary)CITYTextCity name (based on 2016 city boundary)CITY_IDDoubleCity FIPS code (based on 2016 city boundary)MULTIPARTShort IntegerMultipart feature (the number of multiple polygons; '1' = singlepart feature)STACKLong IntegerDuplicate geometry (the number of duplicate polygons; '0' = no duplicate polygons)ACRESDoubleParcel area (in acreage)GEOID20Text2020 Census Block Group GEOIDSLOPEShort IntegerSlope information1APN_DUPLong IntegerDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIODoubleRatio of improvement assessed value to land assessed valueLU19Text2019 existing land useLU19_SRCTextSource of 2019 existing land use2SCAGUID16Text2016 SCAG’s parcel unique IDAPNText2016 Assessor’s parcel numberCITY_GP_COText2016 Jurisdiction’s general plan land use designationSCAG_GP_COText2016 SCAG general plan land use codeSP_INDEXShort IntegerSpecific plan index ('0' = outside specific plan area; '1' = inside specific plan area)CITY_SP_COText2016 Jurisdiction’s specific plan land use designationSCAG_SP_COText2016 SCAG specific plan land use codeCITY_ZN_COText2016 Jurisdiction’s zoning codeSCAG_ZN_COText2016 SCAG zoning codeLU16Text2016 existing land useYEARLong IntegerDataset yearPUB_OWNShort IntegerPublic-owned land index ('1' = owned by public agency)PUB_NAMETextName of public agencyPUB_TYPETextType of public agency3BF_SQFTDoubleBuilding footprint area (in square feet)4BSF_NAMETextName of brownfield/superfund site5BSF_TYPETextType of brownfield/superfund site5FIREShort IntegerParcel intersects CalFire Very High Hazard Local Responsibility Areas or State Responsibility Areas (November 2020 version) (CalFIRE)SEARISE36Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)1 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)SEARISE72Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)2 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)FLOODShort IntegerParcel intersects with a FEMA 100 Year Flood Plain data from the Digital Flood Insurance Rate Map (DFIRM), obtained from Federal Emergency Management Agency (FEMA) in August 10, 2017EQUAKEShort IntegerParcel intersects with an Alquist-Priolo Earthquake Fault Zone (California Geological Survey; 2018)LIQUAFAShort IntegerParcel intersects with a Liquefaction Susceptibility Zone (California Geological Survey; 2016)LANDSLIDEShort IntegerParcel intersects with a Landslide Hazard Zone (California Geological Survey; 2016)CPADShort IntegerParcel intersects with a protected area from the California Protected Areas Database(CPAD) – www.calands.org (accessed April 2021)RIPARIANShort IntegerParcel centroid falls within Active River Areas(2010)or parcel intersects with a Wetland Area in the National Wetland Inventory(Version 2)WILDLIFEShort IntegerParcel intersects with wildlife habitat (US Fish & Wildlife ServiceCritical Habitat, Southern California Missing Linkages, Natural Lands & Habitat Corridors from Connect SoCal, CEHC Essential Connectivity Areas,Critical Coastal Habitats)CNDDBShort IntegerThe California Natural Diversity Database (CNDDB)includes the status and locations of rare plants and animals in California. Parcels that overlap locations of rare plants and animals in California from the California Natural Diversity Database (CNDDB)have a greater likelihood of encountering special status plants and animals on the property, potentially leading to further legal requirements to allow development (California Department of Fish and Wildlife). Data accessed in October 2020.HCPRAShort IntegerParcel intersects Natural Community & Habitat Conservation Plans Reserve Designs from the Western Riverside MHSCP, Coachella Valley MHSCP, and the Orange County Central Coastal NCCP/HCP, as accessed in October 2020WETLANDShort IntegerParcel intersects a wetland or deepwater habitat as defined by the US Fish & Wildlife Service National Wetlands Inventory, Version 2.UAZShort IntegerParcel centroid lies within a Caltrans Adjusted Urbanized AreasUNBUILT_SFDoubleDifference between parcel area and building footprint area expressed in square feet.6GRCRY_1MIShort IntegerThe number of grocery stores within a 1-mile drive7HEALTH_1MIShort IntegerThe number of healthcare facilities within a 1-mile drive7OPENSP_1MIShort IntegerQuantity of open space (roughly corresponding to city blocks’ worth) within a 1-mile drive7TCAC_2021TextThe opportunity level based on the 2021 CA HCD/TCAC opportunity scores.HQTA45Short IntegerField takes a value of 1 if parcel centroid lies within a 2045 High-Quality Transit Area (HQTA)JOB_CTRShort IntegerField takes a value of 1 if parcel centroid lies within a job centerNMAShort IntegerField takes a value of 1 if parcel centroid lies within a neighborhood mobility area.ABS_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within an absolute constraint area. See the Sustainable Communities Strategy Technical Reportfor details.VAR_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within a variable constraint area. See the Sustainable Communities Strategy Technical Reportfor details.EJAShort IntegerField takes a value of 1 if parcel centroid lies within an Environmental Justice Area. See the Environmental Justice Technical Reportfor details.SB535Short IntegerField takes a value of 1 if parcel centroid lies within an SB535 Disadvantaged Community area. See the Environmental Justice Technical Reportfor details.COCShort IntegerField takes a value of 1 if parcel centroid lies within a Community of Concern See the Environmental Justice Technical Reportfor details.STATEShort IntegerThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)8.SBShort IntegerIndex of ADU eligibility according to the setback reduction policy scenario (from 4 to 2 feet) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SMShort IntegerIndex of ADU eligibility according to the small ADU policy scenario (from 800 to 600 square feet ADU) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)PKShort IntegerIndex of ADU eligibility according to parking space exemption (200 square feet) policy scenario (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SMShort IntegerIndex of ADU eligibility according to both the setback reduction and small ADU policy scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_PKShort IntegerIndex of ADU eligibility according to both the setback reduction and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SM_PKShort IntegerIndex of ADU eligibility according to both the small ADU policy and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SM_PKShort IntegerIndex of ADU eligibility according to the setback reduction, small ADU, and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. Source of 2019 existing land use: SCAG_REF- SCAG's regional geospatial datasets;ASSESSOR- Assessor's 2019 tax roll records; CPAD- California Protected Areas Database (version 2020a; accessed in September 2020); CSCD- California School Campus Database (version 2018; accessed in September 2020); FMMP- Farmland Mapping and Monitoring Program's Important Farmland GIS data (accessed in September 2020); MIRTA- U.S. Department of Defense's Military Installations, Ranges, and Training Areas GIS data (accessed in September 2020)3. Type of public agency includes federal, state, county, city, special district, school district, college/university, military.4. Based on 2019 building footprint data obtained from BuildingFootprintUSA (except that 2014 building footprint data was used for Imperial County). Please note that 2019 building footprint data does not cover the entire SCAG region (overlapped with 83% of parcels in the SCAG Region).5. Includes brownfield/superfund site whose address information are matched by SCAG rooftop address locator. Brownfield data was obtained from EPA's Assessment, Cleanup and Redevelopment Exchange System (ACRES) database, Cleanups in my community (CIMC), DTSC brownfield Memorandum of Agreement (MOA). Superfund site data was obtained from EPA's Superfund Enterprise Management System (SEMS) database.6. Parcels with a zero value for building footprint area are marked as NULL to indicate this field is not reliable.7. These values are intended as a rudimentary indicator of accessibility developed by SCAG using 2016 InfoUSA business establishment data and 2017 California Protected Areas data. See documentation for details.8. A detailed study conducted by Cal Poly Pomona (CPP) and available hereconducted an extensive review of state and local requirements and development trends for ADUs in the SCAG region and developed a baseline set of assumptions for estimating how many of a jurisdiction’s parcels

Graph and download economic data for State Tax Collections: T01 Property Taxes for California (QTAXT01QTAXCAT3CANO) from Q1 1994 to Q2 2025 about collection, tax, CA, and USA.

The CDFW Owned and Operated Lands and Conservation Easements dataset is a subset of the CDFW Lands dataset. It contains lands owned (fee title), some operated (wildlife areas, ecological reserves, and public/fishing access properties that are leases/agreements with other agencies that may be publicly accessible) and conservation easements held by CDFW. CDFW Owned and Operated Lands and Conservation Easements replaces the prior dataset, DFG Owned and Operated Lands, which included only fee title lands and some operated lands (wildlife areas, ecological reserves, and public/fishing access properties that are leases/agreements with other agencies and that may be publicly accessible). This is a generalized version dataset that has a shorter attribute table than the original and also has been dissolved based on the fields included. Please note that some lands may not be accessible due to the protection of resources and habitat. It is recommended that users contact the appropriate regional office for access information and consult regulations for CDFW lands in Sections 550, 550.1, 551, 552, 630 and 702. For information on public use regulations on Department lands, please refer to the Public Uses on State and Federal Lands section of the Waterfowl, Upland Game, and Public Use Regulations booklet for both statewide and property-specific regulations https://wildlife.ca.gov/Regulations. All visitors are responsible for knowing and following the general and property-specific regulations.The CDFW Lands dataset is a digitized geographical inventory of selected lands owned and/or administered by the California Department of Fish and Wildlife. Properties such as ecological reserves, wildlife areas, undesignated lands containing biological resource values, public and fishing access lands, and CDFW fish hatcheries are among those lands included in this inventory. Types of properties owned or administered by CDFW which may not be included in this dataset are parcels less than 1 acre in size, such as fishing piers, fish spawning grounds, fish barriers, and other minor parcels. Physical boundaries of individual parcels are determined by the descriptions contained in legal documents and assessor parcel maps relating to that parcel. The approximate parcel boundaries are drawn onto U.S. Geological Survey 7.5'-series topographic maps, then digitized and attributed before being added to the dataset. In some cases, assessor parcel or best available datasets are used to digitize the boundary. Using parcel data to adjust the boundaries is a work in progress and will be incorporated in the future. Township, range, and section lines were based on the U.S. Geological Survey 7.5' series topographic maps (1:24,000 - scale). In some areas, the boundaries will not align with the Bureau of Land Management's Public Lands Survey System (PLSS). See the "SOURCE" field for data used to digitize boundary.

These are the cadastral reference features that provide the basis and framework for parcel mapping and for other mapping. This feature data set contains PLSS and Other Survey System data. The other survey systems include subdivision plats and those types of survey reference systems. This feature data set also include feature classes to support the special conditions in Ohio. This data set represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non rectangular components of the PLSS) Meandered Water, Corners and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-Attribute section of this metadata describes these components in greater detail.