This dataset contains shapefile boundaries for CA State, counties and places from the US Census Bureau's 2023 MAF/TIGER database. Current geography in the 2023 TIGER/Line Shapefiles generally reflects the boundaries of governmental units in effect as of January 1, 2023.

An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protection's CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990+. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system. This service depicts the WHRTYPE description from the fveg dataset (Wildlife Habitat Relationship classes).The full dataset can be downloaded in raster format here: GIS Mapping and Data Analytics | CAL FIREThe service represents the latest release of the data, and is updated when a new version is released. Currently it represents fveg15_1.

Complete accounting of all incorporated cities, including the boundary and name of each individual city. From 2009 to 2022 CAL FIRE maintained this dataset by processing and digitally capturing annexations sent by the state Board of Equalization (BOE). In 2022 CAL FIRE began sourcing data directly from BOE, in order to allow the authoritative department provide data directly. This data is then adjusted so it resembles the previous formats.Processing includes:• Clipping the dataset to traditional state boundaries• Erasing areas that span the Bay Area (derived from calw221.gdb)• Querying for incorporated areas only• Dissolving each incorporated polygon into a single feature• Calculating the COUNTY field to remove the word 'County'Version 24_1 is based on BOE_CityCounty_20240315, and includes all annexations present in BOE_CityAnx2023_20240315. Note: The Board of Equalization represents incorporated city boundaries as extending significantly into waterways, including beyond coastal boundaries. To see the representation in its original form please reference the datasets listed above.Note: The Board of Equalization represents incorporated city boundaries is extending significantly into waterways, including beyond coastal boundaries. To see the representation in its original form please reference the datasets listed above.

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.

Buildings: A simplified point layer of California State Parks buildings, providing location, name, function and other attributes. Current as of October 2024.

The California Energy Commission (CEC) Electric Transmission Line geospatial data layer has been created to illustrate electric transmission in California. When used in association with the other energy related geospatial data layers, viewers can analyze the geographic relationships with the electric transmission across the state. The transmission line data is used to:1. Support the CEC Transmission Planning; 2. Support the CEC electric system analysis in California;3. Enhance electric transmission communication among California electric stakeholders ;4. Support CEC's illustrations of electric infrastructureData Dictionary:Object ID: a unique, not null integer field used to uniquely identify rows in tables in a geodatabase.Name: abbreviated transmission line owner and transmission line capacity in kilovolts (kV).kV: transmission line capacity in kilovolts (kV), data structure is a text string.kV (Sort): transmission line capacity in kilovolts (kV), data structure is a numeric double.Owner: abbreviated transmission line owner name.Status - last reported operational, proposed, closed, or unknown status of the transmission line.Circuit - notes if the transmission line segment is a Single, double, or triple circuit. Null values are unknown. Type - OH is overhead transmission lines, UG is underground, UW is underwater, null values are unknown.Legend - a summarized categories of transmission line owner and transmission capacity value in kilowatts (kV) for map legend purposes.Length (Mile) - the length of the transmission line segment in miles.Length (Feet) - the length of the transmission line segment in feet.TLine Name - the name of the transmission line segment reported to the California Energy CommissionSource - the data source used by California Energy Commission.CommentsCreatorCreator DateLast EditorLast Editor DateGlobalIDShape_LengthShape

This layer shows census tracts that meet the following definitions: Census tracts with median household incomes at or below 80 percent of the statewide median income or with median household incomes at or below the threshold designated as low income by the Department of Housing and Community Development’s list of state income limits adopted under Healthy and Safety Code section 50093 and/or Census tracts receiving the highest 25 percent of overall scores in CalEnviroScreen 4.0 or Census tracts lacking overall scores in CalEnviroScreen 4.0 due to data gaps, but receiving the highest 5 percent of CalEnviroScreen 4.0 cumulative population burden scores or Census tracts identified in the 2017 DAC designation as disadvantaged, regardless of their scores in CalEnviroScreen 4.0 or Lands under the control of federally recognized Tribes.Data downloaded in May 2022 from https://webmaps.arb.ca.gov/PriorityPopulations/.

In late 1996, the Dept of Conservation (DOC) surveyed state and federal agencies about the county boundary coverage they used. As a result, DOC adopted the 1:24,000 (24K) scale U.S. Bureau of Reclamation (USBR) dataset (USGS source) for their Farmland Mapping and Monitoring Program (FMMP) but with several modifications. Detailed documentation of these changes is provided by FMMP and included in the lineage section of the metadata.A dataset was made available (approximately 2004) through CALFIRE - FRAP and the California Spatial Information Library (CaSIL), with additional updates throughout subsequent years. More recently, an effort was made to improve the coastal linework by using the previous interior linework from the 24k data, but replacing the coastal linework based on NOAA's ERMA coastal dataset (which used NAIP 2010). In this dataset, all bays (plus bay islands and constructed features) are merged into the mainland, and coastal features (such as islands and constructed features) are not included, with the exception of the Channel Islands which ARE included.This service represents the latest released version, and is updated when new versions are released. As of June, 2019 it represents cnty19_1.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has now developed and released seven National Land Cover Database (NLCD) products: NLCD 1992, 2001, 2006, 2011, 2016, 2019, and 2021. Beginning with the 2016 release, land cover products were created for two-to-three-year intervals between 2001 and the most recent year. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. NLCD continues to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database. NLCD 2021 adds an additional year to the map products produced for NLCD 2019, with a streamlined compositing process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a theme-based post-classification protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and a scripted operational system. The overall accuracy of the 2019 Level I land cover was 91%. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2021 operational mapping (see https://doi.org/10.1080/15481603.2023.2181143 for the latest accuracy assessment publication). Questions about the NLCD 2021 land cover product can be directed to the NLCD 2021 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

To provide an alternative to the native NHD measuring system of percentage of distance along reach length with one that enhances the ability to examine distance relationships along entire stream courses.

The California Protected Areas Database (CPAD) is a GIS database of lands that are owned in fee and protected for open space purposes by over 1,000 public agencies or non-profit organizations. It is the authoritative GIS database of parks and open space in California.

CPAD is maintained and published by GreenInfo Network (www.greeninfo.org). GreenInfo Network publishes CPAD twice annually.

NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.

Thank you for your interest in DWR land use datasets.

The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.

Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.

For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.

For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.

Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.

Counties in California intended for the NEVI Map.

Wetlands in California are protected by several federal and state laws, regulations, and policies. This layer was extracted from the broader vegetation raster from the CA Nature project which was recently enhanced to include a more comprehensive definition of wetland. This wetlands dataset is used as an exclusion as part of the biological planning priorities in the CEC 2023 Land-Use Screens.This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.For more information about this layer and its use in electric system planning, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

State and federal legislative district service areas approved by the 2020 California Citizens Redistricting Commission. Source: https://gis.data.ca.gov/datasets/CDEGIS::us-congressional-districts/explore

On October 30, 2015 Governor Brown issued an emergency declaration requiring public agencies to identify areas of tree mortality that hold the greatest potential to result in wildfire and/or falling trees and threaten people and property in these areas. Once identified, these areas will be prioritized for removal of dead and dying trees that present a threat to public safety. Tier Two high hazard zones are defined by watersheds (HUC 12, average 24,000 acres) that have significant tree mortality as well as significant community and natural resource assets. Work at the Tier Two level addresses the immediate threat of falling trees and fire risk, and also supports broader forest health and landscape level fire planning issues.This service represents the latest official release of HHZ. It will be updated annually when a new version is released. As of June 2019, it represents HighHazardZones19_1.

This layer consists of the merged footprints of the USFWS critical habitat and the USFWS proposed Bi-State Sage-Grouse critical habitat,1 clipped to California. Critical habitat constitutes areas considered essential for the conservation of a listed species. These areas provide notice to the public and land managers of the importance of the areas to the conservation of this species. Special protections and/or restrictions are possible in areas where Federal funding, permits, licenses, authorizations, or actions occur or are required. The critical habitat footprint shown here is used as part of the biological planning priorities in the CEC 2023 Land-Use Screens and removes technical resource potential from the state. More information about this layer and its use in electric system planning is available in the Land Use Screens Staff Report in the CEC Energy Planning Library. [1] This dataset is obtained from the "Web Links" section (USFWS Proposed Critical Habitat Map) of the Bi-State Sage-Grouse Maps & GIS webpage, available at Maps & GIS | Bi-State Sage-Grouse (bistatesagegrouse.com).

This dataset includes one file for each of the 51 counties that were collected, as well as a CA_Merged file with the parcels merged into a single file.Note – this data does not include attributes beyond the parcel ID number (PARNO) – that will be provided when available, most likely by the state of California.DownloadA 1.6 GB zipped file geodatabase is available for download - click here.DescriptionA geodatabase with parcel boundaries for 51 (out of 58) counties in the State of California. The original target was to collect data for the close of the 2013 fiscal year. As the collection progressed, it became clear that holding to that time standard was not practical. Out of expediency, the date requirement was relaxed, and the currently available dataset was collected for a majority of the counties. Most of these were distributed with minimal metadata.The table “ParcelInfo” includes the data that the data came into our possession, and our best estimate of the last time the parcel dataset was updated by the original source. Data sets listed as “Downloaded from” were downloaded from a publicly accessible web or FTP site from the county. Other data sets were provided directly to us by the county, though many of them may also be available for direct download. Â These data have been reprojected to California Albers NAD84, but have not been checked for topology, or aligned to county boundaries in any way. Tulare County’s dataset arrived with an undefined projection and was identified as being California State Plane NAD83 (US Feet) and was assigned by ICE as that projection prior to reprojection. Kings County’s dataset was delivered as individual shapefiles for each of the 50 assessor’s books maintained at the county. These were merged to a single feature class prior to importing to the database.The attribute tables were standardized and truncated to include only a PARNO (APN). The format of these fields has been left identical to the original dataset. The Data Interoperablity Extension ETL tool used in this process is included in the zip file. Where provided by the original data sources, metadata for the original data has been maintained. Please note that the attribute table structure changes were made at ICE, UC Davis, not at the original data sources.Parcel Source InformationCountyDateCollecDateCurrenNotesAlameda4/8/20142/13/2014Download from Alamenda CountyAlpine4/22/20141/26/2012Alpine County PlanningAmador5/21/20145/14/2014Amador County Transportation CommissionButte2/24/20141/6/2014Butte County Association of GovernmentsCalaveras5/13/2014Download from Calaveras County, exact date unknown, labelled 2013Contra Costa4/4/20144/4/2014Contra Costa Assessor’s OfficeDel Norte5/13/20145/8/2014Download from Del Norte CountyEl Dorado4/4/20144/3/2014El Dorado County AssessorFresno4/4/20144/4/2014Fresno County AssessorGlenn4/4/201410/13/2013Glenn County Public WorksHumboldt6/3/20144/25/2014Humbodt County AssessorImperial8/4/20147/18/2014Imperial County AssessorKern3/26/20143/16/2014Kern County AssessorKings4/21/20144/14/2014Kings CountyLake7/15/20147/19/2013Lake CountyLassen7/24/20147/24/2014Lassen CountyLos Angeles10/22/201410/9/2014Los Angeles CountyMadera7/28/2014Madera County, Date Current unclear likely 7/2014Marin5/13/20145/1/2014Marin County AssessorMendocino4/21/20143/27/2014Mendocino CountyMerced7/15/20141/16/2014Merced CountyMono4/7/20144/7/2014Mono CountyMonterey5/13/201410/31/2013Download from Monterey CountyNapa4/22/20144/22/2014Napa CountyNevada10/29/201410/26/2014Download from Nevada CountyOrange3/18/20143/18/2014Download from Orange CountyPlacer7/2/20147/2/2014Placer CountyRiverside3/17/20141/6/2014Download from Riverside CountySacramento4/2/20143/12/2014Sacramento CountySan Benito5/12/20144/30/2014San Benito CountySan Bernardino2/12/20142/12/2014Download from San Bernardino CountySan Diego4/18/20144/18/2014San Diego CountySan Francisco5/23/20145/23/2014Download from San Francisco CountySan Joaquin10/13/20147/1/2013San Joaquin County Fiscal year close dataSan Mateo2/12/20142/12/2014San Mateo CountySanta Barbara4/22/20149/17/2013Santa Barbara CountySanta Clara9/5/20143/24/2014Santa Clara County, Required a PRA requestSanta Cruz2/13/201411/13/2014Download from Santa Cruz CountyShasta4/23/20141/6/2014Download from Shasta CountySierra7/15/20141/20/2014Sierra CountySolano4/24/2014Download from Solano Couty, Boundaries appear to be from 2013Sonoma5/19/20144/3/2014Download from Sonoma CountyStanislaus4/23/20141/22/2014Download from Stanislaus CountySutter11/5/201410/14/2014Download from Sutter CountyTehama1/16/201512/9/2014Tehama CountyTrinity12/8/20141/20/2010Download from Trinity County, Note age of data 2010Tulare7/1/20146/24/2014Tulare CountyTuolumne5/13/201410/9/2013Download from Tuolumne CountyVentura11/4/20146/18/2014Download from Ventura CountyYolo11/4/20149/10/2014Download from Yolo CountyYuba11/12/201412/17/2013Download from Yuba County