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.

The California State County Boundary data.

This dataset offers high-resolution boundary definitions, which allow users to analyze and visualize California’s county limits within mapping and spatial analysis projects.

The shapefile is part of a ZIP archive containing multiple related files that together define and support the boundary data. These files include:

.shp (Shape): This is the core file containing the vector data for California’s boundary, representing the geographic location and geometry of the state outline.

.shx (Shape Index): A companion index file for the .shp file, allowing for quick spatial queries and efficient data access.

.dbf (Attribute Table): A database file that stores attribute data linked to the geographic features in the .shp file, such as area identifiers or classification codes, in a tabular format compatible with database applications.

.prj (Projection): This file contains projection information, specifying the coordinate system and map projection used for the data, essential for aligning it accurately on maps.

.cpg (Code Page): This optional file indicates the character encoding for the attribute data in the .dbf file, which is useful for ensuring accurate text representation in various software.

.sbn and .sbx (Spatial Index): These files serve as a spatial index for the shapefile, allowing for faster processing of spatial queries, especially for larger datasets.

.xml (Metadata): A metadata file in XML format, often following FGDC or ISO standards, detailing the dataset’s origin, structure, and usage guidelines, providing essential information about data provenance and quality.

This comprehensive set of files ensures compatibility with most GIS software and allows users to perform a wide range of spatial analyses with detailed information on California’s boundary as defined by the U.S. Census Bureau's 2023 MAF/TIGER database.

Note: The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services beginning in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.

Purpose
City boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.

This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This feature layer is for public use.

Related Layers

This dataset is part of a grouping of many datasets:

1. Cities: Only the city boundaries and attributes, without any unincorporated areas
   • With Coastal Buffers
   • Without Coastal Buffers (this dataset)
2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
   • With Coastal Buffers
   • Without Coastal Buffers
3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
   • With Coastal Buffers
   • Without Coastal Buffers
4. City and County Abbreviations
5. Unincorporated Areas (Coming Soon)
6. Census Designated Places
7. Cartographic Coastline
   • Polygon
   • Line source (Coming Soon)

Point of Contact

California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

Field and Abbreviation Definitions

• CDTFA_CITY: CDTFA incorporated city name
• CDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
• CDTFA_COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.
• CENSUS_GEOID: numeric geographic identifiers from the US Census Bureau
• CENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.
• GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
• GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
• CDT_CITY_ABBR: Abbreviations of incorporated area names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 4 characters. Not present in the county-specific layers.
• CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.
• CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.
• AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
• OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
• PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or county
• CENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.
• GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

Land boundaries for Orange County, cities, and unincorporated areas (based on the five supervisorial districts). Contains additional geodemographic data on population and housing from the US Census 2021 American Community Survey (ACS).

This is SCAG’s 2019 city boundary data (v.1.0), updated as of July 6, 2021, including the boundaries for each of the 191 cities and 6 county unincorporated areas in the SCAG region. The original city boundary data was obtained from county LAFCOs to reflect the most current updates and annexations to the city boundaries. This data will be further reviewed and updated as SCAG continues to receive feedbacks from LAFCOs, subregions and local jurisdictions.Data-field description:COUNTY: County name COUNTY_ID: County FIPS CodeCITY: City NameCITY_ID: City FIPS CodeACRES: Area in acresSQMI: Area in square milesYEAR: Dataset year

This web map displays the California Department of Education's (CDE) core set of geographic data layers. This content represents the authoritative source for all statewide public school site locations and school district service areas boundaries for the 2018-19 academic year. The map also includes school and district layers enriched with student demographic and performance information from the California Department of Education's data collections. These data elements add meaningful statistical and descriptive information that can be visualized and analyzed on a map and used to advance education research or inform decision making.

The 1998 Dress Rehearsal was conducted as a prelude to the United States Census of Population and Housing, 2000, in the following locations: (1) Columbia, South Carolina, and surrounding areas, including the town of Irmo and the counties of Chester, Chesterfield, Darlington, Fairfield, Kershaw, Lancaster, Lee, Marlboro, Newberry, Richland, and Union, (2) Sacramento, California, and (3) Menominee County, Wisconsin, including the Menominee American Indian Reservation. This collection contains map files showing various levels of geography (in the form of Census Tract Outline Maps, Voting District/State Legislative District Outline Maps, and County Block Maps), TIGER/Line digital files, and Corner Point files for the Census 2000 Dress Rehearsal sites. The Corner Point data files contain the bounding latitude and longitude coordinates for each individual map sheet of the 1998 Dress Rehearsal Public Law (P.L.) 94-171 map products. These files include a sheet identifier, minimum and maximum longitude, minimum and maximum latitude, and the map scale (integer value) for each map sheet. The latitude and longitude coordinates are in decimal degrees and expressed as integer values with six implied decimal places. There is a separate Corner Point File for each of the three map types: County Block Map, Census Tract Outline Map, and Voting District/State Legislative District Outline Map. Each of the three map file types is provided in two formats: Portable Document Format (PDF), for viewing, and Hewlett-Packard Graphics Language (HP-GL) format, for plotting. The County Block Maps show the greatest detail and the most complete set of geographic information of all the maps. These large-scale maps depict the smallest geographic entities for which the Census Bureau presents data -- the census blocks -- by displaying the features that delineate them and the numbers that identify them. These maps show the boundaries, names, and codes for American Indian/Alaska Native areas, county subdivisions, places, census tracts, and, for this series, the geographic entities that the states delineated in Phase 2, Voting District Project, of the Redistricting Data Program. The HP-GL version of the County Block Maps is broken down into index maps and map sheets. The map sheets cover a small area, and the index maps are composed of multiple map sheets, showing the entire area. The intent of the County Block Map series is to provide a map for each county on the smallest possible number of map sheets at the maximum practical scale, dependent on the area size of the county and the density of the block pattern. The latter affects the display of block numbers and feature identifiers. The Census Tract Outline Maps show the boundaries and numbers of census tracts, and name the features underlying the boundaries. These maps also show the boundaries and names of counties, county subdivisions, and places. They identify census tracts in relation to governmental unit boundaries. The mapping unit is the county. These large-format maps are produced to support the P.L. 94-171 program and all other 1998 Dress Rehearsal data tabulations. The Voting District/State Legislative District Outline Maps show the boundaries and codes for voting districts as delineated by the states in Phase 2, Voting District Project, of the Redistricting Data Program. The features underlying the voting district boundaries are shown, as well as the names of these features. Additionally, for states that submit the information, these maps show the boundaries and codes for state legislative districts and their underlying features. These maps also show the boundaries of and names of American Indian/Alaska Native areas, counties, county subdivisions, and places. The scale of the district maps is optimized to keep the number of map sheets for each area to a minimum, but the scale and number of map sheets will vary by the area size of the county and the voting districts and state legislative districts delineated by the states. The Census 2000 Dress Rehearsal TIGER/Line Files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. These TIGER/Line Files are an extract of selected geographic and cartographic information from the Census TIGER (Topological

The City Official boundary extends six miles off the coast of Los Angeles County as required by the State of California official boundary for City's along the coast. The City Boundary provided here supports map cartography is the traditional view of Long Beach that highlights the Port of Long Beach and shore line. This is not the official City Limits and is commonly used to support map products for the Harbor and beach communities.

This feature service is derived from the Esri "United States Zip Code Boundaries" layer, queried to only CA data.For the original data see: https://esri.maps.arcgis.com/home/item.html?id=5f31109b46d541da86119bd4cf213848Published by the California Department of Technology Geographic Information Services Team.The GIS Team can be reached at ODSdataservices@state.ca.gov.U.S. ZIP Code Boundaries represents five-digit ZIP Code areas used by the U.S. Postal Service to deliver mail more effectively. The first digit of a five-digit ZIP Code divides the United States into 10 large groups of states (or equivalent areas) numbered from 0 in the Northeast to 9 in the far West. Within these areas, each state is divided into an average of 10 smaller geographical areas, identified by the second and third digits. These digits, in conjunction with the first digit, represent a Sectional Center Facility (SCF) or a mail processing facility area. The fourth and fifth digits identify a post office, station, branch or local delivery area.As of the time this layer was published, in January 2025, Esri's boundaries are sourced from TomTom (June 2024) and the 2023 population estimates are from Esri Demographics. Esri updates its layer annually and those changes will immediately be reflected in this layer. Note that, because this layer passes through Esri's data, if you want to know the true date of the underlying data, click through to Esri's original source data and look at their metadata for more information on updates.Cautions about using Zip Code boundary dataZip code boundaries have three characteristics you should be aware of before using them:Zip code boundaries change, in ways small and large - these are not a stable analysis unit. Data you received keyed to zip codes may have used an earlier and very different boundary for your zip codes of interest.Historically, the United States Postal Service has not published zip code boundaries, and instead, boundary datasets are compiled by third party vendors from address data. That means that the boundary data are not authoritative, and any data you have keyed to zip codes may use a different, vendor-specific method for generating boundaries from the data here.Zip codes are designed to optimize mail delivery, not social, environmental, or demographic characteristics. Analysis using zip codes is subject to create issues with the Modifiable Areal Unit Problem that will bias any results because your units of analysis aren't designed for the data being studied.As of early 2025, USPS appears to be in the process of releasing boundaries, which will at least provide an authoritative source, but because of the other factors above, we do not recommend these boundaries for many use cases. If you are using these for anything other than mailing purposes, we recommend reconsideration. We provide the boundaries as a convenience, knowing people are looking for them, in order to ensure that up-to-date boundaries are available.

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

Polygon vector map data covering boundaries for the City of Los Angeles containing 4 features.

Boundary GIS (Geographic Information System) data is spatial information that delineates the geographic boundaries of specific geographic features. This data typically includes polygons representing the outlines of these features, along with attributes such as names, codes, and other relevant information.

Boundary GIS data is used for a variety of purposes across multiple industries, including urban planning, environmental management, public health, transportation, and business analysis.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

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This map outlines the renewable sources of electrical generation in gigawatt-hours(GWh) for all counties in California for 2019. Sources below 1 megawatt (MW) were not included in this map. Counties without a symbol had no utility-scale (commercial) renewable electric generation installed. Data obtained from Quarterly Fuel and Energy Reports (QFER) and the Wind Performance Reporting System (WPRS) databases.

A map with various base layers to be used as a template for creating thematic maps for the Napa County CWPP online maps. Most layers are from Napa County's online gis data catalog but some layers were derived from public data sources such as Wikipedia and others.This map highlights WUI areas as defined by CAL FIRE in their WUI 12_3 layer. Description below:This dataset adds housing density class (DEN4) and wildfire hazard (FHSZ) attributes to WUI12_2 - FRAP’s preliminary result in an effort to capture Wildland Urban Interface (WUI) for the 2015 Assessment. The current dataset is appropriate for displaying the overall pattern of WUI development at the county level, and comparing counties in terms of development patterns. Until the dataset is refined through a field review process, it is not suited for WUI designations for individual houses or neighborhoods.

Three WUI classes are mapped: 1) Wildland Urban Interface – dense housing adjacent to vegetation that can burn in a wildfire, 2) Wildland Urban Intermix - housing development interspersed in an area dominated by wildland vegetation subject to wildfire, and 3) Wildfire Influence Zone - wildfire susceptible vegetation up to 1.5 miles from Wildland Urban Interface or Wildland Urban Intermix.

Housing Density (DEN4) 1) Less than one house per 20 acres 2) One house per 20 acres to one house per 5 acres 3) More than one house per 5 acres to 1 house per acre 4) More than 1 house per acre

Fire Hazard Severity Zone (HAZ_NUM: 1=Moderate, 2=High, 3=Very High) Source: State Resposibility Areas (fhszs06_3), Local Responsibility Areas (fhszl11_1)

This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

© MarineCadastre.gov This layer is a component of BOEMRE Layers.

This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

Currently the following layers are available from this REST location:

OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

Contains 2 datasets:

• lower and single tier municipalities
• upper tier municipalities and districts.

All roads in Grey County. Intersection-to-intersection segments are continuously updated monthly to maintain accurate addressing. Captured at various scales from 1:5000 - 1:20,000 depending on location and jurisdiction. Original source data derived from Ontario Ministry of Natural Resources and Forestry Ontario Road Network (ORN).
Field Name Alias Data Type Description

OBJECTID OBJECTID Object ID GIS Unique identifier

ROAD_NAME ROAD NAME Text Full official road name composed of individual street name components where present, including street name body, street type suffix and directional suffix.

ROAD_NAME_ABBR ROAD NAME ABBREVIATED Text Abbreviated version of road name (E.g. 10th Ave E instead of 10th Avenue East)

ALT_NAME ALTERNATE NAME Text Full alternate road name. This is typically county or provincial highways when a local municipality street name is provided as the official road name. Should be null if no alternate name exists

STREET_NAM STREET_NAM Text Street name body only, the identifying named component of a street name

STREET_TYP STREET_TYP Text Street type (non-abbreviated)

STREET_TYP_SHORT STREET TYPE SHORT Text Street type (abbreviated)

STREET_DIR STREET_DIR Text Street direction (non-abbreviated)

STREET_DIR_SHORT STREET DIRECTION SHORT Text Street direction (abbreviated)

STREET_CLA STREET_CLA Short Street class used to facilitate mapping. Values can be Highways (1), County roads (2), Municipal roads (3), Unmaintained roads (4) and Roads under construction (5)

L_F_ADD L_F_ADD Long Left - From address range

L_T_ADD L_T_ADD Long Left - To address range

R_F_ADD R_F_ADD Long Right - From address range

R_T_ADD R_T_ADD Long Right - To address range

VERIFY VERIFY Short Unchanged (0), or Changed/updated (1). Values of 1 have underwent a modification since data inception, and should have a change log description in the VERIFY_COM field

VERIFY_COM VERIFY_COM Text Logged comments to describe changes to road data during verification

DATE_ADD DATE_ADD Date Date road created in geodatabase. Initialize date was 1/1/2004

HWY_NUM HWY_NUM Text MTO Highway Number

GREYRD_NUM GREYRD_NUM Text Grey Road Number

EDITOR EDITOR Text Last user who edited data

CLOSE_DETR CLOSURE DETOURS Text Roads that are suitable or not suitable for public traffic detours, completed in NOV2013, only those not suitable for detours have been captured. One record marked partial - not Minto-Normanby townline is not passable from Sideroad 25 to Ski Road (Wellington Co.)

EDIT_DATE EDIT_DATE Date Last time data was edited

JURIS_L LEFT JURISDICTION Text Road owner and authority having jurisdiction, who issues permits for the road left segment. May be governed by MTO connecting link or boundary agreement

JURIS_R RIGHT JURISDICTION Text Road owner and authority having jurisdiction, who issues permits for the road right segment. May be governed by MTO connecting link or boundary agreement

MUNICIPAL_L LEFT MUNICIPALITY Text Lower Tier Municipality, determined by the traversal from the "L_F_ADD" to the "L_T_ADD"

MUNICIPAL_R RIGHT MUNICIPALITY Text Lower Tier Municipality, determined by the traversal from the "R_F_ADD" to the "R_T_ADD"

MUN911_L LEFT 911 MUN SHORT Text 3 character municipal name used for 911 CAD, abbreviated version of MUNICIPAL_L.

MUN911_R RIGHT 911 MUN SHORT Text 3 character municipal name used for 911 CAD, abbreviated version of MUNICIPAL_R.

PARITY_L LEFT PARITY Text The even or odd property of the address number range on the Left side of the road segment relative to the FROM address: O=Odd; E=Even; B=Both

PARITY_R RIGHT PARITY Text The even or odd property of the address number range on the Right side of the road segment relative to the FROM address: O=Odd; E=Even; B=Both

ORN_ROAD_CLASS ORN ROAD CLASS Short Road classification per ORN

PAVED_STATUS PAVED STATUS Short Paved (1), Unpaved (2)

DIR_OF_TRAFFIC_FLOW DIR OF TRAFFIC FLOW Short The direction(s) of vehicular or motor traffic flow. Both (1), Positive (2), Negative (3)

MAINT_SUMMER MAINTENANCE SUMMER Text Jurisdiction responsible for summer maintenance

MAINT_WINTER MAINTENANCE WINTER Text Jurisdiction responsible for winter maintenance

MAINT_AGREEMENT MAINTENANCE AGREEMENT Text The agreement record that outlines seasonal maintenance responsibilities (Alfresco/sharepoint url)

BOUNDARY_ROAD BOUNDARY ROAD Text Indicates if a road segment runs along a municipal or county boundary (Yes/No)

ROAD_LENGT ROAD LENGTH (m) Double Length of Road Segment in meters. Geometry of line segment calculated in GIS with UTM NAD83 Zone 17N coordinate system

LANE_COUNT LANE COUNT Short Number of Lanes

SPEED_LIMI SPEED LIMIT Short Speed limit in km/h

Shape Shape Geometry Auto generated line geometry in GIS

Shape.STLength() Shape.STLength() Double Auto generated pseudo length in GIS. Due to the web coordinate system used, this is not the true length.

To download a GeoTIFF of this dataset, go to https://wildfiretaskforce.org/regional-resource-kits-page/- Metric Name: Time Since Last Fire- Tier: 2- Data Vintage: 2022- Unit Of Measure: Years- Metric Definition and Relevance: Time Since Last Fire (TSLF), from the Fire Return Interval Departure (FRID) map, provides information (in years) to indicate the length of time since an area last burned.- Creation Method: Time Since Last Fire (TSLF), from the Fire Return Interval Departure (FRID) map, provides information (in years) to indicate the length of time since an area last burned. Specifically, the number of years elapsed between the most recent fire recorded in the fire perimeters database and the version year of the FRID map being used. To illustrate, if the version year of the FRID map is 2019, and the area in question last burned in 1995, TSLF will be 24 (2019 minus 1995).- Fire Return Interval Departure(FRID): The FRID analysis quantifies the difference between current and pre-settlement fire frequencies, allowing managers to target areas at high risk of threshold-type responses owing to altered fire regimes and interactions with other factors. The FRID methodology was developed and described by Van de Water and Safford (2011). The feature class is now produced and maintained by the U.S. Forest Service, Region 5, Information Management – Mapping and Remote Sensing (MARS) Team. Contemporary FRIs were calculated using the fire dates and footprints from California Interagency Fire Perimeters database (maintained by the California Department of Forestry and Fire Protection (CalFire-FRAP). The vegetation type stratification (i.e. to calculate the FRI for individual vegetation types) was based on the MARS Existing Vegetation (EVEG) map for California from the year 2011, with the vegetation typing (“CALVEG”) cross-walked (grouped) into 28 pre-settlement fire regime (PFR) types. For assorted reasons, portions of San Benito and San Luis Obispo Counties never received a full EVEG Baseline Mapping assessment and thus data in the FRID Central California layer has some holes in these areas. In 2009, an EVEG mapping project was started for these areas but never finalized. San Luis Obispo County, the southern part of Santa Clara County, and all of San Benito County were baseline mapped using the Hardwood Dataset as a foundation for regional dominance (vegtype). Additional data sources from the National Land Cover Database, San Luis Obispo County Farm Data, Farmland Mapping and Monitoring Program, Bureau of Reclamation, and National Hydrology Database were then used to overwrite the Hardwood data where it was relevant. Structural attributes for forested conditions came primarily from the Hardwoods Dataset for canopy values while tree size was derived from a classification of Thematic Mapper 30-meter imagery. Although incomplete as an EVEG database, these “best available data”were used by the RRK team to fill holes in FRID for the Central California RRK project. The MARS team completed a crosswalk from Regional Dominance Type 1 (vegtype) to the FRID PFR attribute and calculations for the “gap” areas were run for fire return interval departure. We have used this “patch” to address FRID needs for the near-term. The data for these areas will show vulnerabilities to analysis at larger scales until a time that these areas can be visually edited to match the level of precision seen in the adjoining Los Padres NF. Other gaps (NoData): Although areas mapped as grasslands and meadows were included in the GIS layer, FRI and departure statistics were not calculated for these types because reliable information about pre-Euro American settlement fire regimes is lacking. These values (-999) have been converted to NoData in the RRK datasets. References: Information on pre-Euromerican settlement FRIs (fire return intervals) was compiled from an exhaustive review of the fire history literature, expert opinion, and vegetation modeling (Van de Water and Safford 2011; Safford and Van de Water 2014). Contemporary FRIs were calculated using the California Interagency Fire Perimeters database (maintained by the California Department of Forestry and Fire Protection (CAL FIRE-FRAP). The vegetation type stratification was based on the US Forest Service existing vegetation map (USDA Forest Service, Mapping and Remote Sensing Team) for California from the year 2011, with the vegetation typing (“CALVEG”) grouped into 28 pre-settlement fire regime (PFR) types, as defined by Van de Water and Safford (2011). The 2011 EVEG map is used as the baseline for all subsequent FRID maps to freeze the underlying vegetation template and permit temporal comparisons without introducing vegetation type change as a confounding factor.

This map outlines the total renewable electrical generation in gigawatt-hours (GWh) for all counties in California for 2019. Sources below 1 megawatt (MW) were not included in this map. Counties without a symbol had no utility-scale (commercial) renewable electric generation installed. The table depicts the amount of renewable energy production for each energy type for every county. Data obtained from Quarterly Fuel and Energy Reports (QFER) and the Wind Performance Reporting System (WPRS) databases.

Orange County City Boundaries.

This is the zoning layer for UNINCORPORATED areas of Los Angeles County. It does not draw at all scales because there are lots of records (so basically for speed and performance), so it is scale dependent. Also, why only for UNINCORPORATED areas? Because there are 88 cities in L.A. County and they each manage their zoning and land use information separately.

For more complete information, see Title 22 (Planning and Zoning) of the Los Angeles County Code, or visit the Department of Regional Planning's website here.

PLEASE NOTE: Santa Catalina Island is not included in this dataset. It is in a separate data layer since Catalina has specific zoning categories that differ from the Countywide zoning categories found in Title 22. The Department of Regional Planning performs all land use planning functions for the UNINCORPORATED areas of Los Angeles County. Our services include long range planning, land development counseling, project/case intake and processing, environmental review and zoning enforcement for each of our County UNINCORPORATED communities.What is an UNINCORPORATED area of Los Angeles County?There are 88 incorporated cities within Los Angeles County, each with its own city council. The areas that are NOT part of these cities are considered to be UNINCORPORATED County territory. More than 65 percent of Los Angeles County is UNINCORPORATED. For the approximately 1 million people living in these areas, the Board of Supervisors and County departments provide the municipal services.LAST UPDATED: 4/9/25 for several zone changes related to the South Bay, West San Gabriel, and Westside Area Plan updates. These updates took effect on 4/10/25.NEED MORE FUNCTIONALITY? If you are looking for more layers or advanced tools and functionality, then try our suite of GIS Web Mapping Applications.