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.

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.

This feature service includes change areas for city boundaries and county line adjustments filed in accordance with Government Code 54900. The boundaries in this map are based on the State Board of Equalization's tax rate area maps for the assessment roll year specified in the COFILE field. The information is updated regularly within 10 business days of the most recent BOE acknowledgement date. Some differences may occur between actual recorded boundaries and boundary placement in the tax rate area GIS map. Tax rate area boundaries are representations of taxing jurisdictions for the purpose of determining property tax assessments and should not be used to determine precise city or county boundary line locations. BOE_CityAnx Data Dictionary: COFILE = county number - assessment roll year - file number; CHANGE = affected city, unincorporated county, or boundary correction; EFFECTIVE = date the change was effective by resolution or ordinance; RECEIVED = date the change was received at the BOE; ACKNOWLEDGED = date the BOE accepted the filing for inclusion into the tax rate area system; NOTES: additional clarifying information about the action. BOE_CityCounty Data Dictionary: COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the BOE's 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).

Counties in California intended for the NEVI Map.

This layer contains the boundaries for California’s 58 counties. County features are derived from the US Census Bureau's 2023 TIGER/Line database and have been clipped to the coastal boundary line and designed to overlay with the California Department of Education’s (CDE) educational boundary layers.

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

The geospatial data presented here as ArcGIS layers denote landcover/landuse classifications to support field sampling efforts that occurred within the Cache Creek Settling Basin (CCSB) from 2010-2019. Manual photointerpretation of a National Agriculture Imagery Program (NAIP) dataset collected in 2012 was used to characterize landcover/landuse categories (hereafter habitat classes). Initially 9 categories were assigned based on vegetation structure (Vegtype1). These were then parsed into two levels of habitat classes that were chosen for their representativeness and use for statistical analyses of field sampling. At the coarsest level (Landcover 1), five habitat classes were assigned: Agriculture, Riparian, Floodplain, Open Water, and Road. At the more refined level (Landcover 2), ten habitat classes were nested within these five categories. Agriculture was not further refined within Landcover 2, as little consistency was expected between years as fields rotated between corn, pumpkin, tomatoes, and other row crops. Riparian habitat, marked by large canopy trees (such as Populus fremontii (cottonwood)) neighboring stream channels, also was not further refined. Floodplain habitat was separated into two categories: Mixed NonWoody (which included both Mowed and Barren habitats) and Mixed Woody. This separation of the floodplain habitat class (Landcover1) into Woody and NonWoody was performed with a 100 m2 moving window analysis in ArcGIS, where habitats were designated as either ≥50% shrub or tree cover (Woody) or <50%, and thus dominated by herbaceous vegetation cover (NonWoody). Open Water habitat was refined to consider both agricultural Canal (created) and Stream (natural) habitats. Road habitat was refined to separate Levee Roads (which included both the drivable portion and the apron on either side) and Interior roads, which were less managed. The map was tested for errors of omission and commission on the initial 9 categories during November 2014. Random points (n=100) were predetermined, and a total of 80 were selected for field verification. Type 1 (false positive) and Type 2 (false negative) errors were assessed. The survey indicated several corrections necessary in the final version of the map. 1) We noted the presence of woody species in “NonWoody” habitats, especially Baccharus salicilifolia (mulefat). Habitats were thus classified as “Woody” only with ≥50% presence of canopy species (e.g. tamarisk, black willow) 2) Riparian sites were over-characterized, and thus constrained back to “near stream channels only”. Walnut (Juglans spp) and willow stands alongside fields and irrigation canals were changed to Mixed Woody Floodplain. Fine tuning the final habitat distributions was thus based on field reconnaissance, scalar needs for classifying field data (sediment, water, bird, and fish collections), and validation of data categories using species observations from scientist field notes. Calibration was made using point data from the random survey and scientist field notes, to remove all sources of error and reach accuracy of 100%. The coverage “CCSB_Habitat_2012” is provided as an ARCGIS shapefile based on a suite of 7 interconnected ARCGIS files coded with the suffixes: cpg, dbf, sbn, sbx, shp, shx, and prj. Each file provides a component of the coverage (such as database or projection) and all files are necessary to open the “CCSB_Habitat_2012.shp” file with full functionality. CCSB_Basin_Map.png represents the CCSB study area color coded by the four primary habitat types identified in this study.

The geospatial data presented here as ArcGIS layers denote landcover/landuse classifications to support field sampling efforts that occurred within the Cache Creek Settling Basin (CCSB) from 2010-2017. Manual photointerpretation of a National Agriculture Imagery Program (NAIP) dataset collected in 2012 was used to characterize landcover/landuse categories (hereafter habitat classes). Initially 9 categories were assigned based on vegetation structure (Vegtype1). These were then parsed into two levels of habitat classes that were chosen for their representativeness and use for statistical analyses of field sampling. At the coarsest level (Landcover 1), five habitat classes were assigned: Agriculture, Riparian, Floodplain, Open Water, and Road. At the more refined level (Landcover 2), ten habitat classes were nested within these five categories. Agriculture was not further refined within Landcover 2, as little consistency was expected between years as fields rotated between corn, pumpkin, tomatoes, and other row crops. Riparian habitat, marked by large canopy trees (such as Populus fremontii (cottonwood)) neighboring stream channels, also was not further refined. Floodplain habitat was separated into two categories: Mixed NonWoody (which included both Mowed and Barren habitats) and Mixed Woody. This separation of the floodplain habitat class (Landcover1) into Woody and NonWoody was performed with a 100 m2 moving window analysis in ArcGIS, where habitats were designated as either ≥50% shrub or tree cover (Woody) or <50%, and thus dominated by herbaceous vegetation cover (NonWoody). Open Water habitat was refined to consider both agricultural Canal (created) and Stream (natural) habitats. Road habitat was refined to separate Levee Roads (which included both the drivable portion and the apron on either side) and Interior roads, which were less managed. The map was tested for errors of omission and commission on the initial 9 categories during November 2014. Random points (n=100) were predetermined, and a total of 80 were selected for field verification. Type 1 (false positive) and Type 2 (false negative) errors were assessed. The survey indicated several corrections necessary in the final version of the map. 1) We noted the presence of woody species in “NonWoody” habitats, especially Baccharus salicilifolia (mulefat). Habitats were thus classified as “Woody” only with ≥50% presence of canopy species (e.g. tamarisk, black willow) 2) Riparian sites were over-characterized, and thus constrained back to “near stream channels only”. Walnut (Juglans spp) and willow stands alongside fields and irrigation canals were changed to Mixed Woody Floodplain. Fine tuning the final habitat distributions was thus based on field reconnaissance, scalar needs for classifying field data (sediment, water, bird, and fish collections), and validation of data categories using species observations from scientist field notes. Calibration was made using point data from the random survey and scientist field notes, to remove all sources of error and reach accuracy of 100%. The coverage “CCSB_Habitat_2012” is provided as an ARCGIS shapefile based on a suite of 7 interconnected ARCGIS files coded with the suffixes: cpg, dbf, sbn, sbx, shp, shx, and prj. Each file provides a component of the coverage (such as database or projection) and all files are necessary to open the “CCSB_Habitat_2012.shp” file with full functionality.

This dataset is one of several available datasets related to California counties that were created as a group designed to work in topological sync with each other. Further details about these paired datasets can be found in their respective metadata. Further details about the full process and update notes can be found in the GDB container metadata.This specific dataset represents the full detailed county dataset with all coding / additional coastal features (islands, inlets, constructed features, etc). The user has the freedom to use this coding to create definition queries, symbolize, or dissolve to create a more generalized dataset as needed.

This website provides a limited number of Substructure Maps in “pdf” format via GIS polygons representing grids containing URL links. Across various areas of Los Angeles County, paper maps were created by Public Works (PW) and its predecessor Departments to show underground utilities such as cable TV, gas, oil, and telephone lines.

Though most of these maps are no longer updated, they can be useful as a research resource. Every reasonable effort has been made to assure the accuracy of this data and the maps referenced. Some cities may provide substructure information for the areas not covered by these grids. Additional and more accurate substructure data and information may also be obtained through the utility companies. Before digging, it is strongly advised to contact the Underground Service Alert (DigAlert Express) at www.digalert.org/digexpress.html or by calling 811.

Please note that California State Law Says, You Must Contact DigAlert!

The County of Los Angeles makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the data provided herein or of any maps referenced. Los Angeles County Public Works recommends that all utility research be conducted under the supervision of a licensed civil engineer.

WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of March 2025. 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 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.This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.PurposeCounty 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 layer removes the coastal buffer polygons. This feature layer is for public use.Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal Buffers (this dataset)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 BuffersWithout Coastal BuffersCity and County AbbreviationsUnincorporated Areas (Coming Soon)Census Designated PlacesCartographic CoastlinePolygonLine source (Coming Soon)Working with Coastal BuffersThe dataset you are currently viewing excludes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCDTFA_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 BureauCENSUS_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 SystemGNIS_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_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 countyCENSUS_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.Boundary AccuracyCounty boundaries were originally derived from a 1:24,000 accuracy dataset, with improvements made in some places to boundary alignments based on research into historical records and boundary changes as CDTFA learns of them. City boundary data are derived from pre-GIS tax maps, digitized at BOE and CDTFA, with adjustments made directly in GIS for new annexations, detachments, and corrections. Boundary accuracy within the dataset varies. While CDTFA strives to correctly include or exclude parcels from jurisdictions for accurate tax assessment, this dataset does not guarantee that a parcel is placed in the correct jurisdiction. When a parcel is in the correct jurisdiction, this dataset cannot guarantee accurate placement of boundary lines within or between parcels or rights of way. This dataset also provides no information on parcel boundaries. For exact jurisdictional or parcel boundary locations, please consult the county assessor's office and a licensed surveyor.CDTFA's data is used as the best available source because BOE and CDTFA receive information about changes in jurisdictions which otherwise need to be collected independently by an agency or company to compile into usable map boundaries. CDTFA maintains the best available statewide boundary information.CDTFA's source data notes the following about accuracy:City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties.In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose.SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon.Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and

description: FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines. These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13); abstract: FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines. These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13)

The Map Books consist of approximately 5,900 maps recorded with the county dating from circa 1850 to 1957. Recorded documents include subdivisions, surveys of property, cemetery plans, and other maps. Information on each map includes date recorded, person recorded for, and title of survey. Additional information may include notarized statement by property owner, statement by licensed surveyor, notice of approval by board of supervisors, and additional approvals by county or city officials. These maps are bound into 108 volumes. The archives have volumes A through Z, and volumes 1 through 82. Volumes not included are 44, 46, 48, 50, 51, 53, 55, 57, 59, 66, 68, 71, 73, 76, and 81.

This map is a compilation of the final set of city and county boundary changes filed with the California State Board of Equalization in accordance with Government Code 54900 for each assessment roll year beginning with the 2021 roll year. Boundary corrections are included in the dataset according to information provided by the city, county, and/or LAFCO. These corrections may or may not have been corrected in the Board of Equalization's records. Each layer is considered FINAL as of June in the year noted by the layer name. The boundaries from 2021 through 2025 are based on the California State Board of Equalization's tax rate area maps and may not align with other sources. For the latest data, please view the "City and County Boundary Line Changes" map.As of April 1, 2024, the maintenance of this map is provided by the California Department of Tax and Fee Administration (CDTFA) for sales and use tax purposes.

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:

This Digital Raster Graphic (DRG) was created using scanned U.S. Geological Survey 7.5-minute 1 to 24,000 scale maps georeferenced in Universal Transverse Mercator (UTM) grid. DRGs can be acquired with or without collar information for use in Geographic Information System (GIS) environment. Collarless DRGs can be edge matched creating a continuous collection of topographic maps.

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 San Bernardino County map viewer is a collection of maps and apps related to various administrative boundaries in San Bernardino County. All data is publicly available. The San Bernardino County map viewer contains the following maps:Parcels: Find and identify parcels by APN or address.Flood Control: Find and identify Flood Control facilities within San Bernardino CountyBoundaries: Explore various administrative boundaries in San Bernardino County, such as Supervisor districts, city limits, US Senate districts and moreHistorical Imagery: Imagery archives for the years 2008 - 2023Power Outages: Power outage data from CalOES showing power outages within San Bernardino County3D Scene: Interactively explore San Bernardino County geographic data in 3D.DIY Map Viewer: Create your own map using a variety of provided datasets, or add your ownThe San Bernardino County Map viewer was created by San Bernardino County's Information Services Department. For more information please contact the Information Services Department (ISD) Help Desk at (909)884-4884.

This feature class contains "land" (surface rights) parcel boundaries delineated for property tax assessment purposes.This feature class includes all private, tax-exempt, and state-assessed land parcels listed on the secured tax roll, but does not include mineral rights (subsurface) parcels, mobilehomes, or unsecured entities.Parcels are modeled as planimetric polygons in a seamless fabric comprising the spatial extent of the County of Kern, in the State of California.Tax Roll Data is available in separate database tables, which can be joined to the feature class using the APN field as a key.

© Kern Council of Governments. Merced County Association of Governments. City of Bakersfield, IT Division, GIS Services. City of Shafter, IT Department, GIS Division. Kern County Assessor's Office, Mapping Section.

This layer is a component of Dev Assessor mxd.