This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

Assessor parcels within the City of Elk Grove.

The 1993 Sacramento County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures before finalizing. The land uses that were gathered were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The data was gathered and digitized by staff of DWR’s Central District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and Central District. Important Points about Using this Data Set: 1. The land use boundaries were hand drawn directly on USGS quad maps and then digitized. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. 2. This survey was a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and, to an extent possible, whatever additional information the aerial photography might provide. For example, the surveyor might have seen a cropped field in the photograph, and the field visit showed a field of corn, so the field was given a corn attribute. In another field, the photograph might have shown a crop that was golden in color (indicating grain prior to harvest), and the field visit showed newly planted corn. This field would be given an attribute showing a double crop, grain followed by corn. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. If the data is to be brought into a GIS for analysis of cropped (or planted) acreage, two things must be understood: a. The acreage of each field delineated is the gross area of the field. The amount of actual planted and irrigated acreage will always be less than the gross acreage, because of ditches, farm roads, other roads, farmsteads, etc. Thus, a delineated corn field may have a GIS calculated acreage of 40 acres but will have a smaller cropped (or net) acreage, maybe 38 acres. b. Double and multicropping must be taken into account. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. To estimate actual cropped acres, the two crops are added together (38 acres of grain and 38 acres of corn) which results in a total of 76 acres of net crop (or planted) acres. 4. Not all land use codes will be represented the survey.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.3, dated April 13, 2022. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. See the CADWR Land User Viewer (gis.water.ca.gov/app/CADWRLandUseViewer) for the most current contact information. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

The Department of Transportation establishes speed limits for every section of roadway based on certain criteria.DOT Speed Limit Information

This shapefile contains tax rate area (TRA) boundaries in Sacramento County for the specified assessment roll year. Boundary alignment is based on the 2021 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

Process servers deliver legal documents to individuals involved in a court proceeding. In California, a process server is defined as any person who makes more than 10 services of process within this state during one calendar year, for specific compensation or in expectation of specific compensation; or any corporation or partnership that derives or expects to derive compensation from service of process within this state. Laws concerning process servers are set forth in California Business and Professions Code (BPC 22350-22360).County Clerk Recorder: Process Servers -- This data was last updated on Jan 07, 2025 at 02:07 PM.

Land-Use Data Quality ControlEvery published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2015 Sacramento County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data were gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of Kim Rosmaier. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Sacramento County conducted by the California Department of Water Resources, North Central Regional Office staff. Land use field boundaries were digitized with ArcGIS 10.3 using 2014 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Agricultural fields were delineated by following actual field boundaries instead of using the centerlines of roads to represent the field borders. Field boundaries were reviewed and updated using 2015 Landsat 8 imagery. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, and are not meant to be used as parcel boundaries. The field work for this survey was conducted from July 2015 through August 2015. Images, land use boundaries and ESRI ArcMap software were loaded onto laptop computers that were used as the field data collection tools. Staff took these laptops into the field and virtually all agricultural fields were visited to identify the land use. Global positioning System (GPS) units connected to the laptops were used to confirm the surveyor's location with respect to the fields. Land use codes were digitized in the field using dropdown selections from defined domains. Agricultural fields the staff were unable to access were designated 'E' in the Class field for Entry Denied in accordance with the 2009 Landuse Legend. Upon completion of the survey, a Python script was used to convert the data table into the standard land use format. ArcGIS geoprocessing tools and topology rules were used to locate errors for quality control. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed. Rural residential land use was delineated by drawing polygons to surround houses and other buildings along with some of the surrounding land. These footprint areas do not represent the entire footprint of urban land. Sources of irrigation water were identified for general areas and occasionally supplemented by information obtained from landowners. Water source information was not collected for each field in the survey, so the water source listed for a specific agricultural field may not be accurate. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

When the districts running on a particular election ballot are identical for 2-6 adjacent regular precincts, California Election Code 12241 allows for those precincts to be consolidated. In Sacramento County it is policy that the consolidated precinct will bear the lowest precinct number of the original regular precincts. Through the 2016 elections, consolidated precincts with 250 or more registered voters were assigned a polling place and designated "Polling Place" precincts. Consolidated precincts with less than 250 registered voters were designated "Mail Ballot" precincts. For every Polling Place Precinct there also existed a coextensive "Vote by Mail" precinct for the registered voters of that precinct who voted by mail. Since the 2018 elections, there is no longer a distinction between "Polling Place" precincts and "Mail Ballot" precincts. All Consolidated Precincts also have a corresponding and coextensive "Vote by Mail" precinct. Because the combination of contests on ballot is unique to a particular election, the set of consolidated precincts is unique to that particular election.Sacramento County Voter Registration and Elections

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.PurposeCity 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 LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal Buffers (this dataset)Counties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities 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 includes 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_CITY: CDTFA incorporated city nameCDTFA_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_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 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

Superseded

https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-for-modeling-version-4-1## A more recent version of this product appears here:

This product will continue to be distributed for archival purposes.

Domain and Product

Changes in the current bathymetry release (version 4) are limited to the region east of the Carquinez Strait (starting around Carquinez Bridge). To facilitate compatibility released by us and our partners, DWR distribute the region west as a separate companion tile and delineate the boundary of active revision in the present product in a place where its source data matches that of other Bay elevation models, e.g., the 2m seamless high-resolution bathymetric and topographic DEM of San Francisco Bay by USGS Earth Resources Observation and Science Center (EROS) (https://topotools.cr.usgs.gov/coned/sanfrancisco.php ), the 2010 San Francisco Bay DEM by National Oceanic and Atmospheric Administration (https://www.ngdc.noaa.gov/metaview/page?xml=NOAA/NESDIS/NGDC/MGG/DEM/iso/xml/741.xml&view=getDataView&header=none ) or the prior (version 3) 10m digital elevation model (https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-v3 ).The 10m DEM for the Bay-Delta is based on the first on the list, i.e. EROS’ 2m DEM for the Bay

New work reported here was done at 2m resolution, although the improvements have been incorporated into the 10m products as much as possible. Relative to the previous DWR release (https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-v3), the 2m DEM product reported here consolidates work at this resolution into a small number of larger surfaces representing approximately one-third of the Delta (link to the Coverage Areas page). Laterally, the 2m models now extend over the levee crest as needed to match well with Delta LiDAR (http://www.atlas.ca.gov/download.html#/casil/imageryBaseMapsLandCover/lidar2009 ), the main terrestrial source of data used in this work. The 10m product (link to the Coverage Areas page) is based on the updated USGS DEM (https://www.sciencebase.gov/catalog/item/58599681e4b01224f329b484 ). In places where updated 2m models overlap the 10 meters, the 10m base elevation model was updated by resampling the new 2m model and adding levee enforcement. At the border between the 2m and 10m models, the two resolutions were locally edge-matched over a small region to maintain smoothness. For more information, please refer to the article: A Revised Continuous Surface Elevation Model for Modeling (link to Chapter 5 in the 2018 Annual Report).

Please note that by agreement with our data providers we distribute only our own integrated maps, not the original source point data.

Data Sources

https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-for-modeling-version-4/resource/981a57b5-e16f-4632-b7e0-4a533534a79c

Coverage Areas

https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-for-modeling-version-4/resource/2e3f2b6e-9f0d-4719-b32a-dff449be18af

The 2000 Sacramento County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures before finalizing. The land uses that were gathered were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The data was gathered and digitized by staff of DWR’s Central District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and Central District. Important Points about Using this Data Set: 1. The land use boundaries were drawn on-screen using developed photoquads. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. 2. This survey was a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and, to an extent possible, whatever additional information the aerial photography might provide. For example, the surveyor might have seen a cropped field in the photograph, and the field visit showed a field of corn, so the field was given a corn attribute. In another field, the photograph might have shown a crop that was golden in color (indicating grain prior to harvest), and the field visit showed newly planted corn. This field would be given an attribute showing a double crop, grain followed by corn. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. If the data is to be brought into a GIS for analysis of cropped (or planted) acreage, two things must be understood: a. The acreage of each field delineated is the gross area of the field. The amount of actual planted and irrigated acreage will always be less than the gross acreage, because of ditches, farm roads, other roads, farmsteads, etc. Thus, a delineated corn field may have a GIS calculated acreage of 40 acres but will have a smaller cropped (or net) acreage, maybe 38 acres. b. Double and multicropping must be taken into account. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. To estimate actual cropped acres, the two crops are added together (38 acres of grain and 38 acres of corn) which results in a total of 76 acres of net crop (or planted) acres. 4. Not all land use codes will be represented in the survey.

Sierra Nevada Conservancy (SNC) boundary. The boundary was mapped to correspond with statute AB 2600 (2004) and as re-defined in SB 208 (2022). Work on the boundary was completed by CalFire, GreenInfo Network, and the California Department of Fish and Game. Meets and bounds description of the area as defined in statute: PRC Section 33302 (f) defines the Sierra Nevada Region as the area lying within the Counties of Alpine, Amador, Butte, Calaveras, El Dorado, Fresno, Inyo, Kern, Lassen, Madera, Mariposa, Modoc, Mono, Nevada, Placer, Plumas, Shasta, Sierra, Siskiyou, Tehama, Trinity, Tulare, Tuolumne, and Yuba, described as the area bounded as follows: On the east by the eastern boundary of the State of California; the crest of the White/Inyo ranges; and State Routes 395 and 14 south of Olancha; on the south by State Route 58, Tehachapi Creek, and Caliente Creek; on the west by the line of 1,250 feet above sea level from Caliente Creek to the Kern/Tulare County line; the lower level of the western slope’s blue oak woodland, from the Kern/Tulare County line to the Sacramento River near the mouth of Seven-Mile Creek north of Red Bluff; the Sacramento River from Seven-Mile Creek north to Cow Creek below Redding; Cow Creek, Little Cow Creek, Dry Creek, and up to the southern boundary of the Pit River watershed where Bear Creek Mountain Road and Dry Creek Road intersect; the southern boundary of the Pit River watershed; the western boundary of the upper Trinity watershed in the County of Trinity; on the north by the boundary of the upper Trinity watershed in the County of Trinity and the upper Sacramento, McCloud, and Pit River watersheds in the County of Siskiyou; and within the County of Modoc, the easterly boundary of the Klamath River watershed; and on the north in the County of Modoc by the northern boundary of the State of California; excluding both of the following: (1) The Lake Tahoe Region, as described in Section 6605.5 of the Government Code, where it is defined as "region" (2) The San Joaquin River Parkway, as described in Section 32510.

According to GreenInfo Network and the California Department of Fish and Game, the blue oak woodland used to define a portion of the Sierra Nevada Conservancy's western boundary was delineated using referenced vegetation and imagery data.

Census 2010 Tract Data with DemographicsCensus Tracts are the second level of Census Block aggregation. They can also be aggregated from Block Groups. Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. They are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. All 2010 Census blocks nest within every other 2010 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas.

These files are clipped from the Census Bureau's TIGER/Line files for the state, available for download on their site.

SACOG Region : El Dorado, Placer, Sacramento, Sutter, Yolo, and Yuba Counties in California

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.