The GIS boundary for the Proposed Thompson Divide Withdrawal that will reserve the identified Federal lands and mineral interest from operation of the public land laws, mining laws, and mineral leasing, mineral materials, and geothermal leasing laws for up to 20 years to protect wildlife, recreation, ecological and scenic values, as described in Federal Register Notice 2022-22448 Vol. 87 No. 199 page 62878. Edits to the boundary have been incorporated from the US Forest Service and from the Bureau of Land Management in order to follow features that allow for legal land descriptions to be generated and eliminate the need for a new cadastral survey. All US Forest Service edits were made with direction USFS land managers from the White River National Forest and the Grand Mesa, Uncompahgre, and Gunnison National Forest. The Greater Thompson Divide withdraws 221,898.23 acres, including approximately 197,744.66 acres of National Forest System lands, approximately 15,464.99 acres of BLM-managed public lands, and approximately 8,688.58 acres of reserved Federal mineral interest, from all forms of entry, appropriation, and disposal under the public land laws; location and entry under the mining laws; and operation of the mineral leasing, mineral materials, and geothermal leasing laws, subject to valid existing rights, for a period of 20 years. The areas described, including both Federal and non-Federal lands, aggregate approximately 257,439.93 acres. Please refer to the Public Land Order (https://www.federalregister.gov:443/documents/2024/04/08/2024-07384/public-land-order-no-7939-thompson-divide-withdrawal-colorado) PLO No. 7939 for more information on the legal land description of the boundary.

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 2024. Expected changes:Metadata is missing or incomplete for some layers at this time and will be continuously improved.We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.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 and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, the coastline is used to separate coastal buffers from the land-based portions of jurisdictions. 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 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 Buffers (this dataset)Without Coastal BuffersPlace AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (Coming Soon)Cartographic 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 authoritative 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 COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCOPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering systemPlace Name: CDTFA incorporated (city) or county nameCounty: 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.Legal 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.GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information SystemPlace Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area namesCNTY Abbr: CalTrans Division of Local Assistance abbreviations of county namesArea_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".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.AccuracyCDTFA"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. COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the California State Board of Equalization"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).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 San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these items, or others, from the shoreline cuts, please reach out using the contact information above.Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions).Updates and Date of ProcessingConcurrent with CDTFA updates, approximately every two weeks, Last Processed: 12/17/2024 by Nick Santos using code path at https://github.com/CDT-ODS-DevSecOps/cdt-ods-gis-city-county/ at commit 0bf269d24464c14c9cf4f7dea876aa562984db63. It incorporates updates from CDTFA as of 12/12/2024. Future updates will include improvements to metadata and update frequency.

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.This dataset is regularly 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 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 Buffers (this dataset)Without 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)State BoundaryWith Bay CutsWithout Bay Cuts Working with Coastal Buffers The 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, gis@state.ca.gov Field 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 San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these

The original source of this data set comes from an extract out of the California Ag Permits (CAP) system in September 2020. The CAP system is used to track and inventory pesticide use permits. The information contained in the CAP database was created/edited during the pesticide use permit application process. The CAP data extract was refined and the boundaries edited to better display in a cartographic setting. The ranch map is a complex and constantly changing data set that must be viewed as a work in progress. While every effort has been made to produce data as accurately as possible, there may be, for various reasons, some missing or inaccurate boundaries and labels. In many cases the data is only as accurate as the source information and maps provided by the permittees/applicants.Due to the nature of ranches in Monterey County, there are many ranches and/or permittees working the same location. As a result, there are often multiple features stacked upon each other.DATA FIELDS:Field Name = DescriptionPermNum = Permit Number: the permittee’s ID number.Permittee = Permittee: the permittee’s name.RanchName = Ranch Name: the ranch's name.SiteID = Site ID: the ranch's site ID number.RMGISAcres = Ranch Map GIS Acres: acreage of the ranch's polygon.RanchPoly = Ranch Polygons: distinguish if the ranch is a single or multiple polygons. - single polygon (ranch is a single polygon). - multiple polygons (ranch is split into multiple polygons).

Parcels represent taxable pieces of property. A parcel is created by the San Diego County Assessor/Recorder/County Clerk (ARCC) to identify a specific portion of real property that is taxed at a certain rate for a certain owner. Tax parcels are typically the same as a legally subdivided lot but are not necessessarily so. For example, a single owner may own a legally subdivided piece of property but there may be two or more tax parcels covering that property. Legal subdivisions are shown in the LOTS layer.Parcels are keyed to the Assessor Parcel Number (APN) and the parcel polygon identifier (PARCELID).The SanGIS parcel layers are “stacked” parcels. That means that for any piece of ground there may be multiple parcels. For example, a condominium building in downtown San Diego may have 200 individual condos. Each condo is a separate taxable parcel. All 200 parcels will be associated with the same physical lot on the ground. When the SanGIS parcel layer is created each individual condo has a polygon representing the physical location of the parent parcel. In this example there will be 200 polygons all stacked on top of each other that represent the taxable parcels and each polygon will have the same physical characteristics (shape, size, area, location) – they are, essentially, copies of each other. However, other associated information (owner, document numbers, etc) will be different for each. In this case, each condo unit will have its own parcel number and there will be no single parcel representing the lot on the ground. Besides condominiums there are two other cases where you will see stacked parcels – possessory interest and mobile homes. Possessory interests have Assessor Parcel Numbers (APNs) that start with 76x. A possessory interest (or PI) parcel represents a taxable interest in the underlying, or parent, parcel but not necessarily ownership. For instance, a private company may have an arrangement with a University to operate a business on campus – a coffee shop or gift shop for example. The private business is taxable and is assinged a 76x APN and that APN is associated with the parent parcel which is owned by the University. Possessory intestests do not represent ownership on the parcel, only a taxable interest in the underlying parent parcel.Mobile home parcel APNs start with 77x. In a manner similar to the possessory interests, mobile home owners own their home (coach) but not the underlying property on which the house sits. The actual mobile home is a separate taxable parcel associated with the mobile home park parent parcel. These taxable parcels all have the same polygon as the underlying parent parcel and will show as stacked parcels as well.This dataset contains parcels as shown on the Assessor Parcel Maps (APM). However, parcels shown in this layer may lag that of the official APM by a number of weeks due to how SanGIS is notified of the newly created parcel and the timing of publication of the parcel layer.This dataset contains the parcel polygon and associated parcel information provided by the County ARCC in thier Master Property Record (MPR file) and Parcel Assessment Record (PAR file). In addition to the MPR and PAR data assigned by ARCC, SanGIS may add situs address information if it has been provided by the addressing authority in which the parcel is situated. The situs address information provided by SanGIS may not be the same as the SITUS address data in the MPR.This dataset contains site address information along with owner names and addresses, and other property information. Key fields in this dataset include:Land use information provided in the NUCLEUS_USE_CD field (225 types with a 3-digit domain). The ASR_LANDUSE field is an older version of this field but comprises more generalized land uses (91 types). Generalized land use zoning information is provided in the NUCLEUS_ZONE_CD field. The ASR_ZONE field is an older version of this field. Land use zoning is generalized comprising 9 zone types. This can provide a useful approximation for parcels that are outside of the San Diego City and County zoning jurisdictions.Please note that land use and zoning fields are not regularly maintained by the Assessor's Office and should only be used as an approximate guide. Updates are only made when there is new construction, or a change in ownership. They are not updated when the County and Local Cities update their zoning data or when permit changes to properties are completed. Please refer to city and County official zoning datasets for official zoning information, and to SANDAG for more current land use data. NOTE: If the name of this layer includes "_NORTH", "_SOUTH", or "_EAST" it represents a subset of the entire San Diego County Parcel Base. That is, the "_NORTH" layer includes only parcels generally in the Northwestern portion of the County. The "_SOUTH" layer includes parcels in the Southwestern portion. And the "_EAST" layer includes parcels in the approximate Eastern half of the County.

Road edges are defined as the edge of the improved surface including the improved shoulder but do not include the unimproved shoulder, only the travel part of the road. The road network is compiled to include all open intersections. Features do not overlap sidewalks, but have the sidewalk area cut out of the road polygons. Overlapping features are acceptable if one of the features is hidden. Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line, and map sheet edge. Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions. Unpaved Median Island: Perimeter of non-traffic grassy, unpaved areas that separate traffic lanes in opposing directions. Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks. Unpaved Traffic Island: Perimeter of non-traffic unpaved, grassy areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks. Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons. Paved Drive: A paved driveway for a building or entranceway for a parking lot. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capitol, etc. If a driveway is less than 200 feet and leads to a parking lot, the entire paved area is captured as Parking Lot. Driveways are photogrammetrically compiled as polygons and not compiled from individual vectors on different levels. Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area is captured as Parking Lot. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Small parking areas, where individuals park their cars in the middle of a block off a public alley, are not captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur. Intersection: A location where more than one road comes together. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections can have more closure lines. Entire traffic circles are coded as intersections. Hidden Road: A section of a road that passes underneath a bridge or overpass and is not visible in an aerial photograph, but the location can be interpreted based on the road on either side of the bridge. Hidden Median: A road median that exists underneath a bridge or overpass and is not fully visible in an aerial photograph, but the location can be interpreted based on the information visible on either side of the bridge.

[Metadata] Underground Injection Control Line - POLYGONS (UIC Polys). NOTE: If you need to determine whether your parcel/project is above or below the UIC line, please contact the DOH Safe Drinking Water Branch (SDWB) at (808) 586-4258. This layer should be used ONLY as a low resolution/rough cut approximation of where the UIC lines are located. May, 2023 - Data is still current, per DOH SDWB. Upon request by the State DOH SDWB, the GIS Program made several modifications to this layer. 1. Changed the UIC_Code attributes from a numeric code field to a text field in order to add clarity to the meaning of the attribute values (whether the area was above or below the UIC line). 2. Created a uic_line layer from the uic_poly layer to reduce confusion when using the layer to depict and refer to the UIC "LINE" and to enable more straightforward symbolization of the layer. The uic_poly layer is being kept in place to allow for easier analysis. For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/uic_poly.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Polygon layer representing United States counties with name attributes.About Natural EarthNatural Earth is a convenient resource for creating custom maps. Unlike other map data intended for analysis or detailed government mapping, it is designed to meet the needs of cartographers and designers to make generalized maps. Maximum flexibility is a goal.Natural Earth is a public domain collection of map datasets available at 1:10 million (larger scale/more detailed), 1:50 million (medium scale/moderate detail), and 1:110 million (small scale/coarse detail) scales. It features tightly integrated vector and raster data to create a variety of visually pleasing, well-crafted maps with cartography or GIS software. Natural Earth data is made possible by many volunteers and supported by the North American Cartographic Information Society (NACIS).Convenience – Natural Earth solves a problem: finding suitable data for making small-scale maps. In a time when the web is awash in geospatial data, cartographers are forced to waste time sifting through confusing tangles of poorly attributed data to make clean, legible maps. Because your time is valuable, Natural Earth data comes ready to use.Neatness Counts–The carefully generalized linework maintains consistent, recognizable geographic shapes at 1:10m, 1:50m, and 1:110m scales. Natural Earth was built from the ground up, so you will find that all data layers align precisely with one another. For example, where rivers and country borders are one and the same, the lines are coincident.GIS Attributes – Natural Earth, however, is more than just a collection of pretty lines. The data attributes are equally important for mapmaking. Most data contain embedded feature names, which are ranked by relative importance. Other attributes facilitate faster map production, such as width attributes assigned to river segments for creating tapers. Intelligent dataThe attributes assigned to Natural Earth vectors make for efficient mapmaking. Most lines and areas contain embedded feature names, which are ranked by relative importance. Up to eight rankings per data theme allow easy custom map “mashups” to emphasize your subject while de-emphasizing reference features. Other attributes focus on map design. For example, width attributes assigned to rivers allow you to create tapered drainages. Assigning different colors to contiguous country polygons is another task made easier thanks to data attribution.Other key featuresVector features include name attributes and bounding box extents. Know that the Rocky Mountains are larger than the Ozarks.Large polygons are split for more efficient data handling—such as bathymetric layers.Projection-friendly vectors precisely match at 180 degrees longitude. Lines contain enough data points for smooth bending in conic projections, but not so many that computer processing speed suffers.Raster data includes grayscale-shaded relief and cross-blended hypsometric tints derived from the latest NASA SRTM Plus elevation data and tailored to register with Natural Earth Vector.Optimized for use in web mapping applications, with built-in scale attributes to assist features to be shown at different zoom levels.

The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 19 of the Atlas, Cretaceous Mannville Group of the Western Canada Sedimentary Basin, Figure 6, Cadomin/Cut Bank Isopach and Lithofacies. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.

See full Data Guide here. Drainage Basin Set:

Connecticut Drainage Basins is 1:24,000-scale, polygon and line feature data that define natural drainage areas in Connecticut. These are small basin areas that average approximately 1 square mile in size and make up, in order of increasing size, the larger local, subregional, regional, and major drainage basin areas. Connecticut Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major, regional, subregional, local, impoundment, or river reach boundary (line) feature. These data include 7,076 basin area (polygon) features and 20,945 basin boundary (line) features. Basin area (polygon) attributes include major, regional, subregional, local, (full) basin number, and feature size in acres and square miles. The full basin number (BASIN_NO) uniquely identifies individual basins and is up to 13 characters in length. There are 7,031 unique basin numbers. Examples include 6000-00-1+*, 4300-00-1+L1, and 6002-00-2-R1. The first digit (column 1) designates the major basin, the first two digits (columns 1-2) designate the regional basin, the first 4 digits (columns 1-4) designate the subregional basin, and the first seven digits (columns 1-7) designate the local basin. Note, there are slightly more basin polygon features (7,076) than unique basin numbers (7,031) primarily because a few water supply watershed boundaries split a basin into two polygon features at the location of a small dam or point of diversion along a stream. Basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to major, regional, subregional, local, stream reach, and lake impoundment drainage basin divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Drainage Basins is the data source for other digital spatial data including the Connecticut Major Drainage Basins, Connecticut Regional Drainage Basins, Connecticut Subregional Drainage Basins, and Connectcut Local Drainage Basins. Purpose: The polygon features define the contributing drainage area for individual reservoirs, lakes, ponds and river and stream reaches in Connecticut. These are hydrologic land units where precipitation is collected. Rain falling in a basin may take two courses. It may both run over the land and quickly enter surface watercourses, or it may soak into the ground moving through the earth until it surfaces at a wetland or stream. In an undisturbed natural drainage basin, the surface and ground water arrive as precipitation and leave either by evaporation or as surface runoff at the basin's outlet. A basin is a self-contained hydrologic system, with a clearly defined water budget and cycle. The amount of water that flows into the basins equals the amount that leaves. A drainage divide is the topographic barrier along a ridge or line of hilltops separating adjacent drainage basins. For example, rain or snow melt draining down one side of a hill generally will flow into a different basin and stream than water draining down the other side of the hill. These hillsides are separated by a drainage divided that follows nearby hilltops and ridge lines. Use these basin data to identify where rainfall flows over land and downstream to a particular watercourse. Use these data to categorize and tabulate information according to drainage basin by identifying the basin number for individual reservoir, lake, pond, stream reach, or location of interest. Due to the hierarchical nature of the basin numbering system, a database that records the 13-digit basin number for individual geographic locations of interest will support tabulations by major, regional, subregional or local basin as well as document the unique 13-digit basin number. To identify either all upstream basins draining to a particular location or all downstream basins flowing from a particular location, refer to the Gazetteer of Drainage Basin Areas of Connecticut, Nosal, 1977, CT DEP Water Resources Bulletin 45, for the hydrologic sequence, headwater to outfall, of drainage basins available at http://cteco.uconn.edu/docs/wrb/wrb45_gazetteer_of_drainage_areas_of_connecticut.pdf Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.). Not intended for analysis with other digital data compiled at scales greater than or more detailed than 1:24,000 scale. Use these data with 1:24,000-scale hydrography data also available from the State of Connecticut, Department of Environmental Protection.

onnecticut Drainage Basins is 1:24,000-scale, polygon and line feature data that define natural drainage areas in Connecticut. These are small basin areas that average approximately 1 square mile in size and make up, in order of increasing size, the larger local, subregional, regional, and major drainage basin areas. Connecticut Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major, regional, subregional, local, impoundment, or river reach boundary (line) feature. These data include 7,076 basin area (polygon) features and 20,945 basin boundary (line) features. Basin area (polygon) attributes include major, regional, subregional, local, (full) basin number, and feature size in acres and square miles. The full basin number (BASIN_NO) uniquely identifies individual basins and is up to 13 characters in length. There are 7,031 unique basin numbers. Examples include 6000-00-1+*, 4300-00-1+L1, and 6002-00-2-R1. The first digit (column 1) designates the major basin, the first two digits (columns 1-2) designate the regional basin, the first 4 digits (columns 1-4) designate the subregional basin, and the first seven digits (columns 1-7) designate the local basin. Note, there are slightly more basin polygon features (7,076) than unique basin numbers (7,031) primarily because a few water supply watershed boundaries split a basin into two polygon features at the location of a small dam or point of diversion along a stream. Basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to major, regional, subregional, local, stream reach, and lake impoundment drainage basin divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Drainage Basins is the data source for other digital spatial data including the Connecticut Major Drainage Basins, Connecticut Regional Drainage Basins, Connecticut Subregional Drainage Basins, and Connectcut Local Drainage Basins.

MECH_POLY: This dataset represents completed mechanical treatments on BLM managed lands in the states of Oregon and Washington. Mechanical treatments are 1.) machine and manual methods of area treatment; 2.) pulling, piling, chopping, grinding, or mowing treatments to consolidate, reduce or clear live or dead vegetation (might be grass, brush, small trees, stump removal), as well as "Cut-Leave" of trees, and soil preparation such as plowing or ripping.

The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 19 of the Atlas, Cretaceous Mannville Group of the Western Canada Sedimentary Basin, Figure 6, Cadomin/Cut Bank Isopach and Lithofacies. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.

This hosted feature layer has been published in RI State Plane Feet NAD 83This dataset is a modified version of the source data that are produced and distributed by the U.S. Census Bureau. ZCTA's associated with Rhode Island were selected from the source national-scale dataset and clipped to the Rhode Island coastline for cartographic purposes.

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.

ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data from Census 2000. The Census Bureau creates ZCTAs for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands for the 2010 Census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. For the 2010 Census, ZCTAs should more accurately represent the actual ZIP Codes at the time of their delineation than they did for Census 2000. This is because that before the tabulation blocks, which the ZCTAs are built from, were delineated for the 2010 Census, the Census Bureau undertook the process of inserting lines that could be used as 2010 Census tabulation block boundaries, and these lines split polygons where the result would be that a significant number of addresses would occur on either one or both sides of the line associated with a single ZIP Code.

Each 2010 Census tabulation block that contains addresses is assigned to a single ZCTA, usually to the ZCTA that reflects the most frequently occurring ZIP Code for the addresses within that tabulation block. As a result, ZIP Codes associated with address ranges found in the Address Ranges relationship file may not always match the ZCTA. Blocks that do not contain addresses but are completely surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. A ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks were it exists. The Census Bureau uses the addresses stored within MTDB to delineate ZCTAs, and at the time of the 2010 Census the MTDB primarily included addresses for residential or at least potentially residential structures, so ZCTAs representing only non-residential structures are infrequent. Also, in each tabulation block, if a choice existed between using a potential city-style mail delivery ZIP Code for an address or a post office box ZIP Code, the city-style mail delivery ZIP Code was preferred for the 2010 Census ZCTA delineation. The Census Bureau identifies 5-digit ZCTAs using a five-character numeric code that represents the most frequently occurring USPS ZIP Code within that ZCTA, and this code may contain leading zeros.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2017 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP17: 2017 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2017) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP17CSA: 2010 census tract with 2017 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP17_AGE_0_4: 2017 population 0 to 4 years oldPOP17_AGE_5_9: 2017 population 5 to 9 years old POP17_AGE_10_14: 2017 population 10 to 14 years old POP17_AGE_15_17: 2017 population 15 to 17 years old POP17_AGE_18_19: 2017 population 18 to 19 years old POP17_AGE_20_44: 2017 population 20 to 24 years old POP17_AGE_25_29: 2017 population 25 to 29 years old POP17_AGE_30_34: 2017 population 30 to 34 years old POP17_AGE_35_44: 2017 population 35 to 44 years old POP17_AGE_45_54: 2017 population 45 to 54 years old POP17_AGE_55_64: 2017 population 55 to 64 years old POP17_AGE_65_74: 2017 population 65 to 74 years old POP17_AGE_75_84: 2017 population 75 to 84 years old POP17_AGE_85_100: 2017 population 85 years and older POP17_WHITE: 2017 Non-Hispanic White POP17_BLACK: 2017 Non-Hispanic African AmericanPOP17_AIAN: 2017 Non-Hispanic American Indian or Alaska NativePOP17_ASIAN: 2017 Non-Hispanic Asian POP17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific IslanderPOP17_HISPANIC: 2017 HispanicPOP17_MALE: 2017 Male POP17_FEMALE: 2017 Female POV17_WHITE: 2017 Non-Hispanic White below 100% Federal Poverty Level POV17_BLACK: 2017 Non-Hispanic African American below 100% Federal Poverty Level POV17_AIAN: 2017 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV17_ASIAN: 2017 Non-Hispanic Asian below 100% Federal Poverty Level POV17_HNPI: 2017 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV17_HISPANIC: 2017 Hispanic below 100% Federal Poverty Level POV17_TOTAL: 2017 Total population below 100% Federal Poverty Level POP17_TOTAL: 2017 Total PopulationAREA_SQMIL: Area in square milePOP17_DENSITY: Population per square mile.POV17_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2017. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The TOP 2015 imagery was mosaiced and manipulated using image processing and segmentation techniques (e.g. unsupervised image classification, normalized difference vegetation index, etc.) to highlight any subtle vegetation signature differences. All of the preliminary results were evaluated for usefulness and the best examples were first converted to digital lines and polygons, were next combined with other relevant AMIS GIS layers (such as the roads network), and the results were used as the base layer for the new AMIS vegetation mapping effort. Building off the base layer, all relevant lines and polygons were exported as shapefiles and converted to ArcGIS coverages. The resulting coverages were run through a series of smoothing routines provided in the ArcGIS software. Following the smoothing, all digital line-work was manipulated to remove extraneous lines, eliminate small polygons, and merged polygons that split obvious stands of homogeneous vegetation. The cleaning stage was considered complete when all resulting polygons matched homogenous stands of vegetation apparent on the TOP 2015 imagery. At this point, the mapping shifted to manual techniques and all vegetation lines and polygons were visually inspected and manually moved, edited and/or updated as needed.

Contains the 1984 General Land Use Map (GLUM), which identifies high-level, general land uses across the Region of Peel in polygon format along with associated land use attributes. The GLUM assigns a broad category to all lands within the Region, thereby identifying trends and patterns in land uses.Updated in July 2014 with polygons split by current municipality boundaries and with topology checked and fixed. Field names were also changed to align with more recent names, although the classification scheme was not.Landsat 5 multispectral (true colour) imagery was used for the update of the dataset. The imagery has a spectral resolution of 30 metres. The acquisition date was 1994-10-15.

This vector polygon dataset represents the building features in Yosemite National Park. This dataset utilizes the updated NPS Building Spatial Data Standard dated 12/15/20217. There are ongoing efforts to improve the spatial and attribute information of the buildings.Initial polygons were digitized from various sources with unknown provenance, likely satellite imagery or CAD files. Many existing building polygons were added or updated from 3D building footprints covering the 2019 Yosemite National Park 3DEP Lidar project area. New buildings are COGOed where possible, otherwise digitized from satellite imagery or extracted from DWG files on an as-needed basis. In 2025 a volunteer georeferenced old maps of the park and digitized some buildings that have been removed since the time of the maps' making. Information about how each building polygon was created is in the Map Method, Map Source, and Source Date fields.Polygons are meant to represent the building footprint, though there are still buildings represented with roof outlines, particularly private residences and others digitized from satellite imagery. Buildings with more than one FMSS Locations are split to delineate the multiple assets, even though the footprint is connected. When two or more footprints share a roof they are represented with multi-part polygons that represent the foundations of the buildings.Attributes in this dataset include identifier fields (building name and label fields, FMSS Location ID, and various other ID fields), the current state of the structure (Status and Is Extant fields), classification (Functional and Facility Use fields as well as Seasonality, Building Code, and Building Type), as well as record level metadata fields. Efforts by various staff members over the years have standardized and corrected many of these fields for most of the buildings, but inaccuracies remain.This dataset is meant for both public and internal use, with sharing status described in the Public Map Display and Data Access fields. Non-extant buildings are marked as No Public Map Display but remain a part of the dataset to provide insight into what the park used to look like.IRMA Data Store Reference

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2022 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP22: 2022 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2022) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP22CSA: 2020 census tract with 2022 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP22_AGE_0_4: 2022 population 0 to 4 years oldPOP22_AGE_5_9: 2022 population 5 to 9 years old POP22_AGE_10_14: 2022 population 10 to 14 years old POP22_AGE_15_17: 2022 population 15 to 17 years old POP22_AGE_18_19: 2022 population 18 to 19 years old POP22_AGE_20_44: 2022 population 20 to 24 years old POP22_AGE_25_29: 2022 population 25 to 29 years old POP22_AGE_30_34: 2022 population 30 to 34 years old POP22_AGE_35_44: 2022 population 35 to 44 years old POP22_AGE_45_54: 2022 population 45 to 54 years old POP22_AGE_55_64: 2022 population 55 to 64 years old POP22_AGE_65_74: 2022 population 65 to 74 years old POP22_AGE_75_84: 2022 population 75 to 84 years old POP22_AGE_85_100: 2022 population 85 years and older POP22_WHITE: 2022 Non-Hispanic White POP22_BLACK: 2022 Non-Hispanic African AmericanPOP22_AIAN: 2022 Non-Hispanic American Indian or Alaska NativePOP22_ASIAN: 2022 Non-Hispanic Asian POP22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific IslanderPOP22_HISPANIC: 2022 HispanicPOP22_MALE: 2022 Male POP22_FEMALE: 2022 Female POV22_WHITE: 2022 Non-Hispanic White below 100% Federal Poverty Level POV22_BLACK: 2022 Non-Hispanic African American below 100% Federal Poverty Level POV22_AIAN: 2022 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV22_ASIAN: 2022 Non-Hispanic Asian below 100% Federal Poverty Level POV22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV22_HISPANIC: 2022 Hispanic below 100% Federal Poverty Level POV22_TOTAL: 2022 Total population below 100% Federal Poverty Level POP22_TOTAL: 2022 Total PopulationAREA_SQMil: Area in square mile.POP22_DENSITY: Population per square mile.POV22_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2022. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2014 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP14: 2014 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2014) CT10FIP14: 2010 census tract with 2014 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP14_AGE_0_4: 2014 population 0 to 4 years oldPOP14_AGE_5_9: 2014 population 5 to 9 years old POP14_AGE_10_14: 2014 population 10 to 14 years old POP14_AGE_15_17: 2014 population 15 to 17 years old POP14_AGE_18_19: 2014 population 18 to 19 years old POP14_AGE_20_44: 2014 population 20 to 24 years old POP14_AGE_25_29: 2014 population 25 to 29 years old POP14_AGE_30_34: 2014 population 30 to 34 years old POP14_AGE_35_44: 2014 population 35 to 44 years old POP14_AGE_45_54: 2014 population 45 to 54 years old POP14_AGE_55_64: 2014 population 55 to 64 years old POP14_AGE_65_74: 2014 population 65 to 74 years old POP14_AGE_75_84: 2014 population 75 to 84 years old POP14_AGE_85_100: 2014 population 85 years and older POP14_WHITE: 2014 Non-Hispanic White POP14_BLACK: 2014 Non-Hispanic African AmericanPOP14_AIAN: 2014 Non-Hispanic American Indian or Alaska NativePOP14_ASIAN: 2014 Non-Hispanic Asian POP14_HNPI: 2014 Non-Hispanic Hawaiian Native or Pacific IslanderPOP14_HISPANIC: 2014 HispanicPOP14_MALE: 2014 Male POP14_FEMALE: 2014 Female POV14_WHITE: 2014 Non-Hispanic White below 100% Federal Poverty Level POV14_BLACK: 2014 Non-Hispanic African American below 100% Federal Poverty Level POV14_AIAN: 2014 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV14_ASIAN: 2014 Non-Hispanic Asian below 100% Federal Poverty Level POV14_HNPI: 2014 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV14_HISPANIC: 2014 Hispanic below 100% Federal Poverty Level POV14_TOTAL: 2014 Total population below 100% Federal Poverty Level POP14_TOTAL: 2014 Total PopulationAREA_SQMIL: Area in square milePOP14_DENSITY: Population per square mile.POV14_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2014. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Connecticut Major Drainage Basins is 1:24,000-scale, polygon and line feature data that define Major drainage basin areas in Connecticut. These large basins mostly range from 70 to 2,000 square miles in size. Connecticut Major Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major basin boundary (line) feature. These data include 10 major basin area (polygon) features and 284 major basin boundary (line) features. Major Basin area (polygon) attributes include major basin number and feature size in acres and square miles. The major basin number (MBAS_NO) uniquely identifies individual basins and is 1 character in length. There are 8 unique major basin numbers. Examples include 1, 4, and 6. Note there are more major basin polygon features (10) than unique major basin numbers (8) because two polygon features are necessary to represent both the entire South East Coast and Hudson Major basins in Connecticut. Major basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to different levels of drainage divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Major Drainage Basin polygon and line feature data are derived from the geometry and attributes of the Connecticut Drainage Basins data.

Connecticut Major Drainage Basins is 1:24,000-scale, polygon and line feature data that define Major drainage basin areas in Connecticut. These large basins mostly range from 70 to 2,000 square miles in size. Connecticut Major Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major basin boundary (line) feature. These data include 10 major basin area (polygon) features and 284 major basin boundary (line) features. Major Basin area (polygon) attributes include major basin number and feature size in acres and square miles. The major basin number (MBAS_NO) uniquely identifies individual basins and is 1 character in length. There are 8 unique major basin numbers. Examples include 1, 4, and 6. Note there are more major basin polygon features (10) than unique major basin numbers (8) because two polygon features are necessary to represent both the entire South East Coast and Hudson Major basins in Connecticut. Major basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to different levels of drainage divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Major Drainage Basin polygon and line feature data are derived from the geometry and attributes of the Connecticut Drainage Basins data.