Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

Status: COMPLETED 2010. The data was converted from the most recent (2010) versions of the adopted plans, which can be found at https://cms3.tucsonaz.gov/planning/plans/ Supplemental Information: In March 2010, Pima Association of Governments (PAG), in cooperation with the City of Tucson (City), initiated the Planned Land Use Data Conversion Project. This 9-month effort involved evaluating mapped land use designations and selected spatially explicit policies for nearly 50 of the City's adopted neighborhood, area, and subregional plans and converting the information into a Geographic Information System (GIS) format. Further documentation for this file can be obtained from the City of Tucson Planning and Development Services Department or Pima Association of Governments Technical Services. A brief summary report was provided, as requested, to the City of Tucson which highlights some of the key issues found during the conversion process (e.g., lack of mapping and terminology consistency among plans). The feature class "Plan_boundaries" represents the boundaries of the adopted plans. The feature class "Plan_mapped_land_use" represents the land use designations as they are mapped in the adopted plans. Some information was gathered that is implicit based on the land use designation or zones (see field descriptions below). Since this information is not explicitly stated in the plans, it should only be viewed by City staff for general planning purposes. The feature class "Plan_selected_policies" represents the spatially explicit policies that were fairly straightforward to map. Since these policies are not represented in adopted maps, this feature class should only be viewed by City staff for general planning purposes only. 2010 - created by Jamison Brown, working as an independent contractor for Pima Association of Governments, created this file in 2010 by digitizing boundaries as depicted (i.e. for the mapped land use) or described in the plans (i.e. for the narrative policies). In most cases, this involved tracing based on parcel (paregion) or street center line (stnetall) feature classes. Snapping was used to provide line coincidence. For some map conversions, freehand sketches were drawn to mimick the freehand sketches in the adopted plan. Field descriptions for the "Plan_mapped_land_use" feature class: Plan_Name: Plan name Plan_Type: Plan type (e.g., Neighborhood Plan) Plan_Num: Plan number LU_DES: Land use designation (e.g., Low density residential) LISTED_ALLOWABLE_ZONES: Allowable zones as listed in the Plan LISTED_RAC_MIN: Minimum residences per acre (if applicable), as listed in the Plan LISTED_RAC_TARGET: Target residences per acre (if applicable), as listed in the Plan LISTED_RAC_MAX: Maximum residences per acre (if applicable), as listed in the Plan LISTED_FAR_MIN: Minimum Floor Area Ratio (if applicable), as listed in the Plan LISTED_FAR_TARGET: Target Floor Area Ratio (if applicable), as listed in the Plan LISTED_FAR_MAX: Maximum Floor Area Ratio (if applicable), as listed in the Plan BUILDING_HEIGHT_MAX Building height maximum (ft.) if determined by Plan policy IMPORTANT: A disclaimer about the data as it is unofficial. URL: Uniform Resource Locator IMPLIED_ALLOWABLE_ZONES: Implied (not listed in the Plan) allowable zones IMPLIED_RAC_MIN: Implied (not listed in the Plan) minimum residences per acre (if applicable) IMPLIED_RAC_TARGET: Implied (not listed in the Plan) target residences per acre (if applicable) IMPLIED_RAC_MAX: Implied (not listed in the Plan) maximum residences per acre (if applicable) IMPLIED_FAR_MIN: Implied (not listed in the Plan) minimum Floor Area Ratio (if applicable) IMPLIED_FAR_TARGET: Implied (not listed in the Plan) target Floor Area Ratio (if applicable) IMPLIED_FAR_MAX: Implied (not listed in the Plan) maximum Floor Area Ratio (if applicable) IMPLIED_LU_CATEGORY: Implied (not listed in the Plan) general land use category. General categories used include residential, office, commercial, industrial, and other.PurposeLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactJohn BeallCity of Tucson Development Services520-791-5550John.Beall@tucsonaz.govUpdate FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

This data set consists of 6 classes of zoning features: zoning districts, special purpose districts, special purpose district subdistricts, limited height districts, commercial overlay districts, and zoning map amendments. All previously released versions of this data are available on the DCP Website: BYTES of the BIG APPLE. Current version: 202508

The State Lands Commission has prepared the Significant Lands Inventory (report) for the California Legislature as a general identification and classification of those unconveyed State school lands and tide and submerged lands which possess significant environmental values. The publication incorporates evaluated and pertinent comments received on the initial draft report which was circulated statewide in February 1975.The absence of a particular digitized waterway in the dataset does not mean that the State does not claim ownership of that parcel or waterway, or that such specific parcel or waterway has no significant environmental values. This dataset is not intended to establish ownership, only to identify those parcels which possess significant environmental values. Staff was unable to physically inventory all of the considered lands; instead, the advice and participation of those with known environmental expertise was utilized as additional to staff survey.Tide and submerged lands are digitized in the WaterBody and WaterLine feature classes; WaterLines for coastal areas, WaterBody for inland areas. Tide and submerged lands under the jurisdiction of the State Lands Commission are those sovereign lands received from the Federal Government by virtue of California's admission to the Union on an equal footing with the original States. Such lands, and State interest therein, are generally the lands waterward of the ordinary high water mark of the Pacific Ocean (seaward to a three-mile limit); tidal bays, sloughs, estuaries; and, navigable lakes and streams within the State.School Lands are digitized in the SchoolLand feature class. State school lands under the jurisdiction of the Commission are largely composed of the 16th and 36th sections of each township. The Federal Government transferred these lands to the State in 1853, in order to establish a financial foundation for a public school system. In cases where the 16th and 36th sections were mineral in character, incomplete as to acreage total, or already claimed or granted by the Federal Government, the State was permitted to select other lands "in lieu" of the specific sections.The public trust of commerce, navigation and fisheries which the State retains on patented sovereign lands should also be considered included in this inventory. Wherever a waterway, or body of water, is listed or mapped, the common trust state interest in patented sovereign lands, if any, is also included.The State Lands Commission emphasized when it adopted this report at its December 1, 1975 meeting that all tide and submerged lands are significant by the nature of their public ownership. Only because of the methodology used for this report are all of these waterways not specifically listed in this inventory.It is the intent of the State Lands Commission that the Significant Lands Inventory be periodically updated. This dataset should be considered informational, to assist the Legislature, the Commission, and the public in considering the environmental aspects of a proposed project and the significant values to be protected therein.

The Metropolitan Council routinely compiles individual land use plans and plan amendments from communities within the seven-county Twin Cities metropolitan area into a single regional data layer. A principal goal of the Regional Planned Land Use dataset is to allow users to view, analyze and display planned land use data for anywhere in the seven county metropolitan area with a consistent land use classification scheme. The Metropolitan Council uses the Regional Planned Land Use (PLU) data to help monitor growth and plan for regional services such as regional parks, transit service, and wastewater collection and treatment.

Although the planned land use data is based on the locally adopted land use plans and designations for each community, it represent only data that has been submitted to the Metropolitan Council for review per the Metropolitan Land Planning Act of 1995 (Minn. Stat 473.864, Subd 2 and 473.175, Subd 1). See Data Quality Information (Section 2 of this metadata) for specifics about the Metropolitan Land Planning Act of 1995 under Completeness information.

Since there is no official State or Regional land use coding scheme that communities must conform with, the variability of content and codes between communities' land use plans is nearly as vast as the number of communities themselves (187). Differences among communities can range from the implementation of different land use categories to conflicting definitions of similar categories. The PLU dataset attempts to effectively level out the variability among communities by translating communities land use categories and descriptions into a common classification scheme developed and endorsed by MetroGIS (a regional GIS data sharing consortium) participants while retaining each communities' original categories. Although the comparability of land use plans between communities has greatly improved as a result of this translation or "regionalization" of communities' land use codes, it is possible that not all community land use definitions have been precisely translated into the most appropriate regional land use category.

In conjunction with other regional information (i.e., land use trend data, households and jobs forecasts), the PLU data can help communities more easily understand regional and sub-regional planning goals and Council staff, working with individual local units of government, can better plan for the future needs and financing of regional services.

- Contact individual communities for more information on their locally adopted planned land use categories.

- See Data Quality Information (Section 2 of this metadata) for specifics about the development of the regional dataset and its accuracy.

- See Entities and Attributes Information (Section 5 of this metadata) for specifics about the regional land use codes and categories.

[Metadata] Description: Detailed Government Landownership in the State of Hawaii as of 2022: County, Federal, State, and State DHHL Lands (by TMK parcel) Sources: County of Kauai, April, 2022; City & County of Honolulu, April 27, 2022; County of Maui, April, 2022; County of Hawaii, April, 2022; State Department of Hawaiian Home Lands, October, 2022. This dataset was created using ownership information provided by the counties via tax map key parcel layers and ownership tables. Parcels were queried using the "Owner" field for state, county, and federal agency names. State GIS staff verified land ownership using the online service QPublic, the 2022 Department of Hawaiian Home Lands layer and other GIS layers and resources. Where ownership was still unclear, State GIS personnel reached out to appropriate agencies for clarification. Standardization and Summary fields "ownedby," “majorowner” and “type” were created using additional filters and queries. The parcel boundaries are intended to provide a visual reference only and do not represent legal or survey level accuracy. Attributes are for assessment purposes only and are subject to change at any time.For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/gov_own_detailed.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.

This dataset is a subset of the statewide parcel dataset. The parcels in this dataset have been assigned a Government Ownership classification using the values "Federal", "State", "County Fee", "Tax Forfeit", or "Tribal" where it can be inferred from other fields in the parcel record. Only parcels from counties that have opted-in to sharing parcel data are included in this dataset.

For more information about the opt-in open parcel dataset, please refer to the opt-in open parcel compilation. https://gisdata.mn.gov/dataset/plan-parcels-open.

The State of Minnesota makes no representation or warranties, express or implied, with respect to the use or reuse of data provided herewith, regardless of its format or the means of its transmission. THE DATA IS PROVIDED “AS IS” WITH NO GUARANTEE OR REPRESENTATION ABOUT THE ACCURACY, CURRENCY, SUITABILITY, PERFORMANCE, MECHANTABILITY, RELIABILITY OR FITINESS OF THIS DATA FOR ANY PARTICULAR PURPOSE. This dataset is NOT suitable for accurate boundary determination. Contact a licensed land surveyor if you have questions about boundary determinations.

This hosted feature layer has been published in RI State Plane Feet NAD 83. THIS IS A FUTURE LAND USE PLANNING MAP CREATED IN 2006. THIS DOES NOT SHOW CURRENT 2025 LAND USE LAND COVER. The Land Use 2025 dataset was developed for the Division of Planning, RI Statewide Planning Program as part of an update to a state land use plan. It evolved from a GIS overlay analysis of land suitability and availability and scenario planning for future growth. The analysis focused on the 37% of the State identified as undeveloped and unprotected in a land cover analysis from RIGIS 1995 land use land cover data. The project studied areas for suitability for conservation and development, based on the location of key natural resources and public infrastructure. The results identified areas with future use potential, under three categories of development intensity and two categories of conservation.These data are presented in the Plan as Figure 121-02-(01), Future Land Use Map. Land Use 2025: State Land Use Policies and Plan was published by the RI Statewide Planning Program on April 13, 2006. The intent of the Plan is to bring together the elements of the State Guide Plan such as natural resources, economic development, housing and transportation to guide conservation and land development in the State. The Plan directs the state and communities to concentrate growth inside the Urban Services Boundary (USB) and within potential growth centers in rural areas. It establishes different development approaches for urban and rural areas.These data have several purposes and applications: They are intended to be used as a policy guide for directing growth to areas most capable of supporting current and future developed uses and to direct growth away from areas less suited for development. Secondly, these data are a guide to assist the state and communities in making land use policies. It is important to note these data are a generalized portrayal of state land use policy. These are not a statewide zoning data. Zoning matters and individual land use decisions are the prerogative of local governments. The land use element is the over arching element in Rhode Island's State Guide Plan. The Plan articulates goals, objectives and strategies to guide the current and future land use planning of municipalities and state agencies. The purpose of the plan is to guide future land use and to present policies under which state and municipal plans and land use activities will be reviewed for consistency with the State Guide Plan. The Map is a graphical representation of recommendations for future growth patterns in the State. It depicts where different intensities of development (e.g. parks, urban development, non-urban development) should occur by color. The Map contains a USB that shows where areas with public services supporting urban development presently exist, or are likely to be provided, through 2025. Within the USB, most land is served by public water service; many areas also have public sewer service, as well as, public transit. Also included on the map are growth centers which are potential areas for development and redevelopment outside of the USB. Growth Centers are envisioned to be areas that will encourage development that is both contiguous to existing development with low fiscal and environmental impacts.NOTE: These data will be updated when the associated plan is updated or upon an amendment approved by the State Planning Council. NOTE: Wetlands were not categorized within the Land Use 2025 dataset.When using this dataset, the RIGIS wetlands dataset should be overlaid as a mask. Full descriptions of the categories and intended uses can be found within Section 2-4, Future Land Use Patterns, Categories, and Intended Uses, of the Plan. https://www.planning.ri.gov/documents/guide_plan/landuse2025.pdf

The OSNI Large-scale boundaries is a polygon dataset consisting of Local Government Districts set in 2012.The data has been extracted from OSNI Largescale database and has been topologically cleansed and attributed to create a seamless dataset. This service is published for OpenData. By download or use of this dataset you agree to abide by the LPS Open Government Data Licence. The OSNI Largescale LGDs 2012 is a polygon dataset consisting of Local Government Districts derived from OSNI Largescale. The boundaries were delineated in 2012 under the Local Government (Boundaries) Order (Northern Ireland) 2012 and used for the 2014 elections.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps

This hosted feature layer has been published in RI State Plane Feet NAD 83 This is a statewide, seamless digital dataset of the land cover/land use for the State of Rhode Island derived using automated and semi-automated methods and is based on orthophotography captured in spring 2011. The project area encompasses the State of Rhode Island and also extends 1/2 mile into the neighboring states of Connecticut and Massachusetts, or to the limits of the source orthophotography. Geographic feature accuracy meets the National Mapping Standards for 1:5000 scale mapping with respect to base level data (roads, hydrography, and orthos). The minimum mapping unit for this dataset is 0.5 acre.The land use classification scheme used for these data was based on the same Anderson Level III modified coding schema used in previous land use datasets in Rhode Island (1988 & 2003/2004). To provide a statewide dataset representing land cover/land use. The dataset is also intended to be incorporated into the Rhode Island Geographic Information System database for use by federal, state and local government and made available to the general public. The intention of this dataset is to serve as an update to the 2003/2004 land cover/land use dataset. Geography for the dataset was based on ground conditions of 2011 four-band orthophotography with a spatial resolution of 0.5 ft and 2011 LiDAR data and data derivatives with a nominal post spacing of 1m. Additional ancillary data used in the production of this dataset were provided by the State of Rhode Island and included 2003/2004 land cover/land use, road centerline, hydrography, railroads, state boundary, municipal boundary, coastline, location of schools, hospitals, governmental facilities, waste disposal sites, etc. Landuse / Landcover for RI is based upon Anderson Level 3 coding described in the United States Geological Survey Publication: "A Land Use And Land Cover Classification System for Use With Remote Sensor Data, Geological Survey Professional Paper 964" Available Online at: https://landcover.usgs.gov/pdf/anderson.pdf.

The map was developed using available parcel polygons attributed with tax assessment data as of project initiation in early 2020, Computer-Assisted Mass Appraisal (CAMA) data dated February 2020, and the Chesapeake Bay Program’s 2017/18 Land Use Land Cover data (2022 edition), subsequently referred to as “CBP LULC.” The map also incorporates land use datasets provided by county and municipal jurisdictions to the extent possible while maintaining standard statewide classification definitions and rules. The product was developed to be consistent with the 2018 National Agriculture Imagery Program (NAIP) imagery and CBP LULC dataset. MDP’s draft updated land use classification scheme is available as a separate document. This product is a beta release for public use and further testing. Methods for developing subsequent releases beyond this 2018 baseline will be refined based on feedback from the user community. Urban Land Uses 11 Low-density residential - Detached single-family/duplex dwelling units, yards, and associated areas. Includes generalized areas with lot sizes of less than five acres but at least one-half acre (0.2 to 2 dwelling units/acre). 12 Medium-density residential - Detached single-family/duplex, attached single-unit row housing, yards, and associated areas Includes generalized areas with lot sizes of less than one-half acre but at least one-eighth acre (2 to 8 dwelling units/acre). 13 High-density residential - Attached single-unit row housing, garden apartments, high-rise apartments/condominiums, mobile home and trailer parks, yards, and associated areas. Includes generalized areas with more than eight dwelling units per acre. This may include subsidized housing. 14 Commercial - Retail and wholesale services. Areas used primarily for the sale of products and services, including associated yards and parking areas. This category may include airports, welcome houses, telecommunication towers, and boat marinas. 15 Industrial - Manufacturing and industrial parks, including associated warehouses, storage yards, research laboratories, and parking areas. Warehouses that are returned by a commercial query should be categorized as industrial. This also includes power plants. 16 Institutional - Elementary and secondary schools, middle schools, junior and senior high schools, public and private colleges and universities, military installations (built-up areas only, including buildings and storage, training, and similar areas), churches, medical and health facilities, correctional facilities, government offices and facilities that are clearly separable from any surrounding natural or agricultural land cover, and other non-profit uses. 17 Extractive - Surface mining operations, including sand and gravel pits, quarries, coal surface mines, and deep coal mines. Status of activity (active vs. abandoned) is not distinguished. 18 Open urban land - Includes parks, open spaces, recreational areas not classified as institutional, golf courses, and cemeteries. Includes only built-up and turf-dominated areas that are clearly separable from any surrounding natural or agricultural land cover. 190 – Very Low Density Residential – Clustered residential parcels that have lot sizes less than 20 acres but at least five acres (0.2 to 0.05 dwelling units/acre) 50 – Water 80 Transportation - Transportation features include impervious roads, roadway rights-of-way, and parcels primarily containing light rail or metro stations and park-and-ride lots. 99 – Other Land - Remaining land not covered under another category. Examples include but are not limited to unbuilt lots, rural land, single-family residential parcels greater than or equal to 20 acres in size, and undeveloped portions of large parcels containing urban uses. May include undeveloped land that is either developable or constrained from further development.Note: Urban Land Use classifications encompass the entire parcel on parcels less than five acres that contain a structure as of 2018 based on the Maryland Department of Planning and Maryland State Department of Assessment and Taxation’s Computer-Assisted Mass Appraisal (CAMA) Building dataset. Elsewhere, the Chesapeake Bay Program’s 2017/18 Land Use Land Cover dataset (2022 edition) is used to delineate the extent of development on a parcel. For more information, see Methodology Documentation.Feature Service Link: https://mdgeodata.md.gov/imap/rest/services/PlanningCadastre/MD_LandUse/MapServer/1This copy has been projected to "WGS 1984 Web Mercator (auxiliary sphere)" and, therefore, is for illustrative purposes only. To use the data for geospatial analysis or area calculations, please download the copy projected to "NAD_1983 StatePlane Maryland FIPS 1900" from MDP's website at https://planning.maryland.gov/pages/ourproducts/downloadfiles.aspx.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

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 SMA implementation is comprised of one feature dataset, with several polygon feature classes, rather than a single feature class. SurfaceManagementAgency: The Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. The SMA feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agencyâ s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. SMA_Withdrawals: The Surface Management Agency (SMA) Withdrawals Geographic Information System (GIS) dataset includes all of the known withdrawals which transfer surface jurisdictional responsibilities to federal agencies. The SMA Withdrawls feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA Withdrawal is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SMA Withdrawals will include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. These data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. SPP_WithdrawalAreas: The Special Public Purpose (SPP) Withdrawals Geographic Information System (GIS) dataset includes all of the known SPP Withdrawal Areas, which limit use or access to Federal lands (e.g. Wilderness, National Monument). The Special Public Purpose Withdrawal Areas feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SPP Withdrawal Area is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SPP Withdrawals include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. These data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.

This dataset is OBSOLETE as of 12/3/2024 and will be removed from ArcGIS Online on 12/3/2025.An updated version of this dataset is available at Land Use FY2024.This data set derives from several sources, and is updated annually with data current through July 1 of the reported year. The primary source is a data dump from the VISION assessing data system, which provided data up to date as of January 1, 2012, and is supplemented by information from subsequent building permits and Development Logs. (Use codes provided by this system combine aspects of land use, tax status, and condominium status. In an effort to clarify land use type the data has been cleaned and subdivided to break the original use code into several different fields.) The data set has further been supplemented and updated with development information provided by building permits issued by the Inspectional Services Department and from data found in the Development Log publication. Information from these sources is added to the data set periodically. Land use status is up to date as of the Last Modified date.Differences From “Official” Parcel LayerThe Cambridge GIS system maintains a separate layer of land parcels reflecting up to date subdivision and ownership. The parcel data associated with the Land Use Data set differs from the “official” parcel layer in a number of cases. For that reason this separate parcel layer is provided to work with land use data in a GIS environment. See the Assessing Department’s Parcel layer for the most up-to-date land parcel boundaries.Table of Land Use CodesThe following table lists all land use code found in the data layer:Land Use CodeLand Use DescriptionCategory0101MXD SNGL-FAM-REMixed Use Residential0104MXD TWO-FAM-RESMixed Use Residential0105MXD THREE-FM-REMixed Use Residential0111MXD 4-8-UNIT-APMixed Use Residential0112MXD >8-UNIT-APTMixed Use Residential0121MXD BOARDING-HSMixed Use Residential013MULTIUSE-RESMixed Use Residential031MULTIUSE-COMMixed Use Commercial0340MXD GEN-OFFICEMixed Use Commercial041MULTIUSE-INDMixed Use Industrial0942Higher Ed and Comm MixedMixed Use Education101SNGL-FAM-RESResidential1014SINGLE FAM W/AUResidential104TWO-FAM-RESResidential105THREE-FM-RESResidential106RES-LAND-IMPTransportation1067RES-COV-PKGTransportation1114-8-UNIT-APTResidential112>8-UNIT-APTResidential113ASSISTED-LIVAssisted Living/Boarding House121BOARDING-HSEAssisted Living/Boarding House130RES-DEV-LANDVacant Residential131RES-PDV-LANDVacant Residential132RES-UDV-LANDVacant Residential1322RES-UDV-PARK (OS) LNVacant Residential140CHILD-CARECommercial300HOTELCommercial302INN-RESORTCommercial304NURSING-HOMEHealth316WAREHOUSECommercial323SH-CNTR/MALLCommercial324SUPERMARKETCommercial325RETAIL-STORECommercial326EATING-ESTBLCommercial327RETAIL-CONDOCommercial330AUTO-SALESCommercial331AUTO-SUPPLYCommercial332AUTO-REPAIRCommercial334GAS-STATIONCommercialLand Use CodeLand Use DescriptionCategory335CAR-WASHCommercial336PARKING-GARTransportation337PARKING-LOTTransportation340GEN-OFFICEOffice341BANKCommercial342MEDICAL-OFFCHealth343OFFICE-CONDOOffice345RETAIL-OFFICOffice346INV-OFFICEOffice353FRAT-ORGANIZCommercial362THEATRECommercial370BOWLING-ALLYCommercial375TENNIS-CLUBCommercial390COM-DEV-LANDVacant Commercial391COM-PDV-LANDVacant Commercial392COM-UDV-LANDVacant Commercial3922CRMCL REC LNDVacant Commercial400MANUFACTURNGIndustrial401WAREHOUSEIndustrial404RES-&-DEV-FCOffice/R&D406HIGH-TECHOffice/R&D407CLEAN-MANUFIndustrial409INDUST-CONDOIndustrial413RESRCH IND CNDIndustrial422ELEC GEN PLANTUtility424PUB UTIL REGUtility428GAS-CONTROLUtility430TELE-EXCH-STAUtility440IND-DEV-LANDVacant Industrial442IND-UDV-LANDVacant Industrial920ParklandsPublic Open Space930Government OperationsGovernment Operations934Public SchoolsEducation940Private Pre & Elem SchoolEducation941Private Secondary SchoolEducation942Private CollegeHigher Education9421Private College Res UnitsEducation Residential943Other Educ & Research OrgHigher EducationLand Use CodeLand Use DescriptionCategory953CemeteriesCemetery955Hospitals & Medical OfficHealth956MuseumsHigher Education957Charitable ServicesCharitable/Religious960ReligiousCharitable/Religious971Water UtilityUtility972Road Right of WayTransportation975MBTA/RailroadTransportation9751MBTA/RailroadTransportation995Private Open SpacePrivately-Owned Open SpaceExplore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription ML type: Stringwidth: 16precision: 0 Map-Lot: This a unique parcel identifier found in the deed and used by the Assessing data system. In a few cases, where parcels have been subdivided subsequent to January 1, 2012, a placeholder Map-Lot number is assigned that differs from that used elsewhere.

MAP type: Stringwidth: 5precision: 0 This Map portion of the unique parcel identifier found in the deed and used by the Assessing data system. In a few cases, where parcels have been subdivided subsequent to January 1, 2012, a placeholder Map-Lot number is assigned that differs from that used elsewhere.

LOT type: Stringwidth: 5precision: 0 This is the Lot portion of the unique parcel identifier found in the deed and used by the Assessing data system. In a few cases, where parcels have been subdivided subsequent to January 1, 2012, a placeholder Map-Lot number is assigned that differs from that used elsewhere.

Location type: Stringwidth: 254precision: 0 In the great majority of cases this is the street address of the parcel as it is recorded in the Registry of Deed record. In instances where edits were made to the base parcel layer the best address available at the time is employed.

LandArea type: Doublewidth: 8precision: 15

LUCode type: Stringwidth: 254precision: 0 The four digit text string in this field indicates the primary usage of a parcel. While the codes are based on the standard Massachusetts assessing land use classification system, they differ in a number of cases; the coding system used here is unique to this data set. Note that other minor uses may occur on a property and, in some cases, tenants may introduce additional uses not reflected here (eg, office space used as a medical office, home based businesses).

LUDesc type: Stringwidth: 254precision: 0 The short description gives more detail about the specific use indicated by the Land Use Code. Most descriptions are taken from the standard Massachusetts assessing land use classification system.

Category type: Stringwidth: 254precision: 0 This broader grouping of land uses can be used to map land use data. You can find the land use data mapped at: https://www.cambridgema.gov/CDD/factsandmaps/mapgalleries/othermaps

ExistUnits type: Doublewidth: 8precision: 15 This value indicates the number of existing residential units as of July 1 of the reported year. A residential unit may be a house, an apartment, a mobile home, a group of rooms or a single room that is occupied (or, if vacant, intended for occupancy) as separate living quarters. This includes units found in apartment style graduate student housing residences and rooms in assisted living facilities and boarding houses are treated as also housing units. The unit count does not include college or graduate student dormitories, nursing home rooms, group homes, or other group quarters living arrangements.

MixedUseTy type: Stringwidth: 254precision: 0 Two flags are used for this field. “Groundfloor” indicates that a commercial use is found on the ground floor of the primary building, and upper floors are used for residential purposes. “Mixed” indicates that two or more uses are found throughout the structure or multiple structures on the parcel, one of which is residential.

GQLodgingH type: Stringwidth: 254precision: 0 A value of “Yes” indicates that the primary use of the property is as a group quarters living arrangement. Group quarters are a place where people live or stay, in a group living arrangement, that is owned or managed by an entity or organization providing housing and/or services for the residents. Group quarters include such places as college residence halls, residential treatment centers, skilled nursing facilities, group homes, military barracks, correctional facilities, and workers’ dormitories.

Most university dormitories are included under the broader higher education land use code, as most dormitories are included in the larger parcels comprising the bulk of higher education campuses.

GradStuden type: Stringwidth: 254precision: 0 A value of “Yes” indicates the parcel is used to house graduate students in apartment style units. Graduate student dormitories are treated as a higher education land use.

CondoFlag type: Stringwidth: 254precision: 0 “Yes” indicates that the parcel is owned as a condominium. Condo properties can include one or more uses, including residential, commercial, and parking. The great majority of such properties in Cambridge are residential only.

TaxStatus type: Stringwidth: 254precision: 0 A value indicates that the parcel is not subject to local property taxes. The following general rules are employed to assign properties to subcategories, though special situations exist in a number of cases.

o Authority: Properties owned the Cambridge Redevelopment Authority and Cambridge Housing Authority. o City: Properties owned by the City of Cambridge or cemetery land owned by the Town of Belmont. o Educ: Includes properties used for education purposes, ranging from pre-schools to university research facilities. (More detail about the level of education can be found using the Land Use Code.) o Federal: Properties owned by the federal government, including the Post Office. Certain properties with assessing data indicating Cambridge Redevelopment Authority ownership are in fact owned by the federal government as part of the Volpe Transportation Research Center and are so treated here. o Other: Nontaxable properties owned by a nonprofit organization and not

Overview

The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.4 (published 24 February 2025). The 11.4 release contains updated boundary lines and data refinements designed to extend the functionality of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.

National Geospatial Data Asset

This dataset is a National Geospatial Data Asset (NGDAID 194) managed by the Department of State. It is a part of the International Boundaries Theme created by the Federal Geographic Data Committee.

Dataset Source Details

Sources for these data include treaties, relevant maps, and data from boundary commissions, as well as national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process includes analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.

Cartographic Visualization

The LSIB is a geospatial dataset that, when used for cartographic purposes, requires additional styling. The LSIB download package contains example style files for commonly used software applications. The attribute table also contains embedded information to guide the cartographic representation. Additional discussion of these considerations can be found in the Use of Core Attributes in Cartographic Visualization section below.

Additional cartographic information pertaining to the depiction and description of international boundaries or areas of special sovereignty can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues: https://data.geodata.state.gov/guidance/index.html

Contact

Direct inquiries to internationalboundaries@state.gov. Direct download: https://data.geodata.state.gov/LSIB.zip

Attribute Structure

The dataset uses the following attributes divided into two categories: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | Core CC1_GENC3 | Extension CC1_WPID | Extension COUNTRY1 | Core CC2 | Core CC2_GENC3 | Extension CC2_WPID | Extension COUNTRY2 | Core RANK | Core LABEL | Core STATUS | Core NOTES | Core LSIB_ID | Extension ANTECIDS | Extension PREVIDS | Extension PARENTID | Extension PARENTSEG | Extension

These attributes have external data sources that update separately from the LSIB: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | GENC CC1_GENC3 | GENC CC1_WPID | World Polygons COUNTRY1 | DoS Lists CC2 | GENC CC2_GENC3 | GENC CC2_WPID | World Polygons COUNTRY2 | DoS Lists LSIB_ID | BASE ANTECIDS | BASE PREVIDS | BASE PARENTID | BASE PARENTSEG | BASE

The core attributes listed above describe the boundary lines contained within the LSIB dataset. Removal of core attributes from the dataset will change the meaning of the lines. An attribute status of “Extension” represents a field containing data interoperability information. Other attributes not listed above include “FID”, “Shape_length” and “Shape.” These are components of the shapefile format and do not form an intrinsic part of the LSIB.

Core Attributes

The eight core attributes listed above contain unique information which, when combined with the line geometry, comprise the LSIB dataset. These Core Attributes are further divided into Country Code and Name Fields and Descriptive Fields.

County Code and Country Name Fields

“CC1” and “CC2” fields are machine readable fields that contain political entity codes. These are two-character codes derived from the Geopolitical Entities, Names, and Codes Standard (GENC), Edition 3 Update 18. “CC1_GENC3” and “CC2_GENC3” fields contain the corresponding three-character GENC codes and are extension attributes discussed below. The codes “Q2” or “QX2” denote a line in the LSIB representing a boundary associated with areas not contained within the GENC standard.

The “COUNTRY1” and “COUNTRY2” fields contain the names of corresponding political entities. These fields contain names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the ‘"Independent States in the World" and "Dependencies and Areas of Special Sovereignty" lists maintained by the Department of State. To ensure maximum compatibility, names are presented without diacritics and certain names are rendered using common cartographic abbreviations. Names for lines associated with the code "Q2" are descriptive and not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS denote independent states. Names rendered in normal text represent dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.

Descriptive Fields

The following text fields are a part of the core attributes of the LSIB dataset and do not update from external sources. They provide additional information about each of the lines and are as follows: ATTRIBUTE NAME | CONTAINS NULLS RANK | No STATUS | No LABEL | Yes NOTES | Yes

Neither the "RANK" nor "STATUS" fields contain null values; the "LABEL" and "NOTES" fields do. The "RANK" field is a numeric expression of the "STATUS" field. Combined with the line geometry, these fields encode the views of the United States Government on the political status of the boundary line.

ATTRIBUTE NAME | | VALUE | RANK | 1 | 2 | 3 STATUS | International Boundary | Other Line of International Separation | Special Line

A value of “1” in the “RANK” field corresponds to an "International Boundary" value in the “STATUS” field. Values of ”2” and “3” correspond to “Other Line of International Separation” and “Special Line,” respectively.

The “LABEL” field contains required text to describe the line segment on all finished cartographic products, including but not limited to print and interactive maps.

The “NOTES” field contains an explanation of special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, limitations regarding the purpose of the lines, or the original source of the line.

Use of Core Attributes in Cartographic Visualization

Several of the Core Attributes provide information required for the proper cartographic representation of the LSIB dataset. The cartographic usage of the LSIB requires a visual differentiation between the three categories of boundary lines. Specifically, this differentiation must be between:

• International Boundaries (Rank 1);
• Other Lines of International Separation (Rank 2); and
• Special Lines (Rank 3).

Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Please consult the style files in the download package for examples of this depiction.

The requirement to incorporate the contents of the "LABEL" field on cartographic products is scale dependent. If a label is legible at the scale of a given static product, a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field contains the preferred description for the three LSIB line types when they are incorporated into a map legend but is otherwise not to be used for labeling.

Use of

This data provides the geographic location for parcel boundary lines within the jurisdiction of the Carteret County, NC and is based on recorded surveys and deeds. This dataset is maintained by the Carteret County GIS Division. Data is updated on an as needed basis. The description for each field name in the layer is included below.FieldAliasMeaningPIN15Parcel NumberTax Parcel ID Number (PIN4+ PIN5)ROLL_TYPERoll TypeRoll type of property (regularly taxed property or tax-exempt)GISMOTHERMother ParcelMother ParcelGISMAPNUMPIN1First 4 digits of PIN15MAPNAMPIN2PIN1 + 2 digitsGISBLOCKPIN3Digits 7 and 8 of PIN15GISPINPIN4PIN2 +PIN3GISPDOTPIN5Digit numbers 9 to 12 of PIN15CONDO_Condo unit #Condo numberGISPRIDOld Tax IDOld parcel number style based on prior mapping system before NC GRID system mapsOWNERTax Owner 1Tax parcel ownerOWNER2Tax Owner 2Secondary tax parcel ownerSITE_HOUSESite House #Site Address House NumberSITE_DIRSite DirSite Address Street directionalSITE_STSite StreetSite Address Street NameSITE_STTYPSite Street TypeSite Address Street Suffix (e.g., Dr., St., etc.)SITE_APTNOSite AptSite Address UnitSITE_CITYSite CitySite Address City/CommunityPropertyAddressPhysical AddressProperty AddressMAIL_ADDRESS1Mailing address and streetConcatenated mailing addressMAIL_ADDRESS2Mailing unitSecondary mailing addressMAIL_CITYMailing cityMailing address CityMAIL_STATEMailing stateMailing address StateMAIL_ZI4Mailing Zip4Mailing address Zip Code + 4MAIL_ZI5Mailing Zip5Mailing address Zip CodeFullMailingAddressFull Mailing AddressFull mailing address concatenatedDBOOKDeed BookDeed book containing the most recent deed to the propertyDPAGEDeed PageDeed page containing the most recent deed to the propertyDDATEDeed Dateunformatted most recent deed date for the propertyDeedDate_2Formatted Deed DateFormatted most recent deed date for the propertyMapBookPlat Map BookMap BookMapPagePlat Map PageMap PagePLATBOOKPlat BookRecorded Plat BookPLATPAGEPlat PageRecorded Plat PageLEGAL_DESCParcel Legal DescriptionLegal descriptionLegalAcresLegal Acres (new)Deeded or platted acresDeededAcresLegal AcresAcres from recorded deedsCalculatedLandUnitsTaxed AcresTaxed land acreageGISacresCalculated AcresCalculated GIS acresGISacres2Calculated Acres (new)Calculated GIS acresLandCodeTax Land Category CodeLand CodeLandCodeDescriptionTax Land Category DescriptionLand Code DescriptionMUNICIPALITYMunicipality/ETJIf parcel is within the corporate limits or ETJTOWNSHIPTownshipTownship codeRESCUE_DISTTax Rescue DistrictTax rescue district that the parcel is withinFIRE_DISTTax Fire DistrictTax fire district that the parcel is withinJurisdictionTax District CodeTax District CodeNBHDNeighborhood CodeNeighborhood codeNeighborhoodNameNeighborhood NameNeighborhood code descriptionBuildingCount# BuildingsNumber of buildings within the propertyY_BLT_HOUSEYear Built HouseYear house was builtBLT_CONDOYear Built CondoYear condo was builtTOT_SQ_FTTotal Sq FootTotal square footage of structure on propertyHtdSqFtHeated Sq FootHeated square footages of structure on the propertyBldgModelBuilding ModelBuilding ModelBEDROOMS# Bedrooms# BedroomsBATHROOMS# Bathrooms# BathroomsBldgUseBuilding UseBuilding UseConditionBuilding ConditionBuilding ConditionDwellingStyleDescriptionDwelling DescriptionDwelling style descriptionExWllDes1Exterior wall 1Exterior wall type 1 descriptionExWllDes2Exterior wall 2Exterior wall type 2 descriptionExWllTyp1Exterior wall 1 codeExterior wall type 1ExWllTyp2Exterior wall 2 codeExterior wall type 2FondDes1Foundation Description Foundation type 1 descriptionFondTyp1Foundation Description CodeFoundation type 1RCovDes1Roof # 1 Covering DescriptionRoof covering type 1 descriptionRCovDes2Roof # 2 CoveringDescriptionRoof covering type 2 descriptionRCovTyp1Roof # 1 CodeRoof covering type 1RCovTyp2Roof # 2 CodeRoof covering type 2RStrDes1Roof Structure DescriptionRoof structure type 1 descriptionRStrTyp1Roof Structure CodeRoof structure type 1GradeBuilding GradeTax gradeGradeAndCDUBuilding Grade & ConditionBuilding Grade & ConditionHeatDes1Heating/Cooling TypeHeating type 1 descriptionHeatTyp1Heating/Cooling CodeHeating type 1FireplaceCountFireplacesFireplacesSTRUC_VALStructure ValueValue of structure(s) on the propertyLAND_VALUETax Land ValueValue of the land on the propertyOTHER_VALOther Structures ValueOther value of the propertyTotal_EMVTotal Estimated Market ValueTotal estimated tax valueSaleImprovedorVacantSALE_PRICEVacant or Improved SaleRecorded Sale PriceVacant of Improved SaleRecorded sale priceSaleDateRecorded Sale DateRecorded sale dateSubdivision_NameSubdivision NameSubdivision NameSubdivision_Platbk_pagSubdivision Plat Book/PakeSubdivision Plat Book and PageCommissioner_DistrictCommissioner District #Commissioner"s DistrictCommissioner_Name1Commissioner NameCommissioner"s NameCommissioner_InfoCommissioner LinkLink to Commissioner"s contact info Elementary_SchoolElementary DistrictElementary school name/districtMiddle_SchoolMiddle School DistrictMiddle School name/districtHigh_SchoolHigh School DistrictHigh school name/districtIsImprovedProperty ImprovedBuilt on = 1, Vacant = 0IsQualifiedQualified SaleQualified = 1, Not Qualified = 0Use_codeTax Use CodeLand use codeUse_descTax Use Code DescriptionLand use descriptionPerm_De1Permit # 1 DescriptionPermit #1 descriptionPerm_De2Permit # 2 DescriptionPermit #2 descriptionPerm_Is1Permit # 1 Issue DatePermit #1 issue datePerm_Is2Permit # 2 Issue DatePermit #2 issue datePerm_N1Permit # 1 NumberPermit #1Perm_N2Permit #2 NumberPermit #2Perm_Ty1Permit # 1 TypePermit #1 typePerm_Ty2Permit # 2 TypePermit #2 typeACTL_DA1Permit #1 Completion DatePermit #1 - actual completion dateACTL_DA2Permit #2 Completion DatePermit #2 - actual completion dateReviewedDateTax Office Review DateDate ReviewedNoise_lvlBogue Air Field Noise LevelNoise level zones surrounding military air basesRisk_levelBogue Landing Risk LevelRisk level for military air plane accident potential within the AICUZ zonesaicuzBogue Air Field AICUZAir Installation Compatible Use Zone - planning zones pertaining to military air bases and the surrounding real estateOBJECTIDOBJECTIDESRI default unique IDSHAPEShapeESRI default fieldSHAPE.STArea()Shape AreaESRI default fieldSHAPE.STLength()Shape PerimeterESRI default field

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.

The purpose of the American Indian and Alaska Native Land Area Representation (AIAN-LAR) Geographic Information System (GIS) dataset is to depict the external extent of federal Indian reservations and the external extent of associated land held in “trust” by the United States, “restricted fee” or “mixed ownership” status for federally recognized tribes and individual Indians. This dataset includes other land area types such as Public Domain Allotments, Dependent Indian Communities and Homesteads. This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary. The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices. Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation. The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.

Administered Lands is a BLM Alaska GIS dataset that combines publicly available borough, municipality, state, federal, and other entity management and ownership GIS data. This is the basis for BLM’s national Surface Management Agency GIS dataset that was developed to fulfill the public and Government’s need to know what agency is managing Federal land in a given area. This data set is comprised of various sources of geospatial information that have been acquired from local, state and federal agencies in order to assemble a comprehensive representation of current land surface manager. There are many land managing agencies and branches of government and this dataset attempts to classify these entities into general categories. This data does not demonstrate or infer land ownership. The business need for this data includes, but is not limited to, land use planning, permitting, recreation, and emergency response. Due to the nature of assembling geospatial information from multiple sources, integration of features into a single layer may introduce inaccurate artifacts. Acquired datasets have been cross-walked to a standardized schema to aid in the depiction of land surface manager across the state of Alaska. This dataset will contain errors. For the most up to date and accurate information, please contact the surface manager agency for the area in which you are interested.