ArcGIS is a platform, and the platform is extending to the web. ArcGIS Online offers shared content, and has become a living atlas of the world. Ready-to-use curated content is published by Esri, Partners, and Users, and Esri is getting the ball rolling by offering authoritative data layers and tools.Specifically for Natural Resources data, Esri is offering foundational data useful for biogeographic analysis, natural resource management, land use planning and conservation. Some of the layers available are Land Cover, Wilderness Areas, Soils Range Production, Soils Frost Free Days, Watershed Delineation, Slope. The layers are available as Image Services that are analysis-ready and Geoprocessing Services that extract data for download and perform analysis.We've made large strides with online analysis. The latest release of ArcGIS Online's map viewer allows you to perform analysis on ArcGIS Online. Some of the currently available analysis tools are Find Hot Spots, Create Buffers, Summarize Within, Summarize Nearby. In addition, we've created Ready-to-use Esri hosted analysis tools that run on Esri hosted data. These are in Beta, and they include Watershed Delineation, Viewshed, Profile, and Summarize Elevation.

Parcels and property data maintained and provided by Lee County Property Appraiser are converted to points. Property attribute data joined to parcel GIS layer by Lee County Government GIS. This dataset is generally used in spatial analysis.Process description: Parcel polygons, condominium points and property data provided by the Lee County Property Appraiser are processed by Lee County's GIS Department using the following steps:Join property data to parcel polygons Join property data to condo pointsConvert parcel polygons to points using ESRI's ArcGIS tool "Feature to Point" and designate the "Source" field "P".Load Condominium points into this layer and designate the "Source" field "C". Add X/Y coordinates in Florida State Plane West, NAD 83, feet using the "Add X/Y" tool.Projected coordinate system name: NAD_1983_StatePlane_Florida_West_FIPS_0902_FeetGeographic coordinate system name: GCS_North_American_1983

 Name
 Type
 Length
 Description


 STRAP
 String
 25
 17-digit Property ID (Section, Township, Range, Area, Block, Lot)


 BLOCK
 String
 10
 5-digit portion of STRAP (positions 9-13)


 LOT
 String
 8
 Last 4-digits of STRAP


 FOLIOID
 Double
 8
 Unique Property ID


 MAINTDATE
 Date
 8
 Date LeePA staff updated record


 MAINTWHO
 String
 20
 LeePA staff who updated record


 UPDATED
 Date
 8
 Data compilation date


 HIDE_STRAP
 String
 1
 Confidential parcel ownership


 TRSPARCEL
 String
 17
 Parcel ID sorted by Township, Range & Section


 DORCODE
 String
 2
 Department of Revenue. See https://leepa.org/Docs/Codes/DOR_Code_List.pdf


 CONDOTYPE
 String
 1
 Type of condominium: C (commercial) or R (residential)


 UNITOFMEAS
 String
 2
 Type of Unit of Measure (ex: AC=acre, LT=lot, FF=frontage in feet)


 NUMUNITS
 Double
 8
 Number of Land Units (units defined in UNITOFMEAS)


 FRONTAGE
 Integer
 4
 Road Frontage in Feet


 DEPTH
 Integer
 4
 Property Depth in Feet


 GISACRES
 Double
 8
 Total Computed Acres from GIS


 TAXINGDIST
 String
 3
 Taxing District of Property


 TAXDISTDES
 String
 60
 Taxing District Description


 FIREDIST
 String
 3
 Fire District of Property


 FIREDISTDE
 String
 60
 Fire District Description


 ZONING
 String
 10
 Zoning of Property


 ZONINGAREA
 String
 3
 Governing Area for Zoning


 LANDUSECOD
 SmallInteger
 2
 Land Use Code


 LANDUSEDES
 String
 60
 Land Use Description


 LANDISON
 String
 5
 BAY,CANAL,CREEK,GULF,LAKE,RIVER & GOLF


 SITEADDR
 String
 55
 Lee County Addressing/E911


 SITENUMBER
 String
 10
 Property Location - Street Number


 SITESTREET
 String
 40
 Street Name


 SITEUNIT
 String
 5
 Unit Number


 SITECITY
 String
 20
 City


 SITEZIP
 String
 5
 Zip Code


 JUST
 Double
 8
 Market Value


 ASSESSED
 Double
 8
 Building Value + Land Value


 TAXABLE
 Double
 8
 Taxable Value


 LAND
 Double
 8
 Land Value


 BUILDING
 Double
 8
 Building Value


 LXFV
 Double
 8
 Land Extra Feature Value


 BXFV
 Double
 8
 Building Extra Feature value


 NEWBUILT
 Double
 8
 New Construction Value


 AGAMOUNT
 Double
 8
 Agriculture Exemption Value


 DISAMOUNT
 Double
 8
 Disability Exemption Value


 HISTAMOUNT
 Double
 8
 Historical Exemption Value


 HSTDAMOUNT
 Double
 8
 Homestead Exemption Value


 SNRAMOUNT
 Double
 8
 Senior Exemption Value


 WHLYAMOUNT
 Double
 8
 Wholly Exemption Value


 WIDAMOUNT
 Double
 8
 Widow Exemption Value


 WIDRAMOUNT
 Double
 8
 Widower Exemption Value


 BLDGCOUNT
 SmallInteger
 2
 Total Number of Buildings on Parcel


 MINBUILTY
 SmallInteger
 2
 Oldest Building Built


 MAXBUILTY
 SmallInteger
 2
 Newest Building Built


 TOTALAREA
 Double
 8
 Total Building Area


 HEATEDAREA
 Double
 8
 Total Heated Area


 MAXSTORIES
 Double
 8
 Tallest Building on Parcel


 BEDROOMS
 Integer
 4
 Total Number of Bedrooms


 BATHROOMS
 Double
 8
 Total Number of Bathrooms / Not For Comm


 GARAGE
 String
 1
 Garage on Property 'Y'


 CARPORT
 String
 1
 Carport on Property 'Y'


 POOL
 String
 1
 Pool on Property 'Y'


 BOATDOCK
 String
 1
 Boat Dock on Property 'Y'


 SEAWALL
 String
 1
 Sea Wall on Property 'Y'


 NBLDGCOUNT
 SmallInteger
 2
 Total Number of New Buildings on ParcelTotal Number of New Buildings on Parcel


 NMINBUILTY
 SmallInteger
 2
 Oldest New Building Built


 NMAXBUILTY
 SmallInteger
 2
 Newest New Building Built


 NTOTALAREA
 Double
 8
 Total New Building Area


 NHEATEDARE
 Double
 8
 Total New Heated Area


 NMAXSTORIE
 Double
 8
 Tallest New Building on Parcel


 NBEDROOMS
 Integer
 4
 Total Number of New Bedrooms


 NBATHROOMS
 Double
 8
 Total Number of New Bathrooms/Not For Comm


 NGARAGE
 String
 1
 New Garage on Property 'Y'


 NCARPORT
 String
 1
 New Carport on Property 'Y'


 NPOOL
 String
 1
 New Pool on Property 'Y'


 NBOATDOCK
 String
 1
 New Boat Dock on Property 'Y'


 NSEAWALL
 String
 1
 New Sea Wall on Property 'Y'


 O_NAME
 String
 30
 Owner Name


 O_OTHERS
 String
 120
 Other Owners


 O_CAREOF
 String
 30
 In Care Of Line


 O_ADDR1
 String
 30
 Owner Mailing Address Line 1


 O_ADDR2
 String
 30
 Owner Mailing Address Line 2


 O_CITY
 String
 30
 Owner Mailing City


 O_STATE
 String
 2
 Owner Mailing State


 O_ZIP
 String
 9
 Owner Mailing Zip


 O_COUNTRY
 String
 30
 Owner Mailing Country


 S_1DATE
 Date
 8
 Most Current Sale Date > $100.00


 S_1AMOUNT
 Double
 8
 Sale Amount


 S_1VI
 String
 1
 Sale Vacant or Improved


 S_1TC
 String
 2
 Sale Transaction Code


 S_1TOC
 String
 2
 Sale Transaction Override Code


 S_1OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_2DATE
 Date
 8
 Previous Sale Date > $100.00


 S_2AMOUNT
 Double
 8
 Sale Amount


 S_2VI
 String
 1
 Sale Vacant or Improved


 S_2TC
 String
 2
 Sale Transaction Code


 S_2TOC
 String
 2
 Sale Transaction Override Code


 S_2OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_3DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_3AMOUNT
 Double
 8
 Sale Amount


 S_3VI
 String
 1
 Sale Vacant or Improved


 S_3TC
 String
 2
 Sale Transaction Code


 S_3TOC
 String
 2
 Sale Transaction Override Code


 S_3OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_4DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_4AMOUNT
 Double
 8
 Sale Amount


 S_4VI
 String
 1
 Sale Vacant or Improved


 S_4TC
 String
 2
 Sale Transaction Code


 S_4TOC
 String
 2
 Sale Transaction Override Code


 S_4OR_NUM
 String
 13

This dataset includes all 7 metro counties that have made their parcel data freely available without a license or fees.

This dataset is a compilation of tax parcel polygon and point layers assembled into a common coordinate system from Twin Cities, Minnesota metropolitan area counties. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.

NOTICE: The standard set of attributes changed to the MN Parcel Data Transfer Standard on 1/1/2019.
https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

See section 5 of the metadata for an attribute summary.

Detailed information about the attributes can be found in the Metro Regional Parcel Attributes document.

The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties have polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. One primary example of this is the condominium, though some counties stacked polygons for condos. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.

The polygon layer is broken into individual county shape files. The points layer is provided as both individual county files and as one file for the entire metro area.

In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.

This is a MetroGIS Regionally Endorsed dataset.

Additional information may be available from each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person at each individual county.

Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin = https://gis-hennepin.hub.arcgis.com/pages/open-data
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://opendata.gis.co.scott.mn.us/
Washington: http://www.co.washington.mn.us/index.aspx?NID=1606

COUNTY ADDRESSINGThis dataset represents officially documented Addresses in Valley County Idaho. The spatial data was originally created for Valley County Emergency Service and Response and location services but is used throughout the County and by the public for many purposes. Addresses are updated daily through the flow of information from the County Planning and Zoning department, as well as from the municipalities and Assessors office. Each municipality (i.e. Cascade, Donnelly, McCall) is responsible for maintaining and administering addressing within their impact areas.GOOGLE ADDRESSINGGoogle Maps is a subset of the Google Earth program, which focuses it's update energies more frequently on bigger cities and densely populated areas. In rural areas, such as Valley County, Google addressing updates are more sporadic and the frequency is unknown. However, Google address ranges and geocoding already provide a robust level of addressing meaning new homes on already-existing streets are more likely to be represented. When new streets and subdivisions are created, the updates may happen more slowly which is why many times throughout the year, Valley County IT sends address updates to Google through the Geo Data Upload portal to try and ensure that Google is up-to-date. To find out how you can update addresses within Google on your own, visit: Set or change your home & work addresses - Computer - Google Maps Help

James City County Data - Updated nightly IGNORE dates on this site.Combination of parcel information from the GIS/Mapping and the Real Estate departments.This table includes multiple improvements per parcel.Also download the GIS and Real Estate Data Field Descriptions.pdf file for a list of field descriptions.This data is updated every night

The Australian Antarctic Data Centre's Davis Station GIS data were originally mapped from aerial photography (February 11, 12 1997). Refer to the metadata record 'Davis Station GIS Dataset'.
Since then various features have been added to these data as structures have been removed, moved or established. Some of these features have been surveyed. These surveys have metadata records from which the report describing the survey can be downloaded.
However, the locations of other features have been obtained from a variety of sources.
The data are included in the data available for download from a provided URL.
The data conforms to the SCAR Feature Catalogue which includes data quality information. See a Related URL below.
Data described by this metadata record has Dataset_id = 104.
Each feature has a Qinfo number which, when entered at the 'Search datasets & quality' tab, provides data quality information for the feature.

Expands the use of internal data for creating Geographic Information System (GIS) maps. SSA's Database Systems division developed a map users guide for GIS data object publishing and was made available in an internal Sharepoint site for access throughout the agency. The guide acts as the reference for publishers of GIS objects across the life-cycle in our single, central geodatabase implementation.

Last Update: 02/04/2025The statewide roads dataset is a multi-purpose statewide roads dataset for cartography and range based-address location. This dataset is also used as the base geometry for deriving the GIS-representation of UDOT's highway linear referencing system (LRS). A network analysis dataset for route-finding can also be derived from this dataset. This dataset utilizes a data model based on Next-Generation 911 standards and the Federal Highway Administration's All Roads Network Of Linear-referenced Data (ARNOLD) reporting requirements for state DOTs. UGRC adopted this data model on September 13th, 2017.The statewide roads dataset is maintained by UGRC in partnership with local governments, the Utah 911 Committee, and UDOT. This dataset is updated monthly with Davis, Salt Lake, Utah, Washington and Weber represented every month, along with additional counties based on an annual update schedule. UGRC obtains the data from the authoritative data source (typically county agencies), projects the data and attributes into the current data model, spatially assigns polygon-based fields based on the appropriate SGID boundary, and then standardizes the attribute values to ensure statewide consistency. UGRC also generates a UNIQUE_ID field based on the segment's location in the US National Grid, with the street name then tacked on. The UNIQUE_ID field is static and is UGRC's current, ad hoc solution to a persistent global id. More information about the data model can be found here: https://docs.google.com/spreadsheets/d/1jQ_JuRIEtzxj60F0FAGmdu5JrFpfYBbSt3YzzCjxpfI/edit#gid=811360546 More information about the data model transition can be found here: https://gis.utah.gov/major-updates-coming-to-roads-data-model/We are currently working with US Forest Service to improve the Forest Service roads in this dataset, however, for the most up-to-date and complete set of USFS roads, please visit their data portal where you can download the "National Forest System Roads" dataset.More information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/transportation/roads-system/

Sewers; Cemeteries; Business Improvement Areas; sidewalks; escarpment; DTM 10 metres; DTM 20 metres; water hydrants; police stations; libraries; colleges; universities; beaches; arenas; sewers; transit; wards; shoreline; parking lots; land use, etc.

This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes: Clipping input datasets to the California boundary Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc) Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California. Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only. Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs) In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources: GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.

The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP), prepared hydro-conditioned geographic information systems (GIS) data layers for use in the updated New Jersey StreamStats 2022 application (U.S. Geological Survey, 2022). This update features improvements in base-elevation resolution from 10 meters to 10 feet and stream centerline hydrography from 1:24,000 to 1:2,400 scale. Hydro conditioning is the process of burning single-line stream centerlines at the 1:2,400 scale into a digital elevation model to produce flow direction and flow accumulation grids. This data release contains raster digital datasets for a 10-foot digital elevation model, a flow direction grid, and a flow accumulation grid for the updated New Jersey Streamstats 2022 application. The eleven 8-digit Hydrologic Unit Codes (HUCs) represented by this dataset are 02020007, 02030103, 02030104, 02030105, 02040104, 02040105, 02040201, 02040202, 02040206, 02040301, and 02040302 (U.S. Geological Survey, 2016). The updated New Jersey StreamStats 2022 application provides access to spatial analytical tools that are useful for water-resources planning and management, as well as engineering and design purposes. The map-based user interface can be used to delineate drainage areas, determine basin characteristics, and estimate flow statistics, including instantaneous flood discharge, monthly flow-duration, and monthly low-flow frequency statistics for ungaged streams. References cited: U.S. Geological Survey, 2016, National Hydrography: U.S. Geological Survey, accessed February 4, 2022, at https://www.usgs.gov/national-hydrography. U.S. Geological Survey, 2022, StreamStats v4.6.2: U.S. Geological Survey, accessed February 4, 2022, at https://streamstats.usgs.gov/ss/.

This dataset is a compilation of county parcel data from Minnesota counties that have opted-in for their parcel data to be included in this dataset.

It includes the following 55 counties that have opted-in as of the publication date of this dataset: Aitkin, Anoka, Becker, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Fillmore, Grant, Hennepin, Houston, Isanti, Itasca, Jackson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Mille Lacs, Morrison, Mower, Murray, Norman, Olmsted, Otter Tail, Pennington, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Saint Louis, Scott, Sherburne, Stearns, Stevens, Traverse, Waseca, Washington, Wilkin, Winona, Wright, and Yellow Medicine.

If you represent a county not included in this dataset and would like to opt-in, please contact Heather Albrecht (Heather.Albrecht@hennepin.us), co-chair of the Minnesota Geospatial Advisory Council (GAC)’s Parcels and Land Records Committee's Open Data Subcommittee. County parcel data does not need to be in the GAC parcel data standard to be included. MnGeo will map the county fields to the GAC standard.

County parcel data records have been assembled into a single dataset with a common coordinate system (UTM Zone 15) and common attribute schema. The county parcel data attributes have been mapped to the GAC parcel data standard for Minnesota: https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

This compiled parcel dataset was created using Python code developed by Minnesota state agency GIS professionals, and represents a best effort to map individual county source file attributes into the common attribute schema of the GAC parcel data standard. The attributes from counties are mapped to the most appropriate destination column. In some cases, the county source files included attributes that were not mapped to the GAC standard. Additionally, some county attribute fields were parsed and mapped to multiple GAC standard fields, such as a single line address. Each quarter, MnGeo provides a text file to counties that shows how county fields are mapped to the GAC standard. Additionally, this text file shows the fields that are not mapped to the standard and those that are parsed. If a county shares changes to how their data should be mapped, MnGeo updates the compilation. If you represent a county and would like to update how MnGeo is mapping your county attribute fields to this compiled dataset, please contact us.

This dataset is a snapshot of parcel data, and the source date of the county data may vary. Users should consult County websites to see the most up-to-date and complete parcel data.

There have been recent changes in date/time fields, and their processing, introduced by our software vendor. In some cases, this has resulted in date fields being empty. We are aware of the issue and are working to correct it for future parcel data releases.

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.

DOWNLOAD NOTES: This dataset is only provided in Esri File Geodatabase and OGC GeoPackage formats. A shapefile is not available because the size of the dataset exceeds the limit for that format. The distribution version of the fgdb is compressed to help reduce the data footprint. QGIS users should consider using the Geopackage format for better results.

OBJECTID: System-generated unique identifier for each record within the feature classGEODBID: Three-digit code that assigns editing responsibility to a community in the GIS ConsortiumFEATUREID: GIS-Consortium-generated unique identifier for each record within the feature class. All FEATUREIDs start with the GEODBID of the community that owns the record.DATECREATED: Date/time stamp from the moment the GIS record was created DATEMODIFIED: Date/time stamp from the last moment the GIS record was changed SOURCE: Organization that provided the data. The GIS Consortium standard is to preface the source with the three-letter municipal code of the community providing the data, followed by a dash. Example: VGV-Public WorksSOURCETYPE: Accuracy context for the recordPIN: Unique numerical code for the description of a piece of land; parcel identification numberGlobalID: System-generated unique identifier for each record that is required in replicated geodatabasesPRODUCTIONNOTES: Technical notes from GIS personnelREPLICAFILTER: Code used to filter data for the creation of custom geodatabasesSHAPE: System-generated geometry type of the featureSHAPE.area: System-generated area of the featureSHAPE.len: System-generated length of the feature

The February 2025 issue of the GIS Office Newsletter features updates about the GIS Office, a summary of the most recent GIS Advisory Council meeting, GIS resources, and more.

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.

Purpose

County 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 Layers

This dataset is part of a grouping of many datasets:

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

Point of Contact

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

Field and Abbreviation Definitions

• 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
• Place Name: CDTFA incorporated (city) or county name
• 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.
• Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
• GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
• 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 System
• Place Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area names
• CNTY Abbr: CalTrans Division of Local Assistance abbreviations of county names
• Area_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.

Accuracy

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. COUNTY = county name; CITY = city name or unincorporated

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feat ...

GIS data: 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 at BYTES of the BIG APPLE- Archive

Updates for this dataset, along with other multilayered maps on NYC Open Data, are temporarily paused while they are moved to a new mapping format. Please visit https://www.nyc.gov/site/planning/data-maps/open-data/dwn-gis-zoning.page to utilize this data in the meantime

On December 6, 2022, the Los Angeles County Board of Supervisors (BOS) adopted the 2022 Countywide Parks Needs Assessment Plus (PNA+) Final Report. Consistent with this Board action, DPR is making GIS data from the PNA+ available to the public here. Composite layers include:Regional Study AreasRural Study AreasRegional Site InventoryLocal ParksBeachesCountywide TrailsTrailheads and Access PointsPriority Areas for Increasing Access to Regional RecreationPriority Areas for Increasing Access to Rural RecreationPriority Area for Environmental RestorationEnvironmental BenefitsEnvironmental BurdensComposite Population VulnerabilityNote that all data sources in the web map are courtesy of the Los Angeles County Department of Parks and Recreation (DPR). If you'd like to learn more about the data and analysis used in the PNA+, visit https://lacountyparkneeds.org/pnaplus-report/.

DISCLAIMER: The data herein is for informational purposes, and may not have been prepared for or be suitable for legal, engineering, or surveying intents. The County of Los Angeles reserves the right to change, restrict, or discontinue access at any time. All users of the maps and data presented on https://lacounty.maps.arcgis.com or deriving from any LA County REST URLs agree to the "Terms of Use" outlined on the County of LA Enterprise GIS (eGIS) Hub (https://egis-lacounty.hub.arcgis.com/pages/terms-of-use).

This dataset is comprised of data that contributes to the Australian Antarctic Data Centre's geographic data of Macquarie Island but is not part of a larger dataset. Data sources include GPS surveys, sketches on maps and advice from Australian Antarctic Division and Tasmanian Parks and Wildlife Service personnel. Data in this dataset has Dataset ID 81 and is included in the the Australian Antarctic Data Centre's geographic data of Macquarie Island available for download (see Related URLs below). The original data provided to the Australian Antarctic Data Centre may also be available for download (see Related URLs below).

DATASET: Alpha version 2000 and 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and MODIS-derived urban extent change built in. REGION: Asia SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described on the website and in: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882 FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - VNM00urbchg.tif = Vietnam (VNM) population count map for 2000 (00) adjusted to match UN national estimates and incorporating urban extent and urban population estimates for 2000. DATE OF PRODUCTION: July 2013 Dataset construction details and input data are provided here: www.asiapop.org and here: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055882