100+ datasets found
  1. a

    Parcels Public Shapefile

    • gis-sonomacounty.hub.arcgis.com
    • gis.sonomacounty.ca.gov
    Updated Mar 11, 2020
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    The County of Sonoma (2020). Parcels Public Shapefile [Dataset]. https://gis-sonomacounty.hub.arcgis.com/datasets/sonomacounty::parcels-public-shapefile/about
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    Dataset updated
    Mar 11, 2020
    Dataset authored and provided by
    The County of Sonoma
    License

    Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
    License information was derived automatically

    Area covered
    Description

    The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. This layer is a partial view of the Information Sales System (ISS) extract, a report of property characteristics taken from the County’s Megabyte Property Tax System (MPTS). This layer may be missing some attributes (e.g., Owner Name) which may not be published to the Internet due to privacy conditions under the California Public Records Act (CPRA). Please contact the Clerk-Recorder-Assessor (CRA) office at (707) 565-1888 for information on availability, associated fees, and access to other versions of Sonoma County parcels containing additional property characteristics.The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

  2. GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD...

    • search.dataone.org
    • portal.edirepository.org
    Updated Apr 5, 2019
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2019). GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Baltimore County [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F352%2F610
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    Dataset updated
    Apr 5, 2019
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Jan 1, 2005
    Area covered
    Description

    AT_2004_BACO File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Baltimore County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 5870 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.897802 East -76.335214 North 39.726520 South 39.192552 Scale Range There is no scale range for this item.

  3. TIGER/Line Shapefile, Current, County, Mineral County, NV, All Roads

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, Current, County, Mineral County, NV, All Roads [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-current-county-mineral-county-nv-all-roads
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Mineral County, Nevada
    Description

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

  4. GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD...

    • search.dataone.org
    • portal.edirepository.org
    Updated Apr 3, 2019
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2019). GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Harford County [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F354%2F610
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    Dataset updated
    Apr 3, 2019
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Jan 1, 2005
    Area covered
    Description

    AT_2004_HARF File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Harford County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).

  5. GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD...

    • search.dataone.org
    • portal.edirepository.org
    Updated Feb 22, 2018
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Anne Arundel County [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F350%2F610
    Explore at:
    Dataset updated
    Feb 22, 2018
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Jan 1, 2005
    Area covered
    Description

    AT_2004_ANNE File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Anne Arundel County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 897 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.838738 East -76.395283 North 39.238726 South 38.708588 Scale Range There is no scale range for this item.

  6. d

    CTA - Bus Stops - Shapefile

    • catalog.data.gov
    • data.cityofchicago.org
    • +3more
    Updated Nov 24, 2023
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    data.cityofchicago.org (2023). CTA - Bus Stops - Shapefile [Dataset]. https://catalog.data.gov/dataset/cta-bus-stops-shapefile
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    Dataset updated
    Nov 24, 2023
    Dataset provided by
    data.cityofchicago.org
    Description

    Point data representing locations of CTA bus stops. See attachment below for information on STATUS and POS fields To view or use these files, compression software and special GIS software, such as ESRI ArcGIS is required. Projected Coordinate System: NAD_1983_StatePlane_Illinois_East_FIPS_1201_Feet

  7. GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA)...

    • search.dataone.org
    • portal.edirepository.org
    Updated Apr 5, 2019
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2019). GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Harford County [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F368%2F620
    Explore at:
    Dataset updated
    Apr 5, 2019
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Jan 1, 2005
    Area covered
    Description

    CAMA_2004_HARF File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 194 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.568860 East -76.081594 North 39.726323 South 39.392952 Scale Range There is no scale range for this item.

  8. CPW Roads Shapefile Download

    • hub.arcgis.com
    Updated Mar 5, 2025
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    Colorado Parks & Wildlife (2025). CPW Roads Shapefile Download [Dataset]. https://hub.arcgis.com/datasets/f07d57957e484827af62ec8c9534318b
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    Dataset updated
    Mar 5, 2025
    Dataset provided by
    Colorado Parks and Wildlifehttps://cpw.state.co.us/
    Authors
    Colorado Parks & Wildlife
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Last Updated: March 4, 2025These data represent all roads within Colorado State Parks where public access is allowed. This is a complete dataset of all public roads within Colorado State Parks and is updated as roads are built, re-routed, or abolished. Occasionally, some roads outside of the boundaries of Colorado State Parks are included to help depict the best route to access various parcels.Initial database work was completed in May 2011 by Tom Williams, under the direction of Matt Schulz, Parks GIS Coordinator.This feature class was created by combining all individual public road shapefiles from the L/parks/work/xxx/themes/roads directory of each park.First, a new standard for roads was created using the NRPA standard for roads as a background (L:\parks\standards\themes\infrastr\Roads_Geodatabase_Standards_20110308.xlsx).A set of coded value domains were created in the geodatabase that was going to house the data to ensure data quality as the data was edited in the future.The final desired fields and all possible fields from the shapefiles were added into a new feature class and then each individual park shapefile was added to the created feature class using the "Append" tool.All fields were condensed into the final desired fields and entries were changed to match the domain for that field. Some information was put into the COMMENTS field so it was not lost in the transition.NOTE FOR FURTHER EDITS: When editing, a drop down pick list will appear for each entry if the field has a domain assigned to it. You must populate using the pick list or you can fill in multiple entries at once by using the field calculator and using the code instead of the code description. Please view the Supplemental Details to see the codes and descriptions.State Forest State Park: Winter Roads were integrated, "Plowed" field = YESColorado Parks and Wildlife Public GIS Data Update ScheduleAdministrative Boundary GIS Data1) First Week in February – to match any changes in Sheep, Goat, or Big Game GMU boundaries published in the Big Game Brochure.2) First Week in March – to update changes in administrative boundaries Regions, Areas, and Districts.3) First Week in August – to update Public Access Properties at the beginning of Big Game hunting seasons.4) First Week in September – to update Walk In Access program property boundaries.5) First Week in November – to update Walk In Access program property boundaries (late season).Wildlife Species GIS Data1) Mid December – at the completion of regional species activity mapping updates

  9. d

    United States Aquifer Database

    • search.dataone.org
    • hydroshare.org
    • +1more
    Updated Dec 30, 2023
    + more versions
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    Merhawi GebreEgziabher; Scott Jasechko; Debra Perrone (2023). United States Aquifer Database [Dataset]. https://search.dataone.org/view/sha256%3A82709f52473af67f57839c34ea9b666c1bbd6ebe02334b273ec02c2160e3854a
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    Dataset updated
    Dec 30, 2023
    Dataset provided by
    Hydroshare
    Authors
    Merhawi GebreEgziabher; Scott Jasechko; Debra Perrone
    Area covered
    Description

    Here we present a geospatial dataset representing local- and regional-scale aquifer system boundaries, defined on the basis of an extensive literature review and published in GebreEgziabher et al. (2022). Nature Communications, 13, 2129, https://www.nature.com/articles/s41467-022-29678-7

    The database contains 440 polygons, each representing one study area analyzed in GebreEgziabher et al. (2022). The attribute table associated with the shapefile has two fields (column headings): (1) aquifer system title (Ocala Uplift sub-area of the broader Floridan Aquifer System), and (2) broader aquifer system title (e.g., the Floridan Aquifer System).

  10. W

    Model area shapefile bores - Groundwater accounts v1

    • cloud.csiss.gmu.edu
    • researchdata.edu.au
    • +3more
    Updated Dec 13, 2019
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    Australia (2019). Model area shapefile bores - Groundwater accounts v1 [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/4e7996ac-bbf2-4df3-945c-2d764e7e69e5
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    Dataset updated
    Dec 13, 2019
    Dataset provided by
    Australia
    Description

    Abstract

    The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from the 'Bores within Clarence-Morton Groundwater model spatial domain' dataset. You can find a link to the parent dataset in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

    This is an ESRI shapefile of the bores selected for Ground Water accounting (see lineage).

    It contains all the data in the CLM_model_area_bores_for_GW_account_V1 spreadsheet within the shapefile attribute table. The spreadsheet contained 2505 geolocated records which are represented as point features in this shapefile.

    Purpose

    Created for report mapping purposes.

    Dataset History

    An event theme was created from the CLM_model_area_bores_for_GW_account_V1 spreadsheet data (see lineage) using the EASTING and NORTHING fields for the X, Y co-ordinates. The event theme was then exported to shapefile, defined with the MGA zone 56 projection.

    Dataset Citation

    Bioregional Assessment Programme (2015) Model area shapefile bores - Groundwater accounts v1. Bioregional Assessment Derived Dataset. Viewed 07 April 2016, http://data.bioregionalassessments.gov.au/dataset/4e7996ac-bbf2-4df3-945c-2d764e7e69e5.

    Dataset Ancestors

  11. M

    Parcels, Compiled from Opt-In Open Data Counties, Minnesota

    • gisdata.mn.gov
    fgdb, gpkg, html +2
    Updated May 13, 2025
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    Geospatial Information Office (2025). Parcels, Compiled from Opt-In Open Data Counties, Minnesota [Dataset]. https://gisdata.mn.gov/dataset/plan-parcels-open
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    html, webapp, jpeg, fgdb, gpkgAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    Geospatial Information Office
    Area covered
    Minnesota
    Description

    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.

  12. A

    Seattle Parks and Recreation GIS Map Layer Shapefile - Football Field Point

    • data.amerigeoss.org
    • datadiscoverystudio.org
    • +1more
    csv, json, kml, zip
    Updated Jul 29, 2019
    + more versions
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    United States[old] (2019). Seattle Parks and Recreation GIS Map Layer Shapefile - Football Field Point [Dataset]. https://data.amerigeoss.org/pt_PT/dataset/showcases/seattle-parks-and-recreation-gis-map-layer-shapefile-football-field-point
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    zip, kml, json, csvAvailable download formats
    Dataset updated
    Jul 29, 2019
    Dataset provided by
    United States[old]
    Area covered
    Seattle
    Description

    Seattle Parks and Recreation GIS Map Layer Shapefile - Football Field Point

    Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata.

    OR

    Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/17

  13. TIGER/Line Shapefile, 2022, County, Saguache County, CO, All Roads

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Saguache County, CO, All Roads [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-saguache-county-co-all-roads
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    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Saguache County, Colorado
    Description

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

  14. TIGER/Line Shapefile, Current, County, Oakland County, MI, All Roads

    • catalog.data.gov
    • datasets.ai
    Updated Dec 15, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, Current, County, Oakland County, MI, All Roads [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-current-county-oakland-county-mi-all-roads
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Oakland County
    Description

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

  15. a

    Parcel Points Shapefile

    • hub.arcgis.com
    • maps.leegov.com
    Updated Aug 15, 2022
    + more versions
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    Lee County Florida GIS (2022). Parcel Points Shapefile [Dataset]. https://hub.arcgis.com/datasets/f13fddbfe8fb444da730974693ee643b
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    Dataset updated
    Aug 15, 2022
    Dataset authored and provided by
    Lee County Florida GIS
    Description

    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
    
  16. Knoxville TN Urban Renewal Mapping Data

    • figshare.com
    zip
    Updated Feb 16, 2024
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    Chris DeRolph (2024). Knoxville TN Urban Renewal Mapping Data [Dataset]. http://doi.org/10.6084/m9.figshare.25199849.v3
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    zipAvailable download formats
    Dataset updated
    Feb 16, 2024
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Chris DeRolph
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Knoxville
    Description

    This dataset contains files created, digitized, or georeferenced by Chris DeRolph for mapping the pre-urban renewal community within the boundaries of the Riverfront-Willow St. and Mountain View urban renewal projects in Knoxville TN. Detailed occupant information for properties within boundaries of these two urban renewal projects was extracted from the 1953 Knoxville City Directory. The year 1953 was chosen as a representative snapshot of the Black community before urban renewal projects were implemented. The first urban renewal project to be approved was the Riverfront-Willow Street project, which was approved in 1954 according to the University of Richmond Renewing Inequality project titled ‘Family Displacements through Urban Renewal, 1950-1966’ (link below in the 'Other shapefiles' section). For ArcGIS Online users, the shapefile and tiff layers are available in AGOL and can be found by clicking the ellipsis next to the layer name and selecting 'Show item details' for the layers in this webmap https://knoxatlas.maps.arcgis.com/apps/webappviewer/index.html?id=43a66c3cfcde4f5f8e7ab13af9bbcebecityDirectory1953 is a folder that contains:JPG images of 1953 City Directory for street segments within the urban renewal project boundaries; images collected at the McClung Historical CollectionTXT files of extracted text from each image that was used to join occupant information from directory to GIS address datashp is a folder that contains the following shapefiles:Residential:Black_owned_residential_1953.shp: residential entries in the 1953 City Directory identified as Black and property ownersBlack_rented_residential_1953.shp: residential entries in the 1953 City Directory identified as Black and non-owners of the propertyNon_Black_owned_residential_1953.shp: residential entries in the 1953 City Directory identified as property owners that were not listed as BlackNon_Black_rented_residential_1953.shp: residential entries in the 1953 City Directory not listed as Black or property ownersResidential shapefile attributes:cityDrctryString: full text string from 1953 City Directory entryfileName: name of TXT file that contains the information for the street segmentsOccupant: the name of the occupant listed in the City Directory, enclosed in square brackets []Number: the address number listed in the 1953 City DirectoryBlackOccpt: flag for whether the occupant was identified in the City Directory as Black, designated by the (c) or (e) character string in the cityDrctryString fieldOwnerOccpd: flag for whether the occupant was identified in the City Directory as the property owner, designated by the @ character in the cityDrctryString fieldUnit: unit if listed (e.g. Apt 1, 2d fl, b'ment, etc)streetName: street name in ~1953Lat: latitude coordinate in decimal degrees for the property locationLon: longitude coordinate in decimal degrees for the property locationrace_own: combines the BlackOccpt and OwnerOccpd fieldsmapLabel: combines the Number and Occupant fields for map labeling purposeslastName: occupant's last namelabelShort: combines the Number and lastName fields for map labeling purposesNon-residential:Black_nonResidential_1953.shp: non-residential entries in the 1953 City Directory listed as Black-occupiedNonBlack_nonResidential_1953.shp: non-residential entries in the 1953 City Directory not listed as Black-occupiedNon-residential shapefile attributes:cityDrctryString: full text string from 1953 City Directory entryfileName: name of TXT file that contains the information for the street segmentsOccupant: the name of the occupant listed in the City Directory, enclosed in square brackets []Number: the address number listed in the 1953 City DirectoryBlackOccpt: flag for whether the occupant was identified in the City Directory as Black, designated by the (c) or (e) character string in the cityDrctryString fieldOwnerOccpd: flag for whether the occupant was identified in the City Directory as the property owner, designated by the @ character in the cityDrctryString fieldUnit: unit if listed (e.g. Apt 1, 2d fl, b'ment, etc)streetName: street name in ~1953Lat: latitude coordinate in decimal degrees for the property locationLon: longitude coordinate in decimal degrees for the property locationNAICS6: 2022 North American Industry Classification System (NAICS) six-digit business code, designated by Chris DeRolph rapidly and without careful considerationNAICS6title: NAICS6 title/short descriptionNAICS3: 2022 North American Industry Classification System (NAICS) three-digit business code, designated by Chris DeRolph rapidly and without careful considerationNAICS3title: NAICS3 title/short descriptionflag: flags whether the occupant is part of the public sector or an NGO; a flag of '0' indicates the occupant is assumed to be a privately-owned businessrace_own: combines the BlackOccpt and OwnerOccpd fieldsmapLabel: combines the Number and Occupant fields for map labeling purposesOther shapefiles:razedArea_1972.shp: approximate area that appears to have been razed during urban renewal based on visual overlay of usgsImage_grayscale_1956.tif and usgsImage_colorinfrared_1972.tif; digitized by Chris DeRolphroadNetwork_preUrbanRenewal.shp: road network present in urban renewal area before razing occurred; removed attribute indicates whether road was removed or remains today; historically removed roads were digitized by Chris DeRolph; remaining roads sourced from TDOT GIS roads dataTheBottom.shp: the approximate extent of the razed neighborhood known as The Bottom; digitized by Chris DeRolphUrbanRenewalProjects.shp: boundaries of the East Knoxville urban renewal projects, as mapped by the University of Richmond's Digital Scholarship Lab https://dsl.richmond.edu/panorama/renewal/#view=0/0/1&viz=cartogram&city=knoxvilleTN&loc=15/35.9700/-83.9080tiff is a folder that contains the following images:streetMap_1952.tif: relevant section of 1952 map 'Knoxville Tennessee and Surrounding Area'; copyright by J.U.G. Rich and East Tenn Auto Club; drawn by R.G. Austin; full map accessed at McClung Historical Collection, 601 S Gay St, Knoxville, TN 37902; used as reference for street names in roadNetwork_preUrbanRenewal.shp; georeferenced by Chris DeRolphnewsSentinelRdMap_1958.tif: urban renewal area map from 1958 Knox News Sentinel article; used as reference for street names in roadNetwork_preUrbanRenewal.shp; georeferenced by Chris DeRolphusgsImage_grayscale_1956.tif: May 18, 1956 black-and-white USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/ARA550590030582/usgsImage_colorinfrared_1972.tif: April 18, 1972 color infrared USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/AR6197002600096/usgsImage_grayscale_1976.tif: November 8, 1976 black-and-white USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/AR1VDUT00390010/

  17. Statewide Crop Mapping

    • data.cnra.ca.gov
    • data.ca.gov
    • +3more
    data, gdb, html +3
    Updated Mar 3, 2025
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    California Department of Water Resources (2025). Statewide Crop Mapping [Dataset]. https://data.cnra.ca.gov/dataset/statewide-crop-mapping
    Explore at:
    zip(94630663), zip(88308707), gdb(85891531), gdb(86886429), shp(107610538), zip(159870566), shp(126828193), gdb(76631083), zip(144060723), zip(140021333), shp(126548912), gdb(86655350), rest service, data, html, zip(169400976), zip(179113742), zip(98690638), zip(189880202)Available download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Description

    NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.

    Thank you for your interest in DWR land use datasets.

    The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.

    Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.

    For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.

    For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

    For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.

    Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.

  18. TIGER/Line Shapefile, Current, County, Richland County, IL, All Roads

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, Current, County, Richland County, IL, All Roads [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-current-county-richland-county-il-all-roads
    Explore at:
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Richland County
    Description

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

  19. T

    Utah Garfield County Parcels LIR

    • opendata.utah.gov
    application/rdfxml +5
    Updated Mar 20, 2020
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    (2020). Utah Garfield County Parcels LIR [Dataset]. https://opendata.utah.gov/dataset/Utah-Garfield-County-Parcels-LIR/t8h9-d3kr
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    json, csv, application/rssxml, xml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Mar 20, 2020
    Area covered
    Utah
    Description

    GIS Layer Boundary Geometry:

    GIS Format Data Files: Ideally, Tax Year Parcel data should be provided in a shapefile (please include the .shp, .shx, .dbf, .prj, and .xml component files) or file geodatabase format. An empty shapefile and file geodatabase schema are available for download at:

    ftp://ftp.agrc.utah.gov/UtahSGID_Vector/UTM12_NAD83/CADASTRE/LIR_ParcelSchema.zip

    At the request of a county, AGRC will provide technical assistance to counties to extract, transform, and load parcel and assessment information into the GIS layer format.

    Geographic Coverage: Tax year parcel polygons should cover the area of each county for which assessment information is created and digital parcels are available. Full coverage may not be available yet for each county. The county may provide parcels that have been adjusted to remove gaps and overlaps for administrative tax purposes or parcels that retain these expected discrepancies that take their source from the legally described boundary or the process of digital conversion. The diversity of topological approaches will be noted in the metadata.

    One Tax Parcel Record Per Unique Tax Notice: Some counties produce an annual tax year parcel GIS layer with one parcel polygon per tax notice. In some cases, adjacent parcel polygons that compose a single taxed property must be merged into a single polygon. This is the goal for the statewide layer but may not be possible in all counties. AGRC will provide technical support to counties, where needed, to merge GIS parcel boundaries into the best format to match with the annual assessment information.

    Standard Coordinate System: Parcels will be loaded into Utah’s statewide coordinate system, Universal Transverse Mercator coordinates (NAD83, Zone 12 North). However, boundaries stored in other industry standard coordinate systems will be accepted if they are both defined within the data file(s) and documented in the metadata (see below).

    Descriptive Attributes:

    Database Field/Column Definitions: The table below indicates the field names and definitions for attributes requested for each Tax Parcel Polygon record.

    FIELD NAME FIELD TYPE LENGTH DESCRIPTION EXAMPLE

    SHAPE (expected) Geometry n/a The boundary of an individual parcel or merged parcels that corresponds with a single county tax notice ex. polygon boundary in UTM NAD83 Zone 12 N or other industry standard coordinates including state plane systems

    COUNTY_NAME Text 20 - County name including spaces ex. BOX ELDER

    COUNTY_ID (expected) Text 2 - County ID Number ex. Beaver = 1, Box Elder = 2, Cache = 3,..., Weber = 29

    ASSESSOR_SRC (expected) Text 100 - Website URL, will be to County Assessor in most all cases ex. webercounty.org/assessor

    BOUNDARY_SRC (expected) Text 100 - Website URL, will be to County Recorder in most all cases ex. webercounty.org/recorder

    DISCLAIMER (added by State) Text 50 - Disclaimer URL ex. gis.utah.gov...

    CURRENT_ASOF (expected) Date - Parcels current as of date ex. 01/01/2016

    PARCEL_ID (expected) Text 50 - County designated Unique ID number for individual parcels ex. 15034520070000

    PARCEL_ADD (expected, where available) Text 100 - Parcel’s street address location. Usually the address at recordation ex. 810 S 900 E #304 (example for a condo)

    TAXEXEMPT_TYPE (expected) Text 100 - Primary category of granted tax exemption ex. None, Religious, Government, Agriculture, Conservation Easement, Other Open Space, Other

    TAX_DISTRICT (expected, where applicable) Text 10 - The coding the county uses to identify a unique combination of property tax levying entities ex. 17A

    TOTAL_MKT_VALUE (expected) Decimal - Total market value of parcel's land, structures, and other improvements as determined by the Assessor for the most current tax year ex. 332000

    LAND _MKT_VALUE (expected) Decimal - The market value of the parcel's land as determined by the Assessor for the most current tax year ex. 80600

    PARCEL_ACRES (expected) Decimal - Parcel size in acres ex. 20.360

    PROP_CLASS (expected) Text 100 - Residential, Commercial, Industrial, Mixed, Agricultural, Vacant, Open Space, Other ex. Residential

    PRIMARY_RES (expected) Text 1 - Is the property a primary residence(s): Y'(es), 'N'(o), or 'U'(nknown) ex. Y

    HOUSING_CNT (expected, where applicable) Text 10 - Number of housing units, can be single number or range like '5-10' ex. 1

    SUBDIV_NAME (optional) Text 100 - Subdivision name if applicable ex. Highland Manor Subdivision

    BLDG_SQFT (expected, where applicable) Integer - Square footage of primary bldg(s) ex. 2816

    BLDG_SQFT_INFO (expected, where applicable) Text 100 - Note for how building square footage is counted by the County ex. Only finished above and below grade areas are counted.

    FLOORS_CNT (expected, where applicable) Decimal - Number of floors as reported in county records ex. 2

    FLOORS_INFO (expected, where applicable) Text 100 - Note for how floors are counted by the County ex. Only above grade floors are counted

    BUILT_YR (expected, where applicable) Short - Estimated year of initial construction of primary buildings ex. 1968

    EFFBUILT_YR (optional, where applicable) Short - The 'effective' year built' of primary buildings that factors in updates after construction ex. 1980

    CONST_MATERIAL (optional, where applicable) Text 100 - Construction Material Types, Values for this field are expected to vary greatly by county ex. Wood Frame, Brick, etc

    Contact: Sean Fernandez, Cadastral Manager (email: sfernandez@utah.gov; office phone: 801-209-9359)

  20. SAFE experimental site layout GIS files

    • zenodo.org
    • explore.openaire.eu
    bin, zip
    Updated Jan 24, 2020
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    Rob Ewers; David Orme; David Orme; Rob Ewers (2020). SAFE experimental site layout GIS files [Dataset]. http://doi.org/10.5281/zenodo.3490675
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    zip, binAvailable download formats
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Rob Ewers; David Orme; David Orme; Rob Ewers
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Description:

    These zipfiles contain shapefiles showing the layout of the SAFE experimental area. The layout shapefile shows the realised locations of the experimental features within the wider converted landscape and the two fragment shapefiles show the planned circular fragments, as originally planned and as marked on the ground using GPS.

    These files were compiled from a wider set of GIS files and further details of the processing can be found here https://www.safeproject.net/dokuwiki/safe_gis/safe_layout.

    Project: This dataset was collected as part of the following SAFE research project: SAFE CORE DATA

    XML metadata: GEMINI compliant metadata for this dataset is available here

    Files: This dataset consists of 2 files: SAFE_GIS_Layout_metadata.xlsx, SAFE_layout_shapefiles.zip

    SAFE_GIS_Layout_metadata.xlsx

    This file only contains metadata for the files below

    SAFE_layout_shapefiles.zip

    Description: Contains three shapefiles. The layout shapefile shows the experimental fragments, riparian reserves and other features of the landscape and the two fragment files show the planned and then field walked edges of the main fractal fragment areas.

    This file contains 3 data tables:

    1. SAFE experimental site layout (described in worksheet SAFE_layout)

      Description: Properties for SAFE_Layout_UTM50N_WGS84 shapefile

      Number of fields: 4

      Number of data rows: Unavailable (table metadata description only).

      Fields:

      • CATEGORY: Category of feature (Field type: categorical)
      • LANDCOVER: Landcover type of feature (Field type: categorical)
      • WIDTH: Width of feature - does not apply to these features so these values are all NA. (Field type: numeric)
      • CODE: Names of fragments (Field type: location)

    2. Walked fragment polygons (described in worksheet SAFE_GPS_fragment_edges)

      Description: Properties for SAFE_GPS_fragment_edges_UTM50N_WGS84 shapefile, containing polygons of proposed fragments defined by walked GPS path in the field.

      Number of fields: 4

      Number of data rows: Unavailable (table metadata description only).

      Fields:

      • CATEGORY: Category of feature (Field type: categorical)
      • LANDCOVER: Landcover type of feature (Field type: categorical)
      • WIDTH: Width of feature - does not apply to these features so these values are all NA. (Field type: numeric)
      • CODE: Names of fragments (Field type: location)

    3. Planned fragment polygons (described in worksheet SAFE_planned_fragments)

      Description: Properties for SAFE_planned_fragments_UTM50N_WGS84 shapefile, containing planned circular footprints of fragments.

      Number of fields: 4

      Number of data rows: Unavailable (table metadata description only).

      Fields:

      • CATEGORY: Category of feature (Field type: categorical)
      • LANDCOVER: Landcover type of feature (Field type: categorical)
      • WIDTH: Width of feature - does not apply to these features so these values are all NA. (Field type: numeric)
      • CODE: Names of fragments (Field type: location)

    Date range: 2010-10-01 to 2019-10-01

    Latitudinal extent: 4.6348 to 4.7539

    Longitudinal extent: 116.9471 to 117.6588

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The County of Sonoma (2020). Parcels Public Shapefile [Dataset]. https://gis-sonomacounty.hub.arcgis.com/datasets/sonomacounty::parcels-public-shapefile/about

Parcels Public Shapefile

Explore at:
3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 11, 2020
Dataset authored and provided by
The County of Sonoma
License

Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
License information was derived automatically

Area covered
Description

The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. This layer is a partial view of the Information Sales System (ISS) extract, a report of property characteristics taken from the County’s Megabyte Property Tax System (MPTS). This layer may be missing some attributes (e.g., Owner Name) which may not be published to the Internet due to privacy conditions under the California Public Records Act (CPRA). Please contact the Clerk-Recorder-Assessor (CRA) office at (707) 565-1888 for information on availability, associated fees, and access to other versions of Sonoma County parcels containing additional property characteristics.The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

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