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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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Depicts the area of activities funded through the NFRR Budget Line Item and reported through the FACTS database. (The activities fall under number of acres treated annually to sustain or restore watershed function: acres of forestlands treated using timber sales, acres of forestland vegetation improved, acres of forestland vegetation established, acres of rangeland vegetation improved, acres treated for noxious weeds/invasive plants on NFS lands, and acres of hazardous fuels treated outside the wildland/urban interface (WUI) to reduce the risk of catastrophic wildland fire) and are self-reported by Forest Service Units. Metadata
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TwitterNote: This is a large dataset. To download, go to ArcGIS Open Data Set and click the download button, and under additional resources select the shapefile or geodatabase option. The Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS) is the agency standard for managing information about activities related to fire/fuels, silviculture, and invasive species. FACTS is an activity tracking application for all levels of the Forest Service. The application allows tracking and monitoring of NEPA decisions as well as the ability to create and manage KV trust fund plans at the timber sale level. This application complements its companion NRM applications, which cover the spectrum of living and non-living natural resource information. This layer represents activities of hazardous fuel treatment reduction that are polygons. All accomplishments toward the unified hazardous fuels reduction target must meet the following definition: Vegetative manipulation designed to create and maintain resilient and sustainable landscapes, including burning, mechanical treatments, and/or other methods that reduce the quantity or change the arrangement of living or dead fuel so that the intensity, severity, or effects of wildland fire are reduced within acceptable ecological parameters and consistent with land management plan objectives, or activities that maintain desired fuel conditions. These conditions should be measurable or predictable using fire behavior prediction models or fire effects models. Go to this url for full metadata description: https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.Activity_HazFuelTrt_PL.xml
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TwitterThis is a publicly available map image service with limited GIS attributes. A downloadable version of this data is now available through the MDOT GIS Open Data Portal: Download MDOT SHA Right-of-Way Polygons (Open Data Portal) The following related versions of this data are available here:MDOT SHA Right-of-Way (Secured)Line dataFull attribute tableAccessible to only MDOT employees and contractors upon requestMDOT SHA Right-of-Way (Map Image Service)Read-only map serviceLine dataLimited attributes (quality level)Accessible to publicMDOT SHA Right-of-Way data is a composite layer of PSD field-collected survey sources, PSD in-house computations, traced PSD hardcopy materials, and historical Maryland Department of Planning (MDP) parcel boundaries.This data product was intended to replace MDOT SHA Planning Level Right-of-Way (Tax Map Legacy), which is an increasingly obsolete legacy product for MDOT SHA Right-of-Way information that in some areas remains the most comprehensive. For continuity, many MDP parcel boundaries found in MDOT SHA Planning Level Right-of-Way (Tax Map Legacy) have been incorporated into MDOT SHA Right-of-Way data with an "Estimated" quality level. Please see below for a description of the primary attribute.-----------------------------------------------------The polygons in this layer are divided into 318 arbitrary grid zones across the State of Maryland. Updates to the parent ROW boundary line data set [MDOT SHA Right-of-Way (Secured)] are made by grid and reflected in this polygon layer.For more information or to report errors in this data, please contact MDOT SHA OIT Enterprise Information Services:Email: GIS@mdot.maryland.gov
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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The SMA implementation is comprised of one feature dataset, with several polygon feature classes, rather than a single feature class. SurfaceManagementAgency: The Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. The SMA feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agencyâ s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. SMA_Withdrawals: The Surface Management Agency (SMA) Withdrawals Geographic Information System (GIS) dataset includes all of the known withdrawals which transfer surface jurisdictional responsibilities to federal agencies. The SMA Withdrawls feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA Withdrawal is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SMA Withdrawals will include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. These data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. SPP_WithdrawalAreas: The Special Public Purpose (SPP) Withdrawals Geographic Information System (GIS) dataset includes all of the known SPP Withdrawal Areas, which limit use or access to Federal lands (e.g. Wilderness, National Monument). The Special Public Purpose Withdrawal Areas feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SPP Withdrawal Area is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SPP Withdrawals include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. These data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.
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TwitterBusiness Analyst Polygons Layer
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Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.
Our self-hosted GIS data cover administrative and postal divisions with up to 6 precision levels: a zip code layer and up to 5 administrative levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.
The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.
Use cases for the Global Boundaries Database (GIS data, Geospatial data)
In-depth spatial analysis
Clustering
Geofencing
Reverse Geocoding
Reporting and Business Intelligence (BI)
Product Features
Coherence and precision at every level
Edge-matched polygons
High-precision shapes for spatial analysis
Fast-loading polygons for reporting and BI
Multi-language support
For additional insights, you can combine the GIS data with:
Population data: Historical and future trends
UNLOCODE and IATA codes
Time zones and Daylight Saving Time (DST)
Data export methodology
Our geospatial data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson
All GIS data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why companies choose our map data
Precision at every level
Coverage of difficult geographies
No gaps, nor overlaps
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
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TwitterThis data represents building outlines as captured primarily from planimetric updates. The data also contains flags for if the building is a school, fire station, county office, library, hospital, or voting location.
Contact: Department of Environmental Services
Data Accessibility: Publicly Available
Update Frequency: As Needed
Last Revision Date: 11/27/2023
Creation Date: 11/27/2023
Feature Dataset Name: Building
Layer Name: Building_poly
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TwitterWARNING: 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:
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:
Point of Contact
California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov
Field and Abbreviation Definitions
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
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TwitterThis polygon layer complies with L3 of the MassGIS Digital Parcel Standard. Parcel editing is completed as needed based on information from the City of Worcester Assessor.More information: Visit the MassGIS Digital Parcel Standard to learn more.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.
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TwitterThe Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS) is the agency standard for managing information aboutactivities related to fire/fuels, silviculture, and invasive species. FACTS is an activity tracking application for all levels of the Forest Service. The application allows tracking and monitoring of NEPA decisions as well as the ability to create and manage KV trust fund plans at the timber sale level. This application complements its companion NRM applications, which cover the spectrum of living and non-living natural resource information. This layer represents Collaborative Forest Landscape Restoration (CFLR) Program project activities. Also included are other High Priority Restoration projects that are funded outside of CFLR. It is important to note that this layer does not contain all of the approved project activities. Instead, these are the accomplishments that project groups uploaded to the Forest Service corporate data holdings in FACTS. As spatial data is a new requirement for the program, improvements to the quality and comprehensiveness of this data is expected in coming years. Metadata
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TwitterActivities meeting the Monarch Butterfly Habitat Restoration initiative are a subset of activities that benefit native plants, and in doing so, benefit pollinators. Activities such as thinning, prescribed fire and other methods of fuel removal, treating invasive species and acres of native plantings can benefit Monarchs. Activities are self-reported by Forest Service Units and are reported when completed. This layer does not contain all activities that benefit Monarchs because this is a relatively new requirement for the program. The quality and comprehensiveness of this data will increase over time. Metadata
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TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
Polygon Layer of the Santa Ana Parks
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TwitterThis data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats. Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format). Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data.
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TwitterThe Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. The SMA feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. The SMA Withdrawals feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA Withdrawal is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SMA Withdrawals will include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.
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TwitterThis dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will 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. The primary example of this is the condominium. 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 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.
Polygon and point counts for each county are as follows (based on the January, 2007 dataset):
Anoka = 129,392 polygons, 129,392 points
Carver = 37,021 polygons, 37,021 points
Dakota = 135,586 polygons, 148,952 points
Hennepin = 358,064 polygons, 419,736 points
Ramsey = 148,967 polygons, 166,280 points
Scott = 54,741 polygons, 54,741 points
Washington = 97,922 polygons, 102,309 points
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2006 document.
Additional information may be available in the individual metadata for 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 listed in the individual county metadata.
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: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
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TwitterThis dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
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. The 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.
Polygon and point counts for each county are as follows (based on the July 2010 dataset unless otherwise noted):
polygons / points
Anoka - 129271 / 129271
Carver - 38205 / 38205
Dakota - 136067 / 150436
Hennepin - 424182 / 424182
Ramsey - 149101 / 168152
Scott - 55213 / 55213
Washington - 98933 / 104100 (October 2009)
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2010 document.
Additional information may be available in the individual metadata for 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 listed in the individual county metadata.
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: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
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TwitterThis dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.
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. The 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.
Polygon and point counts for each county are as follows (Updated annually, current as of 1/15/2014):
polygons / points
Anoka - 130052 / 130052
Carver - 39639 / 39639
Dakota - 138356 / 151873
Hennepin - 425977 / 425977
Ramsey - 148841 / 166648
Scott - 55732 / 55732
Washington - 105525 / 105525
This is a MetroGIS Regionally Endorsed dataset.
Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.
A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2013 document.
Additional information may be available in the individual metadata for 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 listed in the individual county metadata.
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: http://www.hennepin.us/gisopendata
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps
Washington = http://www.co.washington.mn.us/index.aspx?NID=1606
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TwitterThis is a GIS dataset containing digitized and attributed polygon features from scanned Alberta Geological Survey Maps 201, 202, 203 and 204. The data show the surficial geology of the Calgary urban area (NTS areas 82O/01, 82P/04, 82J/16 and 82I/13) and are attributed with stratigraphic unit, lithology, lithogenesis, morphology, veneer material and the unit labels as shown on the maps. The data from the four maps are presented in a single polygon layer.
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TwitterThis is a GIS dataset containing digitized and attributed polygon features from scanned Alberta Geological Survey Maps 201, 202, 203 and 204. The data show the supplemental surficial geology of the Calgary urban area (NTS areas 82O/01, 82P/04, 82J/16 and 82I/13). Polygons, representing a discontinuous layer, are attributed as sand and silt veneer or buried sand, as shown on the maps. The data from the four maps are presented in a single polygon layer.
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TwitterActivity Project Area NEPA represents an area (polygon) within which one or more activities related to the National Environmental Policy Act (NEPA) are aggregated or organized. The data comes from the Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS), which is the agency standard for managing information about activities related to fire/fuels, silviculture, and invasive species. FACTS is an activity tracking application for all levels of the Forest Service.These data are a central source for project area boundaries for use in national information requests and cross unit analysis and makes the project area boundaries and their basic attributes more easily available to field units. It also provides public access to the data during project planning and implementation. Please note that this dataset is not complete and forests continue to improve the quality of the data over time.Metadata and Downloads
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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Depicts the area of activities funded through the NFRR Budget Line Item and reported through the FACTS database. (The activities fall under number of acres treated annually to sustain or restore watershed function: acres of forestlands treated using timber sales, acres of forestland vegetation improved, acres of forestland vegetation established, acres of rangeland vegetation improved, acres treated for noxious weeds/invasive plants on NFS lands, and acres of hazardous fuels treated outside the wildland/urban interface (WUI) to reduce the risk of catastrophic wildland fire) and are self-reported by Forest Service Units. Metadata