Overview

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.

A water right is a legal right to use surface or ground water under the Alaska Water Use Act (AS 46.15). A water right allows a specific amount of water from a specific water source to be diverted, impounded, or withdrawn for a specific use. When a water right is granted, it becomes appurtenant to the land where the water is being used for as long as the water is used. If the land is sold, the water right transfers with the land to the new owner, unless the Department of Natural Resources (DNR) approves its separation from the land. In Alaska, because water wherever it naturally occurs is a common property resource, landowners do not have automatic rights to ground water or surface water. For example, if a farmer has a creek running through his property, he will need a water right to authorize his use of a significant amount of water. Using water without a permit or certificate does not give the user a legal right to use the water. This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Subsurface Water Rights category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction. Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://www.dnr.state.ak.us/las/LASMenu.cfm Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

Download In State Plane Projection Here.

This dataset represents the water feature areas (for example, lakes and ponds) of Lake County, Illinois. The features captured in this polygon dataset include: lakes, ponds, detention/retention basins, river/streams/creeks greater than five feet wide, and islands.

The data has not been field verified and errors and/or omissions may be present.

The names used for the water bodies were collected from a number of sources including: existing datasets, historic maps and/or atlases, US Geologic Survey (USGS) Geographic Names Information System (GNIS), current and historical USGS topographic quadrangle maps, local publications on place names within the county, and platted subdivisions.

The dataset was updated to reflect changes in spring 2022. The water features were compiled using softcopy analytical stereoplotters. This dataset should meet National Map Accuracy Standards for a 1:1200 product and it is georeferenced to the Illinois State Plane, Eastern Zone, using the NAD83 HARN horizontal datum.

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

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

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

See section 5 of the metadata for an attribute summary.

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

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

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

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

This is a MetroGIS Regionally Endorsed dataset.

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

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

The Millennium Coral Reef Mapping Project provides thematic maps of coral reefs worldwide at geomorphological scale. Maps were created by photo-interpretation of Landsat 7 and Landsat 8 satellite images. Maps are provided as standard Shapefiles usable in GIS software. The geomorphological classification scheme is hierarchical and includes 5 levels. The GIS products include for each polygon a number of attributes. The 5 level geomorphological attributes are provided (numerical codes or text). The Level 1 corresponds to the differentiation between oceanic and continental reefs. Then from Levels 2 to 5, the higher the level, the more detailed the thematic classification is. Other binary attributes specify for each polygon if it belongs to terrestrial area (LAND attribute), and sedimentary or hard-bottom reef areas (REEF attribute). Examples and more details on the attributes are provided in the references cited. The products distributed here were created by IRD, in their last version. Shapefiles for 102 atolls of France (in the Pacific and Indian Oceans) as mapped by the Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). The data set provides one zip file per region of interest. Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). Funded by National Aeronautics and Space Administration, NASA grants NAG5-10908 (University of South Florida, PIs: Franck Muller-Karger and Serge Andréfouët) and CARBON-0000-0257 (NASA, PI: Julie Robinson) from 2001 to 2007. Funded by IRD since 2003 (in kind, PI: Serge Andréfouët).

This provides a polygon coastline and islands layer which is based on the Topo50 products. It is a combination of the following layers:

• NZ Coastlines (Topo 1:50k)
• NZ Island Polygons (Topo 1:50k)
• NZ Auckland Is Island Polygons (Topo, 1:50k)
• NZ Campbell Is / Motu Ihupuku Island Polygons (Topo, 1:50k)
• NZ Antipodes Is Island Polygons (Topo, 1:25k)
• NZ Kermadec Is Island Polygons (Topo, 1:25k)
• NZ Bounty Is Island Polygons (Topo, 1:25k)
• NZ Snares Is / Tini Heke Island Polygons (Topo, 1:25k)
• NZ Chatham Is island polygons (Topo, 1:50k)

This topographic coastline is the line forming the boundary between the land and sea, defined by mean high water.

Islands from the NZ Island Polygons layer that lie within the NZ Coastline and Chatham Islands areas (i.e. islands in lakes, rivers and estuaries) have been removed.

The GIS workflow to create the layer is:

1. NZ Coastlines were converted from a polyline to a polygon using a polyline to polygon tool.
2. The resulting coastal polygon was then used as an input into an erase tool and run against the NZ Island Polygon layer to remove all islands lying within the NZ Mainland and Stewart Island.
3. This was then merged with the NZ Chatham Is island polygons (Topo, 1:50k) that have had the islands within the main island polygon removed, NZ Auckland Is Island Polygons (Topo, 1:50k), NZ Campbell Is / Motu Ihupuku Island, NZ Antipodes Is Island Polygons (Topo, 1:25k), NZ Kermadec Is Island Polygons (Topo, 1:25k), NZ Bounty Is Island Polygons (Topo, 1:25k) and NZ Snares Is / Tini Heke Island Polygons (Topo, 1:25k) layers using a merge tool.

For more detailed description of each layer refer to the layer urls above.

APIs and web services This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services ArcGIS Online map services ArcGIS REST API

This 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.

This is an annual version of the MetroGIS Regional Parcel Dataset that can be used with other annual versions to do change analysis and time series investigations. This dataset is intended to contain all updates to each county's parcel data through the end of 2004. It was originally published as the 'January 1, 2005' version of the dataset. See the Currentness Reference below and the Entity and Attribute information in Section 5 for more information about the dates for specific aspects of the dataset.

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, 2005 dataset):

Anoka = 124,042 polygons, 124,042 points
Carver = 32,910 polygons, 32,910 points
Dakota = 130,989 polygons, 141,444 points
Hennepin = 353,759 polygons, 399,184 points
Ramsey = 148,266 polygons, 163,376 points
Scott = 49,958 polygons, 49,958 points
Washington = 93,794 polygons, 96,570 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 2004 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

A GIS polygon shapefile outlining the extent of the 14 individual DEM sections that comprise the seamless, 2-meter resolution DEM for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the north-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 meter elevation contour.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Using the National Vegetation Classification System (NVCS) developed by Natureserve, with additional classes and modifiers, overstory vegetation communities for each park were interpreted from stereo color infrared aerial photographs using manual interpretation methods. Using a minimum mapping unit of 0.5 hectares (MMU = 0.5 ha), polygons representing areas of relatively uniform vegetation were delineated and annotated on clear plastic overlays registered to the aerial photographs. Polygons were labeled according to the dominant vegetation community. Where the polygons were not uniform, second and third vegetation classes were added. Further, a number of modifier codes were employed to indicate important aspects of the polygon that could be interpreted from the photograph (for example, burn condition). The polygons on the plastic overlays were then corrected using photogrammetric procedures and converted to vector format for use in creating a geographic information system (GIS) database for each park. In addition, high resolution color orthophotographs were created from the original aerial photographs for use in the GIS. Upon completion of the GIS database (including vegetation, orthophotos and updated roads and hydrology layers), both hardcopy and softcopy maps were produced for delivery. Metadata for each database includes a description of the vegetation classification system used for each park, summary statistics and documentation of the sources, procedures and spatial accuracies of the data. At the time of this writing, an accuracy assessment of the vegetation mapping has not been performed for most of these parks.

This feature layer contains planimetric polygons located within Linn County, Iowa and outside the City of Cedar Rapids boundaries. Examples of features found within this layer may include:Building footprintsSidewalksDrivewaysEdge of road pavementPaved parkingFor planimetric data within the City of Cedar Rapids boundaries, please contact the City GIS department.Update FrequencyApproximately once a monthAdditional ResourcesVisit Linn County, Iowa on the web.Visit Linn County, Iowa GIS on the web.Visit the Linn County, Iowa GIS portal. This site is updated as needed to reflect maps, apps, and data of interest from various County departments.Contact InformationQuestions? Contact the GIS Division by phone at 319.892.5250 or by email.

esmtrow_poly: This data set represents areal ROWs and Easements. Rights-of-Way and Easements that are linear in nature, such as roads or power lines, have associated widths that can be used to buffer the linear features and create polygon areas. Area entities include these linear buffer features as well as ROWs and Easements described by parcels. These are a portion of the total ENCUMBRANCE data category which includes entities about rights and restrictions. The rights and restrictions relate to the use of federal public land or to the use of non-federal land by the federal and public entities. Example uses might be construction or simply crossing the land. Rights-of-way in this data set include ROW and other land use authorizations issued by the United States under the authorities of Title V and Sec. 302(b) of Federal Land Policy and Management Act (FLPMA) (and other ROW authorities repealed by FLPMA) ,O Act of August 28, 1937, plus the Federal Highway Act and the Mineral Leasing Act. Easements in this data set are the spatial representation of partial interests in non-federal land acquired or reserved by the United States. In general, ROWs are rights granted by BLM and Easements are rights granted to BLM, but there are exceptions. The data set includes both linear and area entities. This data set is not intended to include all ROWs and Easements, but only those most important for common GIS spatial analysis. In addition, only basic information about the ROWs and Easements is provided. Details and the complete rights and restrictions history are found in the authoritative sources: Master Title Plats, case file records, and the LR2000 database.

This 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

A water right is a legal right to use surface or ground water under the Alaska Water Use Act (AS 46.15). A water right allows a specific amount of water from a specific water source to be diverted, impounded, or withdrawn for a specific use. When a water right is granted, it becomes appurtenant to the land where the water is being used for as long as the water is used. If the land is sold, the water right transfers with the land to the new owner, unless the Department of Natural Resources (DNR) approves its separation from the land. In Alaska, because water wherever it naturally occurs is a common property resource, landowners do not have automatic rights to ground water or surface water. For example, if a farmer has a creek running through his property, he will need a water right to authorize his use of a significant amount of water. Using water without a permit or certificate does not give the user a legal right to use the water. This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Subsurface Water Rights category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction. Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://www.dnr.state.ak.us/las/LASMenu.cfm Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

This geodatabase of point, line and polygon features is an effort to consolidate all of the range improvement locations on BLM-managed land in Idaho into one database. Currently, the polygon feature class has some data for all of the BLM field offices except the Coeur d'Alene and Cottonwood field offices. Range improvements are structures intended to enhance rangeland resources, including wildlife, watershed, and livestock management. Examples of range improvements include water troughs, spring headboxes, culverts, fences, water pipelines, gates, wildlife guzzlers, artificial nest structures, reservoirs, developed springs, corrals, exclosures, etc. These structures were first tracked by the Bureau of Land Management (BLM) in the Job Documentation Report (JDR) System in the early 1960s, which was predominately a paper-based tracking system. In 1988 the JDRs were migrated into and replaced by the automated Range Improvement Project System (RIPS), and version 2.0 is currently being used today. It tracks inventory, status, objectives, treatment, maintenance cycle, maintenance inspection, monetary contributions and reporting. Not all range improvements are documented in the RIPS database; there may be some older range improvements that were built before the JDR tracking system was established. There also may be unauthorized projects that are not in RIPS. Official project files of paper maps, reports, NEPA documents, checklists, etc., document the status of each project and are physically kept in the office with management authority for that project area. In addition, project data is entered into the RIPS system to enable managers to access the data to track progress, run reports, analyze the data, etc. Before Geographic Information System technology most offices kept paper atlases or overlay systems that mapped the locations of the range improvements. The objective of this geodatabase is to migrate the location of historic range improvement projects into a GIS for geospatial use with other data and to centralize the range improvement data for the state. This data set is a work in progress and does not have all range improvement projects that are on BLM lands. Some field offices have not migrated their data into this database, and others are partially completed. New projects may have been built but have not been entered into the system. Historic or unauthorized projects may not have case files and are being mapped and documented as they are found. Many field offices are trying to verify the locations and status of range improvements with GPS, and locations may change or projects that have been abandoned or removed on the ground may be deleted. Attributes may be incomplete or inaccurate. This data was created using the standard for range improvements set forth in Idaho IM 2009-044, dated 6/30/2009. However, it does not have all of the fields the standard requires. Fields that are missing from the polygon feature class that are in the standard are: ALLOT_NO, POLY_TYPE, MGMT_AGCY, ADMIN_ST, and ADMIN_OFF. The polygon feature class also does not have a coincident line feature class, so some of the fields from the polygon arc feature class are included in the polygon feature class: COORD_SRC, COORD_SRC2, DEF_FET, DEF_FEAT2, ACCURACY, CREATE_DT, CREATE_BY, MODIFY_DT, MODIFY_BY, GPS_DATE, and DATAFILE. There is no National BLM standard for GIS range improvement data at this time. For more information contact us at blm_id_stateoffice@blm.gov.

Salt Wells-ESRI Geodatabase (ArcGeology v1.3): - Contains all the geologic map data, including faults, contacts, folds, dikes, unit polygons, and attitudes of strata and faults. - List of stratigraphic units and stratigraphic correlation diagram. - Locations of 40Ar/39Ar samples.

NYS Building Footprints - metadata info:The New York State building footprints service contains building footprints with address information. The footprints have address point information folded in from the Streets and Address Matching (SAM - https://gis.ny.gov/streets/) address point file. The building footprints have a field called “Address Range”, this field shows (where available) either a single address or an address range, depending on the address points that fall within the footprint. Ex: 3860 Atlantic Avenue or Ex: 32 - 34 Wheatfield Circle Building footprints in New York State are from four different sources: Microsoft, Open Data, New York State Energy Research and Development Authority (NYSERDA), and Geospatial Services. The majority of the footprints are from NYSERDA, except in NYC where the primary source was Open Data. Microsoft footprints were added where the other 2 sources were missing polygons. Field Descriptions: NYSGeo Source : tells the end user if the source is NYSERDA, Microsoft, NYC Open Data, and could expand from here in the futureAddress Point Count: the number of address points that fall within that building footprintAddress Range : If an address point falls within a footprint it lists the range of those address points. Ex: if a building is on a corner of South Pearl and Beaver Street, 40 points fall on the building, and 35 are South Pearl Street it would give the range of addresses for South Pearl. We also removed sub addresses from this range, primarily apartment related. For example, in above example, it would not list 30 South Pearl, Apartment 5A, it would list 30 South Pearl.Most Common Street : the street name of the largest number of address points. In the above example, it would list “South Pearl” as the most common street since the majority of address points list it as the street. Other Streets: the list of other streets that fall within the building footprint, if any. In the above example, “Beaver Street” would be listed since address points for Beaver Street fall on the footprint but are not in the majority.County Name : County name populated from CIESINs. If not populated from CIESINs, identified by the GSMunicipality Name : Municipality name populated from CIESINs. If not populated from CIESINs, identified by the GSSource: Source where the data came from. If NYSGeo Source = NYSERDA, the data would typically list orthoimagery, LIDAR, county data, etc.Source ID: if NYSGeo Source = NYSERDA, Source ID would typically list an orthoimage or LIDAR tileSource Date: Date the footprint was created. If the source image was from 2016 orthoimagery, 2016 would be the Source Date. Description of each footprint source:NYSERDA Building footprints that were created as part of the New York State Flood Impact Decision Support Systems https://fidss.ciesin.columbia.edu/home Footprints vary in age from county to county.Microsoft Building Footprints released 6/28/2018 - vintage unknown/varies. More info on this dataset can be found at https://blogs.bing.com/maps/2018-06/microsoft-releases-125-million-building-footprints-in-the-us-as-open-data.NYC Open Data - Building Footprints of New York City as a polygon feature class. Last updated 7/30/2018, downloaded on 8/6/2018. Feature Class of footprint outlines of buildings in New York City. Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_BuildingFootprints.mdSpatial Reference of Source Data: UTM Zone 18, meters, NAD 83. Spatial Reference of Web Service: Spatial Reference of Web Service: WGS 1984 Web Mercator Auxiliary Sphere.

Jurisdictional Unit, 2022-05-21. For use with WFDSS, IFTDSS, IRWIN, and InFORM.This is a feature service which provides Identify and Copy Feature capabilities. If fast-drawing at coarse zoom levels is a requirement, consider using the tile (map) service layer located at https://nifc.maps.arcgis.com/home/item.html?id=3b2c5daad00742cd9f9b676c09d03d13.OverviewThe Jurisdictional Agencies dataset is developed as a national land management geospatial layer, focused on representing wildland fire jurisdictional responsibility, for interagency wildland fire applications, including WFDSS (Wildland Fire Decision Support System), IFTDSS (Interagency Fuels Treatment Decision Support System), IRWIN (Interagency Reporting of Wildland Fire Information), and InFORM (Interagency Fire Occurrence Reporting Modules). It is intended to provide federal wildland fire jurisdictional boundaries on a national scale. The agency and unit names are an indication of the primary manager name and unit name, respectively, recognizing that:There may be multiple owner names.Jurisdiction may be held jointly by agencies at different levels of government (ie State and Local), especially on private lands, Some owner names may be blocked for security reasons.Some jurisdictions may not allow the distribution of owner names. Private ownerships are shown in this layer with JurisdictionalUnitIdentifier=null,JurisdictionalUnitAgency=null, JurisdictionalUnitKind=null, and LandownerKind="Private", LandownerCategory="Private". All land inside the US country boundary is covered by a polygon.Jurisdiction for privately owned land varies widely depending on state, county, or local laws and ordinances, fire workload, and other factors, and is not available in a national dataset in most cases.For publicly held lands the agency name is the surface managing agency, such as Bureau of Land Management, United States Forest Service, etc. The unit name refers to the descriptive name of the polygon (i.e. Northern California District, Boise National Forest, etc.).These data are used to automatically populate fields on the WFDSS Incident Information page.This data layer implements the NWCG Jurisdictional Unit Polygon Geospatial Data Layer Standard.Relevant NWCG Definitions and StandardsUnit2. A generic term that represents an organizational entity that only has meaning when it is contextualized by a descriptor, e.g. jurisdictional.Definition Extension: When referring to an organizational entity, a unit refers to the smallest area or lowest level. Higher levels of an organization (region, agency, department, etc) can be derived from a unit based on organization hierarchy.Unit, JurisdictionalThe governmental entity having overall land and resource management responsibility for a specific geographical area as provided by law.Definition Extension: 1) Ultimately responsible for the fire report to account for statistical fire occurrence; 2) Responsible for setting fire management objectives; 3) Jurisdiction cannot be re-assigned by agreement; 4) The nature and extent of the incident determines jurisdiction (for example, Wildfire vs. All Hazard); 5) Responsible for signing a Delegation of Authority to the Incident Commander.See also: Unit, Protecting; LandownerUnit IdentifierThis data standard specifies the standard format and rules for Unit Identifier, a code used within the wildland fire community to uniquely identify a particular government organizational unit.Landowner Kind & CategoryThis data standard provides a two-tier classification (kind and category) of landownership. Attribute Fields JurisdictionalAgencyKind Describes the type of unit Jurisdiction using the NWCG Landowner Kind data standard. There are two valid values: Federal, and Other. A value may not be populated for all polygons.JurisdictionalAgencyCategoryDescribes the type of unit Jurisdiction using the NWCG Landowner Category data standard. Valid values include: ANCSA, BIA, BLM, BOR, DOD, DOE, NPS, USFS, USFWS, Foreign, Tribal, City, County, OtherLoc (other local, not in the standard), State. A value may not be populated for all polygons.JurisdictionalUnitNameThe name of the Jurisdictional Unit. Where an NWCG Unit ID exists for a polygon, this is the name used in the Name field from the NWCG Unit ID database. Where no NWCG Unit ID exists, this is the “Unit Name” or other specific, descriptive unit name field from the source dataset. A value is populated for all polygons.JurisdictionalUnitIDWhere it could be determined, this is the NWCG Standard Unit Identifier (Unit ID). Where it is unknown, the value is ‘Null’. Null Unit IDs can occur because a unit may not have a Unit ID, or because one could not be reliably determined from the source data. Not every land ownership has an NWCG Unit ID. Unit ID assignment rules are available from the Unit ID standard, linked above.LandownerKindThe landowner category value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. A value is populated for all polygons. There are three valid values: Federal, Private, or Other.LandownerCategoryThe landowner kind value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. A value is populated for all polygons. Valid values include: ANCSA, BIA, BLM, BOR, DOD, DOE, NPS, USFS, USFWS, Foreign, Tribal, City, County, OtherLoc (other local, not in the standard), State, Private.DataSourceThe database from which the polygon originated. Be as specific as possible, identify the geodatabase name and feature class in which the polygon originated.SecondaryDataSourceIf the Data Source is an aggregation from other sources, use this field to specify the source that supplied data to the aggregation. For example, if Data Source is "PAD-US 2.1", then for a USDA Forest Service polygon, the Secondary Data Source would be "USDA FS Automated Lands Program (ALP)". For a BLM polygon in the same dataset, Secondary Source would be "Surface Management Agency (SMA)."SourceUniqueIDIdentifier (GUID or ObjectID) in the data source. Used to trace the polygon back to its authoritative source.MapMethod:Controlled vocabulary to define how the geospatial feature was derived. Map method may help define data quality. MapMethod will be Mixed Method by default for this layer as the data are from mixed sources. Valid Values include: GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; DigitizedTopo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; Phone/Tablet; OtherDateCurrentThe last edit, update, of this GIS record. Date should follow the assigned NWCG Date Time data standard, using 24 hour clock, YYYY-MM-DDhh.mm.ssZ, ISO8601 Standard.CommentsAdditional information describing the feature. GeometryIDPrimary key for linking geospatial objects with other database systems. Required for every feature. This field may be renamed for each standard to fit the feature.JurisdictionalUnitID_sansUSNWCG Unit ID with the "US" characters removed from the beginning. Provided for backwards compatibility.JoinMethodAdditional information on how the polygon was matched information in the NWCG Unit ID database.LocalNameLocalName for the polygon provided from PADUS or other source.LegendJurisdictionalAgencyJurisdictional Agency but smaller landholding agencies, or agencies of indeterminate status are grouped for more intuitive use in a map legend or summary table.LegendLandownerAgencyLandowner Agency but smaller landholding agencies, or agencies of indeterminate status are grouped for more intuitive use in a map legend or summary table.DataSourceYearYear that the source data for the polygon were acquired.Data InputThis dataset is based on an aggregation of 4 spatial data sources: Protected Areas Database US (PAD-US 2.1), data from Bureau of Indian Affairs regional offices, the BLM Alaska Fire Service/State of Alaska, and Census Block-Group Geometry. NWCG Unit ID and Agency Kind/Category data are tabular and sourced from UnitIDActive.txt, in the WFMI Unit ID application (https://wfmi.nifc.gov/unit_id/Publish.html). Areas of with unknown Landowner Kind/Category and Jurisdictional Agency Kind/Category are assigned LandownerKind and LandownerCategory values of "Private" by use of the non-water polygons from the Census Block-Group geometry.PAD-US 2.1:This dataset is based in large part on the USGS Protected Areas Database of the United States - PAD-US 2.`. PAD-US is a compilation of authoritative protected areas data between agencies and organizations that ultimately results in a comprehensive and accurate inventory of protected areas for the United States to meet a variety of needs (e.g. conservation, recreation, public health, transportation, energy siting, ecological, or watershed assessments and planning). Extensive documentation on PAD-US processes and data sources is available.How these data were aggregated:Boundaries, and their descriptors, available in spatial databases (i.e. shapefiles or geodatabase feature classes) from land management agencies are the desired and primary data sources in PAD-US. If these authoritative sources are unavailable, or the agency recommends another source, data may be incorporated by other aggregators such as non-governmental organizations. Data sources are tracked for each record in the PAD-US geodatabase (see below).BIA and Tribal Data:BIA and Tribal land management data are not available in PAD-US. As such, data were aggregated from BIA regional offices. These data date from 2012 and were substantially updated in 2022. Indian Trust Land affiliated with Tribes, Reservations, or BIA Agencies: These data are not considered the system of record and are not intended to be used as such. The Bureau of Indian Affairs (BIA), Branch of Wildland Fire Management (BWFM) is not the originator of these data. The

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