This vector tile layer presents the World Street Map (Local Language) style (World Edition) and provides a basemap for the world, symbolized with a classic Esri street map style. This comprehensive street map includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries. Labels are in local languages at large scale. This vector tile layer provides unique capabilities for customization, high-resolution display, and use in mobile devices.This vector tile layer is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.This layer is used in the Streets (Local Language) web map included in ArcGIS Living Atlas of the World.See the Vector Basemaps group for other vector tile layers. Customize this StyleLearn more about customizing this vector basemap style using the Vector Tile Style Editor. Additional details are available in ArcGIS Online Blogs and the Esri Vector Basemaps Reference Document.

HSIP Local Emergency Operations Centers in the United States "The physical location at which the coordination of information and resources to support domestic incident management activities normally takes place. An Emergency Operations Center may be a temporary facility or may be located in a more central or permanently established facility, perhaps at a higher level of organization within a jurisdiction. Emergency Operations Centers may be organized by major functional disciplines (e.g., fire, law enforcement, and medical services), by jurisdiction (e.g., Federal, State, regional, county, city, tribal), or some combination thereof." (Excerpted from the National Incident Management System) The GFI source for this layer contains State and Federal Emergency Operations Centers in addition to local Emergency Operations Centers. This dataset contains these features as well. In cases where an Emergency Operations Center has a mobile unit, TechniGraphics captured the location of the mobile unit as a separate record. This record represents where the mobile unit is stored. If this location could not be verified, a point was placed in the approximate center of the Emergency Operations Centers service area. Effort was made by TechniGraphics to verify whether or not each Emergency Operations Center has a generator on-site and whether or not the Emergency Operations Center is located in a basement. This information is indicated by the values in the [GENERATOR] and [BASEMENT] fields respectively. In cases where more than one record existed for a geographical area (e.g., county, city), TechniGraphics verified whether or not one of the records represented an alternate location. This was indicated by appending "-ALTERNATE" to the value in the [NAME] field. Some Emergency Operations Centers are located at private residences. The [TYPE] field was manually evaluated during the delivery process to compare the records in which the [NAME] field contained "-ALTERNATE". In cases where these values contradicted information that was verified by TechniGraphics (e.g. [NAME] contained "-ALTERNATE" and [TYPE] = "PRIMARY"), the value in the [TYPE] field was changed to match the type indicated by the [NAME] of the verified record. TechniGraphics did not change values in this field if the type was not verified. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard HSIP fields that TechniGraphics populated. Double spaces were replaced by single spaces in these same fields. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this attribute, the oldest record dates from 08/28/2009 and the newest record dates from 11/18/2009.

These geocoded locations are based on the Allegheny County extract of Educational Names & Addresses (EdNA) via Pennsylvania Department of Education website as of April 19, 2018. Several addresses were not able to be geocoded (ex. If PO Box addresses were provided, they were not geocoded.)

This web map created by the Colorado Governor's Office of Information Technology GIS team, serves as a basemap specific to the state of Colorado. The basemap includes general layers such as counties, municipalities, roads, waterbodies, state parks, national forests, national wilderness areas, and trails.Layers:Layer descriptions and sources can be found below. Layers have been modified to only represent features within Colorado and are not up to date. Layers last updated February 23, 2023. Colorado State Extent: Description: “This layer provides generalized boundaries for the 50 States and the District of Columbia.” Notes: This layer was filtered to only include the State of ColoradoSource: Esri Living Atlas USA States Generalized Boundaries Feature LayerState Wildlife Areas:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state wildlife areas layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer hosted in ArcGIS Online Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerMunicipal Boundaries:Description: "Boundaries data from the State Demography Office of Colorado Municipalities provided by the Department of Local Affairs (DOLA)"Source: Colorado Information Marketplace Municipal Boundaries in ColoradoCounties:Description: “This layer presents the USA 2020 Census County (or County Equivalent) boundaries of the United States in the 50 states and the District of Columbia. It is updated annually as County (or County Equivalent) boundaries change. The geography is sources from US Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrology to add a detailed coastline for cartographic purposes. Geography last updated May 2022.” Notes: This layer was filtered to only include counties in the State of ColoradoSource: Esri USA Census Counties Feature LayerInterstates:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: Interstates are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointU.S. Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: U.S. Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointState Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: State Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointMajor Roads:Description: Authoritative data from the Colorado Department of Transportation representing major roads Source: Colorado Department of Transportation Major Roads REST EndpointLocal Roads:Description: Authoritative data from the Colorado Department of Transportation representing local roads Source: Colorado Department of Transportation Local Roads REST EndpointRail Lines:Description: Authoritative data from the Colorado Department of Transportation representing rail lines Source: Colorado Department of Transportation Rail Lines REST EndpointCOTREX Trails:Description: “The Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently their are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments). Responsibility for accuracy of the data rests with the source.These data were last updated on 2/5/2019” Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerNHD Waterbodies:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include waterbodies in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerNHD Flowlines:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include flowline features in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerState Parks:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state parks layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerDenver Parks:Description: "This dataset should be used as a reference to locate parks, golf courses, and recreation centers managed by the Department of Parks and Recreation in the City and County of Denver. Data is based on parcel ownership and does not include other areas maintained by the department such as medians and parkways. The data should be used for planning and design purposes and cartographic purposes only."Source: City and County of Denver Parks REST EndpointNational Wilderness Areas:Description: “A parcel of Forest Service land congressionally designated as wilderness such as National Wilderness Area.”Notes: This layer was filtered to only include National Wilderness Areas in the State of ColoradoSource: United States Department of Agriculture National Wilderness Areas REST EndpointNational Forests: Description: “A depiction of the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with subsequent Executive Orders, Proclamations, Public Laws, Public Land Orders, Secretary of Agriculture Orders, and Secretary of Interior Orders creating modifications thereto, along with lands added to the NFS which have taken on the status of 'reserved from the public domain' under the General Exchange Act. The following area types are included: National Forest, Experimental Area, Experimental Forest, Experimental Range, Land Utilization Project, National Grassland, Purchase Unit, and Special Management Area.”Notes: This layer was filtered to only include National Forests in the State of ColoradoSource: United States Department of Agriculture Original Proclaimed National Forests REST Endpoint

This countywide composite of parcels (cadastral) data for Monmouth County represents digitized property boundaries that were developed from best available local and municipal tax maps data. The normalized parcels data are compatible with the New Jersey Department of Treasury MOD-IV system currently used by tax assessors. Stewardship and maintenance of the data continue under the purview of the Monmouth County GIS Office as well as local municipal tax authorities. Parcel attributes were normalized to a standard structure, specified in the New Jersey GIS Parcel Mapping Standard, to store parcel information and provide a PIN (parcel identification number) field common to the PIN that was to be stored in the PAMS (Property Assessment Management System) database to replace the MOD-IV database. Please note that this parcel dataset is not intended for use as tax maps nor for legal purposes. The dataset is intended to provide reasonable representations of parcel boundaries primarily for planning purposes and cartographic representation. Please note cautions when performing a join with this dataset and MOD-IV property records, specifically regarding duplicate and erroneous records. All records may not be provided for in the parcels data or MOD-IV (Tax List Search) tables because of how the data and tables are constructed, or for temporal mismatches. MOD-IV provides for the uniform preparation, maintenance, presentation and storage of property tax information required by the Constitution of the State of New Jersey, New Jersey Statutes and rules promulgated by the Director of Taxation. MOD-IV maintains and updates all assessment records, and produces all statutorily required tax lists. These lists account for all parcels of real property as delineated and identified on each municipality's official tax map, as well as taxable values and descriptive data for each parcel.

© GIS Office, Monmouth County Planning Board, New Jersey.

There are many useful strategies for preparing GIS data for Next Generation 9-1-1. One step of preparation is making sure that all of the required fields exist (and sometimes populated) before loading into the system. While some localities add needed fields to their local data, others use an extract, transform, and load process to transform their local data into a Next Generation 9-1-1 GIS data model, and still others may do a combination of both.There are several strategies and considerations when loading data into a Next Generation 9-1-1 GIS data model. The best place to start is using a GIS data model schema template, or an empty file with the needed data layout to which you can append your data. Here are some resources to help you out. 1) The National Emergency Number Association (NENA) has a GIS template available on the Next Generation 9-1-1 GIS Data Model Page.2) The NENA GIS Data Model template uses a WGS84 coordinate system and pre-builds many domains. The slides from the Virginia NG9-1-1 User Group meeting in May 2021 explain these elements and offer some tips and suggestions for working with them. There are also some tips on using field calculator. Click the "open" button at the top right of this screen or here to view this information.3) VGIN adapted the NENA GIS Data Model into versions for Virginia State Plane North and Virginia State Plane South, as Virginia recommends uploading in your local coordinates and having the upload tools consistently transform your data to the WGS84 (4326) parameters required by the Next Generation 9-1-1 system. These customized versions only include the Site Structure Address Point and Street Centerlines feature classes. Address Point domains are set for address number, state, and country. Street Centerline domains are set for address ranges, parity, one way, state, and country. 4) A sample extract, transform, and load (ETL) for NG9-1-1 Upload script is available here.Additional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.

Use this web map to link to other geospatial datasets available through county and city sites (Not comprehensive). May need to zoom in to see the participating cities. The county boundaries and city points were published by Washington State agencies and downloaded from geo.wa.gov. Locations are approximate, and no warranties are made regarding this data. The canvas basemap has been compiled by Esri and the ArcGIS user community from a variety of best available sources. Want to have your data site listed? Contact the Geospatial Program Office.

This dataset demarcates the municipal boundaries in Allegheny County. Data was created to portray the boundaries of the 130 Municipalities in Allegheny County the attribute table includes additional descriptive information including Councils of Government (COG) affiliation (regional governing and coordinating bodies comprised of several bordering municipalities), School District, Congressional District, FIPS and County Municipal Code and County Council District.

This dataset is harvested on a weekly basis from Allegheny County’s GIS data portal. The full metadata record for this dataset can also be found on Allegheny County's GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the "Explore" button (and choosing the "Go to resource" option) to the right of the "ArcGIS Open Dataset" text below.

Category: Civic Vitality and Governance

Department: Geographic Information Systems Group; Department of Administrative Services

BioMap is the result of an ongoing collaboration between MassWildlife and the Massachusetts Chapter of The Nature Conservancy (TNC). Since its inception in 2001, this comprehensive tool has become a trusted source of information to guide conservation that is used by a wide spectrum of conservation practitioners. Today’s BioMap builds on previous iterations with the continuing goal of protecting the diversity of species and natural ecosystems within the Commonwealth. BioMap is an important tool to guide strategic protection and stewardship of lands and waters that are most important for conserving biological diversity in Massachusetts.More details...

Geospatial data about US Cities and Towns (Local). Export to CAD, GIS, PDF, CSV and access via API.

Vector polygon map data of property parcels from Mount Vernon containing 11,202 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

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Note from source:

The data made available in this service is for general information and planning purposes only, and should not be relied upon as a sole informational source. The County of Westchester hereby disclaims any liability for any and all damage, loss, or liability which may result, directly or indirectly, from the use of this GIS mapping system by any person or entity.

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Tax parcel boundaries represent approximate property line location and should NOT be interpreted as or used in lieu of a survey, property boundary description, or a definitive municipal tax map. Property descriptions must be obtained from surveys or deeds. As this data was compiled from many different sources, discrepancies will exist along some municipal boundaries. Authoritative and approved tax maps for this municipality ONLY reside with the local assessor. For more information please contact the local assessor's office.

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 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.

This feature layer provides digital tax parcels for the Organized Towns of the State of Maine. Within Maine, real property data is maintained by the government organization responsible for assessing and collecting property tax for a given location. Organized towns and townships maintain authoritative data for their communities and may voluntarily submit these data to the Maine GeoLibrary Parcel Project. "Maine Parcels Organized Towns Feature" and "Maine Parcels Organized Towns ADB" are the product of these voluntary submissions. Communities provide updates to the Maine GeoLibrary on a non-regular basis, which affects the currency of Maine GeoLibrary parcels data. Another resource for real property transaction data is the County Registry of Deeds, although organized town data should very closely match registry information, except in the case of in-process property conveyance transactions. In Unorganized Territories (defined as those regions of the state without a local government that assesses real property and collects property tax), the Maine Revenue Service is the authoritative source for parcel data. "Maine Parcels Unorganized Territory Feature" is the authoritative GIS data layer for the Unorganized Territories. However, it must always be used with auxiliary data obtained from the online resources of Maine Revenue Services (https://www.maine.gov/revenue/taxes/property-tax) to compile up-to-date parcel ownership information. Property maps are a fundamental base for many municipal activities. Although GIS parcel data cannot replace detailed ground surveys, the data can assist municipal officials with functions such as accurate property tax assessment, planning and zoning. Towns can link maps to an assessor's database and display local information, while town officials can show taxpayers how proposed development or changes in municipal services and regulations may affect the community. In many towns, parcel data also helps to provide public notices, plan bus routes, and carry out other municipal services.

This dataset contains municipality-submitted parcel data along with previously developed parcel data acquired through the Municipal Grants Project supported by the Maine Library of Geographic Information (Maine GeoLibrary). Grant recipient parcel data submissions were guided by standards presented to the Maine GeoLibrary Board on May 21, 2005, which are outlined in the "Standards for Digital Parcel Files" document available on the Maine GeoLibrary publications page (https://www.maine.gov/geolib/policies/standards.html). This dataset also contains municipal parcel data acquired through other sources; the data sources are identified (where available) by the field “FMSCORG”. Note: Join this feature layer with the "Maine Parcels Organized Towns ADB" table (https://maine.hub.arcgis.com/maps/maine::maine-parcels-organized-towns-feature/about?layer=1) for available ownership information. A date field, “FMUPDAT”, is attributed with the most recent update date for each individual parcel if available. The "FMUPDAT" field will not match the "Updated" value shown for the layer. "FMUPDAT" corresponds with the date of update for the individual data, while "Updated" corresponds with the date of update for the ArcGIS Online layer as a whole. Many parcels have not been updated in several years; use the "FMUPDAT" field to verify currency.

The CT Municipalities layer consists of individual polygons representing each of the 169 municipalities that make up the state of Connecticut. This feature class is based on the Towns layer originally created by CTDEEP from USGS maps. The towns from the CTDEEP data were dissolved to create 169 records (one for each town). Fields were added and deleted to create a generic schema.The CT Municipalities feature class was created in (municipality) alphabetical order. Fields were added to identify the municipality number and the CTDOT Municipality number, which differ from each other in some cases. In 1947 the town of Saybrook officially changed its name to Deep River. Other State agencies and municipalities changed their numbering systems to reflect this name change, however, most of what is now CTDOT kept their existing numbering system. This is why the CTDOT town number for Deep River is 122, the number formerly assigned to Saybrook.The square miles associated with each town are for their interior land mass area. Coastal communities have boundaries that extend into Long Island Sound. These town boundary extensions into Long Island Sound are not included in the square miles field.CTDOT has created and will maintain a cartographic rendering of the geometric shape of Municipal boundaries. Official Town and City designations as incorporated areas consisting of an authorized governing body are managed by CT's Office of Policy and Management (OPM).CTDOT has undertaken a good faith effort to represent the boundaries cartographically in a fair and equitable fashion, from the best available data compiled from existing state, regional, and local resources including - existing historical cartographic renderings of the boundary locations, supplemental survey information, and map submissions. Corrections can be submitted to the CTDOT for incorporation and correction where applicable.Attribution was assigned to designations managed by a variety of entities that strictly follow Municipal boundaries and additional designations will be added as requested by State, regional, and local partners.

Sourcing accurate and up-to-date map data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

GapMaps Map Data uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographics data across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

GapMaps Map Data also includes the latest Point-of-Interest (POI) Data for leading retail brands across a range of categories including Fast Food/ QSR, Health & Fitness, Supermarket/Grocery and Cafe sectors which is updated monthly.

With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

• Better understand your customers
• Identify optimal locations to expand your retail footprint
• Define sales territories for franchisees
• Run targeted marketing campaigns.

GapMaps Map Data for Asia and MENA can be utilized in any GIS platform and includes the latest estimates (updated annually) on:

1. Population (how many people live in your local catchment)
2. Demographics (who lives within your local catchment)
3. Worker population (how many people work within your local catchment)
4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

Primary Use Cases for GapMaps Map Data:

1. Retail Site Selection - identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.
6. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
7. Customer Profiling
8. Target Marketing
9. Market Share Analysis

TransportationThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau, displays primary roads, secondary roads, local roads and railroads in the United States. According to the USCB, "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."Interstates 20 and 635Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (TIGERweb/Transportation) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 155 (Series Information for All Roads County-based TIGER/Line Shapefiles, Current)OGC API Features Link: (Transportation - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: Census Feature Class Codes (CFCC)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

Local and Literary-themed Trails in Amherst, MA. More Information

This dataset is comprised of the final assessment rolls submitted to the New York State Department of Taxation and Finance – Office of Real Property Tax Services by 996 local governments. Together, the assessment rolls provide the details of the more than 4.7 million parcels in New York State. The dataset includes assessment rolls for all cities and towns, except New York City. (For New York City assessment roll data, see NYC Open Data [https://opendata.cityofnewyork.us]) For each property, the dataset includes assessed value, full market value, property size, owners, exemption information, and other fields. Tip: For a unique identifier for every property in New York State, combine the SWIS code and print key fields.

Unlock precise, high-quality Map data covering 164M+ verified locations across 220+ countries. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

Key use cases of GIS Data helping our customers :

1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.

This map includes change areas for city and county boundaries filed in accordance with Government Code 54900. The initial dataset was first published on October 20, 2021, and was based on the State Board of Equalization's 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 jurisdictions. The boundaries are continuously being revised 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 and should not be used to determine precise city or county boundary line locations.The data is updated within 10 business days of the CDTFA receiving a copy of the Board of Equalization's acknowledgement letter.BOE_CityAnx Data Dictionary: COFILE = county number - assessment roll year - file number (see note*); CHANGE = affected city, unincorporated county, or boundary correction; EFFECTIVE = date the change was effective by resolution or ordinance (see note*); RECEIVED = date the change was received at the BOE; ACKNOWLEDGED = date the BOE accepted the filing for inclusion into the tax rate area system; NOTES = additional clarifying information about the action.*Note: A COFILE number ending in "000" is a boundary correction and the effective date used is the date the map was corrected.BOE_CityCounty Data Dictionary: COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the Board of Equalization's 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).