The Digital City Map (DCM) data represents street lines and other features shown on the City Map, which is the official street map of the City of New York. The City Map consists of 5 different sets of maps, one for each borough, totaling over 8000 individual paper maps. The DCM datasets were created in an ongoing effort to digitize official street records and bring them together with other street information to make them easily accessible to the public. The Digital City Map (DCM) is comprised of seven datasets; Digital City Map, Street Center Line, City Map Alterations, Arterial Highways and Major Streets, Street Name Changes (areas), Street Name Changes (lines), and Street Name Changes (points). All of the Digital City Map (DCM) datasets are featured on the Streets App All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

The City Water Map (CWM), version 2.2, contains information on the water sources for cities internationally. For surface or alluvial groundwater sources, the upstream contributing area is defined. To ease use of the database, information on the spatial locations of the cities shown is also provided. For some cities, information is also available on how wastewater is treated and released, although this part of the database has not been fully developed. The CWM was used as part of a SNAPP working group on Latin America water security. It was also used as part of the Urban Water Blueprint analysis.

This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

Map of Missouri City Texas, showing its City Limits as well as various highlights of the city.

Map of city limits data for Bowie, Cass, Delta, Franklin, Hopkins, Lamar, Morris, Red River, and Titus Counties within Texas and Miller County, Arkansas.For questions, problems, or more information, contact gis@atcog.orghttps://atcog.org/

The Digital City Map (DCM) data represents street lines and other features shown on the City Map, which is the official street map of the City of New York. The City Map consists of 5 different sets of maps, one for each borough, totaling over 8000 individual paper maps. The DCM datasets were created in an ongoing effort to digitize official street records and bring them together with other street information to make them easily accessible to the public. The Digital City Map (DCM) is comprised of seven datasets; Digital City Map, Street Center Line, City Map Alterations, Arterial Highways and Major Streets, Street Name Changes (areas), Street Name Changes (lines), and Street Name Changes (points).

All of the Digital City Map (DCM) datasets are featured on the Streets App

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

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

Collection of static general Bloomington and city street maps of various sizes.

This dataset includes a total of 635 annotated image patches from historical city maps. It is designed for the semantic segmentation of the maps into 5 semantic classes (building blocks, non-built, water, road network, background frame). 330 patches are taken from maps of the city of Paris, while the 305 others are taken from a balanced corpus of city maps from 90 countries all around the world.

Please read the detailed informations about data collection methodology, associated metadata and annotation ontology in README.md hereunder :

Vector polygon map data of city limits from across the State of Texas containing 2142 features.

City limits GIS (Geographic Information System) data provides valuable information about the boundaries of a city, which is crucial for various planning and decision-making processes. Urban planners and government officials use this data to understand the extent of their jurisdiction and to make informed decisions regarding zoning, land use, and infrastructure development within the city limits.

By overlaying city limits GIS data with other layers such as population density, land parcels, and environmental features, planners can analyze spatial patterns and identify areas for growth, conservation, or redevelopment. This data also aids in emergency management by defining the areas of responsibility for different emergency services, helping to streamline response efforts during crises..

This city limits data is 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.

Airport City Mappings and Aggregations

Airport City Mappings and Aggregations

By data.world's Admin [source]

About this dataset

This dataset provides mapping and aggregation data for airports, cities, and countries. It was created for The Pudding's story titled What Airport Traffic Tells Us About the World's Megacities, which was published in July 2018. The flight data included in this dataset was obtained from the ICAO API, with connections excluded in the counts.

The dataset contains information on flights to cities, including a mapping of cities with multiple airports as well as a reference file mapping cities to their corresponding airports. This allows for analysis and understanding of airport traffic patterns within different cities.

In addition to city and airport information, the dataset also includes details about countries where the airports are located. This comprehensive data provides insights into global air travel trends and facilitates further exploration regarding population demographics.

Please note that this dataset does not include specific dates related to flight records but offers a static snapshot of airport-city aggregations at the time it was created.

The original source for this dataset is mentioned as ICAO (International Civil Aviation Organization) through their API. The population data used can be directly downloaded from United Nations sources.

Overall, this expansive collection of data serves as a valuable resource for researchers interested in studying airport traffic patterns and understanding relationships between airports, cities, and countries worldwide

How to use the dataset

Understanding the Columns

• City: The name of the city.
• code_4: The 4-letter code representing the city.
• code_3: The 3-letter code representing the city.
• Airport Name: The name of the airport.
• three-digit code: The three-digit code assigned to the airport.
• four_digit: The four-digit code assigned to the airport.
• l1: The first level of location information for the airport.
• l2: The second level of location information for the airport.
• Country: The country where the airport is located.

Using Flight Data

The dataset includes flight data with mappings from cities to their corresponding airports.

• To find flights to specific cities, refer to /analysis_data/airport-city-aggregations.csv. This file provides mapping and aggregation data specifically for flights to cities, including multiple airports within each city.

• To determine which airports correspond to each city, consult /analysis_data/city-mappings.csv, which contains a mapping of cities with their corresponding airports.

Analyzing Airport Traffic

The dataset allows you to analyze airport traffic patterns and understand connections between different cities worldwide.

• You can filter or group by columns such as City, Country, or Airport Name to aggregate data based on your analysis needs.

• By cross-referencing flight routes depicted in maps provided in conjunction with this dataset (referenced in the source), you can gain insights into the world's megacities and their connectivity.

Population Data

For additional context, population data for cities and countries can be obtained directly from the United Nations (UN).

Example Analysis

You can use this dataset to answer various interesting questions, such as:

• Which are the busiest airports in terms of traffic?
• What are the major airline hubs around the world?
• How is airport traffic distributed across different countries and continents?
• How do flight frequencies vary between cities with multiple airports?
• Are there any emerging airport hubs in developing regions?

Remember to explore

Research Ideas

• Analyzing airport traffic patterns: This dataset can be used to analyze airport traffic patterns by examining the number of flights and passengers for each city and airport. Researchers or analysts can identify the busiest airports, the most popular routes, and the cities with the highest air travel demand.
• Studying city connectivity: The dataset provides information on cities and their corresponding airports, allowing researchers to study the connectivity between different cities around the world. By analyzing flight routes, researchers can gain insights into global transportation networks and identify major hubs for international travel.
• Exploring urbanization and economic development: Since this dataset i...

VDOT collaborated with the Virginia Tourism Corporation to develop the state map, which features Virginia's beaches and encourages travelers to head to the coast and visit the many attractions across the Commonwealth. This link provides access to detailed city maps.

The digital city map, also spatial reference level 3 (RBE3), is the basis for the Official City Map 1:20,000. It is the main product from the spatial data of the spatial reference level 3. The internet map of the city of Braunschweig is also derived from this data. In terms of content, he shows the road network of Braunschweig, the settlement areas, the water network, the railway lines as well as the land use by forests, green areas and agricultural land. The Official City Map 1:20000 Sheet Size: 116 x 103 cm, folded to 11.6 x 25.7 cm, map image 90 x 100 cm circumference: City map, maps of the city centre and region, street directory, aerial view of the entire city. Excerpts from the digital city map are published individually according to the intended use. In doing so, an ongoing database can be used. The generalisation is tailored to the output in scales between 1:15000 and 1:25000.

This is a link to the SpiresGIS General Map on Frederick City's website.

2017, 2016. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project city-level data in GIS-friendly format can be joined with city spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-City-Boundaries/n44h-hy2j) in a geographic information system (GIS) to produce maps of 27 measures at the city-level. There are 7 measures (all teeth lost, dental visits, mammograms, Pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) in this 2019 release from the 2016 BRFSS that were the same as the 2018 release.

Ready to use PDF map of the city of Atlanta including roads and city limits. Dimensions are ANSI E 34 in x 44 in (864 mm x 1118 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org https://atcog.org/ Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

ESRI ArcGIS Online Map based application allowing users to view historical city boundary annexation and detachment information to and from the 88 incorporated cities within Los Angeles County. Public can use widgets that are available in the app to get information for the Annexations. For information regarding Proposed City Annexation/Detachment and Special District Formation, click here.

📝 Dataset Description

This dataset provides a clean and structured mapping of 1,209 Indian cities to their respective 33 states and union territories (as of February 2015). It is an essential resource for data analysts, geospatial researchers, and anyone working with location-based data in India.

🔍 Key Features:

• 📍 Cities: 1,188 unique entries
• 🗺️ States/UTs: 33 unique states and union territories
• 📊 Columns: 2 (city, state)
• 📅 Date Reference: February 2015
• ✅ Ready for use in data cleaning, enrichment, geolocation mapping, and visualization tasks.

💡 Use Cases:

• Mapping cities to states in Indian datasets
• Preparing geospatial plots or choropleths
• Cleaning inconsistent location fields
• Enriching datasets lacking state information

This dataset contains the web-optimised representation of the urban planning plant.

Note: The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services beginning in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.This dataset is regularly updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications. PurposeCity boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This feature layer is for public use. Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal Buffers (this dataset)Counties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal BuffersCity and County AbbreviationsUnincorporated Areas (Coming Soon)Census Designated PlacesCartographic CoastlinePolygonLine source (Coming Soon)State BoundaryWith Bay CutsWithout Bay Cuts Working with Coastal Buffers The dataset you are currently viewing excludes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers. Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov Field and Abbreviation DefinitionsCDTFA_CITY: CDTFA incorporated city nameCDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.CDTFA_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. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.CENSUS_GEOID: numeric geographic identifiers from the US Census BureauCENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.CDT_CITY_ABBR: Abbreviations of incorporated area names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 4 characters. Not present in the county-specific layers.CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or countyCENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead. Boundary AccuracyCounty boundaries were originally derived from a 1:24,000 accuracy dataset, with improvements made in some places to boundary alignments based on research into historical records and boundary changes as CDTFA learns of them. City boundary data are derived from pre-GIS tax maps, digitized at BOE and CDTFA, with adjustments made directly in GIS for new annexations, detachments, and corrections.Boundary accuracy within the dataset varies. While CDTFA strives to correctly include or exclude parcels from jurisdictions for accurate tax assessment, this dataset does not guarantee that a parcel is placed in the correct jurisdiction. When a parcel is in the correct jurisdiction, this dataset cannot guarantee accurate placement of boundary lines within or between parcels or rights of way. This dataset also provides no information on parcel boundaries. For exact jurisdictional or parcel boundary locations, please consult the county assessor's office and a licensed surveyor. CDTFA's data is used as the best available source because BOE and CDTFA receive information about changes in jurisdictions which otherwise need to be collected independently by an agency or company to compile into usable map boundaries. CDTFA maintains the best available statewide boundary information. 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. Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties. In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose. SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon. Coastline CaveatsSome cities have buffers extending into water bodies

Northeastern United States Town Boundary data are intended for geographic display of state, county and town (municipal) boundaries at statewide and regional levels. Use it to map and label towns on a map. These data are derived from Northeastern United States Political Boundary Master layer. This information should be displayed and analyzed at scales appropriate for 1:24,000-scale data. The State of Connecticut, Department of Environmental Protection (CTDEP) assembled this regional data layer using data from other states in order to create a single, seamless representation of political boundaries within the vicinity of Connecticut that could be easily incorporated into mapping applications as background information. More accurate and up-to-date information may be available from individual State government Geographic Information System (GIS) offices. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)