Geospatial data about City of Columbus, Ohio Parcels. Export to CAD, GIS, PDF, CSV and access via API.
Vector polygon map data of property parcels from Columbus, Ohio containing 735,806 features.
Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.
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.
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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This map layer shows street centerlines in central Ohio. Specifically, this layer covers Franklin County and a seven-mile radius beyond. This layer was created by the Mid-Ohio Regional Planning Commission (MORPC) as part of the Location Based Response System (LBRS) initiative of the Ohio Geographically Referenced Information Program (OGRIP). This layer is cooperatively maintained by various entities in the region including MORPC, Columbus, Dublin, Worthington, Westerville, Gahanna, Grove City, Hilliard, and Franklin County.
In 2018, electors voted to create nine districts in the City of Columbus and add two additional council members, for a total of nine councilmembers, representing each of the nine districts. This map layer shows the final residential districts that were approved in December 2021 by City Council. For more information, refer to https://www.columbus.gov/districts/.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This map layer depicts existing sidewalks and crosswalks in Central Ohio. For planning purposes, this layer also includes digitized line segments along roadways that are not presently paved, but could become sidewalks in the future. This layer was initially created by TranSystems, and is now maintained by a partnership of local government entities and the Mid-Ohio Regional planning commission.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This layer shows the boundaries of properties owned or leased by the Columbus Recreation and Parks Department (CRPD). Types of properties include community parks, conservation/natural areas, golf courses, neighborhood parks, and others.
This layer is a component of LucityDPS.
© City of Columbus GIS
Polygon vector map data covering corporate boundaries for Columbus, Ohio containing 1 feature.
Boundary GIS (Geographic Information System) data is spatial information that delineates the geographic boundaries of specific geographic features. This data typically includes polygons representing the outlines of these features, along with attributes such as names, codes, and other relevant information.
Corporate boundaries display the incorporated areas for a city or region.
Boundary GIS data is used for a variety of purposes across multiple industries, including urban planning, environmental management, public health, transportation, and business analysis.
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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This map layer shows bikeways in central Ohio. It is maintained through a partnership between local governments including the cities of Columbus, Dublin, Westerville, Worthington, Hilliard, Gahanna, and Grove City, along with the Metro Parks and Mid-Ohio Regional Planning Commision. The layer includes established multi-use paths, bike lanes, bike boulevards, shared lane makings and routes. This layer also depicts committed and proposed facilities.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This feature layer is a general representation of annexations to the City of Columbus. It is not a legal record. This feature layer is updated throughout the annexations and detachment submission and approval process. Annexations and detachments to the City of Columbus are adopted by legislation approved by City Council and take effect upon recording within the appropriate County Recorder’s Office. This feature layer is a digitized representation of the process for annexation and detachment and is mapped based upon underlying parcel geography from the three County Auditor’s (Franklin, Fairfield, and Delaware) GIS parcel feature layers in which the City of Columbus currently resides.The City of Columbus makes no guarantee as to the accuracy of this mapping. It is provided as a general reference tool. User’s are advised to consult legal annexation records available within the various County Recorder’s Offices when attempting to determine the precise boundaries for the City of Columbus. Users are advised not to use this feature layer if they are unwilling to accept the conditions stated herein.Questions regarding this feature layer should be directed to the City of Columbus, Department of Public Service, Division of Infrastructure Management’s Map Room at OneStopPlans@columbus.gov.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This map layers shows zoning code variances approved by the Columbus City Council, and may include use variances and/or variances for yard, height, or parking requirements of any district. Once effective, council variances are added to the map by legal description of property. The variances date from approximately 2005 to current. Data is created and maintained by the GIS Analyst at the Department of Building and Zoning Services.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This layer includes eight priority areas for the CelebrateOne initiative to reduce the community’s alarming infant mortality rate by 40 percent and cut the racial health disparity gap in half by 2020.
This layer is a component of BaseMap of Columbus Area.
BaseMap of Columbus Area
© City of Columbus GIS
This layer is a component of BaseMap of Columbus Area.
© City of Columbus GIS
From the site: “The Geologic Atlas of the United States is a set of 227 folios published by the U.S. Geological Survey between 1894 and 1945. Each folio includes both topographic and geologic maps for each quad represented in that folio, as well as description of the basic and economic geology of the area. The Geologic Atlas collection is maintained by the Map & GIS Library. The repository interface with integrated Yahoo! Maps was developed by the Digital Initiatives -- Research & Technology group within the TAMU Libraries using the Manakin interface framework on top of the DSpace digital repository software. Additional files of each map are available for download for use in GIS or Google Earth. A tutorial is provided which describes how to download theses files.”
This layer is a component of map311mini.
© Columbus GIS
Geospatial data about City of Columbus, Ohio Roads. Export to CAD, GIS, PDF, CSV and access via API.
The purpose of this map is to show tree canopy coverage at the community and block level. The boundary features are Columbus Communities and Census Blocks symbolized as a color gradient indicating tree canopy coverage with pop-ups configured to show more information about each feature. NAIP imagery becomes visible at the block level and may be turned off by the user. This map was created for the City of Columbus Recreation and Parks Department's Urban Forestry Master Plan project. Tree canopy and other land cover information were derived from 2013 NAIP imagery by Plan-It Geo in 2015 for the Urban Tree Canopy Assessment of Columbus, Ohio and it is not updated. Census Block boundaries are from 2010. The NAIP imagery shown in this map is the latest available.
Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...
This layer is a component of LucityRNP.
© City of Columbus GIS
Geospatial data about City of Columbus, Ohio Parcels. Export to CAD, GIS, PDF, CSV and access via API.