19 datasets found
  1. a

    Storm Drain Webmap

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Oct 1, 2018
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    City of Columbia GIS - South Carolina (2018). Storm Drain Webmap [Dataset]. https://coc-colacitygis.opendata.arcgis.com/maps/d05ea46c1d1d42b8ac399a0c44080321
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    Dataset updated
    Oct 1, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Volunteer groups tag City storm drains to notify the public that these drains are only for stormwater, and lead directly to waterways. This map shows which drains are tagged within the City.

  2. a

    Parks

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Mar 20, 2019
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    City of Columbia GIS - South Carolina (2019). Parks [Dataset]. https://coc-colacitygis.opendata.arcgis.com/datasets/parks/api
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    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    City of Columbia Parks

  3. a

    Landmarks

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 15, 2018
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    City of Columbia GIS - South Carolina (2018). Landmarks [Dataset]. https://coc-colacitygis.opendata.arcgis.com/datasets/ColaCityGIS::landmarks/about
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    Dataset updated
    Aug 15, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    City of Columbia designated historic and modern landmarks.

  4. d

    U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2

    • search.dataone.org
    • data.globalchange.gov
    • +3more
    Updated Dec 1, 2016
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    U.S. Geological Survey Gap Analysis Program, Anne Davidson, Spatial Ecologist (2016). U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2 [Dataset]. https://search.dataone.org/view/083f5422-3fb4-407c-b74a-a649e70a4fa9
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    Dataset updated
    Dec 1, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey Gap Analysis Program, Anne Davidson, Spatial Ecologist
    Time period covered
    Jan 1, 1999 - Jan 1, 2001
    Area covered
    Variables measured
    CL, SC, DIV, FRM, OID, RED, BLUE, COUNT, GREEN, VALUE, and 9 more
    Description

    This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

  5. a

    Bike Share Stations

    • hub.arcgis.com
    Updated Aug 22, 2018
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    City of Columbia GIS - South Carolina (2018). Bike Share Stations [Dataset]. https://hub.arcgis.com/datasets/ColaCityGIS::bike-share-stations
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    Dataset updated
    Aug 22, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Bike share program

  6. a

    FireStations

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 15, 2018
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    City of Columbia GIS - South Carolina (2018). FireStations [Dataset]. https://coc-colacitygis.opendata.arcgis.com/datasets/firestations
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    Dataset updated
    Aug 15, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Columbia-Richland Fire Department serves the citizens of Columbia and Richland County. Fire stations are strategically located throughout the City and the County.

  7. a

    Arrest (1/1/2016 to 12/31/2024)

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jun 11, 2018
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    City of Columbia GIS - South Carolina (2018). Arrest (1/1/2016 to 12/31/2024) [Dataset]. https://coc-colacitygis.opendata.arcgis.com/items/c61a0a2198c8423c9c93d3890c7ffc74
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    Dataset updated
    Jun 11, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Arrest data indicates date/time of arrests, address, report area as well as region in which the arrest occurred. All individuals are considered innocent until proven guilty.

  8. d

    Mineral Resources Data System

    • search.dataone.org
    • data.wu.ac.at
    Updated Oct 29, 2016
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    U.S. Geological Survey (2016). Mineral Resources Data System [Dataset]. https://search.dataone.org/view/3e55bd49-a016-4172-ad78-7292618a08c2
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    Dataset updated
    Oct 29, 2016
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey
    Area covered
    Variables measured
    ORE, REF, ADMIN, MODEL, STATE, COUNTY, DEP_ID, GANGUE, MAS_ID, REGION, and 29 more
    Description

    Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

  9. a

    Data from: Rental Properties

    • hub.arcgis.com
    Updated Jul 19, 2018
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    City of Columbia GIS - South Carolina (2018). Rental Properties [Dataset]. https://hub.arcgis.com/maps/ColaCityGIS::rental-properties
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    Dataset updated
    Jul 19, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Every residential rental property within the City must have a Residential Rental Permit prior to allowing occupancy as a rental unit. This data includes all rental properties in the City of Columbia.

  10. a

    Monitoring Station Webmap

    • coc-colacitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Apr 26, 2018
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    City of Columbia GIS - South Carolina (2018). Monitoring Station Webmap [Dataset]. https://coc-colacitygis.opendata.arcgis.com/maps/d107d477946547ed8820aa48207459c3
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    Dataset updated
    Apr 26, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    The City operates a real-time surface water monitoring system. This link allows the public access to precipitation, stage and flow data. Real-time data can be viewed, and past data can be downloaded.

  11. a

    Field Interview (1/1/2016 - 12/31/2024)

    • coc-colacitygis.opendata.arcgis.com
    Updated Jun 11, 2018
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    City of Columbia GIS - South Carolina (2018). Field Interview (1/1/2016 - 12/31/2024) [Dataset]. https://coc-colacitygis.opendata.arcgis.com/datasets/field-interview-1-1-2016-12-31-2024
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    Dataset updated
    Jun 11, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Field Interview is a collection of data resulting from citizen contact related to suspicious activity.

  12. a

    Arrest (1/1/2016 to 12/31/2024)

    • hub.arcgis.com
    Updated Jun 11, 2018
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    City of Columbia GIS - South Carolina (2018). Arrest (1/1/2016 to 12/31/2024) [Dataset]. https://hub.arcgis.com/datasets/c61a0a2198c8423c9c93d3890c7ffc74
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    Dataset updated
    Jun 11, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Arrest data indicates date/time of arrests, address, report area as well as region in which the arrest occurred. All individuals are considered innocent until proven guilty.

  13. a

    Field Interview Temp (1/1/2016 - 9/30/2019)

    • hub.arcgis.com
    Updated Jun 8, 2018
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    City of Columbia GIS - South Carolina (2018). Field Interview Temp (1/1/2016 - 9/30/2019) [Dataset]. https://hub.arcgis.com/datasets/ColaCityGIS::field-interview-temp-1-1-2016-9-30-2019/about
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    Dataset updated
    Jun 8, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    Field Interview is a collection of data resulting from citizen contact related to suspicious activity.

  14. a

    CodeViolationProperty

    • coc-colacitygis.opendata.arcgis.com
    Updated Aug 15, 2018
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    City of Columbia GIS - South Carolina (2018). CodeViolationProperty [Dataset]. https://coc-colacitygis.opendata.arcgis.com/items/d658c672b0354fa59b654c1f9d0f7f96
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    Dataset updated
    Aug 15, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    This data includes violations of municipal code reported/notices of violation issued by the City of Columbia in the past two months. Examples of code violations: Abandon/Derelict Vehicles, Boarded up housing, Care of premise, Care of vacant lots, Housing cases, Miscellaneous and Zoning.

  15. a

    Officer as Victim (1/1/2016 to 12/31/2024)

    • coc-colacitygis.opendata.arcgis.com
    Updated Jun 28, 2019
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    City of Columbia GIS - South Carolina (2019). Officer as Victim (1/1/2016 to 12/31/2024) [Dataset]. https://coc-colacitygis.opendata.arcgis.com/items/55833ceadf3242288084efff21d18b03
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    Dataset updated
    Jun 28, 2019
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    In instances when the officer becomes the victim when conducting his/her duties, information is collected on type of incident, type of weapon involved in the commission of the crime (please note: the weapon type involved is not necessarily the weapon type used against the officer), as well as demographic information on the officer and suspect.

  16. a

    Solvability Factor Temp (1/1/2016 to 12/31/2017)

    • hub.arcgis.com
    • coctest-colacitygis.opendata.arcgis.com
    Updated Jun 11, 2018
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    City of Columbia GIS - South Carolina (2018). Solvability Factor Temp (1/1/2016 to 12/31/2017) [Dataset]. https://hub.arcgis.com/datasets/1d50f3dd33db48248d9b1a120cf4d12a
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    Dataset updated
    Jun 11, 2018
    Dataset authored and provided by
    City of Columbia GIS - South Carolina
    Area covered
    Description

    The Solvability Factor determines the status of a report throughout the course of the investigation. These status updates help determine clearance rates for the department.

  17. a

    United States

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Nov 3, 2021
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    ArcGIS Living Atlas Team (2021). United States [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/arcgis-content::united-states
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    Dataset updated
    Nov 3, 2021
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This layer shows figures of quit rates and quit levels by the US, BLS regions, and states. Data is from the Bureau of Labor Statistics (BLS) and was released October and November of 2021. The layer default symbology highlights to September 2021 quit rate in comparison to the national figure of 3.0%.According to the October 2021 News Release by BLS:"The number of quits increased in August to 4.3 million (+242,000). The quits rate increased to a series high of 2.9 percent. Quits increased in accommodation and food services (+157,000); wholesale trade (+26,000); and state and local government education (+25,000). Quits decreased in real estate and rental and leasing (-23,000). The number of quits increased in the South and Midwest regions."In the following November News Release:"In September, quits rates increased in 15 states and decreased in 10 states. The largest increases in quits rates occurred in Hawaii (+3.8 percentage points), Montana (+1.5 points), as well as Nevada and New Hampshire (+1.1 points each). The largest decreases in quits rates occurred in Kentucky (-1.1 percentage points), Iowa (-1.0 point), and South Dakota (-0.7 point). Over the month, the national quits rate increased (+0.1 percentage point)."Quit rates: The quits rate is the number of quits during the entire month as a percent of total employment.Quit levels: Quits are the number of quits during the entire month.State and US figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedRegion figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedThis data was obtained in October and November 2021, and the months of data from BLS are as follows:August 2020September 2020April 2021 (only offered for Regions)May 2021June 2021July 2021August 2021September 2021 (preliminary values)For the full data release, click here.The states (including the District of Columbia) that comprise the regions are: Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and VermontSouth: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West VirginiaMidwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and WisconsinWest: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

  18. a

    Oil and Natural Gas Wells

    • hub.arcgis.com
    • alic-algeohub.hub.arcgis.com
    Updated Aug 2, 2018
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    Alabama GeoHub (2018). Oil and Natural Gas Wells [Dataset]. https://hub.arcgis.com/datasets/ALGeoHub::oil-and-natural-gas-wells/about
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    Dataset updated
    Aug 2, 2018
    Dataset authored and provided by
    Alabama GeoHub
    Area covered
    Description

    This map shows the oil and natural gas wells across the United States. Oil and Natural Gas Well: A hole drilled in the earth for the purpose of finding or producing crude oil or natural gas; or producing services related to the production of crude or natural gas. Geographic coverage includes the United States (Alabama, Alaska, Arizona, Arkansas, California, Colorado, Florida, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maryland, Michigan, Mississippi, Missouri, Montana, North Dakota, Nebraska, Nevada, New Mexico, New York, Ohio, Oklahoma, Oregon, Pennsylvania, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wyoming) as well Oil and Natural Gas wells in the Canadian provinces of British Columbia and Manitoba that are within 100 miles of the country's border with the United States. According to the Energy Information Administration (EIA) the following states do not have active/producing Oil or Natural Gas Wells: Connecticut, Delaware, District of Columbia, Georgia, Hawaii, Iowa, Idaho, Massachusetts, Maine, Minnesota, North Carolina, New Hampshire, New Jersey, Rhode Island, South Carolina, Vermont, and Wisconsin. Some states do have wells for underground Natural Gas storage facilities where these have been identified they were included. This layer is derived from well data from individual states and provinces and United States Agencies. This layer is complete for the United States but further development of data missing from two Canadian provinces and Mexico is in process. This update release includes an additional 497,036 wells covering Texas. Oil and gas exploration in Texas takes advantage of drilling technology to use a single surface well drilling location to drill multiple bottom hole well connections to extract oil and gas. The addition of Well data from Texas results in the addition of a related table to support this one surface well to many bottom hole connections. This related table provides records for Wells that have more than one bottom hole linked to the surface well. Sourced from the HIFLD Open Data Portal for Energy.

  19. Microsoft Buildings Footprint Training Data with Heights

    • cityscapes-projects-gisanddata.hub.arcgis.com
    Updated Feb 27, 2019
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    Esri (2019). Microsoft Buildings Footprint Training Data with Heights [Dataset]. https://cityscapes-projects-gisanddata.hub.arcgis.com/datasets/esri::microsoft-buildings-footprint-training-data-with-heights-
    Explore at:
    Dataset updated
    Feb 27, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description

    Microsoft recently released a free set of deep learning generated building footprints covering the United States of America. As part of that project Microsoft shared 8 million digitized building footprints with height information used for training the Deep Learning Algorithm. This map layer includes all buildings with height information for the original training set that can be used in scene viewer and ArcGIS pro to create simple 3D representations of buildings. Learn more about the Microsoft Project at the Announcement Blog or the raw data is available at Github.Click see Microsoft Building Layers in ArcGIS Online.Digitized building footprint by State and City

    Alabama Greater Phoenix City, Mobile, and Montgomery

    Arizona Tucson

    Arkansas Little Rock with 5 buildings just across the river from Memphis

    California Bakersfield, Fresno, Modesto, Santa Barbara, Sacramento, Stockton, Calaveras County, San Fran & bay area south to San Jose and north to Cloverdale

    Colorado Interior of Denver

    Connecticut Enfield and Windsor Locks

    Delaware Dover

    Florida Tampa, Clearwater, St. Petersburg, Orlando, Daytona Beach, Jacksonville and Gainesville

    Georgia Columbus, Atlanta, and Augusta

    Illinois East St. Louis, downtown area, Springfield, Champaign and Urbana

    Indiana Indianapolis downtown and Jeffersonville downtown

    Iowa Des Moines

    Kansas Topeka

    Kentucky Louisville downtown, Covington and Newport

    Louisiana Shreveport, Baton Rouge and center of New Orleans

    Maine Augusta and Portland

    Maryland Baltimore

    Massachusetts Boston, South Attleboro, commercial area in Seekonk, and Springfield

    Michigan Downtown Detroit

    Minnesota Downtown Minneapolis

    Mississippi Biloxi and Gulfport

    Missouri Downtown St. Louis, Jefferson City and Springfield

    Nebraska Lincoln

    Nevada Carson City, Reno and Los Vegas

    New Hampshire Concord

    New Jersey Camden and downtown Jersey City

    New Mexico Albuquerque and Santa Fe

    New York Syracuse and Manhattan

    North Carolina Greensboro, Durham, and Raleigh

    North Dakota Bismarck

    Ohio Downtown Cleveland, downtown Cincinnati, and downtown Columbus

    Oklahoma Downtown Tulsa and downtown Oklahoma City

    Oregon Portland

    Pennsylvania Downtown Pittsburgh, Harrisburg, and Philadelphia

    Rhode Island The greater Providence area

    South Carolina Greensville, downtown Augsta, greater Columbia area and greater Charleston area

    South Dakota greater Pierre area

    Tennessee Memphis and Nashville

    Texas Lubbock, Longview, part of Fort Worth, Austin, downtown Houston, and Corpus Christi

    Utah Salt Lake City downtown

    Virginia Richmond

    Washington Greater Seattle area to Tacoma to the south and Marysville to the north

    Wisconsin Green Bay, downtown Milwaukee and Madison

    Wyoming Cheyenne

  20. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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City of Columbia GIS - South Carolina (2018). Storm Drain Webmap [Dataset]. https://coc-colacitygis.opendata.arcgis.com/maps/d05ea46c1d1d42b8ac399a0c44080321

Storm Drain Webmap

Explore at:
Dataset updated
Oct 1, 2018
Dataset authored and provided by
City of Columbia GIS - South Carolina
Area covered
Description

Volunteer groups tag City storm drains to notify the public that these drains are only for stormwater, and lead directly to waterways. This map shows which drains are tagged within the City.

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