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.
City of Columbia Parks
City of Columbia designated historic and modern landmarks.
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
Bike share program
Columbia-Richland Fire Department serves the citizens of Columbia and Richland County. Fire stations are strategically located throughout the City and the County.
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.
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.
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.
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.
Field Interview is a collection of data resulting from citizen contact related to suspicious activity.
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.
Field Interview is a collection of data resulting from citizen contact related to suspicious activity.
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.
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.
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.
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.
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.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
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
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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.