3 datasets found
  1. m

    20 Richest Counties in Missouri

    • missouri-demographics.com
    Updated Jun 20, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kristen Carney (2024). 20 Richest Counties in Missouri [Dataset]. https://www.missouri-demographics.com/counties_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.missouri-demographics.com/terms_and_conditionshttps://www.missouri-demographics.com/terms_and_conditions

    Area covered
    Missouri
    Description

    A dataset listing Missouri counties by population for 2024.

  2. NWS Paducah Hail Climatology Map

    • noaa.hub.arcgis.com
    Updated Nov 14, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    NOAA GeoPlatform (2017). NWS Paducah Hail Climatology Map [Dataset]. https://noaa.hub.arcgis.com/maps/nws-paducah-hail-climatology-map/about
    Explore at:
    Dataset updated
    Nov 14, 2017
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    This is the basemap for a comprehensive hail climatology covering our forecast area of western Kentucky, southeast Missouri, southern Illinois, and southwest Indiana. Information includes the number of documented large hail reports in each county from 1955 through March 2021, as well as the largest reported hail size for each county.

  3. d

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

    • search.dataone.org
    • data.globalchange.gov
    • +2more
    Updated Dec 1, 2016
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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
    Explore at:
    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

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

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Kristen Carney (2024). 20 Richest Counties in Missouri [Dataset]. https://www.missouri-demographics.com/counties_by_population

20 Richest Counties in Missouri

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 20, 2024
Dataset provided by
Cubit Planning, Inc.
Authors
Kristen Carney
License

https://www.missouri-demographics.com/terms_and_conditionshttps://www.missouri-demographics.com/terms_and_conditions

Area covered
Missouri
Description

A dataset listing Missouri counties by population for 2024.

Search
Clear search
Close search
Google apps
Main menu