The Missouri Public Land Survey System is a 1:24,000 scale geographic information systems (GIS) polygon layer based on the 7.5' United States Geological Survey (USGS) topographic maps. This data set has been extensively edited to improve the accuracy of the original product.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally- recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2019, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 20 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

This document was created to be a basic boundary file for maps requiring counties or city limits The service created is part of a series of basic map services created for the Missouri Office of Geospatial Information.

The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated or updated as part of the the 2023 BAS or the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

This data set contains the boundaries of Missouri's 114 counties plus the boundary of the city of St. Louis. This data set was created to provide the most accurate county boundary data available for the whole state with attributes that are correct and useable.

Missouri’s regional planning commissions (RPCs) works with surrounding local governments to promote and implement planning activities, to coordinate and facilitate economic development, homeland security, and transportation improvements. The RPCs were established as a result of the State and Regional Planning Community Development Act of 1965. RPCs coordinate local issues related to regional planning and development, and they maintain an active working relationship with state government.

In chemography, grid-based maps sample molecular descriptor space by injecting a set of nodes, and then linking them to some regular 2D grid representing the map. They include self-organizing maps (SOMs) and generative topographic maps (GTMs). Grid-based maps are predictive because any compound thereupon projected can “inherit” the properties of its residence node(s)node properties themselves “inherited” from node-neighboring training set compounds. This Article proposes a formalism to define the trustworthiness of these nodes as “providers” of structure–activity information captured from training compounds. An empirical four-parameter node trustworthiness (NT) function of density (sparsely populated nodes are less trustworthy) and coherence (nodes with training set residents of divergent properties are less trustworthy) is proposed. Based upon it, a trustworthiness score T is used to delimit the applicability domain (AD) by means of a trustworthiness threshold TT. For each parameter setup, success of ensuing inside-AD predictions is monitored. It is seen that setup-specific success levels (averaged over large pools of prediction challenges) are highly covariant, irrespectively of the targets of prediction challenges, of the (classification or regression) type of problems, of the specific parametrization, and even of the nature (GTM or SOM) of underlying maps. Thus, success levels determined on the basis of regression problems (445 target-specific affinity QSAR sets) on GTMs and levels returned by completely unrelated classification problems (319 target-specific active-/inactive-labeled sets) on SOMs were seen to correlate to a degree of 70%. Therefore, a common, general-purpose setup of the herein proposed parametric AD definition was shown to generally apply to grid-based map-driven property prediction problems.

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. State Legislative Districts (SLDs) are the areas from which members are elected to state legislatures. The SLDs embody the upper (senate) and lower (house) chambers of the state legislature. Nebraska has a unicameral legislature and the District of Columbia has a single council, both of which the Census Bureau treats as upper-chamber legislative areas for the purpose of data presentation; there are no data by SLDL for either Nebraska or the District of Columbia. A unique three-character census code, identified by state participants, is assigned to each SLD within a state. In Connecticut, Illinois, Louisiana, New Hampshire, Wisconsin, and Puerto Rico, the Redistricting Data Program (RDP) participant did not define the SLDs to cover all of the state or state equivalent area. In these areas with no SLDs defined, the code "ZZZ" has been assigned, which is treated as a single SLD for purposes of data presentation. The generarlized boundaries in this file are based on the most recent state legislative district boundaries collected by the Census Bureau for the 2022 election year and provided by state-level participants through the RDP.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

Map image layer. County Boundary for St. Louis County, Missouri. Link to metadata.

The 2024 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 119th Congress is seated from January 2025 through December 2026. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The cartographic boundary files for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The generalzied boundaries of all other congressional districts are based on information provided to the Census Bureau by the states by May 31, 2024.

The "Map Image Layer - Watershed Boundaries" is the Map Image Layer of Watershed Boundaries. It has been designed specifically for use in ArcGIS Online (and will not directly work in ArcMap or ArcPro). This data has been modified from the original source data to serve a specific business purpose. This data is for cartographic purposes only.The Watershed Boundaries Data Group contains the following layers: DNR Catchments (MnDNR)HUC 12 Boundaries (USGS)HUC 12 IWM Group Boundaries (MPCA)HUC 10 Boundaries (USGS)HUC 8 Boundaries (USGS): HUC 8s represent part or all of a surface drainage basin, a combination of drainage basins, or a distinct hydrologic feature. There are 80 HUC 2s in Minnesota. (i.e. Zumbro (07040004))HUC 6 Boundaries (USGS): HUC 6s are areas which divide the subregions into more than 350 hydrologic accounting units. Minnesota has 17 of the nations hydrologic accounting units: Northwestern Lake Superior (040101), St. Louis (040102), Southwestern Lake Superior (040103), Mississippi Headwaters (070101), Upper Mississippi-Crow-Rum (070102), Minnesota (070200), St. Croix (070300), Upper Mississippi-Black-Root (070400), Upper Mississippi-Maquoketa-Plum (070600), Upper Mississippi-Skunk-Wapsipinicon (070801), Iowa (070802), Des Moines (071000), Upper Red (090201), Lower Red (090203), Rainy (090300), Big Sioux (101702), Missouri-Little Sioux (102300).HUC 4 Boundaries (USGS): HUC 4s are geographic subregions which are drained by a river system, a reach of river and its tributaries in that reach, a closed basin, or a group of streams forming a coastal drainage areas. Minnesota has 12 of the nations 222 subregions: Western Lake Superior (0401), Mississippi Headwaters (0701), Minnesota (0702), St. Croix (0703), Upper Mississippi-Black-Root (0704), Upper Mississippi-Maquoketa-Plum (0706), Upper Mississippi-Iowa-Skunk-Wapsipinicon (0708), Des Moines (0710), Red (0902), Rainy (0903), Missouri-Big Sioux (1017), Missouri-Little Sioux (1023).HUC 2 Boundaries (USGS): HUC 2s are geographic regions which contain the drainage of a major river or a series of rivers. Minnesota has 4 of the nations 21 regions: Great Lakes (R04), Upper Mississippi (R07), Souris-Red-Rainy (R09), and Missouri (R10).These datasets have not been optimized for fast display (but rather they maintain their original shape/precision), therefore it is recommend that filtering is used to show only the features of interest. For more information about using filters please see "Work with map layers: Apply Filters": https://doc.arcgis.com/en/arcgis-online/create-maps/apply-filters.htmFor additional information about the Watershed Boundary Dataset please see:United States Geological Survey Water-Supply Paper 2294: https://pubs.usgs.gov/wsp/wsp2294/Hydrologic Units, The National Atlas of the United State of America: https://pubs.usgs.gov/gip/hydrologic_units/pdf/hydrologic_units.pdfNational Hydrography Dataset, Watershed Boundary Dataset: https://www.usgs.gov/core-science-systems/ngp/national-hydrography/watershed-boundary-dataset

Open Data. Public Safety Answering Point (PSAP) Boundaries within St. Louis County, Missouri. Link to Metadata.