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The land area of Cascade County, MT was 2,698 in 2018. The land area of Ward County, ND was 2,013 in 2018.

Land Area

Water Area

Land area is a measurement providing the size, in square miles, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundary recorded for each entity in the Census Bureau's geographic database. Land area is based on current information in the TIGER® data base, calculated for use with Census 2010.

Water Area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of any lake, reservoir, pond, or similar body of water that is recorded in the Census Bureau's geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two- dimensional feature (rather than as a single line). The portions of the oceans and related large embayments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across. Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions.

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Geographic and Area Datasets Involving Cascade County, MT or Ward County, ND

  • API

    City Infrastructure Needs

    data.orcities.org | Last Updated 2016-08-08T23:16:13.000Z

    Information provided by respondent cities through the 2016 LOC Infrastructure Survey. Data is and aggregation of capital projects needs for the next 20 years.

  • API

    Certified Annual Financial Report (CAFR) Data 2017

    data.orcities.org | Last Updated 2019-04-23T03:41:40.000Z

    This is the City Financial Data for fiscal year 2017. Note that this data has been expanded for FY2017 to include more detailed breakdown of city finances.

  • API

    Annual Financial Report (ACFR) Data 2018

    data.orcities.org | Last Updated 2021-10-28T23:37:31.000Z

    This is the City Financial Data for fiscal year 2017. Note that this data has been expanded for FY2018 to include more detailed breakdown of city finances.

  • API

    System Development Charge Survey Data

    data.orcities.org | Last Updated 2016-09-02T22:00:04.000Z

    Data for the 2016 SDC Survey. NOTE: Some data (such as residential and non-residential fees) are based on an example given to member cities in the survey. The example is provided in the attached survey.

  • API

    Assessor [Archived 05-31-2023] - Parcel Universe

    datacatalog.cookcountyil.gov | Last Updated 2023-05-31T21:51:45.000Z

    A complete, historic universe of Cook County parcels with attached geographic, governmental, and spatial data. When working with Parcel Index Numbers (PINs) make sure to zero-pad them to 14 digits. Some datasets may lose leading zeros for PINs when downloaded. Additional notes:<ul><li>Data is attached via spatial join (st_contains) to each parcel's centroid.</li> <li>Centroids are based on <a href="https://datacatalog.cookcountyil.gov/Property-Taxation/ccgisdata-Parcel-2021/77tz-riq7">Cook County parcel shapefiles</a>.</li> <li>Older properties may be missing coordinates and thus also missing attached spatial data (usually they are missing a parcel boundary in the shapefile).</li> <li>Newer properties may be missing a mailing or property address, as they need to be assigned one by the postal service.</li> <li>Attached spatial data does NOT go all the way back to 1999. It is only available for more recent years, primarily those after 2012.</li> <li>The universe contains data for the current tax year, which may not be complete or final. PINs can still be added and removed to the universe up until the Board of Review closes appeals.</li> <li>Data will be updated monthly.</li> <li>Rowcount and characteristics for a given year are final once the Assessor <a href="https://www.cookcountyassessor.com/assessment-calendar-and-deadlines">has certified the assessment roll</a> for all townships.</li> <li>Depending on the time of year, some third-party and internal data will be missing for the most recent year. Assessments mailed this year represent values from last year, so this isn't an issue. By the time the Data Department models values for this year, those data will have populated.</li> <li>Current property class codes, their levels of assessment, and descriptions can be found <a href="https://prodassets.cookcountyassessor.com/s3fs-public/form_documents/classcode.pdf">on the Assessor's website</a>. Note that class codes details can change across time.</li> <li>Due to decrepencies between the systems used by the Assessor and Clerk's offices, <i>tax_district_code</i> is not currently up-to-date in this table.</li></ul> For more information on the sourcing of attached data and the preparation of this dataset, see the <a href="https://gitlab.com/ccao-data-science---modeling/data-architecture">Assessor's data architecture repo</a> on GitLab. <a href="https://datacatalog.cookcountyil.gov/stories/s/i22y-9sd2">Read about the Assessor's 2022 Open Data Refresh.</a>

  • API

    State Of The Cities 2017

    data.orcities.org | Last Updated 2019-02-15T20:08:13.000Z

    This is the survey responses for the 2017 State of the Cities Report. This data has been coded based on survey response choices. Please consult the attached copy of the survey for more information.

  • API

    City Governance Information

    data.orcities.org | Last Updated 2020-03-06T21:43:50.000Z

    This dataset outlines details of city governance compiled from 242 city charters.

  • API

    Water Rates Survey Data 2017

    data.orcities.org | Last Updated 2018-04-30T21:33:40.000Z

    This is the survey results from the 2017 LOC Water Rates Survey. The attached Survey will help you with the coding of the data.

  • API

    Land Use_data

    opendata.utah.gov | Last Updated 2024-04-10T19:40:16.000Z

    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. 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.