The land area of St. George, SC was 3 in 2012.

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 St. George, SC

  • API

    Special Protection Area Review Data

    data.montgomerycountymd.gov | Last Updated 2024-09-12T09:40:27.000Z

    A Special Protection Area (SPA) is a geographic area designated by the County Council which has high quality or unusually sensitive water resources and environmental features that would be threatened by proposed land development if special water quality protection measures were not applied. This dataset tracks reviews for development in all SPAs. Update Frequency : Daily.

  • API

    SITLA South Block Master Plan_data

    opendata.utah.gov | Last Updated 2024-04-10T19:40:26.000Z

    This dataset depicts the master plan for the 6,116-acre South Block Master Plan Area located within the City of St. George, Utah. The South Block Master Plan serves as a guiding freamework for land use, tranportation, hillside preservation and future zoning.

  • API

    Stormwater Management Concept Information

    data.montgomerycountymd.gov | Last Updated 2024-10-15T09:50:15.000Z

    A stormwater management concept is a statement or drawing, or both, describing the manner in which stormwater runoff from a proposed development will be controlled to minimize damage to neighboring properties and receiving streams and to also prevent the discharge of pollutants into surface waters. Update Frequency : Daily.

  • API

    Current Descriptive Data of Municipal Wastewater Treatment Plants

    data.ny.gov | Last Updated 2019-06-10T18:04:47.000Z

    Data containing municipal wastewater treatment plant design other features, with data current through the most recent survey.

  • API

    2019 Volunteers Count Report - Neighborhoods

    data.cityofnewyork.us | Last Updated 2024-01-25T21:38:46.000Z

    The annual NYC Volunteers Count report is the City’s largest scan of residents volunteering at organizations across New York City. Organizations, including City agencies, Mayoral offices, and nonprofits, are surveyed to understand how residents volunteer within the city’s infrastructure to strengthen communities at the neighborhood level. All participating organizations are recognized for their contributions in the annual NYC Volunteers Count report.

  • API

    Utah Census Data Cities 2009-2013

    opendata.utah.gov | Last Updated 2019-02-11T22:36:06.000Z

    Data derived from Population Estimates, American Community Survey, Census of Population and Housing, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits

  • API

    SITLA South Block Master Plan_data

    opendata.utah.gov | Last Updated 2024-04-10T19:39:41.000Z

    This dataset depicts the master plan for the 6,116-acre South Block Master Plan Area located within the City of St. George, Utah. The South Block Master Plan serves as a guiding freamework for land use, tranportation, hillside preservation and future zoning.

  • 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.

  • API

    Community Survey

    datahub.austintexas.gov | Last Updated 2023-09-13T22:02:29.000Z

    Each year the city of Austin administers a community survey to assess satisfaction with the delivery of the major City Services and to help determine priorities for the community as part of the City's ongoing planning process. To find out more information about the Community Survey and to view the Survey Instruments, please refer to the attachments. The data set for the Community Survey captures data from 2015 through 2019.

  • API

    USAID Construction Assessment, Subawards: Section 10

    datahub.usaid.gov | Last Updated 2024-06-25T02:14:34.000Z

    In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the tenth spreadsheet of thirteenin the USAID Construction Assessment, Subawards. The USAID construction assessment is a survey of the character, scope, value and management of construction activities supported by USAID during the period from June 1, 2011 to June 20, 2013.