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The water area of Redding, CA was 2 in 2018. The water area of Beaverton, OR was 0 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 Redding, CA or Beaverton, OR

  • API

    Baseline Study of Food for Peace Title II Development Food Assistance Program in Niger-- Household Sanitation and Maternal Health

    data.usaid.gov | Last Updated 2018-11-13T05:02:48.000Z

    This dataset captures data about the mothers in the households surveyed as part of the Baseline Study of Food for Peace Title II Development Food Assistance Program in the Maradi and Zinder regions in Niger as well as the water and sanitation resources available to the household. It has 200 columns and 7,337 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Niger. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later.

  • API

    Baseline Study of Food for Peace Title II Development Food Assistance Program in Karamoja, Uganda--Maternal Health and Household Sanitation

    data.usaid.gov | Last Updated 2018-11-13T05:02:49.000Z

    This dataset captures data about the mothers in the households surveyed as part of the Baseline Study of Food for Peace Title II Development Food Assistance Program in Karamoja, Uganda as well as the water and sanitation resources available to the household. This dataset contains data from Modules F and J of the questionnaire and has 295 columns and 4,766 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Uganda. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later. The data asset is comprised of six datasets: 1) a description of all members of the households surveyed, 2) data on maternal health and sanitation practices, 3) data about the children in the household, 4) data describing the agricultural practices of the household, 5) data describing the food consumption of the household (broken into 4 smaller spreadsheets), and 6) and a description of the weights that should be applied during the analysis of the other datasets.

  • 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.