The population density of Anchorage Municipality, AK was 174 in 2018.
Population Density
Population Density is computed by dividing the total population by Land Area Per Square Mile.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Population Datasets Involving Anchorage Municipality, AK
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[ARCHIVED] Census Population Density
data.novascotia.ca | Last Updated 2020-01-06T15:04:30.000Z<b>[ARCHIVED]</b> Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia. This table reports population density. This data is sourced from the Census of Population. Geographies available: provinces, counties, communities, municipalities, district health authorities, community health boards, economic regions, police districts, school boards, municipal electoral districts, provincial electoral districts, federal electoral districts, regional development authorities, watersheds
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Real Property Assessment Equity Statistics By Municipality: Beginning 2004
data.ny.gov | Last Updated 2024-03-05T19:24:08.000ZThe Department of Taxation and Finance annually produces a report documenting the results of the Market Value Survey pertaining to property assessment. The report contains the staff findings regarding assessment equity by municipality in New York State, that is, the degree to which assessments are at a uniform percentage of their market value. Equity is measured primarily by two statistics — the coefficient of dispersion (COD) and the price-related differential (PRD). For more information please go to: http://www.tax.ny.gov/research/property/default.htm
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NOAA - Number of TsunamiReady Communities (cumulative)
performance.commerce.gov | Last Updated 2024-03-28T20:21:54.000ZAmericans live in the most severe weather-prone country on Earth. TsunamiReady Communities support a Weather-Ready Nation by preparing for the occurrence of high impact environmental events. On an annual basis NWS targets 50 new and renewed TsunamiReady communities pending funding availability. A TsunamiReady County or Community or Tribe is defined as a coastal local government entity* that has the authority and ability to adopt the TsunamiReady recognition guidelines for the residents and visitors within its jurisdiction. *The term “local government” here means – (A) a county, parish (LA), borough (AK), or municipality (PR) (B) an incorporated municipality, city, town, or township (C) an Indian tribe or authorized tribal organization, or Alaska Native village or organization (D) a military installation
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MUNICIPAL_BOUNDARY
data.pa.gov | Last Updated 2023-05-28T18:52:33.000Z - API
American Community Survey 2018 - 2022 Estimates by Neighborhood: Basic Demographics
data.cambridgema.gov | Last Updated 2024-02-02T21:51:09.000ZBlockgroup data from the 2018 - 2022 American Community Survey was recompiled by the Cambridge Community Development Department to align with approximate neighborhood boundaries. Categories include: Total Population, Population Density, Land Area, Male/Female, Race and Hispanic Origin, Age Distribution, Number of Households, Population in Households, Persons per Household, Number of Families, Household Types, and Population in Group Quarters.
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Waste Tire Abatement Sites
data.ny.gov | Last Updated 2022-08-12T17:59:04.000ZInformation on designated waste tire abatement sites in New York State, including approximate size, location, and abatement status.
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Municipality Breakdown
impact.stlouisco.com | Last Updated 2019-02-15T21:07:02.000Z - API
Energy and Water Data Disclosure for Local Law 84 2021 (Data for Calendar Year 2020)
data.cityofnewyork.us | Last Updated 2024-01-24T17:29:59.000ZData and metrics on water and energy consumption in privately owned buildings over 25,000 ft2 and in City-owned buildings over 10,000 ft2.
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Energy and Water Data Disclosure for Local Law 84 2019 (Data for Calendar Year 2018)
data.cityofnewyork.us | Last Updated 2024-01-24T17:31:00.000ZData and metrics on water and energy consumption in privately owned buildings over 25,000 ft2 and in City-owned buildings over 10,000 ft2.
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Uninsured Population Census Data CY 2009-2014 Human Services
data.pa.gov | Last Updated 2022-10-18T14:19:11.000ZThis data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.