The population density of Little Falls, MN was 1,197 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 Little Falls, MN
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2019 Volunteers Count Report - Neighborhoods
data.cityofnewyork.us | Last Updated 2024-01-25T21:38:46.000ZThe 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.
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City and Township Population Data
data.ramseycounty.us | Last Updated 2022-03-21T15:37:41.000ZSources: MN State Demographic Center and the Metropolitan Council. Released August 2020. The Minnesota State Demographic Center (our office) and the Metropolitan Council jointly produce population and household estimates for all years between the U.S. Census Bureau's decennial (10-year) counts. The Met Council produces the estimates for the seven counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington, as well as all cities and townships within those counties. Our office produces the estimates for the other 80 Minnesota counties outside of the 7-county metro, as well as all cities and townships within those counties. Notes: New estimates are released annually in late July for the prior year. All data are dated to April 1. Persons per household is calculated by dividing the household population by the number of occupied households in any given geography. The household population does not equal the total population because some residents live in "group quarters" settings (such as college dormitories, nursing facilities, shelters, treatment centers, religious orders, military barracks, or correctional facilities), and thus are not living in households. Cities that cross county boundaries are segmented by each county's portion (labeled "part"), as well as appearing in total under "Multi-County City" in the "COUNTY NAME" column.
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LinkNYC Kiosk Locations
data.cityofnewyork.us | Last Updated 2024-09-10T20:12:43.000ZLinkNYC is the City’s program to provide free high-speed Wi-Fi, nationwide calling, a dedicated 911 button, charging ports for mobile devices, and access to social services. The City has recently begun to roll out a new and improved design of the original LinkNYC kiosk: Link5G. This new design will provide all of the amenities of LinkNYC kiosks, with the added benefit of 4G and 5G connectivity to enhance mobile telecommunications networks. This dataset lists locations for LinkNYC kiosks plus four public payphones in the five boroughs.
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Archery Hunt Totals
data.ramseycounty.us | Last Updated 2023-09-29T20:16:08.000ZRamsey County conducts special permit archery hunts each fall in partnership with the Metro Bowhunters Resource Base. This dataset shares archery harvest totals. The annual hunts have been conducted since 2000. All participating hunters attend a pre-hunt orientation, agree to special hunt rules and pass an archery safety class and shooting proficiency test. Archers may keep their deer or donate the venison to local food shelves. During the hunts, entire parks or portions of a park may be closed. Archery hunting is the county's preferred method of deer population control.
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Master Intersections List
data.cambridgema.gov | Last Updated 2024-09-16T11:30:37.000ZStreet intersections in the City of Cambridge. This dataset contains the complete list of intersections in Cambridge, along with each intersection's geospatial coordinates and relevant administrative boundaries (e.g., Census block, polling district, public safety area). The dataset is sourced from Cambridge's GIS databases. Shapefiles for this data and other Cambridge geospatial data can be found on on the City's GIS Data Dictionary at https://www.cambridgema.gov/GIS/gisdatadictionary
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Tracts 2020
data.delaware.gov | Last Updated 2024-03-01T14:44:49.000Z<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>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.</SPAN></P><P><SPAN>Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2020 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2010 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area.</SPAN></P></DIV></DIV></DIV>
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CTCAC/HCD Resource Opportunity Areas 2022
data.bayareametro.gov | Last Updated 2023-06-08T23:15:47.000ZIn 2017, the California Tax Credit Allocation Committee (CTCAC) and the Department of Housing and Community Development (HCD) created the California Fair Housing Task Force (Task Force). The Task Force was asked to assist CTCAC and HCD in creating evidence-based approaches to increasing access to opportunity for families with children living in housing subsidized by the Low-Income Housing Tax Credit (LIHTC) program. This feature set contains Resource Opportunity Areas (ROAs) that are the results of the Task Force's analysis for the two regions used for the San Francisco Bay Region; one is for the cities and towns (urban) and the other is for the rural areas. The reason for treating urban and rural areas as separate reasons is that using absolute thresholds for place-based opportunity could introduce comparisons between very different areas of the total region that make little sense from a policy perspective — in effect, holding a farming community to the same standard as a dense, urbanized neighborhood. ROA analysis for urban areas is based on census tract data. Since tracts in rural areas of are approximately 37 times larger in land area than tracts in non-rural areas, tract-level data in rural areas may mask over variation in opportunity and resources within these tracts. Assessing opportunity at the census block group level in rural areas reduces this difference by 90 percent (each rural tract contains three block groups), and thus allows for finer-grained analysis. In addition, more consistent standards can be useful for identifying areas of concern from a fair housing perspective — such as high-poverty and racially segregated areas. Assessing these factors based on intraregional comparison could mischaracterize areas in more affluent areas with relatively even and equitable development opportunity patterns as high-poverty, and could generate misleading results in areas with higher shares of objectively poor neighborhoods by holding them to a lower, intraregional standard. To avoid either outcome, the Task Force used a hybrid approach for the CTCAC/HCD ROA analysis — accounting for regional differences in assessing opportunity for most places, while applying more rigid standards for high-poverty, racially segregated areas in all regions. In particular: Filtering for High-Poverty, Racially Segregated Areas The CTCAC/HCD ROA filters areas that meet consistent standards for both poverty (30% of the population below the federal poverty line) and racial segregation (over-representation of people of color relative to the county) into a “High Segregation & Poverty” category. The share of each region that falls into the High Segregation & Poverty category varies from region to region. Calculating Index Scores for Non-Filtered Areas The CTCAC/HCD ROAs process calculates regionally derived opportunity index scores for non-filtered tracts and rural block groups using twenty-one indicators (see Data Quality section of metadata for more information). These index scores make it possible to sort each non-filtered tract or rural block group into opportunity categories according to their rank within the urban or rural areas. To allow CTCAC and HCD to incentivize equitable development patterns in each region to the same degree, the CTCAC/HCD analysis 20 percent of tracts or rural block groups in each urban or rural area, respectively, with the highest relative index scores to the "Highest Resource” designation and the next 20 percent to the “High Resource” designation. The region's urban area thus ends up with 40 percent of its total tracts with reliable data as Highest or High Resource (or 40 percent of block groups in the rural area). The remaining non-filtered tracts or rural block groups are then evenly divided into “Low Resource” and “Moderate Resource” categories. Excluding Tracts or Block Groups The analysis also excludes certain census areas from being categorized. To improve the accuracy of the mapping, tracts and rural bl
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National Community Based Survey of Supports for Healthy Eating and Active Living (CBS HEAL)
data.cdc.gov | Last Updated 2023-08-25T15:08:48.000ZCommunity-Based Survey of Supports for Healthy Eating and Active Living (CBS HEAL) is a CDC survey of a nationally representative sample of U.S. municipalities to better understand existing community-level policies and practices that support healthy eating and active living. The survey collects information about policies such as nutrition standards, incentives for healthy food retail, bike/pedestrian-friendly design, and Complete Streets. About 2,000 municipalities respond to the survey. Participating municipalities receive a report that allows them to compare their policies and practices with other municipalities of similar geography, population size, and urban status. The CBS HEAL survey was first administered in 2014 and was administered again in 2021. Data is provided in multiple formats for download including as a SAS file. A methods report and a SAS program for formatting the data are also provided.