The population density of Mobile County, AL was 337 in 2015.
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 Mobile County, AL
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WAOFM - Census - Population and Housing, 2000 and 2010
data.wa.gov | Last Updated 2021-09-01T17:20:31.000ZPopulation and housing information extracted from decennial census Public Law 94-171 redistricting summary files for Washington state for years 2000 and 2010.
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Deer Tick Surveillance: Adults (Oct to Dec) excluding Powassan virus: Beginning 2008
health.data.ny.gov | Last Updated 2024-05-01T18:05:44.000ZThis dataset provides the results from collecting and testing adult deer ticks, also known as blacklegged ticks, or by their scientific name <i>Ixodes scapularis</i>. Collection and testing take place across New York State (excluding New York City) from October to December, when adult deer ticks are most commonly seen. Adult deer ticks are individually tested for different bacteria and parasites, which includes the bacteria responsible for Lyme disease. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide adult tick infections at a precise location and at one point in time. Both measures, tick population density and percentage, of ticks infected with the specified bacteria or parasite can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.
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Deer Tick Surveillance: Nymphs (May to Sept) excluding Powassan virus: Beginning 2008
health.data.ny.gov | Last Updated 2024-05-01T18:07:53.000ZThis dataset provides the results from collecting and testing nymph deer ticks, also known as blacklegged ticks, or by their scientific name <i>Ixodes scapularis</i>. Collection and testing take place across New York State (excluding New York City) from May to September, when nymph deer ticks are most commonly seen. Nymph deer ticks are individually tested for different bacteria and parasites, which includes the bacteria responsible for Lyme disease. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide nymph tick infections at a precise location and at one point in time. Both measures, tick population density and percentage, of ticks infected with the specified bacteria or parasite can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.
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Choose Maryland: Compare Counties - Demographics
opendata.maryland.gov | Last Updated 2024-07-09T17:43:22.000ZPopulation profile - total, rate of change, age, and density.
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WAOFM - Census - Population Density by County by Decade, 1900 to 2020
data.wa.gov | Last Updated 2023-07-06T16:48:57.000ZWashington state population density by county by decade 1900 to 2020.
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Trips by Distance
data.bts.gov | Last Updated 2024-04-30T19:08:37.000ZHow many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our mobility statistics program. The "Trips by Distance" data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day. Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air. The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed. These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit. These data are made available under a public domain license. Data should be attributed to the "Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland and the United States Bureau of Transportation Statistics." Daily data for a given week will be uploaded to the BTS website within 9-10 days of the end of the week in question (e.g., data for Sunday September 17-Saturday September 23 would be updated on Tuesday, October 3). All BTS visualizations and tables that rely on these data will update at approximately 10am ET on days when new data are received, processed, and uploaded. The methodology used to develop these data can be found at: https://rosap.ntl.bts.gov/view/dot/67520.
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Mobility Trends County Modeling Dataset
datahub.transportation.gov | Last Updated 2024-08-08T20:59:05.000ZThe Mobility Trends County Modeling dataset consists of the accumulation of the three performance metrics: VMT, GHG, and TMS, alongside each of the trend indicators: GDP, Population, Lane Miles, Unemployment Rate, Charging Stations, Telework, Unlinked Passenger Trips, E-commerce, Population Density, and on-demand service revenue. The goal of Mobility Trends and Future Demand research project is to enhance FHWA’s empirical understanding of the impact of trends on travel behavior and transportation demand, and ultimately system performance and the user experience. At the core of this research project is the identification and analysis of trends to support a variety of modeling, forecasting, and ‘what if’ projections to support policy and decision making.
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Deer Tick Surveillance: Nymphs (May to Sept) Powassan Virus Only: Beginning 2009
health.data.ny.gov | Last Updated 2024-05-01T18:00:16.000ZThis dataset provides the results from collecting and testing nymph deer ticks, also known as blacklegged ticks, or by their scientific name <i>Ixodes scapularis</i>. Collection and testing take place across New York State (excluding New York City) from May to September, when nymph deer ticks are most commonly seen. Nymph deer ticks are tested in “pools”, or groups of up to ten adult ticks per pool, for the Powassan virus, also known as Deer tick virus. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide nymph tick minimum infection rates at a precise location and at one point in time. Both measures, tick population density and minimum infection percentages, can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.
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Deer Tick Surveillance: Adults (Oct to Dec) Powassan Virus Only: Beginning 2009
health.data.ny.gov | Last Updated 2024-05-01T18:04:12.000ZThis dataset provides the results from collecting and testing adult deer ticks, also known as blacklegged ticks, or by their scientific name Ixodes scapularis. Collection and testing take place across New York State (excluding New York City) from October to December, when adult deer ticks are most commonly seen. Adult deer ticks are tested in “pools”, or groups of up to ten adult ticks per pool, for the Powassan virus, also known as Deer tick virus. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide adult tick minimum infection rates at a precise location and at a point in time. Both measures, tick population density and minimum infection percentages, can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.
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WAOFM - April 1 - Population Density by County, 2000 to Present
data.wa.gov | Last Updated 2024-07-11T21:24:42.000ZIntercensal and postcensal estimates of population density by county 2000 to present.