As of 2024, Chugach State Park in Anchorage, Alaska, was the largest city park in the United States by a long shot, spanning 464,318 acres. Second in the ranking was the Great Dismal Swamp in the Coastal Plain Region of southeastern Virginia and northeastern North Carolina, at 113,000 acres. A wide variety of park authorities Most parks in the U.S. are owned by the municipality, state, county, regional agency, or the federal government. Both McDowell Sonoran Preserve and South Mountain Preserve are part of the state park system along with most of the parks in the ranking. One of the more well-known park authorities is the National Park Service (NPS) – an agency of the federal government. The Golden Gate National Recreation Area was the most visited NPS park in 2024 alongside many other well-known U.S. parks. What defines a park? Parks in the U.S. are often called a variety of names, just a few of which are: forest, reserve, preserve and wildlife management area. Sometimes the differences between parks in the U.S. can vary massively from monuments to expansive woodland. In 2024, Central Park in New York, topped the ranking of the most visited city parks in the U.S.

The city park with the highest annual visitation in 2023 was Central Park in New York, accounting for a total of ********** visitors. The second most visited city park in that year was Golden Gate Park in San Francisco, with nearly half the visitation of Central Park, at **********.

This graph depicts the size of county-owned city parks in the U.S. in 2010. The Bear Creek Pioneers Park in Houston has an area of 2,168 acres.

Reason for Selection Protected natural areas in urban environments provide urban residents a nearby place to connect with nature and offer refugia for some species. They help foster a conservation ethic by providing opportunities for people to connect with nature, and also support ecosystem services like offsetting heat island effects (Greene and Millward 2017, Simpson 1998), water filtration, stormwater retention, and more (Hoover and Hopton 2019). In addition, parks, greenspace, and greenways can help improve physical and psychological health in communities (Gies 2006). Urban park size complements the equitable access to potential parks indicator by capturing the value of existing parks.Input DataSoutheast Blueprint 2024 extentFWS National Realty Tracts, accessed 12-13-2023Protected Areas Database of the United States(PAD-US):PAD-US 3.0 national geodatabase -Combined Proclamation Marine Fee Designation Easement, accessed 12-6-20232020 Census Urban Areas from the Census Bureau’s urban-rural classification; download the data, read more about how urban areas were redefined following the 2020 censusOpenStreetMap data “multipolygons” layer, accessed 12-5-2023A polygon from this dataset is considered a beach if the value in the “natural” tag attribute is “beach”. Data for coastal states (VA, NC, SC, GA, FL, AL, MS, LA, TX) were downloaded in .pbf format and translated to an ESRI shapefile using R code. OpenStreetMap® is open data, licensed under theOpen Data Commons Open Database License (ODbL) by theOpenStreetMap Foundation (OSMF). Additional credit to OSM contributors. Read more onthe OSM copyright page.2021 National Land Cover Database (NLCD): Percentdevelopedimperviousness2023NOAA coastal relief model: volumes 2 (Southeast Atlantic), 3 (Florida and East Gulf of America), 4 (Central Gulf of America), and 5 (Western Gulf of America), accessed 3-27-2024Mapping StepsCreate a seamless vector layer to constrain the extent of the urban park size indicator to inland and nearshore marine areas <10 m in depth. The deep offshore areas of marine parks do not meet the intent of this indicator to capture nearby opportunities for urban residents to connect with nature. Shallow areas are more accessible for recreational activities like snorkeling, which typically has a maximum recommended depth of 12-15 meters. This step mirrors the approach taken in the Caribbean version of this indicator.Merge all coastal relief model rasters (.nc format) together using QGIS “create virtual raster”.Save merged raster to .tif and import into ArcPro.Reclassify the NOAA coastal relief model data to assign areas with an elevation of land to -10 m a value of 1. Assign all other areas (deep marine) a value of 0.Convert the raster produced above to vector using the “RasterToPolygon” tool.Clip to 2024 subregions using “Pairwise Clip” tool.Break apart multipart polygons using “Multipart to single parts” tool.Hand-edit to remove deep marine polygon.Dissolve the resulting data layer.This produces a seamless polygon defining land and shallow marine areas.Clip the Census urban area layer to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Clip PAD-US 3.0 to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Remove the following areas from PAD-US 3.0, which are outside the scope of this indicator to represent parks:All School Trust Lands in Oklahoma and Mississippi (Loc Des = “School Lands” or “School Trust Lands”). These extensive lands are leased out and are not open to the public.All tribal and military lands (“Des_Tp” = "TRIBL" or “Des_Tp” = "MIL"). Generally, these lands are not intended for public recreational use.All BOEM marine lease blocks (“Own_Name” = "BOEM"). These Outer Continental Shelf lease blocks do not represent actively protected marine parks, but serve as the “legal definition for BOEM offshore boundary coordinates...for leasing and administrative purposes” (BOEM).All lands designated as “proclamation” (“Des_Tp” = "PROC"). These typically represent the approved boundary of public lands, within which land protection is authorized to occur, but not all lands within the proclamation boundary are necessarily currently in a conserved status.Retain only selected attribute fields from PAD-US to get rid of irrelevant attributes.Merged the filtered PAD-US layer produced above with the OSM beaches and FWS National Realty Tracts to produce a combined protected areas dataset.The resulting merged data layer contains overlapping polygons. To remove overlapping polygons, use the Dissolve function.Clip the resulting data layer to the inland and nearshore extent.Process all multipart polygons (e.g., separate parcels within a National Wildlife Refuge) to single parts (referred to in Arc software as an “explode”).Select all polygons that intersect the Census urban extent within 0.5 miles. We chose 0.5 miles to represent a reasonable walking distance based on input and feedback from park access experts. Assuming a moderate intensity walking pace of 3 miles per hour, as defined by the U.S. Department of Health and Human Service’s physical activity guidelines, the 0.5 mi distance also corresponds to the 10-minute walk threshold used in the equitable access to potential parks indicator.Dissolve all the park polygons that were selected in the previous step.Process all multipart polygons to single parts (“explode”) again.Add a unique ID to the selected parks. This value will be used in a later step to join the parks to their buffers.Create a 0.5 mi (805 m) buffer ring around each park using the multiring plugin in QGIS. Ensure that “dissolve buffers” is disabled so that a single 0.5 mi buffer is created for each park.Assess the amount of overlap between the buffered park and the Census urban area using “overlap analysis”. This step is necessary to identify parks that do not intersect the urban area, but which lie within an urban matrix (e.g., Umstead Park in Raleigh, NC and Davidson-Arabia Mountain Nature Preserve in Atlanta, GA). This step creates a table that is joined back to the park polygons using the UniqueID.Remove parks that had ≤10% overlap with the urban areas when buffered. This excludes mostly non-urban parks that do not meet the intent of this indicator to capture parks that provide nearby access for urban residents. Note: The 10% threshold is a judgement call based on testing which known urban parks and urban National Wildlife Refuges are captured at different overlap cutoffs and is intended to be as inclusive as possible.Calculate the GIS acres of each remaining park unit using the Add Geometry Attributes function.Buffer the selected parks by 15 m. Buffering prevents very small and narrow parks from being left out of the indicator when the polygons are converted to raster.Reclassify the parks based on their area into the 7 classes seen in the final indicator values below. These thresholds were informed by park classification guidelines from the National Recreation and Park Association, which classify neighborhood parks as 5-10 acres, community parks as 30-50 acres, and large urban parks as optimally 75+ acres (Mertes and Hall 1995).Assess the impervious surface composition of each park using the NLCD 2021 impervious layer and the Zonal Statistics “MEAN” function. Retain only the mean percent impervious value for each park.Extract only parks with a mean impervious pixel value <80%. This step excludes parks that do not meet the intent of the indicator to capture opportunities to connect with nature and offer refugia for species (e.g., the Superdome in New Orleans, LA, the Astrodome in Houston, TX, and City Plaza in Raleigh, NC).Extract again to the inland and nearshore extent.Export the final vector file to a shapefile and import to ArcGIS Pro.Convert the resulting polygons to raster using the ArcPy Feature to Raster function and the area class field.Assign a value of 0 to all other pixels in the Southeast Blueprint 2024 extent not already identified as an urban park in the mapping steps above. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.Use the land and shallow marine layer and “extract by mask” tool to save the final version of this indicator.Add color and legend to raster attribute table.As a final step, clip to the spatial extent of Southeast Blueprint 2024.Note: For more details on the mapping steps, code used to create this layer is available in theSoutheast Blueprint Data Downloadunder > 6_Code. Final indicator valuesIndicator values are assigned as follows:6= 75+ acre urban park5= 50 to <75 acre urban park4= 30 to <50 acre urban park3= 10 to <30 acre urban park2=5 to <10acreurbanpark1 = <5 acre urban park0 = Not identified as an urban parkKnown IssuesThis indicator does not include park amenities that influence how well the park serves people and should not be the only tool used for parks and recreation planning. Park standards should be determined at a local level to account for various community issues, values, needs, and available resources.This indicator includes some protected areas that are not open to the public and not typically thought of as “parks”, like mitigation lands, private easements, and private golf courses. While we experimented with excluding them using the public access attribute in PAD, due to numerous inaccuracies, this inadvertently removed protected lands that are known to be publicly accessible. As a result, we erred on the side of including the non-publicly accessible lands.The NLCD percent impervious layer contains classification inaccuracies. As a result, this indicator may exclude parks that are mostly natural because they are misclassified as mostly impervious. Conversely, this indicator may include parks that are mostly impervious because they are misclassified as mostly

‘Total tweets’ enumerates all public tweets posted from a GPS latitude/longitude inside that city. ‘Park tweets’ is the total number of tweets posted from inside parks. The ‘% tweets in park’ column calculates Park tweets / total Tweets. ‘Park visitors’ is the number of unique users who tweeted inside one of that city’s municipal park locations as defined by Trust for Public Land’s ParkServe. ‘Parks visited’ is the number of unique facilities from which a tweet was posted within that city. ‘Tweets per capita’ is number of total messages for the entire period divided by the city’s population in 2012.

In 2024, New York City had the highest public park and recreation spending of any city in the United States at approximately *** billion U.S. dollars. Second in the ranking was Chicago, Illinois, which spent around *** million U.S. dollars on parks and rec.

In 2024, the city in the United States with the highest share of parkland was Anchorage, Alaska, where approximately 84 percent of the city was parkland. In second place, with almost half the percentage of parkland was Fremont, California, where 43 percent of the city was parkland.

In 2024, Anchorage, Alaska led all U.S. cities in parkland per 1,000 residents, offering roughly 3,183 acres. Chesapeake, Virginia followed in second place, with 243 acres per 1,000 residents.

Natural Earth is a public domain map dataset available at 1:10, 1:50 and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

When prioritizing regions for conservation protection, decisions are often based on the principle that a single large (SL) reserve should support more species than several small (SS) reserves of the same total area (SLOSS). This principle remains a central paradigm in conservation planning despite conflicting empirical evidence and methodological concerns. In urban areas where small parks tend to dominate and policies to promote biodiversity are becoming increasingly popular, determining the most appropriate prioritization method is critical. Here, we document the role of SLOSS in defining the seasonal diversity of birds in 475 parks in 21 US cities. Collections of small parks were consistently associated with higher species richness, spatial turnover, and rarity. Collections of both small and large parks were associated with higher phylogenetic and functional diversity whose patterns varied across seasons and cities. Thus, collections of small parks are a reliable source of species richness driven by higher spatial turnover and rarity, whereas collections of both small and large parks contain the potential to support higher phylogenetic and functional diversity. The presence of strong intra-annual and geographic variation emphasizes the need for regional prioritization strategies where multiple diversity metrics are examined across parks and seasons.

Smart Visitor Counters for Parks Market Outlook

According to our latest research, the Global Smart Visitor Counters for Parks market size was valued at $580 million in 2024 and is projected to reach $1.42 billion by 2033, expanding at a robust CAGR of 10.5% during 2024–2033. A major factor driving the growth of this market globally is the increasing emphasis on data-driven park management and visitor experience optimization. As parks and recreational spaces face mounting pressure to balance conservation with accessibility, the deployment of advanced visitor counting solutions has become essential for resource allocation, crowd management, and infrastructure planning. The integration of IoT, AI, and real-time analytics into smart visitor counters is transforming how park authorities understand visitor patterns, enabling them to make informed decisions that enhance both operational efficiency and visitor satisfaction.

Regional Outlook

North America currently holds the largest market share in the smart visitor counters for parks market, accounting for approximately 39% of the global revenue in 2024. The region’s dominance is attributed to its mature technological infrastructure, widespread adoption of smart city initiatives, and significant investments in public park modernization. The United States, in particular, has been at the forefront of integrating advanced visitor management solutions in national and urban parks, driven by strong governmental support, public-private partnerships, and a culture that prioritizes data-driven decision-making. Additionally, the presence of leading technology providers and a high level of awareness among park authorities have contributed to rapid deployment and continuous innovation in this sector. These factors collectively position North America as the benchmark for smart visitor counter adoption and innovation.

The Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR exceeding 13.2% through 2033. This remarkable growth is fueled by rapid urbanization, increasing investments in tourism infrastructure, and government initiatives aimed at enhancing the quality and safety of public recreational spaces. Countries such as China, Japan, Australia, and South Korea are leading the charge, with large-scale deployments of smart visitor counting systems in both urban and nature parks. The proliferation of smart city projects, coupled with rising disposable incomes and growing environmental awareness among the population, is accelerating the adoption of advanced park management technologies. Furthermore, partnerships between international technology vendors and local authorities are fostering knowledge transfer and facilitating the customization of solutions to meet unique regional needs.

In emerging economies across Latin America, the Middle East, and Africa, the adoption of smart visitor counters for parks is gaining momentum, albeit at a slower pace due to infrastructural and budgetary constraints. While there is a clear recognition of the benefits of digital visitor management, challenges such as limited funding, inadequate technical expertise, and fragmented policy frameworks often hinder widespread implementation. Nonetheless, localized demand is rising as governments and non-profit organizations prioritize sustainable tourism and conservation. International development agencies and technology donors are increasingly supporting pilot projects in these regions, laying the groundwork for future market expansion. The gradual rollout of affordable, easy-to-deploy solutions tailored to local conditions is expected to bridge the adoption gap and drive incremental growth over the forecast period.

Report Scope

Hundreds of millions of visitors travel to U.S. national parks every year to visit America’s iconic landscapes. Concerns about air quality in these areas have led to strict, yet controversial pollution control policies. We document pollution trends in U.S. national parks and estimate the relationship between pollution and park visitation. From 1990-2014, average ozone concentrations in national parks were statistically indistinguishable from the 20 largest U.S. metropolitan areas. Further, relative to U.S. cities, national parks have seen only modest reductions in days with ozone concentrations exceeding levels deemed unhealthy by the U.S. Environmental Protection Agency. We find a robust, negative relationship between in-park ozone concentrations and park visitation. Still, 35% of all national park visits occur when ozone levels are elevated.

About this dataset

Context

This list ranks the 1 cities in the Manassas Park city, VA by American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Native American Population: This column displays the rank of cities in the Manassas Park city, VA by their American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Native American Population: The Native American population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Manassas Park city Native American Population: This tells us how much of the entire Manassas Park city, VA Native American population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Park Safety Monitoring Analytics Market Outlook

According to our latest research, the Global Park Safety Monitoring Analytics market size was valued at $2.1 billion in 2024 and is projected to reach $6.8 billion by 2033, expanding at a robust CAGR of 13.6% during the forecast period of 2025–2033. A primary factor fueling this remarkable growth is the increasing emphasis on public safety and security within recreational spaces worldwide. As urbanization accelerates and more people frequent parks for leisure and fitness, authorities and private park operators are prioritizing advanced analytics solutions to proactively monitor, detect, and mitigate safety risks. The integration of artificial intelligence, IoT sensors, and real-time data analytics is revolutionizing how parks manage incidents, crowd flow, and emergency response, thus driving substantial investments in park safety monitoring analytics technologies globally.

Regional Outlook

North America currently dominates the Park Safety Monitoring Analytics market, accounting for the largest share of 38% in 2024. This leadership is attributed to the region’s mature infrastructure, high adoption of advanced safety technologies, and robust government regulations mandating public safety in recreational spaces. Cities across the United States and Canada have made significant investments in smart surveillance, AI-driven threat detection, and integrated emergency response systems within urban and national parks. The presence of leading technology vendors and a proactive approach to adopting digital solutions have further propelled North America’s market value, which is forecast to maintain steady growth throughout the next decade. Additionally, strong collaboration between public agencies and private stakeholders has accelerated the deployment of comprehensive park safety analytics platforms, setting a benchmark for other regions.

Asia Pacific is projected to be the fastest-growing region in the Park Safety Monitoring Analytics market, registering a remarkable CAGR of 16.4% from 2025 to 2033. This rapid expansion is fueled by increasing urbanization, a surge in public infrastructure investments, and heightened awareness about safety in public spaces. Countries such as China, Japan, South Korea, and India are investing heavily in smart city initiatives, which include the integration of safety analytics in parks and recreational areas. The growing middle class, rising tourism, and government-led digital transformation programs are further driving the demand for advanced safety monitoring solutions. Local governments are also partnering with technology firms to pilot AI-enabled surveillance and crowd management tools, making Asia Pacific a hotbed for innovation and market growth in this sector.

Emerging economies in Latin America and the Middle East & Africa are experiencing a gradual uptick in the adoption of park safety monitoring analytics, albeit at a slower pace compared to developed regions. These markets face challenges such as limited funding, infrastructural gaps, and varying regulatory standards, which can impede widespread implementation. However, localized demand for safer public spaces, especially in urban centers and tourist destinations, is prompting municipalities and private operators to explore affordable and scalable analytics solutions. Policy reforms and international collaborations are beginning to facilitate technology transfer and capacity building, paving the way for future growth. Nevertheless, the market share of these regions remains modest, and overcoming barriers related to digital literacy and resource allocation will be crucial for unlocking their full potential.

Report Scope

LoRa Sensor Mesh for Parks Security Market Outlook

According to our latest research, the Global LoRa Sensor Mesh for Parks Security market size was valued at $1.2 billion in 2024 and is projected to reach $4.6 billion by 2033, expanding at a CAGR of 16.8% during 2024–2033. This robust growth is primarily fueled by the increasing demand for advanced, scalable, and energy-efficient security solutions in public and private park spaces globally. The rapid proliferation of IoT technologies, combined with the unique long-range, low-power capabilities of LoRa sensor mesh networks, is transforming how urban and natural parks address security, asset tracking, and environmental monitoring. As urbanization accelerates and public safety concerns mount, municipalities and private operators are investing heavily in smart security infrastructures, with LoRa sensor mesh emerging as a preferred backbone due to its reliability, scalability, and cost-effectiveness.

Regional Outlook

North America currently holds the largest share of the LoRa Sensor Mesh for Parks Security market, accounting for approximately 38% of the global revenue in 2024. This dominance is attributed to the region's advanced technological infrastructure, high rate of IoT adoption, and significant investments from both public and private sectors in smart city initiatives. The United States, in particular, has seen widespread integration of LoRa sensor mesh systems in urban parks, recreational areas, and nature reserves, driven by proactive government policies and substantial funding for public safety modernization. Additionally, the presence of leading technology providers and a mature ecosystem for IoT deployment further reinforce North America's market leadership, making it a bellwether for global trends in parks security innovation.

The Asia Pacific region is expected to be the fastest-growing market, with a projected CAGR of 20.5% during the forecast period. This rapid growth is underpinned by increasing urbanization, rising investments in smart city infrastructure, and heightened focus on public safety across countries such as China, Japan, South Korea, and India. Governments in these nations are actively promoting the adoption of IoT-enabled security solutions to address growing challenges related to park safety, environmental monitoring, and asset management. The region’s strong manufacturing base and burgeoning technology sector also contribute to lower hardware costs and faster deployment cycles, making LoRa sensor mesh solutions more accessible to a broader range of end-users.

Emerging economies in Latin America, the Middle East, and Africa are gradually embracing LoRa sensor mesh technology, although adoption rates remain modest due to infrastructure constraints and budgetary limitations. However, localized demand for affordable, low-maintenance security systems in public parks and nature reserves is rising, driven by increasing awareness of safety issues and the need to protect valuable natural resources. Policy initiatives aimed at digital transformation and public safety improvement are beginning to gain traction, but challenges such as limited technical expertise, inconsistent regulatory frameworks, and funding gaps continue to hinder widespread implementation. Nevertheless, these regions represent significant untapped potential, especially as technology costs decline and international development agencies prioritize smart infrastructure projects.

Report Scope

In 2024, the city with the highest spending per capita on parks and recreation in the United States was Irvine, California. The city spent around 643 U.S. dollars per resident on parks and recreation that year.

The purpose of this data package is to offer demographic data for U.S. cities. The data sources are multiple, the most important one being the U.S. Census Bureau, American Community Survey. In this case, the data was organized by the Big Cities Health Coalition (BCHC). Others are the New York City Department of City Planning and Department of Parks and Recreation, data being available through the NYC Open Data.

The city in the United States with the largest number of off-leash dog parks per 100,000 residents was Boise, Idaho, with nine off-leash dog parks per 100,000 residents in 2024. This is followed by Portland, Oregon which accounted for 5.7 dog parks per 100,000 residents.

About this dataset

Context

The dataset tabulates the Manassas Park city population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Manassas Park city. The dataset can be utilized to understand the population distribution of Manassas Park city by age. For example, using this dataset, we can identify the largest age group in Manassas Park city.

Key observations

The largest age group in Manassas Park city, VA was for the group of age 35-39 years with a population of 1,677 (9.82%), according to the 2021 American Community Survey. At the same time, the smallest age group in Manassas Park city, VA was the 80-84 years with a population of 119 (0.70%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Manassas Park city is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Manassas Park city total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Manassas Park city Population by Age. You can refer the same here