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Mapping the fastest growing cities in the U.S. and charting U.S. population growth with Census data.
The year 2020 was a big year for data! It marked the update of the United States Census decennial collection of national geographic, demographic, and socioeconomic data. As our databank grows, so does our commitment to understanding our nation.
Data can make a difference.
One way researchers, analysts, urban planners, developers, economists, and stakeholders alike observe and understand the nation is through population changes. As such, we tracked the United States population growth rate in Studio, Urban SDK's GIS data visualization tool.
One way that population change is calculated is based on geographic boundaries called Core-Based Statistical Areas (CBSA’s). A CBSA is significant in that it is a boundary with 10,000 - 50,000 people sharing a geographic and socioeconomic commonality. The populous of each CBSA is tied to the common urban area by commuting.
CBSAs take into account major cities as well as their surrounding area. As such, CBSAs are useful geographical boundaries because they present a more even way of looking at population change.
Oftentimes, population changes are dominated by specific major cities that already encompass a large population, thus skewing population change. Population density, as well as population increase, must be taken into consideration when observing population growth.
The CBSA model takes population change a step further.
A Core-Based Statistical Area takes into consideration population within a set threshold of people, while also incorporating common socioeconomic associations.
The average CBSA saw an increase in population from 2010 to 2019 The population changes observed within a CBSA can paint a clearer picture of the factors influencing changes in urban sprawl, development, and economics.
The Urban SDK team has compiled a map of the top 10 Core-Based Statistical Areas with the highest population growth. It models population growth based on the 2010 through 2019 Census to better visualize the fastest growing cities in the U.S.
Using the features of the Urban SDK Studio, users can easily filter through the data entries they wish to view.
Census data can oftentimes be monotonous, cumbersome, and difficult to understand when viewing on a static spreadsheet.
For example, the CBSA data downloaded straight from the Census has over 40 columns of data!
To make a difference with data, users must understand what they are looking at.
Using the Urban SDK Studio and its tools allows users to visualize the data, present it well, and highlight meaningful points.
The Tooltip feature in the Urban SDK Studio can quickly clean up your data view.
When observing the population changes across the CBSAs, users can interactively highlight data of interest. With this particular dataset, users can view population percentages, immigration fluctuation, ranking, and reasoning tied to population growth.
When viewing the map, the audience can observe that the North Dakota CBSA has seen the largest increase in population. The top two CBSAs with the highest population growth since 2010 are both located in western North Dakota.
By hovering over the corresponding CBSA polygon in Williston, and Dickinson, ND, users learn that an increase in the oil industry has fueled the growth of the midwestern area.
This is in stark contrast to the population growth in the Myrtle Beach, SC area, which is due to climate and attractiveness to recent retirees.
The average CBSA has seen an increase in population by around 7%.
Each of the CBSA’s hosted on the Urban SDK map has seen a population increase that is greater than 28%.
Population growth can be attributed to industry booms, technological advancements, lifestyle shifts, and many other human and economic drivers.
Understanding population data will help stakeholders make better urban planning decisions. Viewing trends and preparing for population fluctuations ahead of the boom is not only lucrative but can impact the safety and success of communities.
Leveraging data to make a difference will lead to smarter cities, and beyond.