Category Archives: Population

Metro Population & Components of Change Trends 2010-2016

.. tools and data to examine how the U.S. by metro population is changing. Is the population moving away or into metros of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

This section provides information on how and why the population is changing by metro from 2010 to 2016 in terms of components of change: births, deaths and migration. It provides a summary of tools, interactive table and GIS project, to analyze population change by metro using latest Census Bureau estimates through 2016. These data are used by ProximityOne to develop/update annual demographic-economic projections.  See related Web page to access full interactive table and more detail.

Patterns of Population Change by Metro, 2010-2016
The following graphic shows how metros (MSAs – Metropolitan Statisticsl Areas) changed from 2010 to 2016 based on percent population change. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Narrative Analysis of Metro Demographic Change in Context
A narrative summary and analysis of metro demographic characteristics and change, contextually with other data and geography, is provided for each metro in the Situation & Outlook Reports. See more about the wide-ranging subject matter that are knitted together in the schedule of updates. Examine metro dynamics in context of the U.S. overall and related states and counties.

The nation’s 382 Metropolitan Statistical Areas (MSAs) had a population of 277.1 million in 2016 (86% of the total population). MSAs increased by 2.3 million people from 2015. The nation’s 551 Micropolitan Statistical Areas (MISAs) had a population of 27.7 million in 2016 (9% of the total population). MISAs increased by 16,000 people from 2015. See more highlights below

MSAs and MISAs together, or metro areas, comprised the set of Core-Based Statistical Areas (CBSAs). Each metro/CBSA is defined as a set of one or more contiguous counties.

Related Sections
• Metros Main
• Situation & Outlook Reports
• City/Place Population Trends
• County Population Trends
• County Population Projections to 2060
• ProximityOne Data Service

Examining Population Components of Change
Population change can be examined in terms of components of change. There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Examining a county’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring.

See more about these topics below:
• Natural Increase/Change; birth & deaths
• Migration; net international, net domestic, net migration

Using the Interactive Table – Peer Group Analysis
Use the full interactive table to examine U.S. national scope metros by population and components of change. Consider an application where you want to study metros having a 2016 population between 250,000 and 300,000. Use the tools below the interactive table to select these metros as illustrated in the graphic shown below. The graphic shows these metros ranked on the overall U.S. metro rank (percent population change 2010-2016). As shown in the graphic, the Greeley, CO metro was ranked 11th among all metros and the fastest growing metro in this group. Use the tools/buttons below the table to create custom views.

Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining Appalachia City Characteristics & Trends

.. using tools and data to examine geographic, demographic, economic characteristics of the Appalachia Region .. Appalachia is a region that includes parts of 13 states, 420 counties, and has long been challenged with poverty. This section is part of a series focused on Appalachia.  See related more detailed Web section.

The Appalachia Region; Lay of the Land
The population of Appalachia increased from 25.1 million in 2010 to 25.5 million in 2016, an increase of 289,806. The following graphic shows how Appalachia region counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2016. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Cities in Appalachia
In 2016, there were 2,393 cities in Appalachia. Seven cities had population over 100,000; 16 cities had over 50,000 population and 213 cities had 10,000 or more population.

The following graphic shows cities (red markers) with 2016 population of 10,000 or more in the Appalachia region in context of counties (yellow fill pattern). Click graphic for larger view; expand browser window for best quality view. Larger view shows city names except where labels could overlap.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Growing Cities
The following view shows cities as green markers having 5,000+ 2016 population with growth of 500+ or more population, 2010-2016.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Cities & Metros in Appalachia
The following graphic shows Metropolitan Statistical Areas (green fill pattern) that intersect with Appalachia region counties. Note that some metros only partly intersect with Appalachia. County boundaries are shown as overlay on metros. For example, only northern counties of the Atlanta metro (see pointer) are Appalachia counties. “Edge” Appalachia metros create opportunities for nearby Appalachia counties. Cities within Appalachia and having 50,000+ 2016 population are shown with orange markers. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Characteristics of Metros, Cities and School Districts
• Demographic-economic profiles for selected cities
Examples (click link above to view other cities; click links below for specific city profiles):
.. Cumberland, MD [2421325] (19,978)
.. Frostburg, MD [2430900] (8,676)
Access any/all U.S. city(s) — http://proximityone.com/places15dp1.htm
• Demographic-economic profiles for selected school districts
Examples (click link above to view other districts; click links below for specific district profiles):
.. Allegany County Public Schools, MD [2400030]
.. Pittsburgh School District, PA [4219170]
Access any/all U.S. school district(s) — http://proximityone.com/sd15dp1.htm
• S&O metro reports

Examining Characteristics of All Cities/Places
Use these resources to examine all U.S. cities/places.
• Cities/Places Main Section
• America’s Communities Program — city profiles
• All Cities/Places — 4 Web section/tables
• City Population Estimates & Trends 2010-2016 interactive table

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

City Population Characteristics & Trends: 2010-2016

.. the change in U.S. city population from 2010 to 2016 ranged from growth of 345,647 in New York City to a decline of -38,293 in Detroit, MI. New York City is actually five counties; the next largest city growth was Houston, TX with a 197,857 population gain.  Examine how the population is changing in cities of interest using the interactive table and other tools described in this post.  Use the interactive table to view a selected city, all cities in a state, cities in a county, cities in a metro or cities in a peer group size class.  See related Web section for more details.

Use the U.S. by cities shapefile with your GIS projects. See details. Thematic pattern maps illustrating use of these resources are shown below.

The July 1, 2016 Census Bureau model-based estimates (see about these data) for the U.S. 19,510 incorporated cities show a total population of 203,314,546 compared to 192,174,578 as of Census 2010. These areas are incorporated cities as recognized by their corresponding state governments and granted certain governmental rights and responsibilities.

Patterns of City Percent Change in Population 2010-16
— Cities 10,000 Population & Over
Use the CV XE GIS software with cities GIS project to examine characteristics of city/place population, 2010-2016. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more. Use the interactive table below to see that among cities with 2016 population of 10,000 and over that Buda, TX had the largest percent change (98.8%) while Avenal, CA experienced the largest percent decrease (-18.4).

– View developed using the CV XE GIS software.
– Click graphic for larger view.

Fastest Growing Cities in the Dallas, TX Metro
— Cities 10,000 Population & Over; create views like this for any metro/county
It is easy to see which cities are growing the fastest using the thematic pattern view below. It is also easy to see how the cities relate to each other geographically and in context of county boundaries. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more in the Dallas metro area.

– View developed using the CV XE GIS software.

Drill-down — Fastest Growing Cities in the Dallas, TX Metro
— Cities 10,000 Population & Over
Zoom into the north Dallas metro area and label the cities with name. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more in the Dallas metro area.

– View developed using the CV XE GIS software. Click graphic for larger view; expand browser window for best quality view.

City/Place Demographics in Context
State & Regional Demographic-Economic Characteristics & Patterns
.. individual state sections with analytical tools & data access to block level
Metropolitan Area Situation & Outlook
.. continuously updated characteristics, patterns & trends for each/all metros
Related City/Place Demographic-Economic Interactive Tables
ACS 2015 5-year estimates
.. General DemographicsSocialEconomicHousing Characteristics

Using the Interactive Table
Use the full interactive table to examine U.S. national scope cities by annual population and change 2010-2016. The following graphic illustrates use of the table to view the largest cities ranked on 2016 population. Use the tools/buttons below the table to create custom views.

Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Relating ZIP Codes to City/Places

.. relating ZIP codes to cities .. 214 ZIP code areas intersect with New York city — what are these ZIP codes, their population and how many are completely within the city? What part of a ZIP code area of interest intersects with what city? Conversely, what ZIP code areas intersect with a city of interest? This section provides data and tools that can be used to answer these types of questions and gain insights into geospatial relationships. See more detailed information in the related full Web section.

The 2010 ZIP Code Tabulation Area (ZCTA) to City/Place relationship data provide a means to equivalence ZCTAs with Census 2010 cities/places. ZCTAs are geographic areas defined as sets of Census 2010 census blocks closely resembling USPS ZIP codes (lines, not areas). ZCTA boundaries are fixed for the intercensal period 2010 through 2020. Census 2010 vintage city/place areas are likewise defined as sets of Census 2010 census blocks. The ZCTA-City/place relationship data are developed through the use of the intersecting census block geography and associated Census 2010 Summary File 1 demographic data.

ZCTA-Place Relationships
The following graphic shows relationships between two selected ZCTAs (red boundaries) and related cities/places (blue fill pattern) in the Pima/Cochise County, AZ area. Relationships between these geographies are reviewed in examples shown below.

– View developed using CV XE GIS and related GIS project.

Using the ZCTA-Place Relationship Data
Two examples illustrating how to use the ZCTA-place relationship data are provided below. The examples are interconnected to the GIS project used to develop the map views, interactive table and data file described in this section. Example 1 describes how to use the data for a ZIP code area entirely located within one city/place. Example 2 describes how to use the data for a ZIP code area located in more than one city/place and area not located in any city/place.

ZCTA to Place Relationships: Example 1
In this example, ZCTA 85711, highlighted in red in the graphic shown below, falls wholly within place 77000, outlined in bold black below. As a result, there is only one corresponding record for ZCTA 85711 in the relationship file. The 2010 Census population for this relationship record is 41,251 (POPPT) which is equal to the 2010 Census population for ZCTA 85711 (ZPOP). See more details about this example.

ZCTA to Place Relationships: Example 2
In this example, ZCTA 85630, highlighted below in red in the graphic shown below, contains two places: all of place 62280 and part of place 05770, both are outlined in black below. As a result, there are two corresponding relationship records in the relationship file. For the first relationship record, the total 2010 Census population for ZCTA is 2,819 (ZPOP). See more details about this example.

Using the Interactive Table
Use the full interactive table to examine U.S. national scope ZCTA-city/place relationships. The following graphic illustrates how ZIP code can be displayed/examined for one city — Tucson, AZ. Each row summarizes characteristics of a ZIP code in Tucson. The last row in the graphic shows characteristics of ZIP code 85711 — the same ZIP code reviewed in Example 1 above.

Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

115th Congressional Districts: Analysis and Insights

.. interpretative data analytics; tools, data & methods ..  this section is focused on 115th Congressional District geographic, demographic and economic patterns and characteristics. Use tools and data reviewed here to examine/analyze characteristics of one congressional district (CD) or a group of CDs based on state, party or other attribute. Use the GIS resources described here for general CD reference/pattern/analytical views, to examine current demographics and demographic change and for redistricting applications. See this related Web section for more details.

Examining the 115th Congressional Districts
• the 115th Congress runs from January 2017 through December 2018.
• FL, MN, NC, VA have redistricted since the 114th CD vintage;
  .. some 115th CDs have new boundaries compared the 114th CDs.
• view, rank, compare CDs using the interactive table.
  .. table uses ACS 2015 data for 115th CDs & include incumbent attributes.
  .. examine districts by party affiliation.
• use these more detailed 114th CD interactive tables
  .. data based on 2015 American Community Survey – ACS 2015.
  .. corresponding data for the 115th CDs from ACS 2016 available Sept 2017.
• use the new GIS project including 114th & 115th CDs described below.
  .. create CD thematic and reference maps;
  .. examine CDs in context of other geography & subject matter.
• join us in the April 25 Data Analytics Lab session

Visual Analysis of Congressional Districts
The following views 1) provide insights into patterns among the 115th CDs and 2) illustrate how 114th to 115th geographic change can be examined. Use CV XE GIS software with the GIS project to create and examine alternative views.

Patterns of Household Income by 115th Congressional District
The following graphic shows the patterns of the median household income by 115th Congressional District based on the American Community Survey 2015 1-year estimates (ACS2015). The legend in the lower left shows data intervals and color/pattern assignment

.. view developed with ProximityOne CV XE GIS and related GIS project.

Charlotte NC-SC Metro Area
  – with 114th/115th Congressional District 12

The following graphic shows North Carolina CD 12 with 114th boundary (blue) and 115th boundary (pale yellow) and Charlotte metro bold brown boundary. Click graphic for larger view with more detail. Expand browser window for best view.

.. view developed using the CVGIS software.

• View zoom-in to Charlotte city & Mecklenburg County.

115th Congressional District Interactive Table
Use the interactive table to examine characteristics of one congressional district (CD) or a group of CDs. The following graphic illustrates use of the interactive table. First, the party type was selected, Democratic incumbents in this example. Next, the income and educational attainment columns were selected. Third, the set of districts were sorted on median household income. It is quick and easy to determine that CA18 has the highest median household income and that the MHI is $1,139,900. Try using the table to examine districts of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Creating Custom School District Maps

…tools & data to map & geospatially analyze school districts. Ready-to-use state-by-state GIS projects may be downloaded enabling you to view and create custom maps almost instantly. Benefit from the power of using GIS software to perform tasks not available on Web-based mapping options. Use the latest school district and related shapefiles. See more information about using these resources in this related Web section.

Federal Revenue per Student by School District
Create views similar to the one shown below. Optionally combine layers as illstrated here by showing four Texas metros.

.. view developed with CV XE GIS and related GIS project.

Extending Reference and Analytical Possibilities

Texas by School District
Examine reference maps at the state, regional or local level. Optionally combine with roads/streets and other layers.

Patterns of Economic Prosperity by School District
Select from many ready-to-use demographic-economic subject matter items to create custom pattern views.

Drill-down — Houston Metro Area by School District
Zoom-in to a school district of interest. Set attributes of district as shown here.

County/School District
Visually examine the boundaries or school districts and counties. This view shows Harris County, TX area; select a county of interest.

Drill-down to Street Level
Add road/street and other layers. Drill-down within Fort Bend ISD, Houston metro, showing general earth surface features with streets layers. Mouse used to click on street (see pointer) and display mini-profile of street segment attributes.

Use for Analysis, Reference or in the Classroom
Schools and teachers: consider using these resources for classroom use. Familiarize students about how GIS resources can be used with a minimum of learning time and no cost. Enable students to use their own geography and adapt that learning to more general geography. See related Mapping Statistical Data ready-to-use GIS projects.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining County Migration: 2010-2016

.. tools and data to examine U.S. by county migration 2010 to 2016 … is the population moving away or into your counties of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

The total net international migration among all counties 7/1/2010 – 7/1/2016 was 5,641,260, an annual average of 940,432. The sum of net domestic migration among counties is zero by definition, but domestic migration among counties varies radically by size and direction. This section is focused on U.S. by county migration from 2010 to 2016. Migration is one component of change used to develop population estimates. See more about county population estimates and components of change in this related Web section.

Largest 10 Counties Based on 2016 Population
This table shows how domestic migration varies widely among the most populated counties. Use this interactive table to develop your own custom views for counties of interest.

Patterns of Population Change by County, 2010-2016
– the role and impact of migration
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2016. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Examining Population Components of Change
– net migration and natural change
Population change can be examined in terms of components of change. There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Examining a county’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring.

Using the Interactive Table
– examining migration by county
Use the interactive table to examine characters of counties by states, metro or peer group. The following graphic illustrates use of the interactive table to view net migration for the Houston metro by county. The net migration button was used to select only the net migration columns, FindCBSA button used to show only counties in this metro and the final step was to sort the resulting table on 2016 population. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.