Tag Archives: CV XE GIS

America’s Cities: Examining Characteristics & Trends

… examining city/place demographic-economic characteristics .. of the approximate 29,323 U.S. cities/places, there are just 548 “large cities” .. those with population of 65,000 population or more.  A semi-arbitrary classification, these are cities/places that meet a size criteria for which American Community Survey (ACS) 1-year estimates are developed annually.  This results in the availability of extensive annual demographic-economic data that are much more current than available for all other cities/places (incorporated cities and CDPs).  Click this link to display a list of these cities/places that include 42 CDPs.  They comprise 2017 population of 119,342,501 of the total U.S. population 325,719,178 (36.6%).

Visual Analysis of City/Place Population Dynamics
Use the CV XE GIS software with city/place GIS project to examine characteristics of city/place population. The following view shows patterns of population percent change by city in the Charlotte, NC/SC metro area.


… view developed using the CV XE GIS software.
… click map for larger view and details including city name.

Access updated city/place for all 29,323 U.S. cities/places based on data from American Community Survey 5-year estimates (ACS2017).  Only here, for example, can you compare income characteristics and educational attainment, and much more, among all cities/places or peer groups .. or examine one/a few of interest to you.

Interactive Tables
Use interactive tables to view, rank, compare cities for any selected item; examine peer groups. Four pages/tables:
• General Demographics
• Social Characteristics
• Economic Characteristics
• Housing Characteristics
Related:
• City/Place GeoDemographics Main Section
• Annual City/Place Population Estimates & Trends
• Similar ACS tables: Census Tracts | ZIP Codes | State, Metro & County

Using API Tools to Access Trend Data; Build Data Files
An example: Examine Citizen Voting Age Population; 2014-2017 annually
Using API Tools to access ACS 2017 1 year estimates for all cities/places:
.. item D084 (CVAP: citizen voting age population) in the interactive table
.. click here to view list of places 65,000 population and over and CVAP
.. join us in the Data Analytics Web Sessions to learn more

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
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.

Census 2020 P.L. 94-171 Redistricting Data Updates

.. we are just two years away from the first census block level data from Census 2020.  The initial block level data will be the P.L. 94-171 redistricting data.  But before that, the initial Census 2020 TIGER/Line shapefiles/GIS files, the geography, will become available in November 2020, maybe earlier.  Stakeholders will be able to see how block and tract codes and geography have changed in many areas since 2010.  The prototype P.L. 94-171 data (see final file layout and subject matter items) are expected in the last week of March 2019 and will cover the Providence County, RI area. This post shows illustrative views and related details about the area. The Census 2020 P.L. 94-171 program and plans are reviewed in this Federal Register notice.

The applications/views shown below have been developed using the ProximityOne CV XE GIS software and related GIS project.

Census 2020 Data Access and Use Program
ProximityOne operates a comprehensive Census 2020 Data Access and Use Program providing tools to integrate and analyze these data with other data for redistricting, planning, evaluation, management, general analysis and policy-related applications. Contact us for more information; mention Census 2020 Data Access and Use Program in text section.

Providence, RI Census 2020 P.L. 94-171 Prototype
The Census 2020 P.L. 94-171 prototype covers Providence County, RI, part of the Providence-Warwick, RI-MA MSA (39300) — see Situation& Outlook report. Providence County is shown with cross-hatch pattern in the following graphic.

The next graphic shows a zoom-in to the county with cities/places shown with green fill pattern.

The next graphic shows patterns of economic prosperity for the county based on ACS 2017 median household income by census tract — blue, higher and red, lower.

The next graphic shows Census 2010 blocks for the county. Demographics described in the P.L. 94-171 file described about will be provided at the census block level.

Census block boundaries are primarily defined by roads. Providence County roads are shown in the next view.

The next view shows a zoom-in to the downtown Providence city area. Census blocks are shown with red boundaries and labeled with the 15-character U.S. national scope unique census block code. The pointer is located in census block 440070012001001, or 44-007-001200-1001, expressed as SS-CCC_TTTTTT-BBBB. Access these Census 2010 data (an example) using the Census FactFinder tool via this link. This is the “P1 RACE” table. The Census 2010 population of the block was 598. This census block is one of 13,597 Census 2010 census blocks comprising Providence County.

Rhode Island 116th Congressional Districts 01 and 02 (labeled) split Providence city (cross-hatch pattern) as shown in the graphic below. Pointer shows CD boundary.

Similar to above, the graphic below shows census blocks in context of Providence city (bold green boundary) and CDs 01 and 02.

Next Steps
This section provides a geographic orientation the Census 2020 P.L. 94-171 prototype area. A subsequent post (March 2019) will extend on this post with Census 2020 P.L. 94-171 data and related details. Use the downloadable project and software to examine geodemographics and redistricting operations.

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
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 Gross Domestic Product

.. what is the annual per capita real-valued output of counties of interest? How is this measure trending? Why is this important? This section reviews tools and data to examine county-level Gross Domestic Product (GDP) trends and patterns. The first ever county-level GDP estimates to be developed as a part of the official U.S. national scope GDP estimates were released in December 2018. The county GDP estimates join the county-level personal income by major source, both now part of the Regional Economic Information System (REIS). See more detail about topics reviewed in this post in the related County GDP web section.

Patterns of Real Per Capita GDP by County
The graphic below shows patterns of per capita real GDP, 2015, by county.

– View developed using CV XE GIS and related GIS project.
– create custom views; add your own data, using the GIS project.

Gross Domestic Product (GDP) by county is a measure of the value of production that occurs within the geographic boundaries of a county. It can be computed as the sum of the value added originating from each of the industries in a county.

Example … use this interactive table to see that 2015 Los Angeles County, CA total real GDP of $656 billion was just slightly larger that than of New York County, NY (Manhattan) at $630 billion. Yet, the total 2015 population of Los Angeles County of 10.1 million is 6 times larger than that of New York County of 1.6 million — see about steps. GDP provides very different size measures, and economic insights, compared to population.

In 2015, real (inflation adjusted) Gross Domestic Product (GDP) increased in 1,931 counties, decreased in 1,159, and was unchanged in 23. Real GDP ranged from $4.6 million in Loving County, TX to $656.0 billion in Los Angeles County, CA.

This post is focused on U.S. national scope county level estimates of Gross Domestic Product (GDP) annually 2012 through 2015. This marks the first time county level GDP estimates have been developed, a part of the Regional Economic Information System (REIS). Use the interactive table to rank, compare, query counties based on per capita GDP, current GDP, real GDP by type of industry. Use the related GIS project to develop thematic map views such as the one shown below. See more about these data.

Current Annual Estimates & Projections
ProximityOne uses these and related data to develop and analyze annual Situation & Outlook demographic-economic estimates and projections. GDP items included in the table below are included in the “annual 5-year” projections as shown in the schedule of release dates; next release April 18, 2019 and quarterly.

Examining County GDP Using GIS Tools
Use the County REIS GIS project. Make your own maps; select different item to map; modify colors, labels. Zoom in views of selected states shown below. Graphics open in a new page; expand browser window for best view. Patterns: see highlighted layer in legend to left of map; MSAs bold brown boundaries with white shortname label
counties labeled with name and 2015 per capita real GDP
.. Arizona .. Alabama .. California .. Colorado .. Iowa .. Georgia .. Kansas .. Missouri
.. New York .. Nevada .. North Carolina .. South Carolina .. Nevada .. Texas .. Utah .. Vermont

Using the County GDP Interactive Table
The graphic below illustrates use of the interactive table. Tools below the table have been used to view only per capita real GDP for all sectors (total sources) and for county with total population between 50,000 and 60,000. Counties were then ranked on 2015 per capita real GDP (rightmost column).

– click graphic for larger view.

Using County GDP: Data Analytics Web Sessions
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.

Block Group Demographic Data Analytics

.. use tools described here to access block group data from ACS 2016 (or ACS2017 in December 2018) using a no cost, menu driven tool accessing the data via API. Select from any of the summary statistic data. Save results as an Excel file or shapefile. Add the shapefile to a GIS project and create unlimited thematic pattern views. Add your own data. Join us in a Data Analytics Web session where use of the tool with the ACS 2017 data is reviewed.

See related Web section for more details.
– examine neighborhoods, market areas and sales territories.
– assess demographics of health service areas.
– create maps for visual/geospatial analysis of locations & demographics.

Illustration of Block Group Thematic Pattern Map – make for any area

– click graphic to view larger view
– pointer (top right) shows location of Amazon HQ2

Topics in this how-to guide (links open new sections/pages)
• 01 Objective Thematic Pattern Map View
• 02 Install the CV XE GIS software
• 03 Access/Download the Block Group Demographic-Economic Data
• 04 Download the State by Block Group Shapefile
• 05 Merge Extracted Data (from 03) into Shapefile (04)
• 06 Add Shapefile to the GIS Project; Set Intervals
• 07 Viewing Profile for Selected Block Group
• 08 BG Demographics Spreadsheet
• 09 Block Group Demographics GIS Project
• 10 Why Block Group Demographics are Important

Data Analytics Web Sessions
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.

How the New York Metro is Changing

.. or more precisely, how the New York Metropolitan Statistical Area (MSA) is changing. As of Census 2010 the New York MSA (officially the New York-Newark-Jersey City, NY-NJ-PA MSA) consisted of 20 counties. With the new OMB metropolitan statistical areas defined as of February 2013, the New York MSA became 22 counties, absorbing the Poughkeepsie, NY MSA two counties (Dutchess and Orange). The Poughkeepie MSA was removed from the official MSAs. The delineation remained that way until the new September 2018 delineations when the Census 2010 delineation was restored. Now, the Poughkeepsie, NY MSA exists as a 2 county area and the New York MSA exists as a 20 county area (both as they existed geographically in Census 2010).

These metro-county relationships are shown in the graphic presented below. The Poughkeepsie, NY MSA is shown with the blue cross-hatch to the north and the New York MSA is shown with the salmon color pattern.

– view developed using the CV XE GIS software and related GIS project.
– see the related New York Metro Situation & Outlook report.

What Difference Does it Make?
A lot! First, during the interim period 2013-2018, the Poughkeepsie, NY MSA lost the metropolitan area identity/status as conferred by the OMB delineations. It might have been omitted from size class market development and research analyses. Related, that metro was not included as a tabulation or estimation area of MSAs by Federal statistical agencies. An example of the impact is that the official demographic estimates for the Poughkeepsie, NY MSA developed by the Census Bureau were not tabulated as such and omitted from various statistical reports. Also, the removal of designation and now adding the designation back, creates a hiccup in the time series — affecting both the Poughkeepsie NY MSA and the New York MSA.

Detailed Demographic Profiles for New York MSA and Poughkeepsie, NY MSA
.. click link to view profile.

New York-Newark-Jersey City, NY-NJ-PA MSA
  Bergen County, NJ (34003)
  Essex County, NJ (34013)
  Hudson County, NJ (34017)
  Hunterdon County, NJ (34019)
  Middlesex County, NJ (34023)
  Monmouth County, NJ (34025)
  Morris County, NJ (34027)
  Ocean County, NJ (34029)
  Passaic County, NJ (34031)
  Somerset County, NJ (34035)
  Sussex County, NJ (34037)
  Union County, NJ (34039)
  Bronx County, NY (36005)
  Kings County, NY (36047)
  Nassau County, NY (36059)
  New York County, NY (36061)
  Putnam County, NY (36079)
  Queens County, NY (36081)
  Richmond County, NY (36085)
  Rockland County, NY (36087)
  Suffolk County, NY (36103)
  Westchester County, NY (36119)
  Pike County, PA (42103)

Poughkeepsie-Newburgh-Middletown, NY (CBSA 39100)
  Dutchess County, NY (36027)
  Orange County, NY (36071)

Looking Forward
The September 2018 CBSA delineations define counties that will be used for Census 2020 (likely, there could be yet further changes) — 384 MSAs in the U.S. In the cases of the New York MSA and the Poughkeepsie, NY MSA, it appears that the geography (component counties) used for Census 2010 will be the same as for Census 2020. Going forward, ProximityOne estimates and projections will use the most current vintage of CBSAs.

Data Analytics Web Sessions
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.

U.S. House of Representatives 2020 Apportionment

.. Congressional Apportionment by State .. 2010 & projected 2020 state by state congressional seats.

What will the results of Census 2020 tell us us about how the House of Representatives will be reapportioned, state by state? This section examines scenarios which might occur based on state population projections. See related Web section http://proximityone.com/apportionment.htm for more detail and interactive table.

Use the GIS tools and project to make your own map views … see details
.. use in classroom .. research .. reference .. collaboration.

This section has been developed using
– 2020 apportionment population projections
.. part of the ProximityOne Situation & Outlook (S&O)
– the reapportionment/redistricting feature of the CV XE GIS software
The 2020 population projections reflect anticipated change under one scenario. Those values are then used in the CV XE GIS reapportionment operation to compute the number of House seats shown in the related table.

Apportionment of the U.S. House of Representatives
— based on the 2010 Census

– view created with CV XE GIS. Click graphic for larger view with more detail.

Apportionment of the U.S. House of Representatives
— based on ProximityOne 2020 Population Projections

– view created with CV XE GIS. Click graphic for larger view with more detail.

Congressional apportionment is the process of dividing the 435 memberships, or seats, in the House of Representatives among the 50 states based on the population figures collected during the decennial census. The number of seats in the House has grown with the country. Congress sets the number in law and increased the number to 435 in 1913. The Constitution set the number of representatives at 65 from 1787 until the first Census of 1790, when it was increased to 105 members. More about apportionment.

Initial Census 2020 demographic data, the apportionment data, will be released by December 31, 2020. See related Census 2010 Apportionments.

Apportionment totals were calculated by a congressionally defined formula, in accordance with Title 2 of the U.S. Code, to divide among the states the 435 seats in the U.S. House of Representatives. The apportionment population consists of the resident population of the 50 states, plus the overseas military and federal civilian employees and their dependents living with them who could be allocated to a state. Each member of the House represents, on average, about 710,767 people for Census 2010.

Using the Interactive table
The following graphic illustrates use of the 2010 & 2020 apportionment by state and historical apportionment 1910 to 2010. Sort on any column; compare apportionment patterns over time. Click graphic for larger view.
Use the interactive table at http://proximityone.com/apportionment.htm#table.

Congressional District/State Legislative District Group
Join the CDSLD Group (http://proximityone.com/cdsld.htm), a forum intended for individuals interested in accessing and using geodemographic data and analytical tools relating to voting districts, congressional districts & state legislative districts and related geography with drill-down to intersection/street segment and census block level. Receive updates on topics like that of this section.

Data Analytics Web Sessions
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 State-to-State Geographic Mobility

.. tools, resources and insights to examine U.S. by state migration 2011-2017 and migration flows in 2016 .. this post is an excerpt from the more detailed Web page http://proximityone.com/statemigration.htm.

In examining future demographic trends, the most challenging component of change to project (develop data values into the future) is migration. Migration, comprised net domestic and net international migration, is a function of many factors whose cause and effect behavior can change year by year, and geographic area by area. While this section is focused on states, the same scope of data is available to the county and sub-county levels. In this section, U.S. by state migration is examined using two data sources: annual population and components of change model-based estimates (2010-2017 model-based estimates) and annual American Community Survey estimates (ACS 2016 estimates). While these Census Bureau programs are highly related, the migration data/subject matter differ some.

State Net Domestic Migration, 2011-2017
The following graphic shows patterns net domestic migration for the period 2011-2017, based on the model-based estimates. The patterns of migration change, direction and magnitude are immediately evident. Click on the graphic to see a larger view showing more detail. Expand browser to full screen for best quality view. The larger view shows a portion of a mini-profile for Florida. The mini-profile illustrates how these data are comprised … annual net domestic migration estimates and the sum over the years 2011-2017. See the interactive table to view these data, and related components of change, in a tabular, numeric form. Use the GIS project (details here) to create similar views for any state; visual analysis of outmigration for any state showing outmigration by destination state. Label areas as desired. Add other layers. Add your own data.

View created with CV XE GIS. Click graphic for larger view with more detail.

State OutMigration by Destination State
The model-based estimates, reviewed above, do not provide detail on state-to-state migration. Those data are provided by the related ACS 2016 estimates. Note that the ACS 2016 1-year estimates are for the calendar year 2016. From these data we can get the following migration detail … In 2016, there were an estimated 605,018 people who moved from a residence 1 year earlier, in a different state, to Florida. Florida experienced the largest number of movers (inflows) from other states among all states. 60,472 of these movers were from New York. See the interactive table in this section to examine similar characteristics for any state. These data are based on the 2016 ACS 1 year estimates. See about related data.

The American Community Survey (ACS) asks respondents age 1 year and over whether they lived in the same residence 1 year ago. For people who lived in a different residence, the location of their previous residence is collected. The state-to-state migration flows are created from tabulations of the current state (including the District of Columbia) of residence crossed by state of residence 1 year ago.

Movers Within and Between States & Selected Areas During 2016
Use the interactive table to examine state outmigration by destination state. View, compare, query, rank and export data of interest.

Data Analytics Web Sessions
.. is my area urban, rural or …
.. how do census blocks relate to congressional district? redistricting?
.. how can I map census block demographics?
Join me in a Data Analytics Web Session, every Tuesday, where we review access to and use of data, tools and methods relating to GeoStatistical Data Analytics Learning. We review current topical issues and data — and how you can access/use tools/data to meet your needs/interests.

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.