Tag Archives: Census tract

Census Tract-City Relationship Table

.. what census tracts are located in cities of interest? What are their codes? Conversely, do you have census tract codes and need to know corresponding city(s)? Get answers here.

This section provides access to an interactive table useful to examine relationships among Census 2010 census tracts, cities/places, and counties. Many cities and counties that might be experiencing demographic-economic decline will often have bright spots that are groups of a few or many census tracts. Census tracts are important sub-county geography in data analytics. See the related section on census data analytics. See more about census tracts and data analytics below in this section.

Relating Census Tracts to Cities & Counties
Census tracts are sub-county areas and nest coterminously within counties. The 6-character tract code is unique within county. For cities 10,000 and larger, there are some number of whole census tracts within the city. But around the perimeter of cities, census tracts will often be partly within and partly outside of the city. The following graphic shows the relationship of tracts, cities and counties in the Plano city area (green fill pattern) located mostly in Collin County within the Dallas metro. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using census tract demographics and the relative ease to gain insights using geospatial data analytics tools.

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

Using the Interactive Relationship Table
A small part of Plano is located in Denton county (see north-south bold red-brown boundary). Tract 021627 (see pointer) is located in Denton County and includes a part of Plano. To determine what geography tract 021627 intersects, click the Tract> button below the interactive table shown below. See that the tract is contained in parts of 4 cities.

Census Tract to City/Place & County Equivalence Table
The following graphic illustrates use of the interactive table to view/examine the relationship between census tract 48121021627 (in Denton County, TX) and the city of Plano, TX. Click graphic for larger view.

The above view was developed using the interactive table:
– click the ShowAll button
– click the FindTract button (preset to locate this tract).

Click the ShowAll button and enter a city/place (case-sensitive) name of interest to view the set of intersecting tracts. See the table usage notes below the table in the related Web page. We review operation of the table in the 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.

State and Regional Decision-Making Information

Organized on a state-by-state basis, use tools and geographic, demographic and economic data resources in these sections to facilitate planning and analysis. Updated frequently, these sections provide a unique means to access to multi-sourced data to develop insights into patterns, characteristics and trends on wide-ranging issues. Bookmark the related main Web page; keep up-to-date.

Using these Resources
Knowing “where we are” and “how things have changed” are key factors in knowing about the where, when and how of future change — and how that change might impact you. There are many sources of this knowledge. Often the required data do not knit together in an ideal manner. Key data are available for different types of geography, become available at different points in time and are often not the perfect subject matter. These sections provide access to relevant data and a means to consume the data more effectively than might otherwise be possible. Use these data, tools and resources in combination with other data to perform wide-ranging data analytics. See examples.

Select a State/Area

Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
D.C.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

Topics for each State — with drill-down to census block
Visual pattern analysis tools … using GIS resources
Digital Map Database
Situation & Outlook
Metropolitan Areas
Congressional Districts
Counties
Cities/Places
Census Tracts
ZIP Code Areas
K-12 Education, Schools & School Districts
Block Groups
Census Blocks

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.

Tip of the Day — Census Tract Data Analytics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

This section is focused on tools and methods to access and use census tract demographic-economic measures. Median household income ($MHI), median housing value ($MHV) and other selected items are used to illustrate operations and options.

This section illustrates use of census tract data from the 2014 American Community Survey (ACS1014) 5-year estimates. These are the most comprehensive demographic-economic data from the Census Bureau at the census tract level. These “5-year estimates” are centric to mid-2012. See more about 2010-2021 annual estimates and projections.

Methods described here apply to many other geographies; see related tip sections. See related section on ZIP code applications.

Five data access and use options are reviewed. Each method illustrates how $$MHI, $MHV and other data can be analyzed/used in different contexts.

Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related sections:
Census tracts main section
Evolution of Census Tracts: 1970-2010
Demographic-Economic Estimates & Projections
Census tract and ZIP code equivalencing
Using census tracts versus ZIP code areas
Single year of age demographics

Option 1. View the data as a thematic pattern map; use the GIS tools:
Patterns of Economic Prosperity ($MHI) by Census Tract … the following graphic shows $MHI for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals; expand browser window for best quality view.

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

See details about each option in the related Web page.

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.

Citizen Voting Age Population by Block Group

.. tools and resources to access and analyze citizen voting age population by block group … ideally analysts and stakeholders will examine patterns and characteristics of the citizen voting age population (CVAP) by block group. This is partly because of the extreme variability of CVAP within higher level geography — even at the census tract level. This becomes even more important in more densely populated areas. See about ACS 2014 CVAP block group demographics in this related Web section.

Patterns of ACS 2014 CVAP Population by Block Group
— Houston Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

The size, characteristics and distribution of the citizen voting age population by block group is very important.
• Block groups are the most granular geography at which we can study these demographics.
• The size of the citizen voting age population ultimately determines election outcomes.

This section provides thematic pattern map views and analyses of selected metros. These applications can be replicated for any area. They serve as an “analytical basis” that can be augmented with other methods and data (e.g., voter registration, voter propensity, voter turnout, and other election factors) to gain insights into election outcomes under alternative scenarios. Equally important, this information can be used to better equip voters with the potential impact of improved voting activity for their own neighborhood and larger areas (e.g., even congressional districts).

Using these GIS Resources; Obtaining Custom Maps & Analyses
Contact us (or call 888.364.7656) for maps and analyses for areas of interest or to use the integrated, ready-to-use, national scope GIS software, GIS project and datasets. Add your own data; create custom views.

CVAP Block Group Thematic Pattern Map shown below for Selected Areas
• Atlanta
• Chicago
• Los Angeles
• Kansas City
• Washington, DC

Patterns of ACS 2014 CVAP Population by Block Group
— Atlanta Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Chicago Area
See legend in upper right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Los Angeles Area
See legend in upper right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Kansas City Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Washington, DC Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

ACS 2014 CVAP Block Group Demographics
For the 217,479 block groups covering the U.S. wall-to-wall, the median citizen population value is 1,165 (291.8 million population) and the median citizen voting age population is 885 (220 million population). The median total population is 1,252 (314 million population). These data are based on the 2014 American Community Survey ACS 2014 CVAP special tabulation completed in early 2016. WHile the focus here is on the total population, the same scope of data is integrated into the shapefiles used here for 13 race/origin population groups. The 13 race/origin groups include:
  • American Indian or Alaska Native Alone
• Asian Alone
• Black Alone
• Native Hawaiian or Other Pacific Islander Alone
• White Alone
• American Indian or Alaska Native and White
• Asian and White
• Black and White
• American Indian or Alaska Native and Black
• Remainder of Two or More Races
• not Hispanic
• Hispanic (of any race)

Related CVAP Sections
Census Tracts; ACS 2009-13 special tabulation
Census Tracts; ACS 2009-13 special tabulation – Hispanic focus
Tracts & Congressional Districts; ACS 2009-13 special tabulation

See this blog post in this full, more detailed Web section.

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.

Low and Moderate Income Demographics by Block Group

.. tools and resources to access and use low and moderate income demographics by block group … the U.S. Department of Housing and Urban Development (HUD) sponsored development of the ACS 2006-10 “low and moderate income population (LMI) by block group” special tabulation released in 2015. This is an important data resource for HUD as well as others who need to examine characteristics of the LMI population by block group and related small area geography. See related Web section for more details on topics covered here data.

This section reviews tools to use these data on a national or local level:
1. Site analysis tools
2. GIS software and national scope LMISD BG GIS project
3. National scope BG-level interactive table
See the related Web section for more detailed information.

Patterns of LMI Population by Block Group
The following graphic shows block groups with 51% or more LMI population with orange fill pattern. See related zoom-in views. Click graphic for broader Chicago area view. Expand browser window for best quality view.

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

Block Groups & American Community Survey (ACS) Data
There are several features of block groups that make this an important geography for data analytics. Block groups average 1,200 population and are the the smallest geographic area for which the ACS data are tabulated. The approximate 220,000 block groups are subdivisions of census tracts and cover the U.S. wall-to-wall. Only ACS provides national scope demographic-economic data at the block group level.

Analytical Tools & the ACS LMI Block Group Data
Tools reviewed below make use of one specific block group (170317115002) in the Chicago area. The tools may be applied to any other block group (BG) or set of BGs. Block groups are uniquely identified by the 12 character BG geocode. The BG code 170317115002 refers to block group 2 in census tract 711500 in county 031 in state 17.

1. Study Area Comparative Analysis Reports
Examine characteristics of circular area reports based on block groups within those areas. The following graphic shows a partial view of a 1- and 3-mile radius report developed for lat-lon location (41.7324422, -87.6410861) BG 170317115002 internal lat-lon. Click graphic to view entire report. This type of report can be prepared for any address/location/lat-lon and area size from less that one mile to many miles. These reports include a much larger set of demographic-economic data than included in the HUD LMISD. The comparative analysis structure makes it easy to compare one site/location with another and their difference.

.. report developed with ProximityOne SiteReport.

2. Using GIS Resources
— LMI 51% or More; Chicago Area Block Groups

Block groups with 51% or more LMI population shown with orange fill pattern. Mini profile displayed for block group at pointer – 170317115002 – find in table below. LMI percent shown as 55.03%. LMI-BG layer shown in context with Public Use Microdata Area 03531. Develop custom estimates of the population for this PUMA using the ACS PUMS data. Integrate other types of geography and data. Click graphic for broader Chicago area view. Expand browser window for best quality view.

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

See more information here about using the GIS project used to develop maps in this section and more generally develop your own maps and perform geospatial analysis.

3. Using the Interactive Table
Use the interactive table to view, query, rank and analyze LMI demographics by block group. The following graphic illustrates one application. The state of Arizona is selected using the state selection tool below the table. The Low Income column header cell is dbl-clicked, sorting the table on the estimate of the Low Income population by block group. It is easy to see that BG 040270116002(blue highlighted) has the largest Low Income population among all BGs in Arizona.

Try using the interactive table for geography of interest. The interactive table is a very useful tool when used in combination with the GIS application.

What’s next is data integration. Upcoming posts will review similar, but different, updated block group demographics and their use with data reviewed here. See the main block group Web page.

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 to Assess the Hispanic Vote for the 2016 Elections?

.. a good place to start finding an answer to this question is to use the Hispanic citizen voting age population (CVAP) data. We take a look at using those data here. You can use these same tools and data to examine areas of interest.

This section is focused on using census tract level CVAP data. Census tracts cover the U.S. wall-to-wall with well-defined boundaries and average 4,000 population. The 73,057 census tracts offer a good granularity to examine citizen voting age population for neighborhoods and sections of cities or counties.

While the focus is on the Hispanic population, this population group is comprised of many specific origins (more about Hispanic population by specific origin). And, although this section is focused on the Hispanic population, the CVAP data are tabulated for several race/ethnicity combinations. We could apply these same tools to other race/ethnic combinations.

%Hispanic CVAP by Census Tract; Houston Area
— in context of Texas 114th Congressional District 29 (black boundary)
.. view developed with ProximityOne CV XE GIS and related GIS project.

This map shows how Texas 114th CD 29 has many census tracts that have high concentrations and percent of Hispanic CVAP (see legend at lower right in graphic). It is easy to where the Hispanic vote potential is by tract throughout the central Houston area. Develop thematic map patterns like this for any area of the U.S. Optionally link in voting districts/precincts, state legislative districts among many others. Modify appearance with different colors, interval/color assignments, labels among other settings.

CVAP data are available for several types of geographic areas (states, counties, census tracts, block groups, among others) from the annually updated American Community Survey (ACS) CVAP special tabulation.

How to Assess the Hispanic Vote for the 2016 Elections?
Identifying the census tracts having large numbers of Hispanic CVAP and high percentages, is a step one. But an important one. The next steps involve 1) determining the scope of the registered to vote Hispanic CVAP and 2) the registered to vote Hispanic CVAP turn-out on voting day or by absentee ballot.

Use the Interactive Table to Examine Hispanic CVAP
Use the interactive table in this related section to analyze patterns among census tracts where numbers and percent of Hispanic CVAP are large. Follow these steps to analyze pattern in the central Houston:

• Click ShowAll button below table (resets table).
• Click CountyFIPS button below table.
– refreshes table with only tracts in county 48201 (Harris County/Houston).
• Click Hispanic button below table at far right.
– refreshes table with same rows but now selected columns.
• Click the “CVAP Hispanic” column header twice.
– sorts in descending order; view now appears as:

Tract 48201221300 has the highest Hispanic CVAP (3,405) among all tracts in Harris County (48201). This tract is shown in the map below (see pointer; a zoom in to the map shown above). The tract is labeled with the tract code and the Hispanic CVAP population (3,405).

Examining Texas CD 114 29 CVAP Characteristics
The CV XE GIS Site Analysis tool was used to examine CVAP characteristics for the set of census tracts intersecting with Texas CD 114 29. This is a close but rough approximation as census tracts are not fully coterminous with CD boundaries. In this case there are 136 tracts intersecting with CD 29. Approximately 98% of the composite tracts area is coincident with the CD 29 area.

In the 2014 House election, the total CD 29 votes cast was less than 50,000. The incumbent won the election with 42,000 votes. Meanwhile, the total population for the 136 tract area was 708,709, the total CVAP was 332,060 and the Hispanic CVAP was 202,495 (ACS 2014 estimates). Roughly 150,000 eligible Hispanic CVAP voters did not vote. How to assess the potential impact of a further engaged Hispanic CVAP?

Analyzing Elections/Geographic Areas of Interest
Apply these same methods to any area in the U.S. to determine those census tracts having the highest Hispanic CVAP and the *potential* to have a relatively large Hispanic Vote in the 2016 Elections.

Join me in a Data Analytics Lab session to discuss more details about analyzing characteristics of the citizen voting age population. 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.

Healthcare Data Analytics: Market Analysis

What factors best determine where a clinic, hospital or professional practice is located? For those that exist, how to best determine the scope and needs of the market served? Understanding healthcare market dynamics is one way these entities can improve their business and operation by using Health Data Analytics. Professionals skilled with Health Data Analytics can help their organization, or clients, better achieve their vision and improve performance.

This section is focused on analyzing healthcare markets and infrastructure using Geographic Information System (GIS) tools and related data resources. Participants in the Certificate in Data Analytics may optionally use the tools and resources described here. See overview of steps to install and use the GIS project and datasets illustrated in more detail in the related Web section.

Using GIS to Analyze Healthcare Market Characteristics
Illustrating GIS start-up view discussed in this section.

– View developed using CV XE GIS; click graphic for larger view.

Analyzing healthcare markets involves examining characteristics of healthcare facilities in context of competitive position and market potential. Geographic Information System (GIS) tools can be used to knit together geographic, demographic, economic and business data to perform these analyses. This document makes use of the Atlanta area to illustrate applications. In an actual study, the geographic focus could be a city, county, metro, state or some combination, anywhere in the U.S., or the U.S. overall.

Understanding Needs and Visions
A first step involves an assessment of your situation — your needs, visions and data that you have to work with. The results of this assessment and data that you provide help develop/frame a market study in context of GIS project(s).

Market Infrastructure Analytical Framework
The following graphic shows the start-up view of the Atlanta area Healthcare Data Analytics (HCDA) GIS project. This GIS project involves use of many layers and types of data as shown in the legend at left of map window. Selection of the type of geography, scope of geography and scope of subject matter are key elements in setting up the market infrastructure analytical framework. This is a proxy/example for the GIS project that would be developed to meet your needs/application focus.

The above view shows a thematic pattern of median household income by census tract (averaging 4,000 population). Pattern analysis helps you visualize demographic-economic characteristics by census tract — in this example you can easily see patterns of economic prosperity. This example uses median household income; we can draw upon hundreds of subject matter items and depict other types of patterns.

Examining the Healthcare Infrastructure
The graphic below shows selected types of healthcare facilities.
See legend to the left of map:
• Hospitals – blue triangle markers
• Assisted Living Facilities (ALF) – green circle markers
• Nursing Homes – red square markers

Site Analysis — Examining Characteristics of Healthcare Facilities
The yellow circle marker shows the hypothetical location of a prospective new facility. A 5-mile radius site study area — from the yellow marker — is used to select existing nursing homes; characteristics of the competition. Nursing homes show as cross-hatched; circular area is study zone.

Display of the 9 facilities selected above.

See the related Web section to view further details.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about using these data in context of data analytics with other geography and other subject matter.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

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

Evolution of Census Tracts: 1970-2010

… examining statistical area geographic change … in the world of small area demographic-economic data analysis, census tracts are often a preferred level of geography. Subdivisions of counties (or county equivalent), census tracts cover the U.S. from wall-to-wall. Each county is comprised of one or more census tracts. Averaging 1,200 population, tract geography often corresponds to neighborhood areas. For Census 2010, there were 73,057 census tracts defined. Their reasonably static geography between each decennial census is an important feature for many applications. See related more detailed Web section

Annual census tract demographic-economic updates from the American Community Survey 5-year estimates (ACS0913), make census tracts even more appealing. But it has not always been that way. And, longitudinal comparison of demographic-economic change at the tract level can be challenging where tract geography and codes change with a new decennial census.

2010 marked the 100th anniversary of the census tract. Extensive use of the census tract started with the 1970 census and has evolved since then. This section illustrates how census tracts evolved between 1970 and 2010 using GIS resources. A GIS project was developed that includes census tract shapefiles for each census 1970 through 2010.

Visualizing Demographic Patterns by Census Tract
The following graphic shows patterns of economic prosperity by Census 2010 census tract in the Dallas, Texas metro area (Dallas metro component counties & demographic change). Census tract geography and demographic patterns are reviewed for part of Collin County. The following view shows median household income (MHI), based on ACS 2013 5-year estimates, by census tract. See MHI intervals/colors in legend at left of map. Boundaries/patterns are shown for Census 2010 tracts “0316.??” (black boundaries) in context of 1970 census tract “031600”. Historical views of this area, illustrating how tract boundaries have changed over time, are shown later in this section.

– Click graphic for larger view showing Census 2010 tract codes.
– View developed with CV XE GIS.
Click to view tract area (red boundaries) in context of broader region

1970 Census Tracts
A very small part of the U.S. was covered by 1970 census tracts.
The following view shows 1970 census tracts with orange fill pattern.

  View developed with CV XE GIS.

1980 Census Tracts
A larger part of the U.S. was covered by 1980 census tracts. The following view shows 1980 census tracts with orange fill pattern.

  View developed with CV XE GIS.

A Brief History
Initial census tract data was with the 1910 census and included a handful of cities. Starting with the 1940 census, census tracts became an official statistical geography tabulation area. Starting with the 1970 census, and the first more extensive data in machine-readable form (magnetic tapes used with mainframe computers), census tracts became a more popular geography for the analysis of small area data. For both the 1970 and 1980 censuses, census tracts did not fully cover the U.S. For the 1990 census, census tracts and the quasi-equivalent “block numbering areas” (BNAs) covered the U.S. wall-to-wall. Starting with Census 2000, BNAs were retired and transformed into census tracts. Use of census tracts for demographic-economic analysis has continued gain in popularity. Now, census tract estimates are available annually from the American Community Survey 5-year estimates (ACS0913). Access ACS 5-year estimates via interactive tables.

1970 Census Tracts: Collin County; Dallas Metro
1970 census tract “031600” shown with bold black boundary.

  View developed with CV XE GIS.

1980 Census Tracts: Collin County; Dallas Metro
1980 census tracts 0316.?? (same general geography as covered by tract “031600” in 1970) shown with bold black boundary. This view shows tracts labeled with the 6-character census tract code, unique within county.

  View developed with CV XE GIS.

1990 Census Tracts: Collin County; Dallas Metro
1990 census tracts 0316.?? (same general geography as covered by tract “031600” in 1970) shown with bold black boundary. This view shows tracts labeled with the census tract “base” plus “suffix” code separated by a decimal point. In 1980, note that there is no 1130.01 or 1130.02 as shown above for the 1970 vintage tracts . The codes 1130.03 and 113003 are equivalent. The 6-character, no decimal version, is preferred in all cases when used as a geocode.


  View developed with CV XE GIS.

2000 Census Tracts: Collin County; Dallas Metro
2000 census tracts 0316.?? (same general geography as covered by tract “031600” in 1970) shown with bold black boundary.

  View developed with CV XE GIS.

2010 Census Tracts: Collin County; Dallas Metro
2010 census tracts 0316.?? (same general geography as covered by tract “031600” in 1970) shown with bold black boundary.

  View developed with CV XE GIS.

Equivalencing Census 2000 and Census 2010 Tract Geography
As shown above, the area covered by Census 2000 tracts 1130.15 and 1130.18 become Census 2010 tract 1146.00. Comparing the above map views for Census 2000 and Census 2010 shows (upper left tracts) shows Census 2000 tract 031644 is split into Census 2010 tracts 031656, 031657 and 031658. To compare demographic change for Census 2000 tract 031644 requires combining data tabulated for Census 2010 tracts 031656, 031657, 031658 and other partial Census 2010 tracts intersecting with Census 2000 tract 031644. See more about these relationships at Census 2010 Demographics for Census 2000 Geography. Use the interactive table in that section to view the relationship among these tracts. The graphic shown below illustrates use of that table. A query has been placed on Census 2000 tract 031644 (see button below table and query value 48085031644). The table nowe shows rows only for Census 2000 031644. See the corresponding Census 2010 tracts in columns to right.

The following graphic shows the relationship between these tracts.

To replicate this view in the interactive table, follow these steps:
• Click ShowAll button below table.
• Key in Census 2000 tract code 48085031644 to right of Find in GeoID00 button.
• Click Find in GeoID00 button.
• The view above appears in the table.

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.

American Community Survey 2013 Release Schedule

Data from the American Community Survey (ACS) are an indispensable part of most analyses involving demographic-economic characteristics and patterns.  These data help analysts and decision-makers compare characteristics of one area to another.  In many ways uniquely, these data help you understand where and how patterns are changing.  The ACS data can be used to develop insights into new areas of opportunity, what areas show diminishing potential, what areas might be most suited to what you do and programs that you operate.  Census 2010 and ACS data provide the most current Census-sourced demographics for wide-ranging geography.  An important feature of these data is the availability of national scope small area demographic-economic data … data at the census tract, block group and ZIP code area levels among many others.

ACS 2013 Release Dates
Annual ACS updates — new and more recent data — are released in the fall of each year.  The ACS 2013 data release schedule is as follows:

09.18.14 — American Community Survey 2013 1-year Estimates
    2013 estimates for areas of 65,000 population or more.
10.23.14 — American Community Survey 2013 3-year Estimates
    2011-2013 estimates for areas of 20,000 population or more.
12.04.14 — American Community Survey 2013 5-year Estimates
    2009-13 demographics-economic estimates for all areas.

ACS 2013 Public Use Microdata Sample (PUMS); early 2015
ACS 2013 SDST – School District Special Tabulation (May 2015)

See more about these data at the progressively updated ACS 2013 Web site.

Examining Neighborhood Change

Goto ProximityOne  How have neighborhoods of interest changed between 2000 and 2010?  Since 2010?  How will a neighborhood change going forward?  How does a neighborhood’s current and trending characteristics compare to adjacent of peer neighborhoods?  This section is focused on resources and methods to examine neighborhood geographic, demographic and economic characteristics and change. View related Web section, providing more detail.

The exact geographic definition of a neighborhood is elusive; neighborhood geography is not defined by a national standard.  Many areas have multiple neighborhood renderings.  While many counties/cities have well defined neighborhoods, most do not. To examine the demographic-economic characteristics of a neighborhood, the best options are to use a combination of census blocks, block groups and census tracts.

Nob Hill Neighborhood … San Francisco, CA
The Nob Hill neighborhood in San Francisco has changed in population from 20,142 in 2000 to 18,599 in 2010. The White alone population has grown a little while the Asian alone population has decreased from 11,532 (2000) to 9,705 (2010).  These population data are from Census 2000 and Census 2010 and determined by aggregating census block level data.  The Nob Hill census block geography did not change from 2000 to 2010 (75 census blocks).  Many neighborhoods and census block boundaries and codes change over time complicating longitudinal analysis of neighborhoods.  The Nob Hill neighborhood is shown in the following graphic with bold blue boundary; Census 2010 census blocks are shown with lighter blue boundaries.

nobhill1

The Nob Hill neighborhood in context of San Francisco.
nobhill2

Neighborhood Demographic-Economic Characteristics
Demographic-economic characteristics of neighborhoods play an important role as decision-making information.  The similarity, or dissimilarity, of these small area geographies are the basis for many local government planning operations ranging from law enforcement to transportation.  They help businesses determine where to locate — to serve markets where demand for their product or services is greatest.  Knowing about neighborhood geography and demographic-economic characteristics are critical to real estate businesses.

Census Blocks, Block Groups and Census Tracts
Census blocks, block groups and census tracts are the most useful geographies from which we can develop neighborhood demographic-economic characteristics.  These geographies are all defined by the Census Bureau and nest together.  All counties are comprised of a set of contiguous census tracts. Census tracts average 4,000 population and are comprised of block groups that average 1,200 population.  Block groups are comprised of a set of blocks that average 100 population.  In built-up urban areas, a census block is often the same as a city block bounded by streets.   These areas are defined for each decennial census and most boundaries do not change for the decade.  These features of known boundaries, covering the U.S. wall-to-wall, non-changing geography, nesting geographic hierarchy — and the availability of extensive demographic-economic data — make them the ideal choices to examine neighborhood characteristics and change.  There are advantages and disadvantages for each type of geography.

Census Blocks
The most appealing feature of census blocks is geographic detail.  There are more than 11 million Census 2010 census blocks; approximately 1/3 of these are water blocks and have no population.  These are the smallest geographic areas for which the Census Bureau tabulates demographic data.  The most limiting feature with using census block demographics is that only decennial census data are available by block; no richer demographics such as income or educational attainment.

Block Groups
The most appealing feature of block groups is geographic detail combined with availability of 1) decennial census data, 2) richer demographics from the American Community Survey (ACS) and 3)  annual updates from ACS.  Like blocks, there are no richer demographics for block groups from the decennial census.  There are 217,000 Census 2010 block groups. The most limiting features of block group demographics from ACS include 1) a relative high margin of error associated with ACS estimates, 2) a reduced scope of subject matter data compared to census tracts, and 3) data access and integration is challenging.

Census Tracts
Census tracts were originally designed by the Census Bureau as a pseudo-neighborhood areas averaging 4,000 population.  Approximately 73,000 Census 2010 census tracts cover the U.S. wall to wall.  Over time, the demographic-economic composition of many tracts change.  Tracts changing the most are often of most interest.  The advantages of using census tracts is similar to that for block groups.  Compared to block groups, tract estimates are more reliable and there is a broader set of subject matter available.  Tract data are easier to access and use that block or block group data.  One of the most limiting features of using census tracts to characterize neighborhoods is that tract geography often cuts through more than one neighborhood. 

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.