Category Archives: Block Groups

Location-Based Demographics Update

.. tools you can use to examine characteristics of addresses/locations .. many of us are interested in knowing attributes of addresses or locations. Often knowing address latitude-longitude is important so that the addresses can be viewed on a map .. see below.  Some might need to know what census block, or other geography, in which an address is located .. or what school district is an address located in.  Others need to know demographic-economic attributes of the neighborhood or area where an address is located.  These types of attributes can be obtained for addresses using the Location-Based Demographic (LBD) tools.  The LBD tool has just been made a part of the CV XE GIS software.  The LBD tool is available in all versions of CV XE GIS, including the no fee User Group version. See more about using the LBD tools to look-up and analyze address/location attributes.

Viewing Geocoded Addresses on a Map – automatically
The following view shows addresses geocoded using the LBD tool. Markers show addresses of 27 Trader Joe’s locations in the Los Angeles area. LBD automatically creates a shapefile that is added to your GIS project. The markers are labeled with population ages 18 and over in the corresponding census tract. Marker color/styles reflect different levels of median household income. A separate census tract layer shows patterns of economic prosperity.

Click graphic for larger view. Expand browser window. A mini profile is displayed showing demographic-economic attributes for the marker at pointer.

View the locations without the tract thematic pattern layer:

Make similar views for your addresses.

Get Started Using the LBD Tool
1 – join the User Group .. click here to join (no fee).
2 – run the installer to install on a Windows machine .. requires your userid.
3 – with CV XE GIS running, click Tools>Find Address/LBD
    enter an address .. a form appears showing characteristics of the address.
4 – see more about using the tools on the LDB page.

GeoStatistical Data Analytics Learning Sessions
We are developing a series of “GeoStatistical Data Analytics” (GSDA) Learning Sessions/modules. One of these is focused on using the LBD tools and methods in the broader context of data analytics. We plan to develop the GSDA models for self-guided use by analysts/practitioners as well as in the classroom setting with teacher/student materials. Upcoming blog posts will describe the program in more detail.

Data Analytics Web Sessions
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.

Congressional District/State Legislative District Data Analytics Sessions

.. join me in the Congressional District/State Legislative District Data Analytics Sessions .. http://proximityone.com/cdsld/cdsld_vasessions.htm .. face-to-face sessions in the Washington, DC area.

Legislative Districts & Patterns of Neighborhood Economic Prosperity
Census tracts labeled with median household income in context VA House District 11 (bold blue boundary) in Fairfax County, VA. Use the GIS project to examine any state legislative district.

— click for larger view
— view created using CV XE GIS & associated GIS project.

CDSLD Sessions These sessions are focused on tools, data and analytical methods relating to Congressional Districts (115th CDs) and State Legislative Districts (2016 cycle SLDs). We focus on national and Virginia CDs and SLDs in context of the total population, voting population, the Citizen Voting Age Population characteristics and patterns with drill down to census blockblock groupcensus tractelection precinctcity/placeZIP codecountymetro and other geography.

Program details as PDF: http://proximityone.com/cdsld/cdsld_vasessions.pdf.

Anyone may attend. There is no fee. There is no promotional content. Sessions are presented by Warren Glimpse an expert on the topics covered. Learn more about the potentials of using these tools, data and methods. Get answers to your questions to learn more about what data are available, options to access the data, how to integrate these data with other data and insights into how you can use and the data. Attend one or many sessions. While there are core topics, new related material and updates are covered in each session. Join in as a continuing program. Develop and extend data analytics skills.

Patterns of Economic Prosperity by VA Senate District
– Virginia Upper/Senate SLDs by Median Household Income

– click graphic for better quality view; districts labeled with district code

More About Congressional Districts & State Legislative Districts
See the related section for more information:
• 115th Congressional Districts ..
.. Main .. http://proximityone.com/cd115.htm
.. demographic-economic tables http://proximityone.com/cd161dp1.htm
• State Legislative Districts Main .. http://proximityone.com/sld2016.htm
.. with demographic-economic interactive table
• Virginia State Legislative Districts .. http://proximityone.com/sld_va.htm
.. interactive table with incumbency details

CDSLD Data Analytics Web Sessions
Unable to join the face-to-face session? Join me in a Data Analytics Web 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.

Analyzing Block Group Demographics

.. tools & data to analyze sub-census tract households, education, income, housing, more … Block Groups, subdivisions of census tracts, are the smallest geographic areas for which “richer demographics” are developed by the Census Bureau. Block group demographic-economic estimates, based on Census 2010 geography, are annually updated beginning with American Community Survey (ACS) 2010. The latest ACS estimates for these 217,740 areas covering U.S. wall-to-wall are from ACS 2015. The ACS 2016 update will be released in December 2017.  See the related Web section for more detail about accessing and using block group geography and demographic-economic data.

Patterns of Economic Prosperity by Block Group
The following graphic shows patterns of median household income by block group in the Houston, TX area. Markers show block groups with 10 or more housing units having value of $2 million or more. Markers are labeled with the number of housing units having value of $2 million or more in that block group. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using block group demographics and the relative ease to gain insights using geospatial data analytics tools.

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

Block Group Demographic-Economic Data & Shapefiles
… selection of key demographic-economic attributes; annual update
… subject matter categories include:
  • Total population>
  • Population by gender iterated by age
  • Population by race/origin
  • Households by type of household
  • Educational attainment by detailed category
  • Household Income by detailed category
  • Housing units by owner/renter occupancy
  • Housing units by units in structure
  • Housing units by detailed value intervals

See the related Web section for a detailed list of items.

Use these Data on Your Computer
Use the above U.S. national scope dataset with your own software or in ready-to-use GIS projects with the CV XE GIS software.

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 Houston Metro Demographic-Economic Characteristics

.. tools & data to examine metro demographic-economic characteristics .. this Houston, TX metro focused section is one of several similar metro sections that will be covered in weeks ahead.  Each metro-focused section provides a summary of tools and data that can be used to view, rank, compare, analyze conditions and trends within the metro and this metro relative to other metros, regions and the Nation.  The ready-to-use GIS project/datasets provide the basis for extended data/geographic views and analysis immediately.  See more detail about topics covered in this related Web section.

Relating your data to demographic-economic characteristics and trends in a region involves more than information provided by a report or set of statistical tables. It is important to use your data to be able to identify areas of missed opportunity and competitive position. It is important to have a “10,000 foot” view as well as understanding individual neighborhoods and market/service areas. Geographic Information System (GIS) tools, with the right set of geographic, demographic and economic data can facilitate decision-making through the use of visual and tabular data analytics.

This section provides information on installing and using the Houston Metro Demographic-Economic GIS software and project/datasets. This same scope of data, tools and operation is available for any metro, state or combination.

10,000 Foot View
The following graphic shows patterns of median household income by census tract for the Houston metro area. This is the start-up view when using the GIS tools and data described below. The color patterns/intervals are shown in the highlighted layer in legend at left of map window. Use the GIS tools described below to develop thematic pattern maps for a range of data and criteria.

.. view developed using the CVGIS software.

See more about census tracts; see tracts main page.

Several additional views follow, developed using this same GIS project. These views illustrate different levels of geographic granularity and patterns of different subject matter.

Median Household Value by Block Group
See more about block groups; see block groups main page.

.. view developed using the CVGIS software.

Population/Housing Unit by Block
See more about census blocks; see census block main page.

.. view developed using the CVGIS software.

Zoom-in to Sugarland/Fort Bend County
See more about cities/places; see cities/places main page.
Access data for any city using interactive table.

.. view developed using the CVGIS software.

Further Zoom-in Showing Street/Road Detail
See more about streets.

.. view developed using the CVGIS software.

Additional Information
See the related Houston metro Situation & Outlook Report.

Using the GIS Software and Project/Datasets
(requires Windows computer with Internet connection)
1. Install the ProximityOne CV XE GIS
… run the CV XE GIS installer
… requires UserID; take all defaults during installation
2. Download the Houston Metro GIS project fileset
… requires UserID; unzip Houston Metro GIS project files to local new folder c:\p1data
3. Open the c:\p1data\us1_metros_houston.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named c:\p1data\us1_metros_houston.gis
4. Done. The start-up view is shown above.

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.

Developing Geographic Relationship Data

.. tools and methods to build and use geographic relationship files … which census blocks or block groups intersect with one or a set of school attendance zones (SAZ)? How to determine which counties are touched by a metropolitan area? Which are contained within a metropolitan area? Which pipelines having selected attributes pass through water in a designated geographic extent? This section reviews use of the Shp2Shp tool and methods to develop a geographic relationship file by relating any two separate otherwise unrelated shapefiles. See relasted Web page for a more detiled review of using Shp2Shp.

As an example, use Shp2Shp to view/determine block groups intersecting with custom defined study/market/service area(s) … the only practical method of obtaining these codes for demographic-economic analysis.

– the custom defined polygon was created using the CV XE GIS AddShapes tool.

Many geodemographic analyses require knowing how geometries geospatially relate to other geometries. Examples include congressional/legislative redistricting, sales/service territory management and school district attendance zones.

The CV XE GIS Shape-to-Shape (Shp2Shp) relational analysis feature provides many geospatial processing operations useful to meet these needs. Shp2Shp determines geographic/spatial relationships of shapes in two shapefiles and provides information to the user about these relationships. Shp2Shp uses the DE-9IM topological model and provides an extended array of geographic and subject matter for the spatially related geometries. Sh2Shp helps users extend visual analysis of geographically based subject matter. Examples:
• county(s) that touch (are adjacent to) a specified county.
• block groups(s) that touch (are adjacent to) a specified block group.
• census blocks correspond to a specified school attendance zone.
• attributes of block groups crossed by a delivery route.

Block Groups that Touch a Selected Block Group
The following graphic illustrates the results of using the Shp2Shp tool to determine which block groups touch block group 48-85-030530-2 — a block group located within McKinney, TX. Shp2Shp determines which block groups touch this block group, then selects/depicts (crosshatch pattern) these block groups in the corresponding GIS map view.

Geographic Reference File
In the process, Shp2Shp creates a geographic relationship file as illustrated below. There are six block groups touching the specified block group. As shown in the above view, one of these block groups touches only at one point. The table below (derived from the XLS file output by Shp2Shp) shows six rows corresponding to the six touching block groups. The table contains two columns; column one corresponds to the field GEOID from Layer 1 (the output field as specified in edit box 1.2 in above graphic) and column 2 corresponds to the field GEOID from Layer 2 (the output field as specified in edit box 2.2 in above graphic). The Layer 1 column has a constant value because a query was set (geoid=’480850305302′) as shown in edit box 1.3. in the above graphic. Any field in the layer dataset could have been chosen. The GEOID may be used more often for subsequent steps using the GRF and further described below. It is coincidental that both layers/shapefiles have the field named “GEOID”.

Layer 1 Layer 2
480850305302 480850305272
480850305302 480850305281
480850305302 480850305301
480850305302 480850305311
480850305302 480850305271
480850305302 480850305312

Note that in the above example, only the geocodes are output for each geography/shape meeting the type of geospatial relationship. Any filed within either shapefile may be selected for output (e.g., name, demographic-economic field value, etc.)

How it Works — Shp2Shp Operations
The following graphic shows the settings used to develop the map view shown above.

See related section providing details on using the Shp2Shp tool.

Geographic Relationships Supported
The Select Relationships dropdown shown in the above graphic is used to determine what type of spatial relationship is to be used. Options include:
• Equality
• Disjoint
• Intersect
• Touch
• Overlap
• Cross
• Within
• Contains
See more about the DE-9IM topological model used by Shp2Shp.

Try it Yourself

See full details on how you can use any version, including the no fee versin, of CV XE GIS to use the Shp2Shp tools. Here are two examples what you can d. Use any of the geospatial relatoinships. Apply your own queries.

Using Touch Operation
Select the type of geographic operation as Touch. Click Find Matches button. The map view now shows as:

Using Contains Operation
Click RevertAll button. Select the type of geographic operation as Contains. Click Find Matches button. The map view now shows as:

Relating Census Block and School Attendance Zones
The graphic shown below illustrates census blocks intersecting with Joyner Elementary School attendance zone located in Guilford County Schools, NC (see district profile). The attendance zone is shown with bold blue boundary. Joyner ES SAZ intersecting blocks are shown with black boundaries and labeled with Census 2010 total population (item P0010001 as described in table below graphic). Joyner ES is shown with red marker in lower right.


– view developed using CV XE GIS and related GIS project; click graphic for larger view

See more about this application in this related 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.

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.