Tag Archives: census blocks

Census 2020 Residential Address Counts by Block

.. using Census 2020 residential address count data to examine change since 2010 .. the Census Bureau has released preliminary Census 2020 residential address counts by Census 2010 census block. These data, count of residential addresses and group quarters addresses, reflect updates as of October 2019 and do not represent final Census 2020 counts. The data will continue to be updated to support Census 2020. See related Web section with more detail and updates.

Importance and Use
These data are of immediate value in determining and analyzing how the number of housing units have changed, 2010 to 2019. Since the data are at the census block level, they may be aggregated to any other Census-defined summary level/type of geographic area such as block group, tract, ZIP code, city, county, school district, etc. These data are also important as they give us a “year in advance look” at how small area demographics are changing since 2010. Before this, the most recent census block data were from Census 2010. A lot has happened in many areas. These data provide insights into that change. The Census 2020 block level data will be released in early 2021 for Census 2020 census block geography. So, another important feature of these data is that they are summarized for Census 2010 census block boundaries. Census 2010 and 2020 block boundaries may differ, particularly in areas experiencing larger demographic growth/change. An important limitation is that they are counts, subject to change as the Census data are collected/tabulated.

Comparing Census 2010 Housing Units with Census 2020 Address Counts
The following graphic shows patterns of Census 2010 housing counts with the Census 2020 (late 2019 vintage) residential address counts by census block. This view is focused on census tract 3608100700 (tract 000700) in Queens County, NY (code shown near center of graphic). Individual blocks are labeled with block code (4 digits) with the Census 2010 housing units (yellow label) and Census 2020 residential address count (green label) shown below the block code. As an example, the block located at the pointer has block code 3006 (or full national scope unique block code 36-081-00700-3006) with a Census 2010 count 44 housing units and a Census 2020 (late 2019 count) of 232 residential addresses. Click graphic for larger view. Expand browser window to full screen for best quality view.

.. view created with ProximityOne CV XE GIS software and related GIS project.

More About Using these Data
We have summarized these data at the census tract level and are evaluating their use, in combination with other data, to develop current estimates and projections to 2025.

Data Analytics Web Sessions
Join me in a Demographics 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 Block, Block Group & Census Tract GeoDemographics

Census tracts, block groups and blocks are the important small area statistical geographic areas for which data from Census 2010 are tabulated. Data for census tracts and block groups are also tabulated annually from the American Community Survey. For example. in December 2018, we will have new “richer demographics” annual estimates centric to each year 2008 through 2015 for Census 2010 tracts and block groups … data such as educational attainment, language spoken, housing and household characteristics,  income characteristics and employment and other demographic-economic attributes.

Largest Population New York City (NYC) Census Blocks
The following graphic shows the NYC Census 2010 census block having the largest Census 2010 population that is not a group quarters population block. The Lincoln Center census block shown in the graphic (red boundary) has 4,067 population and 2,922 housing units.

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

This block (36 061 015500 6000) occupies 0.033 square miles. It has a population density of 122,333 (population per square mile). The NYC block with the largest population is on Rikers Island and has a group quarters population of 8,634 and 0 housing units. For Census 2010, there were 350,169 census blocks covering the state of New York; 13,356 census blocks were water blocks. For the State of New York, as of Census 2010 the average census block population was 55 (57 excluding water blocks).

Census 2010 and Census 2020
These geographies have generally stable geographic areas and codes from one decennial census (e.g., Census 2010) to the next (e.g., Census 2020). Many of these areas will change in terms of code and area for Census 2020, though the geographic changes will typically be small or not at all.

Census 2020 block, block group and tract codes and geometry will be available in late 2020. Initial block level demographics will be available in March 2021.

Census 2010 & Current GeoDemographics
These areas cover the U.S. from wall-to-wall and generally non-changing in terms of boundary and geographic code (geocode) until Census 2020. This section provides a summary of new Web pages with more detail about each of these geographies:
census tracts and tract codes .. 73,056 areas
census block groups and block group codes .. 217,740 areas
census blocks and block codes .. 11,078,297 areas

Each of these pages provides an interactive table to view tallies of Census 2010 for each of these small area geographies.

Combining Address Data with Small Area Geography
The address of the Office of the California Secretary of State, located at 1500 11th St, Sacramento, CA 95814, was geocoded using the APIGeocoder and converted into a shapefile for Geographic Information System applications.  The location is shown as a red marker in the map views shown below, illustrating each type of small area geography: tracts. block groups and blocks.

Census Tracts
Tracts are labeled with green tract codes. Address 1500 11th St, Sacramento, CA 95814 is shown by red marker.  The address is in tract 06067001101.

View created using CV XE GIS.

Block Groups
Block groups are labeled with red block group codes.  Tract 06067001101 is comprised of block groups: 060670011011 and 060670011012.  See pointer in map view; the block group within tract boundary.

View created using CV XE GIS.

Zoom-in to Census Block
Blocks are labeled with yellow block codes. The address is located in block 060670011011085.

View created using CV XE GIS.

Further Zoom-in Showing Streets
Streets are labeled with street names. Identify tool is used to show mini-profile for 1500 block of 11th Street.

View created using CV XE GIS.

Is the tract code 11.01 or 001101?
Both. Census tracts within a county are identified by a 4-digit basic code between 0001 and 9999, and may have a 2-digit suffix ranging from .01 to .98; for example, 6059.02. The decimal point separating the 4-digit basic tract code from the 2-digit suffix is shown in Census Bureau printed reports and maps. For geo-referencing, the decimal point is implied and does not appear; the 6-character tract code with lead zeroes is used — a character string with no blanks and all numbers.

Accessing and Using these Geographies & Related Demographics
There are several ways these geographies can be used.
• The geocodes are the “handles” to access demographic-economic statistical data.
• The geographies may be visually, geospatially, related as shapefiles.
.. the Census Bureau makes these shapefiles available for use in user appications.
.. the shapefiles typically do not include demographic-economic data.

Access Census 2010 Census Block (and Block Group/Tract) data:
• P.L. 94-171 Redistricting Data — http://proximityone.com/cen2010_pl94171.htm
• Summary File 1 — http://proximityone.com/cen2010_sf1.htm

Access Census Block Group and Tract richer demographics:
• 2016 American Community Survey (ACS) 5-year estimates
  — http://proximityone.com/acs1216.htm
• Access annual counterparts to above section
• Census blocks — http://proximityone.com/cenblk.htm
• Census block groups — http://proximityone.com/blockgroups.htm
• Census tracts — http://proximityone.com/tracts.htm

Alternatively use the Census Bureau APIs or CV XE GIS APIGateway.

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.

Redistricting & Census 2020

.. most states will not have new redistricting plans until after Census 2020. Redistricting is the process of developing a redistricting plan for 2 or more areas (districts) disjoint and contiguous that are contained within the collective area of all districts based on some criteria. Redistricting is perhaps most familiar with regard to congressional districts and state legislative districts based on a set of demographic characteristics … but may apply to many other types of geographies. This post briefly reviews the Census 2020 & Redistricting Program.

Redrawing the Pennsylvania 115th Congressional Districts
The following views show Pennsylvania 115th Congressional Districts in their gerrymandered configuration (old) and the redrawn configuration (February 2018, new). Counties shown with light gray boundary. Click graphic for larger view. Expand browser window for best quality view.
Pennsylvania 115th CDs — Old

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

Pennsylvania 115th CDs — New, redrawn February 2018

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

Census 2020 & Redistricting Program
The ProximityOne Census 2020 & Redistricting Program enables participants to engage now in preparation for redistricting based on Census 2020. Use resources and processes provided by ProximityOne and the Congressional Districts/State Legislative Districts Group (CDSLD) .. participate in hands-on redistricting for your areas of interest. We start now using Census 2010 redistricting data, current congressional districts and state legislative districts, and related data/tools. Progressively, we move toward accessing the live Census 2020 redistricting data (March 2021). There is no cost to participate. See more about the Census 2020 & Redistricting Program at http://proximityone.com/cen2020_redistricting.htm. Join the CDSLD Group via this form to receive updates on the program and begin participation.

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 the Census 2020 redistricting Program. 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.

New 2016 Digital Roads Database

.. new resources for updated geographic reference and statistical mapping and geography for routing logistics and optimization .. The Census Bureau TIGER/Line is a continuously updated geographic database used for geographic reference and geospatial processing of data from various Census statistical programs including the decennial census Census 2010 and American Community Survey (ACS 2014). The public use version of TIGER is released annually that includes updates developed during the year. ProximityOne integrates the TIGER geographic updates in the Digital Map Database. Warren Glimpse, founder of ProximityOne, developed the GBF/DIME used as the prototype for TIGER/Line development.  See related Web section for more details, interactive table and access to GIS resources.

The TIGER database includes many types of files and data. The data are developed in the form of shapefiles and dbase files that may be used directly with the ProximityOne CV XE GIS software at no fee. Perform wide-ranging mapping and geospatial analysis applications using these GIS resources. See more aboutmapping statistical data.

TIGER/Line Roads Data
This section is focused mainly on the use of the TIGER/Line “edges” shapefile. The edges shapefile U.S. wall-to-wall street/road coverage in the form of line shapefiles. Lines classified as roads are intersection-to-intersection road segments. Line segment fields include name, left- and right-side high and low addresses, and many related attributes.

Use the U.S. by county interactive table below to examine attributes of TIGER 2016 street/road coverage. ProximityOne developed these county summary data by processing each county edges shapefile. See about using the edges shapefile with the CV XE GIS software below in this section.

Illustrative Applications
The following sequence of graphics shows an example of a “road segment” in context of related geography. These applications focus on an area in Kansas City, MO (Jackson County),. Jackson County has 52,139 TIGER 2016 road segments. See the related step-by-step summary of how you can create these and similar map views using CV XE GIS below in this section.

Road Segment Map View & Profile
– Starbucks locations shown as red markers; pointer on road segment by a Starbucks location.
– View illustrates how non-Census, non-statistical data can be integrated with TIGER.
– Clicking on the road segment (in GIS operation), a mini-profile displays.
– The profile shows attributes of the selected road segment.
.. the TLID value shows the unique ID for this segment among all segments in U.S.
.. left- and right-side high and low address ranges and included in the profile.

Corresponding Census Block Profile
– The road segments are boundaries for census blocks.
– The census block boundaries are shown using a related TIGER blocks shapefile.
– The more that 11 million census blocks cover the U.S. wall-to-wall.
– The census block code (290950073002017) is shown as a label in the map graphic and in the profile.

Neighborhood & Shopping Area View
– A zoom-out shows the location, roads and blocks for a broader areas.

Regional View
– A further zoom-out shows the focus area view in context of the metro counties (a related TIGER shapefile)
– The January 2016 Kansas City city area (orange cross-hatch pattern) is shown using a related TIGER 2016 shapefile.

TIGER 2016 Roads
TIGER/Line 2016 vintage files were released in August 2016. While many aspects of road coverage remain as described in this section, TIGER/line 2016 includes many updates as well as “new vintage” geography for school districts, state legislative districts, congressional districts and other political/statistical area geography.
• More about TIGER 2016.
• More about TIGER/Line in general.

TIGER 2016 Road/Street Name/Address Coverage
— Interactive Table
The following graphic illustrates use of the interactive table to examine the number and characteristics of road segments by county. This view shows the top 10 counties based on the number of total road segments.

– click graphic for larger view

Using TIGER/Line with CV XE GIS
These operations require a Windows computer with Internet connection
1. Install the ProximityOne CV XE GIS
… run the CV XE GIS installer
… take all defaults during installation
2. Download the TIGER Roads project fileset
… requires ProximityOne User Group ID (join now)
… unzip TIGER Roads GIS project files to local folder c:\tiger2016
3. Open the c:\tiger2016\riger2016_kc.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named c:\tiger2016\tiger2016_kc.gis
4. Done. The start-up view is shown at top of this 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.

Developing & Using Map Graphics

.. steps to develop map graphics & visual analysis of market/study areas .. map graphics are an important part of most demographic-economic analyses and essential for many applications. Not only are are maps needed to show geographic boundaries and the relative location of geography within a broader area, they can come alive by showing patterns. A thematic pattern map of median household income by block group is a good example; higher and lower areas of economic prosperity by neighborhood can be immediately determined. Map graphics can improve our ability to communicate complex information. Convey information faster. Make more compelling presentations. Collaborate more effectively through the use of map graphics.  See related Web section for more details.

The focus of this section is on creating and using KML files to prepare map graphics for use in developing Market-Study Area Comparative Analysis Reports. These files and map graphics also have broader uses. Steps are reviewed to develop the KML circular area map graphics files, convert them to shapefile structure and integrate both files into mapping and GIS applications and put them into operational use. 

KML (Keyhole Markup Language) files are XML structured files useful for visualizing geographic objects (like circles) using Internet-based browsers, notably Google Earth. Why develop/use KML files? They are easy to create with precision, there is little to no learning curve, they can be used in many venues and they are free to develop. KML files can be used side-by-side with shapefiles. Shapefiles, structured very much unlike KML files, are the dominant vector-based file structure used in GIS applications involved in both viewing and geospatial analysis. 

Developing Circular KML Files & Map Graphics
An “objective view” of this section is shown in the following graphic. The graphic shows a study site location (red marker), 1-mile & 3-mile radius circles. The site location is a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. The view shows a circular KML-based graphics in context of patterns of median household income by block group. Develop similar views for any area, any site circular configuration, using steps reviewed in this section.

– view developed using CV XE GIS

Creating the KML Circular Graphics File
Proceed through the next steps to develop a KML file used to create the graphic below on left — a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. Graphic on the right is a Starbucks location in Paris, used to illustrate this process works globally. Both graphics include study area center point and 1-mile and 3-mile radius circles.

302 Nichols Road, Kansas City, MO 64112
23 Avenue de Wagram, 75001 Paris, France

Start the create KML file application
• Key in address 302 Nichols Road, Kansas City, MO 64112 to Google Maps
.. see the latitude-longitude (39.041548,-94.592965) in the URL bar.
• Open this web page to create the circles & save results as KML file.
• Refresh this page if making a new KML file.
• Set the colors and lines to medium, blank and clear.
• Enter coordinates — key in lat 39.041548 and lon -94.592965
.. these for for this example
.. enter the values for your location of interest
Add center point
• In the Radius Distance, key in 0.05 miles
• Click Draw Radius blue button (at right of longitude).
Add site 1 circle
• In the Radius Distance, key in 1.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
Add site 2 circle
• In the Radius Distance, key in 3.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
View study area geography
• Optionally navigate up to the map view and make the view similar to the graphic at the top of this page 
.. this step is not required but might be useful to verify the study area appearance.
Save KML file
• Navigate down the page to “Google Earth KML Output”. Click the blue button Generate KML.
• Click “Download KML file Here.” Save the file to a folder and make a note of the file path and name
.. save the file as c:\sitereport\302nichols.kml (this file and filename are used below).
Done
• The three part KML file has been created and saved to the local computer. 
• Finished using this browser application.

This same process may be used again to create similarly structured KML files of any radius about any point for any location in the world. 

Loading a KML file into Google Maps
Optionally create the objective map graphic using the following steps. Or, the KML file may be used with the CV XE GIS software (see below) enabling yet further analytical possibilities. 

 Click this link to start the Google MyMaps application.
• When the new page opens click create new map button
• Next click import button
• Enter the file path/name as created above (c:\sitereport\302nichols.kml), or any KML file.
• Edit the MyMaps rendering to achieve preferred view.
• Use preferred screen capture tool to save that part of the map view as a graphic for the study report.

Using the KML File with an Existing GIS Project and converting the KML file to shapefile structure

1. Add the KML file to an Existing CV XE GIS Project
• Start the CV XE GIS software and open the project file c:\cvxe\1\cvxe_us2.gis (distributed with installer).
.. uncheck Locations and $MHI x BG layers in legend panel.
• Click the AddLayer button (second button from left on toolbar)
• Select the KML file that was created above (c:\sitereport\302nichols.kml) .. circles appear in the map window.
• Use LayerEditor to adjust settings for KML layer (transparent, bold outline)
• Navigate to zoom-in view and smaller map window.
• Use Toolbar button Save to Image (button 7 from left) to save the map window view to a .jpg file.

Navigate to this view:

2. Converting a KML File to a Shapefile
This step requires the CV XE GIS Basic or higher level version. After the KML layer appears in the above sequence, proceed as follows:

• Click File>ExportShapefile.
• Select the KML layer name.
• Set Coordinate System edit box value to NAD83.
• Click OK button.
• On the Export Layer/FileSave dialog, select an output file path and name.
• The shapefile is generated and may be reused with any GIS project.

3. Editing attributes of the study area shapefile and project file
There are three shapes in the shapefile (center point, circle 1, circle 2). 
Modify the appearance of these shapes/objects by using the Select tool (mouse in Select mode).
• In legend panel click on circles layer; name turns blue indicating this is the active layer.
• In the map window, click in the circle; the profile/editor appears (pop-up)
• Initially all three shapes have the name “Polygon”.
.. change the object names successively to Point1 (the small circle), Circle1 and Circle2.
• The shapefile attributes have been permanently changed.
• When each shape/object has been renamed, use the LayerEditor to modify the appearance of each shape.
.. the changes modify the project file and not the shapefile.
.. optional save the project (overwriting the former version) or save the project with a new name.

Renaming a shape to “Point1”
Click for larger view

Using LayerEditor to set attributes of the study area layer
Click for larger view

View of final study area layer in context of broader project
Click for larger view

View as above with $MHI x BG checked on/visible
Click for larger view
 

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

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

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.

Neighborhood Analysis: Block & Block Group Demographics

.. steps to analyze NYC Chelsea area demographics that can be applied to any neighborhood … demographic characteristics of the Chelsea area in New York City, an area west of Avenue of the Americas between 14th and 34th Streets, is radically different from adjacent areas. This topic was covered in a “great wealth divide” New York Times story. This section reviews how census block and block group demographic-economic data can be used to examine these patterns. A GIS project is used that associates census block and block group data for visual analysis Methods summarized here can be applied to any area. Use the tools described in this section to obtain demographic-economic profiles for any neighborhood based on an address. See related Web page for more detail.

See related post on Most Populated New York City Census Blocks.

Study Area in Context of Broader Area
The study area, a group of selected census tracts, is shown as the red cross-hatched area in context of lower Manhattan in the view below.

  — view created using CV XE GIS and associated GIS Project

Zoom-in View of Study Area
The next view shows a zoom-in to the study area. Block groups are shown with a red boundary. Chelsea Park is visible as the green area above the pointer south of 29th street.

  — view created using CV XE GIS and associated GIS Project

Census Block Demographics in Context of Block Groups
The next view shows a further zoom-in showing census blocks with black boundary and block groups with red boundary. Census blocka are shown with a semi-transparent yellow fill pattern (population greater than 4) and gray fill pattern (blocks with population less than 5). The block group containing Chelsea Park (green area above pointer) contains three census blocks, 2 with no population and one with 1,010 population. Block data are from Census 2010; there are no post-Census 2010 block level demographics available. The analysis could be extended to shown wide-ranging demographics at the block level.

  — view created using CV XE GIS and associated GIS Project

Examining Socioeconomic Attributes
In this further zoom-in, Chelsea Park (green area) is shown near the pointer. Census block population labels are turned off for blocks with 5 or more population to help show a less cluttered view. Block groups are labeled with two values. The yellow upper label shows the median housing value (MHV). The green lower label shows median household income (MHI). Both data items are based on the American Community Survey 5-year estimates (ACS 2013) are centric to 2011. The ACS data are updated annually; as of October 2015, the latest data are from ACS 2013; the ACS 2014 data become available December 2015. The ACS 2013 5 year estimates are top-coded at $1,000,001 for MHV and $250,001 for $MHI.


  — view created using CV XE GIS and associated GIS Project

The block group containing Chelsea Park has a median household income of $26,440; the median housing value estimate is not available (too few owner-occupied units to develop MHV estimate). The Chelsea Park block group code is “360610097002” — this code uniquely identifies this block group among all other block groups in the U.S.

The block group immediately to the south of the Chelsea Park block group median household income of $21,750; the median housing value estimate is $1,000,001 (top-coded). The code for this block group code is “360610093006”.

While the MHI for BG 360610093006 might seem like it should be higher, a look at the number of households by income interval explains this number. Almost half of the households in the BG have a household income below $20,000. Analytical options that might be considered include using mean household income or mean family income instead of median.

Compare number of households by household income intervals for these two block groups.

Compare Your Block Group of Interest to Chelsea Park BG
Compare the above BG attributes to any BG of interest:
1. Copy and paste this string into text editor (eg, Notepad) window (do not press enter after paste):
http://factfinder.census.gov/bkmk/table/1.0/en/ACS/13_5YR/B19001/1500000USXXXXXXXXXXX|1500000US360610097002

2. Click here, key in an address then click Find to locate the 11 character BG code.
— scroll down to “2010 Census Blocks” and then further to “GEOID”
— copy the first 11 digits of the GEOID value to clipboard see illustrative graphic.

3. Paste those 11 characters into the URL, replacing the “XXXXXXXXXXXX”; this modification must be exact.

4. Press Enter. A profile appears comparing your BG to the Chelsea Park BG 360610097002.

Data Analytics Lab Session
Join me in a Data Analytics Lab session. There is no fee. Discuss how tools and methods reviewed in this section can be applied 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.

Business Data Analytics: Methods & Tools

Business Data Analytics can help most any business more effectively reach goals and objectives. Whether a new or established business, serving a county or national market, similar tools and methods apply. See related Web version for more details.

• How can you examine patterns/characteristics of existing customers?
• Where are prospective customers and possible unknown opportunities?
• How do you best define your market area?
  – what geographies have the largest number of prospects?
• What are the sales potential in this market area?
  – what are the best measures to examine sales potential?
• What is your competitive position?
  – how many other establishments offer a similar service in your market area?
• How can your sales data identify geographic areas of opportunity?

Tools and methods described here can help answer these questions and facilitate strategic planning. Here are key steps to using Business Data Analytics in your business. These applications make use of a GIS project and data for a business located in the San Diego area. Click link to view graphics.
Business locations
Territories served
Market characteristics
Urban population by block; population by tract
Customer locations
Prospect locations
Competitor locations
Composite of above
Related topics

Locations [goto top]
Where are the business locations/stores/operations
Blue triangle markers show existing locations. Are these the ideal locations?

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Territories Served [goto top]
What territories do locations serve? Are they developed correctly?
Territories for service/market areas are shown as color-shaded areas.
— flexibly re-define territories

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Market Characteristics [goto top]
What are the market characteristics?
Graphic shows patterns of median household income (MHI) by census tract;
— identifying areas with best opportunity
— examine wide-ranging demographic-economic characteristics
— market area tracts shown with cross-hatch pattern
— MHI intervsls/color correspondence shown in legend at left of map
— ranges can be customized/shifted to suit

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Urban Population by Block; Population by Tract [goto top]
Urban census blocks are shown with an orange fill pattern.
– examine scope of urban areas and how they relate to business development.
Census tract population is shown as a label for all tracts.
– identify population concentrations/attributes for small areas.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Customers [goto top]
Red markers show existing customers.
— linked to customer/product database

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Prospects [goto top]
Orange and green markers show prospects based on different sources/criteria.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Competitors [goto top]
What is the competitive position/where are competitors located?
Red triangle markers show where competitors are located.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Composite View [goto top]
Integrating business operating environment.
Graphic shows zoom-in to Encinatas location with all features shown separately in above views.
Roads/streets have been added; optionally use for routing and locational analysis.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Related Topics for Extended Analysis [goto top]
These extended topics make use of the data and analyses reviewed above. These topics will be covered in subsequent sections.

• Determining performance relative to the market characteristics
• Assessing impact of external and internal factors affecting operations
  – supply chain, labor force, costs, demand …
• Examining financial situation and outlook?
• Determining areas of missed opportunity
  – metros, hot spots within metros (tracts)
• Using collective data in models for predictive analyses
  – how might things change, when where and how?
• How to interpret statistical releases
  – determining which relevant, assessing implications for impact
• How to most effectively make team/collaborative/management decisions

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.

New York City: Census Block Demographics

.. census blocks are the smallest geographic areas for which decennial census data (and data from any Federal statistical program) are tabulated. Census blocks are geographically defined by the Census Bureau in coordination with local agencies. For Census 2010, there were a total of 11,078,297 census blocks covering the U.S. wall-to-wall. 541,776 of these blocks are water blocks, mainly located in coastal areas. Approximately one-third of all census blocks have zero population. See more about accessing and using census block demographics in this related Web section

Related New York City posts:
Manhattan Financial Sector Earnings – monthly/quarterly attributes
    .. examine establishment characteristics by type of business
        for any New York City borough or the metro
NYC Chelsea area and demographic analysis
Patterns of Block Group Income Inequality
    .. illustrative applications in Pelham, NY vicinity; north of NYC & NYC overall

Census block data are important to demographic/market analysis in part due to the data being counts of population and housing units rather than estimates (subject to errors of estimation). Block data are also important due to their geographic granularity, very detailed geography. Block data provide a good way to aggregate small area demographics into territories, markets and service areas using GIS tools. We have not only demographic data for blocks but also their geographic attributes: location/boundary and area. Make maps and perform geospatial analysis using census block shapefiles. Use census block geography with non-census data for wide-ranging analyses.

Largest Population New York City (NYC) Census Blocks
The following graphic shows the NYC Census 2010 census block having the largest Census 2010 population that is not a group quarters population block.
The Lincoln Center census block shown in the graphic (red boundary) has 4,067 population and 2,922 housing units.

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

This block (36 061 015500 6000) occupies 0.033 square miles. It has a population density of 122,333 (population per square mile).

The NYC block with the largest population is on Rikers Island and has a group quarters population of 8,634 and 0 housing units.

For Census 2010, there were 350,169 census blocks covering the state of New York; 13,356 census blocks were water blocks. For the State of New York, as of Census 2010 the average census block population was 55 (57 excluding water blocks).

More about census blocks. In built-up urban areas, a census block often shares a boundary with a conventional 4-sided city block. Census blocks are normally bounded by roads and in some cases other types of physical boundaries. For Census 2010, each census block is coded as urban or rural; this is the basis for defining urban or rural population and geographies such as urbanized areas. See urban population and urban/rural ZIP Codes. Census block geography nest within block groups and census tracts.

Upcoming sections will focus on accessing, integrating and using New York City block group and census tract demographic-economic data. Unlike census blocks, annually updated demographic-economic data are available for block groups and census tracts from the American Community Survey.

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.

Voting District Geography & Demographics

.. voting district, or election precinct, demographics are typically hard to acquire, making analysis of voting districts a challenging task. Voting district analysis is of interest for many reasons. Voting districts are the lowest common denominator for most election areas — from city council to the U.S. House of Representatives. This section illustrates how voting district (VTD) geography can be examined in context of other geography and how voting district demographics can be analyzed using GIS resources. These applications make use of Fairfax County, VA,
part of the Washington, DC metro, but can be developed for most counties/areas across the U.S.

Voting Districts & Neighborhood Patterns
The following view uses the Fairfax County GIS project to examine voting districts (black boundaries) in context of neighborhood economic prosperity. The current vintage VTD shapefile (213 VTDs) was obtained from the County. This view shows median household income by census tract. Using the GIS layer editor, different types of demographic-economic subject matter (such as educational attainment, housing value, language spoken at home …) could be used.

… Click graphic for larger view. View developed using CV XE GIS.

Voting District Scope and Vintages
As of Census 2010, there were 177,808 VTDs covering the U.S. While shapefiles for Census 2010 vintage VTDs are available as a part of the TIGER geographic database, most of these areas have now been updated owing to redistricting and the 2012 and 2014 elections. VTD boundaries can change frequently. While Census 2010 demographic data were tabulated for Census 2010 VTDs, these demographics of less interest to analyzing post-redistricting scenarios due to the changing VTD geography.

Voting District Drill-down Demographics
The following view uses the same Fairfax County GIS project to examine census block demographics by voting district. The graphic shows a zoom-in view focused on the Sherwood VTD in southeast Fairfax County. Using the CV XE GIS site analysis tool, all census blocks are selected within the Sherwood VTD (cross-hatched). A subset of blocks could have been selected to examine just part of the VTD. The table to the right of the map shows the aggregated total population and housing units for this VTD. As of Census 2010 there were 1,380 population in this VTD. Other demographic attributes, such as population by age, gender, or race/origin could be integrated into the shapefile using data sourced from Census 2010 Summary File 1.

… Click graphic for larger view. View developed using CV XE GIS.

There are 27 census blocks that comprise the Sherwood VTD. Using the View File button in the above operation, these 27 census block records can be viewed using the CV XE GIS dBrowser tool. A partial view of the records is shown below. This file can be exported for use with other software.

… Click graphic for larger view. View developed using CV XE GIS.

VTDs and Schools & School Attendance Zones
Using the GIS project, the attendance zone and schools layers can be checked/shown. School locations can be examined by VTD; VTDs intersecting attendance zones can be examined. What VTDs are relevant to which schools/attendance zones?  What is the demographic composition of these VTDs?  The following view shows high schools (red markers) and high school attendance zones (red boundaries).  Note in the legend to the left of map view, that different types of schools and attendance zones can be viewed in wide-ranging combinations. Other types of geography can be added to the mix such as voting districts.  The VTD/precincts layer is not shown in the following view so that the view of schools and attendance zones is not obstructed.  It can be added to the view by clicking the checkbox by the Precincts layer in the legend panel to the left of the map view.

… Click graphic for larger view. View developed using CV XE GIS.

VTDs and One Person, One Vote
In May 2015, the Supreme Court agreed to consider redefining ‘one-person, one-vote’ principle. See USATODAY story. How might this ruling impact election precinct geography?

Issues to be examined in upcoming sections include determining the size of the voting age population by VTD and the size of the citizen voting age population. These attributes could be examined at the block group level of geography, not reviewed here. See additional information on the citizen voting age population.

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.