American Community Survey 2018: Geography & Access

.. there are 519 core-Based Statistical Areas (metros & micros) included as American Community Survey (ACS) 2018 tabulation areas. 2018 demographic-economic estimates are included for these and many other types of political/statistical areas — the subject of this section. This is the first in a series of posts about accessing, integrating and using the ACS 2018 data. Learn more about effective ways to use these and related data. See the main web section for more detail and access to the interactive table. The release date for the ACS 2018 data is September 26, 2019.

ACS 2018 1-year Tabulation Areas: 519 Core-Based Statistical Areas
— MSAs and MISAs

– view developed using ProximityOne CV XE GIS and related GIS project.
– geospatial analyze ACS 2018 1 year estimates integrated with your data to examine patterns; gain insights.

The 2018 American Community Survey (ACS 2018 main) is a nationwide survey designed to provide annually updated demographic-economic data for national and sub-national geography. ACS provides a wide range of important data about people and housing for every community across the nation. The results are used by everyone from planners to retailers to homebuilders and issue stakeholders like you. ACS is a primary source of local data for most of the 40 topics it covers, such as income, education, occupation, language and housing.

Determining What Data are Tabulated
The graphics below illustrate 1) the scroll section that lists the types of tabulation areas (summary levels) and 2) use of the interactive table to display a selection of CBSAs/metros (summary level 310).

ACS 2018 1-Year Summary Levels
The scroll section (see in web page) shows the summary level code (left column), part or component if applicable and summary level name.

ACS 2018 1-Year Estimates — Areas Published — Interactive Table
The interactive table (click link to view actual interactive table) enables you to list the geographic areas tabulated. This graphic shows CBSAs (MSAs and MISAs) tabulated. GeoID1 shows the unique tabulation area geocode for an area among all areas. GeoID1 inlcudes the summary level (first 3 characters), followed by state FIPS code where applicable, ‘US’ and finally the geocode for the specific area.

Demographic-Economic 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.

Housing Price Index 2017Q3-2018Q3

.. this past week the 3rd quarter 2018 (2018Q3) Housing Price Index (HPI) was released for the U.S., states and metros. As a leading economic indicator, the HPI often gives insights into how the housing market and economy might be changing in the months ahead. The fact that the HPI data are quarterly and become available with a short lag time makes the measure even more valuable. This section provides an update on the HPI 2018Q3 and quarterly data for the past year. See the related Web page for more detailed data and access to the HPI data via interactive table.

Visual Analysis of 2017Q3-2018Q3 HPI Patterns
The following graphic shows housing value appreciation 2017Q3-2018Q3 by metro based on the HPI.

Click graphic for larger view and details. This view developed using CV XE GIS and related GIS project. Members of the ProximityOne User Group (join now, no fee) may used the CV XE GIS software and GIS project to create similar views with different HPI measures. Zoom-in. Add labels. Add other geography/data. Create views/graphics for reports and stories.

The Larger Picture
The HPI is calculated using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. By itself, the HPI provides limited insights into the broader picture of “the why” and “how otherwise” states and metros are changing. The Situation & Outlook Metro Profiles provide an integrated view of the HPI measure in combination with other economic, demographic and business activity measure. View the HPI integrated with other subject matter … choose a metro. Metro Profiles are updated continuously and are available for each of the metropolitan area.

HPI Interactive Table
Use the HPI interactive table to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all Metropolitan Statistical Areas (MSAs), states and the U.S. The graphic shown below illustrates use of the interactive table to rank all metros in descending order on the percent change over the past year.

Updates & Related Measures
Quarterly HPI measures are used to updated the interactive table, GIS project and Metro Profiles. HPI by county, ZIP Code and census tract are updated annually. The 2018 county, ZIP Code and census tract HPI data are scheduled for release in February 2019.

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

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

How the New York Metro is Changing

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

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

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

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

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

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

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

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

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

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

Insights into County/Metro Business Establishment Patterns

.. new data, released this past week, enable us to better assess county and metro business establishment patterns .. these data help businesses understand how sales of their products and services align with markets .. what counties might be underserved? .. where should marketing and sales operations be ramped up or reduced in scope/reallocated? .. what do these tell us us about organization of market territories? how are these characteristics trending by county? Use the this interactive table to examine business establishments characteristics by county and metro by type of business. See more detail in the related Web section about topics covered in this post. 

• U.S. establishments rose 1.2% from 7,663,938 in 2015 to 7,759,807 in 2016.
• First quarter employment was up 2.1% from 124,085,947 to 126,752,238
• Annual payroll was up 2.9% from $6.3 trillion in 2015 to $6.4 trillion in 2016.

Based on the 2016 data (new April 2018), there are 7.3 million establishments in Metropolitan Statistical Areas (MSAs). In these MSAs ..
• 5.3 million establishments have fewer than 10 employees.
• 6,522 of these establishments have 1,000 or more employees.
• 374 of these establishments have 5,000 or more employees.

MSAs by Number of Establishments with 1,000 or more Employees
The following graphic shows Metropolitan Statistical Areas (MSAs) by number of establishments with 1,000 or more employees. Click graphic for larger view view showing metros labeled with number of these establishments. Expand brower to full window for best quality view.
.. View developed with CV XE GIS software and related GIS project.

Business Establishment Characteristics Updated in Metro Reports
Examine 2014, 2015, 2016 mini trend profiles for establishments by 2-digit sector in Metro Situation & Outlook Reports Choose any MSA by clicking column 3 in this table .. then view section 6.3. Examples:
New York .. Los Angeles .. Miami .. Chicago .. Dallas .. Houston .. Denver .. Seattle

Gaining Insights
Gain insights into these types of patterns by county by detailed type of business (NAICS). Use the interactive table below to examine business establishment characteristics for counties and metros of interest. Data reviewed in this section are based on the Census-sourced County Business Patterns released in April 2018. We have integrated current population estimates with the establishment data in the interactive table.

Tools You Can Use
• create maps and geospatially analyze business establishments at 6-digit industry detail with ready-to-use GIS project/tools .. see related section for details.
• Use the APIGateway tools to build custom business establishment datasets.
• Use the interactive table to query/view sort business establishment characteristics by county and metro.

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.

Metro 2016 Demographic-Economic Data Analytics: Social Characteristics

.. part one of four parts focused Metro 2016 Demographic-Economic Data Analytics.  This post is on Social Characteristics; ahead: general demographics, economic characteristics and housing characteristics. See related Web section.

Patterns of Educational Attainment by Metro
The following graphic shows patterns of educational attainment (percent college graduate) by Metropolitan Statistical Area (MSA). Legend shows color patterns associated with percent college graduate values.

– View developed using CV XE GIS software and associated GIS project.
– use these resources to develop similar views for any area.
– modify subjects, zoom, colors, labels, add your data.

A Selected Social Characteristic & How Metros Vary
In 2016, the U.S. percent college graduates was 31.3 percent (of the population ages 25 and over) while Metropolitan Statistical Areas (MSAs) ranged from 11.3% (Lake Havasu City-Kingman, AZ MSA) to 60.6% (Boulder, CO MSA). See item/column S067 in the interactive table to view, rank, compare, analyze metros based on this measure for 2016 … in context of related social characteristics. These data uniquely provide insights into many of the most important social characteristics.

Social Characteristics – Subject Matter Covered
– Households by Type
– Relationship
– Marital Status
– Fertility
– Grandparents
– School Enrollment
– Educational Attainment
– Veteran Status
– Disability Status
– Mobility; Residence 1 Year Ago
– Place of Birth
– Citizenship Status
– Year of Entry
– Region of Birth
– Language Spoken at Home
– Ancestry
– Computers & Internet Use

Metro Data Analytics
Use tools, resources and methods to access, integrate and analyze social characteristics for metropolitan areas or Core-Based Statistical Areas (CBSAs). The table includes data for 382 Metropolitan Statistical Areas (MSAs) and 129 Micropolitan Statistical Areas (MISAs). These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics — reviewed here
• Economic Characteristics
• Housing Characteristics
See related Metro Areas Population & Components of Change time series data.

Focusing on Specific Metros & Integrated Multi-sourced Data
While these data provide a good cross section of data on social characteristics, this access structure is a) for one time period and b) data sourced from one statistical program. Also, there is a lot going on in metros; these are typically large areas with many important and diverse smaller geographies such as cities, counties and neighborhoods among other others.

Use the Metropolitan Situation & Outlook (S&O) reports to develop extended insights. See this example of the Washington, DC MSA S&O Report. Examine trends and projections to 2030. Inegrate your own data.

Using the Interactive Table
The following example illustrates use of the metro social characteristics interactive table … try using it on areas of interest. This view, showing metros partly or entirely in Arizona, was first developed by using the state selection tool below the table Next the selected columns button the table is used to examine educational attainment columns/items. The final step was to click the header cell on the “S067” item to sort metros on percent college graduates. It is easy to determine that the Flagstaff metro has the highest percent college graduates (home to Northern Arizona University).

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.

Metro Population & Components of Change Trends 2010-2016

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

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

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

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

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

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

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

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

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

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

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

Click graphic for larger view.

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

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

Examining 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.

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using 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.

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.

Census 2020 LUCA Program and You

.. what would be the financial impact of a one-percent understatement in the Census 2020 population count? Many political districts are drawn based upon population change and shifts, and allocations of government funding and services are made based upon official population data. Consider this one specific example. For each one-percent of the Atlanta MSA population missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be on the order of $414 million per year. How and why? At margin, each person not counted in the decennial census results in a per capita disposable income loss for the area in the magnitude of $5,494 in 2000, and $6,770 per person in 2020. 61,100 people undercounted times $6,770 yields $414 million.

This section is about the Censue 2020 Local Update of Census Addresses (LUCA) program and how it might impact the reduction in undercount .. and make the data more accurate for wide-ranging needs and uses. Read on for details about the LUCA program.

Atlanta-Sandy Springs-Roswell, GA MSA
The Atlanta metro shown with black bold boundary. More about this metro.

– View developed with CV XE GIS software.
– Click graphic to view patterns of neighborhood economic prosperity.

Financial Impact Details … the 2015 per capita current transfer payments (PCTP) in the Atlanta-Sandy Springs-Marietta MSA were $6,132, up from $5,494 in 2010. The PCTP figure in 2020 may be $6,770. For each one-percent of the Atlanta MSA population (61,100 people) missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be in the order of $414 million (61,100 x $6,770) per year as of Census 2020.  $414 million per year based on the 2020 population and PCTP.

Financial Impact in Your Areas of Interest
Estimate the financial impact in your areas of interest. Get the 2010 and 2015 population and PCTP data from the REIS Interactive Table for any county or state.  Compute the 2020 population and PCTP values, potential undercount to determine the financial impact on an area of interest

Census 2020 LUCA Overview
The Census 2020 LUCA program is an initiative of the Census Bureau, partnering with thousands of state and local governments across the U.S. At the core of this program, Census provides address list data to communities; those communities compare those data with their own data and provide address/geographic updates back to the Census Bureau.  The updated address and geographic data are integrated into the TIGER/Line files  — geographic backbone for collecting and tabulating the Census results. This important MAF/TIGER address-plus update program will help insure improved accuracy for Census 2020. LUCA is a geographic data development program engaging local communities across the U.S.

ProximityOne works with local areas to improve the TIGER/Line files leading up to Census 2020. Using the CV XE GIS software and specialized expertise, we helped hundreds of governmental units, including all of the State of Georgia, improve the coverage and content of the TIGER/Line files and thus the accuracy and completeness of Census 2010.

The Census 2020 LUCA program is starting now in 2016.  See the full schedule and related details in the LUCA 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.