Monthly Archives: February 2015

Guide to ZIP Code Data Resources

.. what are the options to access and use ZIP Code area geographic, demographic and economic data? This section provides an overview of selected options available to access ZIP code area data from Census 2010, American Community Survey and 5-year current estimates and projections. A ZIP Code Area (ZCA) is a set of generally contiguous of Census 2010 census blocks that approximates the corresponding U.S. Postal Service (USPS) ZIP code delivery area. The USPS does not define ZIP code delivery areas as polygons; rather they are a collection of lines/streets and roads. See the related section about ZIP Code area data access options. See corresponding Web page for more details on topics covered here.

In this section:
1. Geography
2. Census 2010 Demographics
3. American Community Survey 2011 Demographic-Economic Data
4. American Community Survey 2012 Demographic-Economic Data
5. American Community Survey 2013 Demographic-Economic Data
6. Current Estimates & Projections
American Community Survey 2014 estimates to be released in December 2015.

1. Geography
Data for ZIP code areas (ZCAs) described below are for ZIP code areas defined as of Census 2010. In general, the boundaries have not been changed since that time. In contrast, some USPS ZIP codes have been added/modified since Census 2010. Census 2010 ZCAs do not cover the U.S.wall-to-wall as the result of some geographies not being populated. However, in most urbanized areas Census 2010 ZIP code areas closely approximate USPS ZIP code delivery areas as of 2010. The USPS does not provide boundaries for USPS ZIP code areas. There are approximately 33,120 Census 2010 ZIP Code areas.

1.1. Equivalence Files. ZCA component census blocks may be determined by using the Census 2010 Summary File 12010SF1 geographic header record. Block level records in that file contain both the block geocode and the ZCA code.

How do ZCAs intersect with other geography? What part of a ZCA is in what county? ZCA-to-other geography equivalence files may also be developed using the 2010SF1 geographic header record. Equivalence files available include (links open a new page):
ZCA to County
ZCA to City/Place
ZCA to MCD/Town/County Subdivision
ZCA to School District
ZCA to Census Tract
ZCA to 111th/112th/113th/114th Congressional District
ZCA to Metropolitan and Micropolitan Statistical Areas

1.2. Shapefiles: Mapping ZIP Code Areas. Create ZCA reference and/or thematic pattern maps using the CV XE GISand ZCA shapefiles. Members of the ProximityOne User Group may use the GeoGateway feature to download ZCA boundary files and add the ZCA boundary shapefile as a layer in a GIS project. The graphic below shows Texas ZIP Code areas (dark blue boundary) with a zoom-in to Harris County (bold black boundary)/Houston area. The view was created from scratch in minutes using the CV XE GIS GeoGateway tool.

Click graphic for larger view showing ZIP codes as labels. View developed with CV XE GIS.

2. Census 2010 Demographics
Census 2010 demographics are available for ZIP code areas. There are no “richer demographics” (such as educational attainment, income, employment, language spoken, enrollment, housing value etc.) available for any type of tabulation area — owing to the fact that those questions were not on the questionnaire.

2.1. Demographic Profile Summary File. A recommended collection of Census 2010 data for ZIP code areas is available from the “Demographic Profile Summary File.” See more about theDPSF structure and content. See corresponding Web page to acquire this dataset.

2.2. Census 2010 More Detailed Subject Matter. More detailed Census 2010 ZCA data are available from the Census 2010 Summary File 1 and the Census 2010 Summary File 2. The more detailed Census 2010 data may be viewed/downloaded using the Census Bureau FactFinder or Census API or using custom extracts developed by ProximityOne.

3. 2011 ACS Demographic-Economic Data
2011 American Community Survey 5-year demographic-economic estimates (ACS0711) for Census 2010 ZCAs were released in December 2012. These estimates are centric to mid 2009.

3.1. 2011 ACS Interactive Tables. View, rank, sort, query 2012 ACS ZIP Code area data via interactive table (links open a new page):
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

3.2. Augmented 2011 ACS Interactive Tables. Extract ZCA data from 2011 ACS interactive tables to Excel.
Members of the ProximityOne User Group may access the following similarly structured table and extract data for ZCAs and save in text files or Excel files — requires UserID; links open a new page:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

The only difference between the above sets of Web sections is the data extraction feature.

3.3. 2011 ACS Demographic-Economic Profile Datasets. The same subject matter data shown in the interactive tables area available in the form of datasets. There are four datasets corresponding to the content and data organization shown in the tables. See corresponding Web page to acquire these datasets.

3.4. 2011 ACS More Detailed Subject Matter. More detailed 2011 ACS data may be viewed/downloaded using the Census Bureau FactFinder or Census API or custom extracts developed by ProximityOne.

4. 2012 American Community Survey Demographic-Economic Data
2012 American Community Survey 5-year demographic-economic estimates (ACS0812) for Census 2010 ZCAs were released in December 2013. These estimates are centric to mid 2010.

4.1. 2012 ACS Interactive Tables. View, rank, sort, query 2012 ACS ZIP Code area data via interactive table (links open a new page):
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

4.2. 2012 ACS Demographic-Economic Profile Datasets. The same subject matter data shown in the interactive tables area available in the form of datasets. There are four datasets corresponding to the content and organization shown in the tables. See corresponding Web page to acquire these datasets.

4.3. 2012 ACS More Detailed Subject Matter. More detailed 2012 ACS data may be viewed/downloaded using the Census Bureau FactFinder or Census API or custom extracts developed by ProximityOne.

5. 2013 American Community Survey Demographic-Economic Data
2013 American Community Survey 5-year demographic-economic estimates (ACS0913) for Census 2010 ZCAs were released in December 2014. These estimates are centric to mid 2011.

5.1. 2013 ACS Demographic-Economic Profile Datasets. The same subject matter data shown in the interactive tables area available in the form of datasets. There are four datasets corresponding to the content and organization shown in the above ACS 2012 tables. See corresponding Web page to acquire these datasets.

5.2. 2013 ACS More Detailed Subject Matter. More detailsd 2013 ACS data may be viewed/downloaded using the Census Bureau FactFinder or Census API or custom extracts developed by ProximityOne.

6. ZIP Code 5-Year Demographic-Economic Estimates & Projections
ProximityOne develops annually updated demographic-economic estimates and projections for ZIP Code areas. See more about the ZIP Code 5-Year Annual Estimates & Projections.

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.

Evolution of Census Tracts: 1970-2010

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

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

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

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

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

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

  View developed with CV XE GIS.

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

  View developed with CV XE GIS.

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

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

  View developed with CV XE GIS.

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

  View developed with CV XE GIS.

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


  View developed with CV XE GIS.

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

  View developed with CV XE GIS.

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

  View developed with CV XE GIS.

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

The following graphic shows the relationship between these tracts.

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

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

Census Tract Demographics by ZIP Code

.. analyzing census tract demographics by ZIP code … a wide range of demographic-economic data for census tracts and ZIP code areas are now developed annually as a part of the American Community Survey (ACS). Census tract and ZIP code area demographics are popular for examining characteristics of sub-county areas. This section reviews use of resources to analyze census tract demographics in context of ZIP code areas. For many analytical and decision-making applications these methods might be preferred to analyzing ZIP code area demographics alone. See related Web section for more detail on topics covered here.

Census tracts provide a more granular geography than ZIP code areas, have well known boundaries, have little change over the decade and provide a more uniform population size, averaging 4,000 population. Census tracts are more suitable for demographic analysis as compared to ZIP code areas. Yet, users of these data seek to understand patterns by ZIP code areas. This section reviews how that can be done. The applications make use of census tract demographics based on the ACS 2013 5-year estimates.

Geographic Information System (GIS) resources are used here. The census tract to ZIP code area relationship can also be be shown in an equivalence table. See the census tract to ZIP Code area interactive equivalence table. While the equivalence table is very useful, use of GIS tools offer a much more powerful method of understanding demographic-economic relationships. These applications are focused on the Chicago area, but the same set of resources can be used anywhere in the U.S.

Patterns of Economic Prosperity by Census Tract
The graphic presented below shows patterns of the economic prosperity (median household income/MHI) by census tract in the Chicago area. MHI intervals and corresponding colors are shown in the legend at the left of the map. It is easy to see where concentrations of high and low MHI exist by census tract.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using TractZIP GIS Project.

Relating ZIP Codes to Census Tracts
The graphic presented below shows a view similar to the map shown above. In this view ZIP code areas have been added. ZIP code areas are shown by black boundaries and labeled with the ZIP Code. As above, it is easy to see where concentrations of high and low MHI exist by census tract are located and now — how the distribution relates to ZIP code areas. Click graphic for larger view that shows ZIP codes as labels.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using TractZIP GIS Project.

Neighborhood Drill-Down
The graphic presented below shows a zoom-in view in the vicinity of the pointer in the map shown above. ZIP code areas have a bolder black boundary and ZIP codes are shown as labels. K-12 school locations have been added, illustrating how yet other area characteristics can be integrated. The tracts thematic pattern layer is shown with see-through transparency enabling a background view of highways and related earth surface geography.

Relating Tract Codes/Areas to ZIP Codes/ZIP Code Areas
The graphic presented below shows a zoom-in view of ZIP code view similar to the map shown above. In this view the focus is placed on ZIP code area 60622 — it could be any ZIP code. This view shows the ZIP code with white label and census tracts with yellow labels. It is easy to see which census tracts intersect with ZIP code 60622, which tracts are wholly versus partly included in the ZIP code area and the MHI for each tract intersecting ZIP code 60622.

Analyzing Areas of Interest — Using the GIS Resources
Install the GIS software and project used to develop map views presented above for areas of interest. Add other types of geography such as geocoded address data. Select alternative demographic-economic measures. Create custom map graphics. See the main Web section for details.

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.

Financial Institutions & Neighborhood Characteristics

Examining patterns of financial institutions, neighborhoods and geographic-demographic-economic relationships … this section is one of several related sections focused on data and resources useful to analyze America’s banks and savings institutions. This section is focused on use of Geographic Information System (GIS) tools to examine the nation’s 96,000 FDIC-insured institutions/branch offices in context of neighborhoods and economic prosperity. This is not intended as a study to draw conclusions, but rather to illustrate how these data and tools can be used to perform more detailed analyses for any metro, county or city in the U.S. See related more detailed Web section.

This section illustrates use of FDIC Deposit Market Share (DMS) data by institution. Subsequent sections will integrate other related data into the GIS applications including the FFIEC “Census 2014/2015” dataset (data by state, metro, county and census tract).

Deposit Market Share
The Deposit Market Share (DMS) is the percentage of deposits an FDIC-insuredinstitution has within a defined geographic market. We use these data in GIS applications reviewed below. See the example of the DMS Report in the related Web section. These data are based on the annual Summary of Deposits survey of FDIC-insured institutions. The DMS data provide information for each/all FDIC-insured institutions by address and a range of related attributes. Market presence and growth rate analyses can be examined annually by institution or bank holding company.

The 2014 annual DMS address-based data were geocoded and converted into a shapefile for GIS analysis. The DMS shapefile was integrated into a GIS project. The GIS project also includes a U.S. national scope census tracts shapefile with demographic-economic data from the 2013 American Community Survey 5-year estimates (ACS2013). GIS tools can be used to examine a single institution, institutions within a geographic area or aggregated within a geographic area. Optionally examine these institutional locations in context with patterns of neighborhood or regional economic prosperity (or choose many other types of subject matter).

Branch Locations by Size; Houston, Texas
The map presented below shows banks as markers in the Houston, TX area. Harris County appears with bold blank boundary. Bank markers shown by 2014 deposit size class. See size class/color patterns in legend at left of map.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using Banks2015 GIS Project.

Branch Locations in Context of Neighborhood Economic Prosperity
Similar to the map above, the map below shows banks as markers in the Houston, TX area. Patterns of economic prosperity (based on median household income – MHI) are shown by census tract/neighborhood. See MHI intervals/color patterns in legend at left of map. It is easy to see where concentrations of banks in more affluent neighborhoods.

Click graphic for larger view; view developed with CV XE GIS.

Selecting Specific Institutions — using site analysis tool
The map presented below shows financial institution locations as markers with a zoom-in to neighborhood level. The site analysis tool is used to select a set of institution locations within a census tract (red boundary, yellow label) — tract code 4115.01 or 411501, located in Harris County, TX. See more about census tracts. Eight locations are selected (hatched markers) using the circle selection method (any location intersecting with circle is selected). Alternatively select only one institution, visually cherry-pick certain institutions or apply a select-from-list query. One variable is summarized, sum of deposits 2014 ($2.2 billion for sum of these 8 locations).

Click graphic for larger view; view developed with CV XE GIS.

Tabular View of Selected Institutions
The view presented below shows the data grid populated with attributes of the eight selected locations (see above). This view is displayed by using the View File button — see at right of map view in above graphic. The table/grid shows the institution/branch name, sum of deposits for that location, and other attributes. Optionally save this selection of locations an a dbase/CSV/Excel/text file for further analysis.

Click graphic for larger view; view developed with CV XE GIS.

Deposit Market Share Report
The view presented below shows the Deposit Market Share Report for ZIP code 77027. This report is for the ZIP code area that includes the selected locations shown above. See the full interactive DMS report.

Click graphic for larger view.

Top 50 Commercial Banks & Savings Institutions Interactive Table
The following graphic shows the largest Commercial Banks & Savings Institutions among all FDIC-Insured Institutions based domestic deposits as of June 30, 2014. See full interactive table.

Click graphic for larger view.

Upcoming Blog Posts on Related Topics
Upcoming blog topics will include using the following data resources integrated into the GIS and related applications focused on financial institution and market research and analysis.
  • FFIEC tract level estimates (2010, 2013, 2014)
  • FFIEC 2015 tract estimates (not yet released)
  • ProximityOne tract demographic-economic estimates (2015) and projections (2020).
  • FFIEC “Census2014” dataset, containing 1,200+ subject matter items
  • Quarterly CEW county time series data on financial services sector establishments.
  • Other FDIC institutional characteristics by address/location.

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 is developer of the CV XE GIS software used to develop the GIS project and views shown in this section. 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.

Voting Rights Act Demographics

Examining patterns of the citizen voting age population … the Voting Rights Act prohibits development of voting districts that discriminate against potential voters on the basis of race and/or language minority status. To examine how voting districts comply with the Voting Rights Act requires data on the citizen voting age population (CVAP) by race/origin for small geographic areas. The ACS 2013 5-yearCVAP special tabulation (released February 2015) provides these estimates for census tracts and block groups (and higher level geography). See the related Web section for more detail.

The CVAP estimates provide only one part of the required data. The voting district boundaries and census block boundaries/demographics are also needed to be used in combination with the CVAP estimates. Using GIS tools, the CVAP estimates can be used in mapping applications, such as those reviewed in this section, in combination with voting district boundaries to reveal potential non-compliance in the structure of voting districts.

Use this interactive table in this section to view/rank/compare/query national scope citizen and CVAP estimates by race/ethnicity by census tract. See more about the ACS CVAP data.

Patterns of CVAP Hispanic Population by Neighborhood
The map presented below shows patterns of the Hispanic citizen voting age population as a percent of total population by census tract in the Los Angeles area. Percentage intervals by green color pattern are shown in legend at left of map. Congressional Districts are shown with dark blue boundaries and labeled with congressional district codes. It is easy to see where concentrations of percent Hispanic citizen voting age population are located and how the distribution relates to congressional districts.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using CVAP2013 GIS Project.

Patterns of CVAP Asian Alone Population by Neighborhood
The map presented below shows patterns of the Asian alone citizen voting age population as a percent of total population by census tract in the Los Angeles area. Percentage intervals are shown by blue color patterns are shown in legend at left of map. Congressional Districts are shown with dark blue boundaries and labeled with congressional district codes. It is easy to see where concentrations of percent Asian alone citizen voting age population are located and how the distribution relates to congressional districts.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using CVAP2013 GIS Project.

Examining Relationships Among Key Geography and Demographics
An upcoming post will review use of GIS tools examine the relationship between 1) census tracts and the CVAP data, 2) voting districts and 3) census blocks and census block demographics in more detail. That section will review use of downloadable GIS tools and resources that can be used to examine these geographic-demographic relationships in more detail. Voting Rights Act (VRA) stakeholders can better see how to use these data and tools to achieve VRA goals.

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 is an expert in developing hard-to-estimate demographic estimates and projections. 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.

Future of Indonesia: Demographic Trends

Indonesia, the world’s fourth most populous country … the population of Indonesia is projected to change from 243.4 million in 2010 to 300.2 million in 2050. How will Indonesia age-cohort patterns in 2010 compare to those projected for 2050? How do these patterns compare with those of the United States?

This section illustrates use of population pyramids to examine age by gender demographic patterns for Indonesia as of 2010 and 2050. See related Web section. Similar population pyramids can be developed for any country. Population pyramids help us visualize and more easily understand age-gender structure — and how it is changing over time.

Indonesia — red hatch pattern
Indonesia
Click graphic for larger view; view developed with CV XE GIS.
Map view developed using World GIS Project.

Additional Views:
Jakarta region zoom-in showing provinces
Jakarta city zoom-in with urban area

Indonesia Demographic Dynamics
The age and gender structure of a population is one of its most important and formative features, because nearly all demographic characteristics and processes vary by age and gender. Age and gender composition is also revealing in that it reflects those demographic characteristics and processes. Population pyramid chart graphics can help us visualize and more easily understand age-gender structure — and how it is changing over time.

Population pyramids for 2010 and 2050 are shown below for Indonesia with associated popualtion by age-gender tabular data. Click graphic for larger view of supplemental Web page.

A top-heavy pyramid suggests negative population growth that might be due to many factors, including high death rates, low birthrates and increased emigration. A bottom-heavy pyramid suggests high birthrates, falling or stable death rates and potential for rapid population growth.

The population pyramid shows a male population bar chart (left side of pyramid, blue) symmetrically with a female population bar chart (right side of pyramid, light red). Each bar shows the population by 5-year age group, 0-4 years to 80-84 years and 85 years and over.

Indonesia, Total Population, 2010

Click graphic for larger view.

Indonesia, Total Population, 2050

Click graphic for larger view.

More About Indonesia Demographics; Examining Other Countries
Use the ChartGraphics tools to get answers to these types of questions and gain insights world by country age-cohort patterns over time … into the future. Population pyramids developed using ChartGraphics provide an easy-to-develop and consume visual analysis of these patterns.

ChartGraphics is available at no fee to ProximityOne User Group members. Join now, there is no fee.

About the Author
— Warren Glimpse, developer of the CV XE GIS and ChartGraphics software, is former senior Census Bureau statistician responsible for innovative data access and use operations. He is developer of the Columbia, MO GBF/DIME used as the prototype for the Census Bureau TIGER/Line system, the digital map database underlying wide-ranging Web-based mapping applications. 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.

Creating Thematic Pattern Maps

Decision-making can be influenced by a thematic pattern map that conveys a strong message. Thematic pattern maps can often transcend spoken language and facilitate communication on an issue. The speed at which humans consume and interpret visual information is far faster than possible with tabular data presentation. Our ability to recall a visual message/graphic exceeds that of recalling tabular data. See corresponding Web section.

An important feature of GIS tools is the ability to modify the appearance of a thematic pattern view. A thematic pattern view is a rendering of the data by colors and patterns to reflect different data values. The flexibility to perform these operations is often not available in Web-based mapping tools. Desktop GIS tools offer more control over using the data and performing geospatial analyses. The ability to change the pattern appearance may be desired to show different colors/patterns representing data values and/or change a data value range corresponding to a color/pattern.

This section builds on the U.S. by County & State Daytime Population GIS project (view that section) and illustrates steps that you can use to modify the appearance of the thematic pattern. The GIS project can be downloaded and used with GIS tools as described in that section.

Visual Analysis of County Employment-Residence Ratio Patterns
The following graphic shows patterns of the Employment-Residence (E-R) Ratio by county for the Atlanta area (Atlanta metro bold outline). See more about the E-R Raiot.

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

Modifed Pattern View
The next view shows patterns with a different range of values. See color pattern/data ranges in legend panel at left of map. Comparing the view below to the one above, the number of intervals has been reduced from five to three and interval values have been modified. We might want to make this change to have a view that shows more succinctly which counties have an E-R value greater than 1 versus less than 1. To account for counties that are close to the value of 1, a narrow mid-range section/interval is used. Is the view presented below “better” than the view shown above? The bold red and blue in the upper view are more dramatic. But the issue here is less on making the most impactful view and more on the mechanics of how to make changes to the pattern view. There are many factors that go into making the most impactful view, a topic for another time.

Using the Layer Editor to Modify Map Appearance/Pattern View
After installing the CV XE software and the GIS project, the Daytime/E-R Ration project is opened. Next, the CV XE Layer Editor is used to change the appearance of the county E-R layer. To start the Layer Editor, double-click the name “County E-R Ratio” in the legend panel at the left of map (see in view above). The Layer Editor form appears as shown below. Using the Layer Editor, the first step is to modify the Section settings. Two intervals are removed and the range values settings are changed as shown below.

Next, while still in the Layer Editor, click the Area tab to modify colors. The new colors will be a muted blue, lighter yellow and orange (choose any).

Next, in the new settings, the outlines (county polygon boundaries) are all set to black as shown below.

The final step is to click the OK button and the modified view is shown. This action closes the Layer Editor form and the map view is refreshed. See Modified Pattern View shown above. If this view is not as expected, similar steps can be repeated. Exiting CV XE at this point will not save the setting for a project that is subsequently re-started. In this example, the project might be saved with the name (File>Save Project As) “c:\daytime2013\daytime_pop_2013new.gis”. The view shown in the modified version above has been included in the project installer and is named “c:\daytime2013\daytime_pop_2013a.gis”.

Using the Modifed Pattern View
Use the Pan/Drag tool on the toolbar to drag the map view to the Houston area as shown below. In this example, the Metro layer was modified. The CBSAFP (Core-Based Statistical Area FIPS code) value was modified to CBSAFP=’26420′ … changing the code 12060 for the Atlanta metro to 26420 for the Houston metro A view can be created for any area .. one county, any region, a state or the U.S.

The same methods of modifying a view using the Layer Editor can be performed on any shapefile layer in any CV XE GIS project. A related section will illustrate how similar steps can be applied to develop a trend view of demographic change using this same project.

About the Author
— Warren Glimpse, developer of the CV XE GIS software, is former senior Census Bureau statistician responsible for innovative data access and use operations. He is developer of the Columbia, MO GBF/DIME used as the prototype for the Census Bureau TIGER/Line system. 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.