Tag Archives: decision-making

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.

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.