Category Archives: Geographic Information Systems

Location-Based Demographics Update

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

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

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

View the locations without the tract thematic pattern layer:

Make similar views for your addresses.

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

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

Data Analytics Web Sessions
Join me in a Data Analytics Web Session, every Tuesday, where we review access to and use of data, tools and methods relating to GeoStatistical Data Analytics Learning. We review current topical issues and data — and how you can access/use tools/data to meet your needs/interests.

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

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.

Communities of U.S. Foreign Born Population

.. examining the U.S. foreign born population and how/where foreign born by country of origin communities exist .. the U.S. foreign born population includes anyone who is not a U.S. citizen at birth, including those who have become U.S. citizens through naturalization. The native born population includes anyone who is a U.S. citizen at birth, including those who were born in the U.S., Puerto Rico, a U.S. Island Area or abroad to U.S. citizen parent(s). Use the interactive table to examine foreign born population by country by census tract.

As of 2016, the U.S. foreign born population was estimated to be 43,739,345 compared to the total U.S. population of 323,127,515 (13.5%). See the related Web section for more detailed information about the U.S. foreign born population.

Chinese Foreign Born Population & $MHI Patterns; New York City Area
– red markers show census tracts with 500 or more Chinese foreign born
– neighborhood level views provide insights into patterns of economic prosperity
– census tract thematic patterns of median household income

– view developed with CV XE GIS software using related GIS project and datasets.

Importance of the Foreign Born Data … knowing about the geographic, demographic and economic attributes of the foreign born population tells us about the size, distribution and characteristics of the immigrant population. Projections of the foreign born population tell us how our country will grow. See more in this related section.

An Illustrative View. The Chinese foreign born population is used in the graphic below to illustrate the distribution of U.S.national scope foreign born population. Other population groups could have been used. Based on the ACS 2016 5-year estimates, there are 851 census tracts having 500 or more Chinese foreign born population (of a total 73,056 tracts). Twenty of the 25 tracts having the largest number of Chinese foreign born population are located in New York City. Determine which tracts using the related interactive table.

Chinese Foreign Born Population Patterns
– China is one of 162 country/country groups reviewed in this section
– red markers show census tracts with 500 or more Chinese foreign born
– the distribution is wide and difficult to gain insights

– view developed with CV XE GIS software using related GIS project and datasets.

Communities of Foreign Born Population
These additional views illustrate how selected foreign born country population clusters in many cases. Some develop communities without formal boundaries or any formally designated structure. Use the GIS project and tools to develop your own views for country combinations and areas of interest.

India Foreign Born Population & $MHI Patterns; New York City Area
– red markers show census tracts with 500 or more India foreign born
– neighborhood level views provide insights into patterns of economic prosperity
– census tract thematic patterns of median household income

– view developed with CV XE GIS software using related GIS project and datasets.

Asia Foreign Born Population & $MHI Patterns; Houston, TX Area
– red markers show census tracts with 500 or more Asia foreign born
.. all Asia countries (item 047 in country list above in this section
– neighborhood level views provide insights into patterns of economic prosperity
– census tract thematic patterns of median household income

– view developed with CV XE GIS software using related GIS project and datasets.

Cuba Foreign Born Population & $MHI Patterns; Miami, FL Area
– red markers show census tracts with 500 or more Cuba foreign born
– neighborhood level views provide insights into patterns of economic prosperity
– census tract thematic patterns of median household income

– view developed with CV XE GIS software using related GIS project and datasets.

Vietnam Foreign Born Population & $MHI Patterns; Los Angeles, CA Area
– red markers show census tracts with 500 or more Vietnam foreign born
– neighborhood level views provide insights into patterns of economic prosperity
– census tract thematic patterns of median household income

– view developed with CV XE GIS software using related GIS project and datasets.

Using the Interactive Table
— Foreign Born Population by Country by Census Tract

The following graphic illustrates use of the interactive table to examine census tracts in Queens County, NY (code 36081, New York City). South East Asia countries (columns) have been selected and sorted in descending order on China. The table shows the size of the China foreign born population by census tract; the census tract code is shown in the left column.

Use the interactive table and examine areas of interest to you.

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.

 

Housing Price Index Updates & Trends

.. this past week we have updated Housing Price Index data and tools to examine patterns and trends for the U.S., states, metros and counties .. the Housing Price Index (HPI) is one of many measures useful to gain insights into the housing market. The HPI provides information on how housing value appreciation is changing for areas of interest. Use the interactive table to view, compare, sort metros/CBSAs based on annual HPI 2010-2017 and housing value appreciation during the period. These annual data, with a 2000 base index value of 100, provide insights into longer term patterns.  The HPI is alos updated quarterly for U.S./state/metro areas quarterly for analyses requiring more recent data.  These data are new as of February 2018.

Visual Analysis of Housing Price Appreciation
The following graphic shows housing value appreciation as of 2017 based on the HPI with 2000 base of 100 by county in the Charlotte, NC-SC metro area. See more about by HPI by county for the Charlotte metro.

– view developed using CV XE GIS and related GIS project.
– Click graphic for larger view and details.

See similar HPI 2017 patterns view for the Houston, TX metro.

Housing Price Appreciation 2010-2017 — Largest 10 Metros
This table, derived from the  interactive table, shows the largest 10 metros based on total population. the HPI 2010, HPI 2017, housing price appreciation 2010-2017 and total population are presented in the table. Click the CBSA code link to view HPI by county component for the metro and an extended series.

 Metro CBSA HPI2010 HPI2017 HPA1017 Pop2016
 New York   35620 159.53 172.76 8.29 20,153,634
 Los Angeles   31080 169.83 242.78 42.95 13,310,447
 Chicago   16980 117.48 124.58 6.04 9,512,999
 Dallas   19100 120.89 175.35 45.05 7,233,323
 Houston   26420 134.02 183.52 36.93 6,772,470
 Washington   47900 166.82 198.74 19.13 6,131,977
 PhiladelphiaA   37980 157.26 162.91 3.59 6,070,500
 Miami   33100 140.43 213.91 52.33 6,066,387
 Atlanta   12060 103.95 129.24 24.33 5,789,700
 Boston   14460 134.33 165.27 23.03 4,794,447

– Metro names abbreviated; use table to view full name and code.

Using the HPI Annual 2010-2017 Interactive Table
The following graphic illustrates use of the HPI Annual 2010-2017 interactive table. Click graphic for larger view. This view shows metros in the 250,000-300,000 population peer group. Set your own criteria using tools below the table. There are 23 metros in this group. The table has been sorted on housing price appreciation (HPA) from 2010-2017 (second column from right). It shows that the Merced, CA metro had the highest HPA — 82.13% di=uring this period.

Use the interactive table and examine areas of interest.

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.

 

 

Examining Health Care Infrastructure by ZIP Code

.. small area data providing information on sub-county and sub-city/place geographies are challenging to locate and use — particularly in context of demand for healthcare services and demographic attributes of associated neighborhoods. Develop insights into the healthcare infrastructure by ZIP code using the two related resources reviewed here — 1) individual ZIP code demographic-economic profiles and 2) ZIP code demographic-economic interactive tables. One way to examine the healthcare infrastructure for an area is to view/analyze the number and attributes (employment, earnings) of healthcare establishments by types of business/industry (such as physicians office or hospitals). Data and tools reviewed here provide insights into characteristics and patterns of national scope ZIP code areas — examine your ZIP codes of interest.

Option 1 — ZIP Code Profiles
.. examining the healthcare infrastructure in context of the related demographic-economic situation … the following graphic shows ZIP code 10514 (Westchester County, NY) with a bold red boundary.  Census tracts are shown with black boundaries with tract codes as white labels. See more about ZIP-Tract relationships. Cities/places are shown with blue cross-hatch pattern.

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

The above map graphic is part of a ZIP Code 10514 profile (click link to view complete profile). Section 3.1. of the profile shows the number healthcare establishments in the ZIP Code as partly shown in this graphic:

The portion of the table shows the NAICS/type of business code at left, followed by type of business description and the number of establishments at the right.

Examine other characteristics of this ZIP code profile and in context of others via this related Web section. These profiles update in May 2018.

Option 2 — ZIP Code Health Care Sector comparative analysis
.. examining the healthcare infrastructure for a set of ZIP codes in a state, metro, county or peer group … use the interactive table located here to view/rank/compare health care business establishments by type of business for a selected set of ZIP codes. This table shows a query placed on the table to show the total number of offices of physicians for ZIP codes in the vicinity of ZIP 10514. It shows that there are 14 offices of physicians establishments and 13 have 1-4 employees.

About These and Related ZIP Code Data
Data used to develop the tools/resources described above are based in part on the Census Bureau County Business Patterns program. These establishment data update annually.

ZIP code demographic-economic interactive tables
Use the following tables to examine a wide range of ZIP code demographic-economic conditions:
  • General Demographics
  • Social Characteristics
  • Economic Chacteristics
  • Housing CHaracteristics

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 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.

Congressional District/State Legislative District Data Analytics Sessions

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

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

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

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

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

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

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

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

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

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

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