Category Archives: Metro Areas

Examining America’s 10 Largest Urban Areas

.. why it matters .. among other reasons, these 10 areas have 24% of the total U.S. population. Three have increased by more than 20% in the past 5 years.

More than 80-percent of America’s population is urban, but far more than 80-percent of America’s geography is rural. Census 2010 shows that America’s urban population increased by 12.1 percent from 2000 to 2010, compared to the national overall growth rate of 9.7 percent. Urban areas now account for 80.7 percent of the U.S. population, compared to 79.0 percent in 2000.

America’s 10 Largest Urbanized Areas
The following table shows the largest 10 Urbanized Areas (UAs) based on the American Community Survey 2011 and 2016 1-year estimates (ACS2016) and change over the period. UAs are sorted in descending order based on the 2016 population estimate. Note that Atlanta, Dallas and Houston moved up in rank.

Geodemographic relationships vary widely between the urbanized areas (UAs). Some, such as Miami, comprise most or all of the urban area within the corresponding metropolitan statistical area. Others, such as Philadelphia, are nested within a mix of adjacent urban areas interspersed with rural areas. Among other things, these different geodemographic structures reflect how planning, needs assessment and market development vary widely from associated metro-to-metro. These data show the importance and need to consider the urban/rural population distribution even in the largest metros.

Visual Analysis — Dallas Urbanized Area
The urbanized area (UA) of the corresponding metropolitan statistical area (MSA) generally occupies less than half of the MSA.
See the Dallas-Fort Worth-Arlington, TX MSA Situation and Outlook Report

… View developed using CV XE GIS.

Map Views for Each of the Largest 10 Urbanized Areas
Maps for each of the 10 largest UAs are shown at
http://proximityone.com/urbanareas_2016.htm.

Each graphic shows the designated urbanized area in a darker salmon color fill pattern, associated metropolitan statistical area with bold brown boundary, and other urban areas with a lighter shade of salmon fill color, counties black boundaries and yellow labels. The ACS 2016 UA population is shown as a white label under the UA name. The ACS 2016 estimates are the most recent data available and will update with 2017 estimates in late 2018.

More About Analyzing Urban/Rural Patterns and Characteristics
See the related section on America’s urban/rural population and geography:
http://proximityone.com/urbanpopulation.htm.

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 L

Creating Custom Demographic Datasets with API Tools

.. develop national scale spreadsheet files with virtually no learning time .. easy-to-use API operations to create national scope demographic-economic datasets based on American Community Survey 2016 1-year estimates .. custom subject matter selections. See more detail in related web sections ACS2016 and ACS2016_API.

Benefits and utility … how to acquire a spreadsheet showing the population of all cities with population estimates based on the ACS 2016 1-year data? … or, housing units, median household income, median housing value, etc.? Variations of this need frequently arise — what is the list of largest California counties sorted on total population: What are the 25 metros having the highest median household income? Which 10 congressional districts have the highest poverty incidence? Which urban areas have the highest educational attainment?

Use simple API calls described below to get answers to these types of questions — and more.  Create files that can be used for recurring applications. An example …

Urban Areas with 2016 Population 65,000+ Population
… results from using the API downloaded data … the following graphic shows urban areas with 65,000 or more 2016 population; zoom-in to Texas. The full national scope GIS project is available as described below; examine U.S. or any region. The file used to develop this view was created using the results of the API call reviewed below (requires integration of those data into the urban areas shapefile). Click graphic for larger view; expand browser window. Larger view shows urban areas labeled with name and mini profile for Dallas UA showing all subject matter items downloaded (via API) as described below.

… View developed using CV XE GIS.
… See more about Urban Population & Urban Areas.

Access ACS 2016 1-Year Data Using API Tools
Here are the API links … use these API calls to access/download selected items for selected geographies. See more about using API tools. Click a link and receive a return page with CSV-like structured data. See usage notes below. As these are ACS 2016 1 year estimates; geographies are only available for areas 65,000+ population.
Click a link:
• All U.S. cities/places
• All U.S. counties
• All U.S. CBSAs
• All U.S. Urban Areas
• All 115th Congressional Districts
• All U.S. states
• U.S. only

The following data retrieval operations are by state. These are examples using Arizona (FIPS state code 04).
• All [within state] Elementary School Districts
• All [within state] Secondary School Districts
• All [within state] Unified School Districts

API Call Returned Data Usage Notes
Clicking the All U.S. cities/places link above generates a new page with content very much like a CSV file. Try it .. click an above link.

See the related ACS2016_API web section for more details.

Items Retrieved in the API Calls
The sample header record above shows the subject matter item listed at the left in the following set of items. Modify API call and use other subject matter items. See full array of subject matter – xlsx file.
.. B01003_001E – Total population
Age
.. B01001_011E — Male: 25 to 29 years (illustrating age cohort access)
.. B01001_035E — Female: 25 to 29 years (illustrating age cohort access)
Race/Origin
.. B02001_002E – White alone
.. B02001_003E – Black or African American alone
.. B02001_004E – American Indian and Alaska Native alone
.. B02001_005E – Asian alone
.. B02001_006E – Native Hawaiian and Other Pacific Islander alone
.. B02001_007E – Some other race alone
.. B02001_008E – Two or more races
.. B03001_003E – Hispanic (of any race)
Income
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
Housing & Households
.. B25001_001E – Total housing units
.. B25002_002E – Occupied housing units (households)
.. B19001_017E — Households with household income $200,000 or more
.. B25003_002E — Owner Occupied housing units
.. B25075_025E — Housing units value $1,000,000 to $1,499,999
.. B25075_026E — Housing units with value $1,500,000 to $1,999,999
.. B25075_027E — Housing units with value $2,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

The rightmost fields/columns in the rows/records contain the area name and geographic codes.

Using API Tools for Data Analytics
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 L

Important Upcoming Data Releases: September 2017

.. monthly updates on recent & upcoming data analytics tools & resources .. this section provides a monthly update on important new data developments and applications/developments to further their use in data analytics. A focus of this section is on new or revised geographic, demographic and economic data. Most of these data are used to develop and update ProximityOne census tract-level up demographic-economic projections to 2022 and county-level up population by single year of age projections to 2060. See about September projection updates below on this page. This section is organized into recent past data updates and upcoming (month ahead) data releases and may be updated to reflect new or extended details. See related news and updates:
• What’s New daily updates
• Situation & Outlook Calendar

See related Web section.

Recent Past Data Releases/Access

U.S. by Census Tract 2017 HMDA Low & Moderate Income (FFIEC)
• Release date — 8/17; next update — mid 2018
• 2017 annual HMDA data — covers all income levels not only LMI
• New 2017 HMDA data
• See more information – access data.

U.S. by County Population by Single Year of Age (NCHS)
• Release date — 8/22/17; next update — mid 2018
• 2010 through 2016 annual population by single year of age
• New 2016 data extending annual series 2010 forward
• See more information – access updates.

Housing Price Index (FHFA)
• Release date — 8/22/17; next update — 11/28/17
• Quarterly HPI
• New 2017Q2 data extending quarterly time series.
• See more information – access updates.

Quarterly Gross Domestic Product by State (BEA)
• Release date — 9/20/17; next update — 11/21/17
• Quarterly GDP by Industry
• New 2017Q1 data extending quarterly time series.
• See more information – access data.

Upcoming Data Releases/Access 

2017 TIGER Digital Map Database (Census)
• Expected ~ 9/7/17
• Topologically Integrated Geographic Encoding & Referencing (TIGER) data.
• Geographic data; predominately shapefiles.
.. intersection to intersection road segment geography and attributes.
• New 2017 GIS/mapping shapefiles for use with wide-ranging data
.. including with Census 2010, ACS 2016 & other subject matter.
• See more information – updates to access summarized in that section.

Census of Employment and Wages (BLS/CEW)
• Release date — 9/6/17; next update — 12/5/17
• AKA ES-202 data — establishments, employment & wages by NAICS code/type of business
• U.S. by county.
• New 2017Q1 data extending quarterly time series.
• See more information.

2016 American Community Survey 1-year estimates (Census/ACS)
• Release date — 9/14/17
• Wide-ranging demographic-economic data for areas having population 65,000+
.. all states, CDs, PUMAs, MSAs and larger cities/CBSAs/school districts/counties (817 of 3142)
• New 2016 estimates.
• See more information – updates to access summarized in that section.

SY 2015-16 Annual School & School District Characteristics (NCES)
• Expected ~ 9/14/17
• National school school & school district characteristics.
• New 2015-16 school year administratively reported data.
• Schools … see more information – access updates.
• School District … see more information – access updates.

2016 Annual Gross Domestic Product by Metro (BEA)
• Release date — 9/20/17
• GDP by Industry by Metro
• New 2016 data extending time series
• See more information – access updates.

Census Tract Estimates and Projections to 2022 — ProximityOne
• Release data ~ 9/27/17
• National census tract and higher level geography demographic-economic updates
• Annual estimates & projections; 2010 through 2022
• Updated to reflect/integrate data released through 9/2017 as summarized above   • See more information.

County Population by Single Year of Age Projections to 2060 — ProximityOne
• Release data ~ 9/27/17
• National county and higher level geography demographic updates
• Annual estimates & projections; 2010 through 2060
• Updated to reflect/integrate data released through 9/2017 as summarized above.   • See more information.

Notes [goto top]
– BEA – Bureau of Economic Analysis
– BLS – Bureau of Labor Statistics
– Census – Census Bureau
– FFIEC – Federal Financial Institutions Examination Council
– FHFA – Federal Housing Finance Agency
– NCES – National Center for Education Statistics
– NCHS – National Center for Health Statistics

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

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

Low & Moderate Income Census Tracts; 2017 Update

..  data and tools to analyze characteristics and patterns of census tract geography with a focus on low and moderate income.   See related Web page for more detail.

Of the total 75,883 census tracts for which low and moderate income data were tabulated in the HMDA 2017 data, 6,023 (8.7%) were low income, 16,873 (24.5%) were moderate income, 32,509 (47.1%) were middle income and 19,159 (27.8%) were upper income. See more about these classifications. Find out about your tracts/neighborhoods of interest and how they compare to others using data and tools provided in this section.

Analysis of the low, moderate, middle, and upper income of the population and households by small area geography is important to housing market stakeholders, lenders, investors, cities/neighborhoods and others. Low and moderate income data by block group and census tract are used for compliance, eligibility determination and program performance in many Federal programs and agencies.

• Use the interactive table below to view, query, compare, sort census tracts.
• Use tract estimates & projections to examine changing characteristics.
– extended demographic-economic measures, annual 2010-2022

Low & Moderate Income by Census Tract
The following view shows census tracts designated as low and moderate income (orange fill pattern) in the the Houston, TX MSA (bold brown boundary) area. These are tracts having income level with codes 1 and 2 in the interactive table. A wide range of market insights can be created zoom-in views for counties, cities and neighborhoods and linking these with other data. Make variations of this view using ProximityOne data and tools described in this section.

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

View similar maps for these areas:
.. Atlanta metro
.. Chicago, IL metro
.. Dallas, TX metro
.. Knoxville, TN metro
.. with drill-down views for Knoxville city
.. Los Angeles, CA metro
.. San Francisco, CA metro

Using the Interactive Table
  – Examining LMI Tracts in Your Metro

Use the interactive table to view, query, sort compare tracts based on various demographic and LMI characteristitcs. The following graphic illustrates how the table can be used to view low and moderate income tracts for the Charlotte, NC-SC metro.
– click ShowAll button below table.
– enter a CBSA code in the edit box at right of Find CBSA LMI>.
– click the Find CBSA LMI button.
Resulting display of Charlotte metro LMI tracts only.

– 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.

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.

Creating & Using Location Shapefiles

.. GIS tools and methods to develop and update location shapefiles .. location shapefiles are essential to most GIS applications. Location shapefiles, or point shapefiles, enable viewing/analyzing locations on a map and attributes of these locations such store or customer ID, street address, city, date updated, value, ZIP code and wide-ranging attributes about the location. This section reviews tools and methods to develop and use location shapefiles. See more detail about topics covered in this section in the related Web page.

Viewing/Analyzing Store Locations in the Dallas, TX Area
The following graphic illustrates how store locations can be shown in context of other geography and associated demographic-economic attributes. This view shows store locations (red markers) in context of Dallas city (blue cross-hatch pattern) and broader metro area. Markers shown in this view are based on a location shapefile created using steps described below. The identify tool is used to click on a location and show attributes in a mini-profile.

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

View the locations contextually with thematic patterns by tract or other geography. Combine views of store, customer, agent, competitor and other location shapefiles.
The following view shows patterns of median household income by census tract.

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

Development of location shapefiles often starts with a list of addresses. Locations are not always address-oriented; they might be geographically dispersed measurement or transaction locations — having no address assigned. In applications reviewed here, locations are organized as rows in a CSV file. Each CSV file contains like-structured attributes for each location. The example used in this section uses store locations located in the Dallas, TX area.

There are two basic methods used to create location shapefiles: 1) geocoding address-data contained in the source data file or 2) using the latitude-longitude of the location included in the source data file record. The focus here is on option 2 — using the latitude-longitude of the location already present in the source data file.

Creating a Location Shapefile
The process of creating a location shapefile uses the CV XE GIS Manage Location Shapefile feature. With CV running, the process is started with File>Tools>ManageLocationShapefile. The following form appears.

.. ManageLocationShapefile feature/operation in ProximityOne CV XE GIS.

CV XE GIS provides other ways to create location shapefiles:
• Tools>AddShapes>Points — click points on the map window canvas.
• Tools>FindAddress — creates a single point shapefile based on specified address.
• Tools>FindAddress (Batch) — creates a point shapefile based on specified file of address records.
See details in User Guide.

Steps to Create a Location Shapefile
The process of creating the shapefile “C:\cvxe\1\locations1pts.shp” can be viewed by clicking the Run button on the form (with CV running). Two input CSV structured files are required:
• data definition file
• source data file

There are two sets of illustration location input files included with the CV installer:
• locations1_dd.csv and locations1.csv (7 locations in Johnson County, KS)
• locations2_dd.csv and locations2.csv (252 locations in Dallas and Houston)
These files are located in the \1 (typically c:\cvxe\1) folder. The marker/location shapefile used in the map shown above was created using the lcoations2 input files.

Data Definition File
The Data Definition (DD) file is an ASCII/text file structured as a CSV file. It may created with any text editor. The DD file is specific to the source data file. But in the case of recurring source data files for different periods the same DD file might apply to many source data files. There are several rules and guidelines for development of the DD file:
• there is one line/record for each field in the source data file.
• each line/record must be structured in an exact form:
.. each line/record is comprised of exactly 4 elements separated by a comma:
.. 1 field name for subject matter item
– must consist of 1 to 10 characters and include no blanks or special characters
.. 2 field type: C for character, N for numeric
.. 3 field length: an integer specifying the maximum with of the field
.. 4 maximum number of decimals for field (value is 0 for character fields)
The DD File must include three final fields:
LATITUDE,n,12,6
LONGITUDE,n,12,6
GEOID,c,15,0
The structure of these three DD file records must be as shown above. The source data file, described below, must have the LATITUDE and LONGITUDE fields populated with accurate values. The GEOID field may populated with either an accurate value of placeholder value like 0.

Example. Data for each store for the default DD file name “C:\cvxe\1\locations1_dd.csv” include the following fields/attributes:
  NAME,C,45,0
STORE,c,15,0
ADDRESS,c,60,0
CITY,c,40,0
LATITUDE,n,12,6
LONGITUDE,n,12,6
GEOID,c,15,0

Optionally create a DD File using the Create DD File button on the form. Clicking this button will create a DD File containing attributes of the dBase file specified in the associated edit box. The DD File name is created from the dBase file name. If the dBase file name is “c:\cvxe\1\locations1pts.dbf”, the DD File will be named “c:\cvxe\1\locations1pts_dd.csv”.

About the GEOID
The GEOID is a 15 character code which defines the Census 2010 census block containing each location. The GEOID is generally assigned by the ManageLocationShapefile operation and is one of the important and distinctive features of this tool. The GEOID is used to uniquely determine, with the GIS application, any of the following: state, county, census tract, block group, or census block.

The GEOID, as used in this section, is the 15 character Census 2010 geocode for the census block. The GEOID value 481130002011012 (see in location profile in map at top of section) is structured as:
state FIPS code: 48 (2 chars)
county FIPS code: 113 (3 chars)
census tract code 000201 (6 chars)
census block code: 1012 (4 chars) (block group code: 1 — first of 4 characters)

About the Source Data File
The Source Data File is an ASCII/text file structured as a CSV file. It is typically developed by exporting/saving an Excel or dBase file in CSV structure. There are several rules and guidelines for development of the source data file:
• fields must be structured and arranged as defined in the DD File.
• character fields must not contain embedded commas.
• final items in record sequence must be:
.. LATITUDE – must have accurate decimal degree value; 6 digit precision suggested.
.. LONGITUDE- must have accurate decimal degree value; 6 digit precision suggested.
.. GEOID – this may be 0, not assigned or the accurately assigned GEOID value.
– optionally create/rewrite the GEOID used in the new shapefile.

Updates; Combining Vintages of Location Attributes
Location based data might update frequently, even daily. The recommended method to add, update and extend the scope of location-based data is to create new address shapefiles corresponding to different vintages or dates covered. The structure of the files must be the same so that they files can be used together or separately. Suppose there is one set of data covering year to date and a second set of data covering the following month. The ManagePointShapefile operation would be run once for each time period. Two shapefiles would be created. These shapefiles may be added to a GIS project and used separately or in combination to view/analyze patterns.

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.