Tag Archives: mapping

Developing Geographic Relationship Data

.. tools and methods to build and use geographic relationship files … which census blocks or block groups intersect with one or a set of school attendance zones (SAZ)? How to determine which counties are touched by a metropolitan area? Which are contained within a metropolitan area? Which pipelines having selected attributes pass through water in a designated geographic extent? This section reviews use of the Shp2Shp tool and methods to develop a geographic relationship file by relating any two separate otherwise unrelated shapefiles. See relasted Web page for a more detiled review of using Shp2Shp.

As an example, use Shp2Shp to view/determine block groups intersecting with custom defined study/market/service area(s) … the only practical method of obtaining these codes for demographic-economic analysis.

– the custom defined polygon was created using the CV XE GIS AddShapes tool.

Many geodemographic analyses require knowing how geometries geospatially relate to other geometries. Examples include congressional/legislative redistricting, sales/service territory management and school district attendance zones.

The CV XE GIS Shape-to-Shape (Shp2Shp) relational analysis feature provides many geospatial processing operations useful to meet these needs. Shp2Shp determines geographic/spatial relationships of shapes in two shapefiles and provides information to the user about these relationships. Shp2Shp uses the DE-9IM topological model and provides an extended array of geographic and subject matter for the spatially related geometries. Sh2Shp helps users extend visual analysis of geographically based subject matter. Examples:
• county(s) that touch (are adjacent to) a specified county.
• block groups(s) that touch (are adjacent to) a specified block group.
• census blocks correspond to a specified school attendance zone.
• attributes of block groups crossed by a delivery route.

Block Groups that Touch a Selected Block Group
The following graphic illustrates the results of using the Shp2Shp tool to determine which block groups touch block group 48-85-030530-2 — a block group located within McKinney, TX. Shp2Shp determines which block groups touch this block group, then selects/depicts (crosshatch pattern) these block groups in the corresponding GIS map view.

Geographic Reference File
In the process, Shp2Shp creates a geographic relationship file as illustrated below. There are six block groups touching the specified block group. As shown in the above view, one of these block groups touches only at one point. The table below (derived from the XLS file output by Shp2Shp) shows six rows corresponding to the six touching block groups. The table contains two columns; column one corresponds to the field GEOID from Layer 1 (the output field as specified in edit box 1.2 in above graphic) and column 2 corresponds to the field GEOID from Layer 2 (the output field as specified in edit box 2.2 in above graphic). The Layer 1 column has a constant value because a query was set (geoid=’480850305302′) as shown in edit box 1.3. in the above graphic. Any field in the layer dataset could have been chosen. The GEOID may be used more often for subsequent steps using the GRF and further described below. It is coincidental that both layers/shapefiles have the field named “GEOID”.

Layer 1 Layer 2
480850305302 480850305272
480850305302 480850305281
480850305302 480850305301
480850305302 480850305311
480850305302 480850305271
480850305302 480850305312

Note that in the above example, only the geocodes are output for each geography/shape meeting the type of geospatial relationship. Any filed within either shapefile may be selected for output (e.g., name, demographic-economic field value, etc.)

How it Works — Shp2Shp Operations
The following graphic shows the settings used to develop the map view shown above.

See related section providing details on using the Shp2Shp tool.

Geographic Relationships Supported
The Select Relationships dropdown shown in the above graphic is used to determine what type of spatial relationship is to be used. Options include:
• Equality
• Disjoint
• Intersect
• Touch
• Overlap
• Cross
• Within
• Contains
See more about the DE-9IM topological model used by Shp2Shp.

Try it Yourself

See full details on how you can use any version, including the no fee versin, of CV XE GIS to use the Shp2Shp tools. Here are two examples what you can d. Use any of the geospatial relatoinships. Apply your own queries.

Using Touch Operation
Select the type of geographic operation as Touch. Click Find Matches button. The map view now shows as:

Using Contains Operation
Click RevertAll button. Select the type of geographic operation as Contains. Click Find Matches button. The map view now shows as:

Relating Census Block and School Attendance Zones
The graphic shown below illustrates census blocks intersecting with Joyner Elementary School attendance zone located in Guilford County Schools, NC (see district profile). The attendance zone is shown with bold blue boundary. Joyner ES SAZ intersecting blocks are shown with black boundaries and labeled with Census 2010 total population (item P0010001 as described in table below graphic). Joyner ES is shown with red marker in lower right.


– view developed using CV XE GIS and related GIS project; click graphic for larger view

See more about this application in this related Web section.

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

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

Accessing & Using ZIP Code Demographics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

… February 2017 updates .. 5 ways to access/analyze the most recent estimates of median housing value and other subject matter by ZIP Code area .. updates on accessing/downloading/using American Community Survey (ACS1115) 5-year estimates. See more detail in related Web section.

Site analysis (Option 5 below)
– create site analysis profiles from a location/ZIP code.

Contents
Five data access and use options, listed in the links below, are reviewed. Each method illustrates how ZIP code demographic-economic data can be accessed/ analyzed/used in different contexts. The most basic data access/data download is illustrated in Option 3. The following links open new windows that take you to the related section with more detail.
Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
.. Option 3a – Extended ZIP Code subject matter access.
.. Option 3b – ZIP code urban/rural data access.
.. Option 3c – Additional API ACS data access resources.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related ZIP Code Data Access & Use sections
Interactive access to demographics based on an address
Summary of ZIP Code Data Resources & Tools
10 Reasons to use Census Tracts Versus ZIP Codes
Analyzing Census Tract Demographics by ZIP Code Area
ZIP Code to Census Tract Equivalence Table
ZIP Code Urban/Rural Geography & Demographics
Mapping ZIP Code Demograhics
Housing Price Index by 5-digit ZIP Code – time series; annual updates
Housing Price Index by 3-digit ZIP Code – time series; quarterly updates
ZIP Code Business Establishment, Employment & Earnings by industry
ZIP Code Retail Trade Establishment & Sales by industry
ZIP Code Equivalence Tables — ZIP Code to School District

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.

Urban Area Demographic Trends 2010-15

.. tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015 .. examining urban areas in context of metropolitan areas .. the four fastest growing Urbanized Areas (UAs) from 2010 to 2015 were in Texas. McKinney, TX UA led the nation with an increase of 27.5% in total population. View, rank, compare 2010 and 2015 demographic characteristics for UAs using the interactive table in this related section. Urban areas (Urbanized Areas and Urban Clusters) are important for many reasons. More than metros and cities, urban area geography better reflects how the urban and rural population is changing. Both metros and cities can change geographic boundary over the years. Urban areas are based on Census 2010 and unchanging between 2010 and 2020. Annual demographic updates are available from the American Community Survey (ACS 2015).

This section is focused on tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015. Use the interactive table >in the related section to view, rank, query urban areas and demographic change for larger urban areas. Use the related GIS tools and data to develop related thematic and relationship maps. Perform geospatial analysis of geographic and demographic-economic characteristics using the resources we have developed. Gain insights into patterns that might affect you. Use these resources to collaborate on how, where, what, when and why of change.

McKinney TX Urbanized Area in Context of City
The McKinney, TX UA (bold orange pattern) is shown in context of McKinney city (cross-hatched area) and other urban areas (lighter orange pattern). It is easy to see that some parts of the city are rural and that the UA extends beyond the city in many areas. See more about the McKinney UA and in comparison to other urban areas using the interactive table.


– view created using CVGIS software and related GIS project.

Most Urbanized Areas (UAs, 435 of 487) have population 65,000 population or more resulting in the availability of annual demographic-economic estimates. Data are fresher than available for smaller urban areas (ACS 5-year estimates for areas under 65,000). This means more current data to assess more recent characteristics. As annual data are available UAs enabling analysis of change over time. The “2010s” marks the first time these refreshed, time series-like data have been available for urban areas. Businesses and those examining change performing market analysis benefit from the ability to examine characteristics or urban areas in combination with counties and metros.

Houston Urbanized Area in Context of Houston Metro
The Houston metro has a bold brown boundary. It is easy to see how the Houston UA (darker orange fill pattern) geographically relates to the metro. Other urban areas (all) are shown with a lighter orange fill pattern. It is easy to see the urban/pattern character of the general region. While the Houston UA is the largest, there are four UAs that intersect with Houston metro. Use the interactive table below to view their names and characteristics.


– view created using CVGIS software and related GIS project.

Urbanized Areas tend to be associated with metropolitan areas having a similar name. But very often there are multiple UAs within a metro; sometimes one is not dominant. Often there are several UAs in a metro having similar size. Use the interactive table below to view the relationship of UAs and metros (CBSAs).

Using Interactive Table
Use the interactive table to view, rank, compare, query urban areas based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the urbanized areas ranked in descending order based on 2010-2015 population. The rightmost column shows the area percent change in population over the period.

Fastest Growing Urbanized Areas, 2010-15

Try it yourself. Use the table to examine urban area patterns and characteristics based on your selected criteria.

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.

School District Demographic Trends: 2010-2015

.. data and tools to examine how school districts of interest are changing … based on total population, the largest 10 school districts in 2015, all experienced an increase in total population over the period 2010-2015. Five of these districts had a decrease in school age population (ages 5-17 years). Four of these districts had a decrease in the number of related children in families ages 5-17 years. See characteristics of districts in this interactive table. See the related Web section for more details.

School Districts with 2015 Population 100,000 or More
More than 600 of the total 13,245 school districts have a total 2015 population of 100,000 or more (red markers).

– view developed with CVGIS software and related GIS project.

Using New 2015 Estimates Released December 2016
– for use in 2017 ESEA Title I Allocations
Analyze annual demographic data for each U.S. school district for the period 2010 through 2015. These data include the Federal official 2015 estimates available for all districts. Developed for use as inputs for the ESEA Title I allocation formula, the data have broader uses of interest to school district demographics stakeholders. Use the interactive table in this section to view, rank, compare, query demographic characteristics of districts of interest.

The annual estimates for each school district include:
• total population
• number of children ages 5 to 17
• number of related children ages 5 to 17 in families in poverty

Using Interactive Data Tools
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic measures. The following graphics illustrate how the table can be used. Click graphic for larger view.

Total Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

School Age Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Related Children Ages 5-17 in Poverty
– 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Try it yourself. Use the table to examine a set of districts on your selected criteria in for a state/area of interest.

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 Diversity by State 2015

.. states with the highest race/origin diversity in 2015 were Hawaii, California and New Mexico. States with the lowest diversity were West Virginia, Maine and Vermont. Higher levels of diversity tend to provide a better framework for understanding, tolerance and cooperative developments and progress. Use the interactive table to view, rank, compare states on the diversity index, percent population by race/origin and population by race/origin.

What is the chance that the next person I meet will be different from me, in terms of race origin? The Diversity Index is a number on a scale from 0 to 100 that shows the chance that two people chosen randomly from an area will be different by race and origin. A higher number means more diversity, a lower number, less diversity.

2015 Diversity Patterns by State
The following graphic shows patterns of the percent non-White population (see legend in lower right) the 2015 diversity index as a label for each state

– view developed using CVGIS and related project.
– use the software and project to create variations of this view; add your own data.

See the related section on diversity. USA TODAY used ProximityOne population projections to 2060 by county to examine diversity trends between 2010 and 2060 – a 50-year trend analysis.

This section provides a new estimate of the 2015 diversity index for the U.S. by state based on the latest data. The 2015 population by race/origin estimates are the most recent official Federal U.S. by state data (updated annually). See more about these estimates; access individual state profiles. In addition, the computational methodology is summarized. The U.S. by state demographics dataset is provided as a part of the U.S. State Diversity GIS project. Analyze alternative computations and views of the diversity index.

Examining the 2015 Diversity Index & Race/Origin by State
Some illustrative examples of the interactive table to view … click the Diversity Index column header cell in the table to sort states in ascending order on the Diversity Index. Click that column header cell again to sort states/rows in descending order on the Diversity Index. Find state(s) of interest; see what peer group those states are in based on demographic measures of interest.

Double-click the %Hispanic column header cell in the table to see that New Mexico has the highest %Hispanic population. Click the “population columns only” button below the table, navigate to far right and double-click the Hispanic column header cell to see that California has the largest Hispanic population.

Interactive Table Example
The following graphic illustrates use of the interactive table. States are ranked in descend order on the 2015 Diversity Index.

– 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.

New 2016 Digital Roads Database

.. new resources for updated geographic reference and statistical mapping and geography for routing logistics and optimization .. The Census Bureau TIGER/Line is a continuously updated geographic database used for geographic reference and geospatial processing of data from various Census statistical programs including the decennial census Census 2010 and American Community Survey (ACS 2014). The public use version of TIGER is released annually that includes updates developed during the year. ProximityOne integrates the TIGER geographic updates in the Digital Map Database. Warren Glimpse, founder of ProximityOne, developed the GBF/DIME used as the prototype for TIGER/Line development.  See related Web section for more details, interactive table and access to GIS resources.

The TIGER database includes many types of files and data. The data are developed in the form of shapefiles and dbase files that may be used directly with the ProximityOne CV XE GIS software at no fee. Perform wide-ranging mapping and geospatial analysis applications using these GIS resources. See more aboutmapping statistical data.

TIGER/Line Roads Data
This section is focused mainly on the use of the TIGER/Line “edges” shapefile. The edges shapefile U.S. wall-to-wall street/road coverage in the form of line shapefiles. Lines classified as roads are intersection-to-intersection road segments. Line segment fields include name, left- and right-side high and low addresses, and many related attributes.

Use the U.S. by county interactive table below to examine attributes of TIGER 2016 street/road coverage. ProximityOne developed these county summary data by processing each county edges shapefile. See about using the edges shapefile with the CV XE GIS software below in this section.

Illustrative Applications
The following sequence of graphics shows an example of a “road segment” in context of related geography. These applications focus on an area in Kansas City, MO (Jackson County),. Jackson County has 52,139 TIGER 2016 road segments. See the related step-by-step summary of how you can create these and similar map views using CV XE GIS below in this section.

Road Segment Map View & Profile
– Starbucks locations shown as red markers; pointer on road segment by a Starbucks location.
– View illustrates how non-Census, non-statistical data can be integrated with TIGER.
– Clicking on the road segment (in GIS operation), a mini-profile displays.
– The profile shows attributes of the selected road segment.
.. the TLID value shows the unique ID for this segment among all segments in U.S.
.. left- and right-side high and low address ranges and included in the profile.

Corresponding Census Block Profile
– The road segments are boundaries for census blocks.
– The census block boundaries are shown using a related TIGER blocks shapefile.
– The more that 11 million census blocks cover the U.S. wall-to-wall.
– The census block code (290950073002017) is shown as a label in the map graphic and in the profile.

Neighborhood & Shopping Area View
– A zoom-out shows the location, roads and blocks for a broader areas.

Regional View
– A further zoom-out shows the focus area view in context of the metro counties (a related TIGER shapefile)
– The January 2016 Kansas City city area (orange cross-hatch pattern) is shown using a related TIGER 2016 shapefile.

TIGER 2016 Roads
TIGER/Line 2016 vintage files were released in August 2016. While many aspects of road coverage remain as described in this section, TIGER/line 2016 includes many updates as well as “new vintage” geography for school districts, state legislative districts, congressional districts and other political/statistical area geography.
• More about TIGER 2016.
• More about TIGER/Line in general.

TIGER 2016 Road/Street Name/Address Coverage
— Interactive Table
The following graphic illustrates use of the interactive table to examine the number and characteristics of road segments by county. This view shows the top 10 counties based on the number of total road segments.

– click graphic for larger view

Using TIGER/Line with CV XE GIS
These operations require a Windows computer with Internet connection
1. Install the ProximityOne CV XE GIS
… run the CV XE GIS installer
… take all defaults during installation
2. Download the TIGER Roads project fileset
… requires ProximityOne User Group ID (join now)
… unzip TIGER Roads GIS project files to local folder c:\tiger2016
3. Open the c:\tiger2016\riger2016_kc.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named c:\tiger2016\tiger2016_kc.gis
4. Done. The start-up view is shown at top of this section.

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

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