2014 Border to Border
Transportation Conference
Using Spatial Analytics to Streamline Data
Workflows in Transportation Planning
Transit, Freight, and Airports Case Studies
By Arturo Bujanda
November 19, 2014
Agenda
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Objectives
Objective
What is spatial intelligence and geoanalytics?
Data structure
Geoanalytic tools useful in transportation planning
Case studies
Assisting transportation planning efforts
Conclusion
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Project objectives
 Explore the application of spatial intelligence (SI) and
geoanalytics to streamline data workflows in
transportation planning.
 Provide guidance for practitioners to:
• Analyze demographic, social, economic, and transportation
trends.
• Conduct geospatial analyses useful in travel demand modeling
(TDM), transit, freight and airport planning applications.
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Agenda
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Objective
What is spatial intelligence
intelligenceand
andgeoanalytics?
geoanalytics?
Data structure
Geoanalytic tools useful in transportation planning
Case studies
Assisting transportation planning efforts
Conclusion
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Spatial intelligence and geoanalytic tools
 Combine GIS analysis and visualization capabilities
with extensive data packages that are constantly
updated in the cloud.
 Represent an innovative alternative to integrate
datasets and spatial tools from multiple sources (eg.
the cloud) to solve complex transportation problems.
 Have the potential to become standardized procedures
for updating travel demand models (TDM) in many
transportation agencies.
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Spatial Intelligence and Geoanalytic Tools:
Main Interface of Esri Business Analyst (BA)
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Agenda
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Objective
What is spatial intelligence and geoanalytics?
Data
Data structure
structure
Geoanalytic tools useful in transportation planning
Case studies
Assisting transportation planning efforts
Conclusion
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BA combines wizard-driven data in the cloud,
ready to use, and easier to manage and share
 Updated demographics and income profiles with
forecasts for up to five years.
 Census 2010 demographics and a summary profiles.
 Tapestry segmentation area profiles.
 Consumer spending for retail goods and services.
 U.S. businesses by industry, sales volume, location,
name, employees.
 The 2005–2009 data from the ACS is available in GISready format
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BA provides the following levels of geography
for data analysis:
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U.S.
Sate
Core-based statistical area (CBSA)
Designated market area (DMA)
County
County subdivision
Place
Zip code
Tract
Block group
Congressional districts
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Agenda
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Objective
What is spatial intelligence and geoanalytics?
Data structure
Geoanalytic
Geoanalytic tools
toolsuseful
usefulinintransportation
transportationplanning
planning
Case studies
Assisting transportation planning efforts
Conclusion
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Tools in BA were designed to assist solving a
variety of business-critical purposes, including:
 Target-marketing, analyzing customers, site selection, and
designing territories and routes. Examples include:
• Enhancing Shopping Center Performance
ArcNews, Winter 2010/2011.
• A Formula for Revitalization
ArcUser, Summer 2010
• PETCO Improves Location Selection
Integrated Solutions for Retailers, May 2010
• Finding Success in a Soft Economy
ArcNews, Spring 2009
• The Who, What, Where, and How About Customers, Constituents,
Donors
ArcNews Online, Winter 2008/2009
 Nonetheless, we have found that some of such tools offer great
potential for their application in TDM and transportation
planning purposes
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Settings for Data Apportionment Areas
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Agenda
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Objective
What is spatial intelligence and geoanalytics?
Data structure
Geoanalytic tools useful in transportation planning
Case studies
studies
Assisting transportation planning efforts
Conclusion
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Construction of Traffic Analysis Zones (TAZ)
 Project objective: develop a travel demand model (TDM) that
integrates two border communities in a binational conurbation
into a single transportation and economic system.
 The integration of BA with in TDM efforts proved valuable for
the construction TAZs, the collection of socioeconomic and
demographic data, and loading the TDMs.
 Income differentials between the two cities, in two different
countries, made it impossible to compare socioeconomic data.
 BA allowed us to successfully process and integrate data for the
overall binational conurbation for its subsequent input in a TDM.
This case study not only demonstrates the effectiveness of using the extensive
BA data package for the US, but also the use of custom layers and tools to
create TAZs as the case of the Mexican AGEBs.
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Original TAZs and AGEBs merged into resultant
Super-zones and were used to extract data from BA
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Demographic Analysis of Bus Rapid Transit
(BRT) Corridor (Galicia, 2010)1
 Project objective: estimate current and projected
population by stop or corridor for bus-rapid transit (BRT)
ridership forecasting using BA.
 Galicia (2010) demonstrated that it was possible to obtain
demographic data using BA along any given stop or BRT
corridor in the US.
 Obtained reliable information avoiding data requests to
other agencies.
 BRT stations were set as retail stores in BA, and
passengers were treated as customers of the BRT
according to the location and other amenities (ie. walking
distance).
1. Cabrera, Luis David Galicia. Decision Support Tools for Bus Rapid Transit Corridor Planning. Civil
Engineering, The University of Texas at El Paso. Ann Arbor, MI: ProQuest LLC. 2010. UMI: 3433512.
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Business centers in BA 2010 and BRT stops along
the Las Vegas MAX BRT line (Galicia, 2010)1
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BA Trade Area Creation Process Used to Extract
Demographic Data (Galicia, 2010)1
1. Cabrera, Luis David Galicia. Decision Support Tools for Bus Rapid Transit Corridor Planning. Civil
Engineering, The University of Texas at El Paso. Ann Arbor, MI: ProQuest LLC. 2010. UMI: 3433512.
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Service Coverage Area for Las Vegas MAX along
the BRT Corridor (Galicia, 2010)1
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Identification of freight generation clusters for
potential intermodal terminal locations
 Project objective: examine the potential viability for an alternative
transportation system for trailers and containers in a binational,
cross-border setting.
 The Freight Shuttle is designed to move trailers and containers, via
automated transporters, over distances of 5 to 500 miles on an
emission-free, electric-powered guideway system.
• www.freightshuttle.com
 BA was a crucial tool for the market study, the analysis of the
location of potential customers, and the exploration of potential
terminal locations in the El Paso–Juarez binational region.
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Identification of Freight
Generation Clusters for
Potential Intermodal
Terminal Locations
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Airports Analysis and Planning: Measuring
Surface Accessibility
 Project objective: examine and document the role of aviation
along the Texas-Mexico border, and identify border-specific
issues and challenges.
 According the National Plan of Integrated Airport Systems
(NPIAS), most Americans reside within 20 miles of an airport.
 This case study explores the surface accessibility of an airport to
population leaving in regions within a 50 mile buffer of the
Mexican border.
 BA was the tool of choice to assess their impact on analyzed
airports in Texas and Mexico.
 Of the current total U.S. population of 306 million people, all
but 5.6 million live within 20 miles of a NPIAS airport
considering reliever and general aviation airports.
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Driving Distances from the Mexico Border
System Airports Based on Primary Highways
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Real Influence (Cross-Border) Area of Texas Airports
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Driving Times from the Texas Border Airports:
10, 20, and 40 minutes
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Agenda
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Objective
What is spatial intelligence and geoanalytics?
Data structure
Geoanalytic tools useful in transportation planning
Case studies
Assisting
Assisting transportation
transportationplanning
planningefforts
efforts
Conclusion
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Streamline Workflows in Transportation
Planning
 Metropolitan agencies face the challenge of administering data
that is not uniform, consistent, or timely, which translate into
inefficiencies with negative impacts for transportation planners.
 Many government and businesses are harnessing big data and
the cloud to solve complex problems. However, some
transportation planning agencies seems to lag behind such
efforts.
 Integrating SI and geoanalytics in transportation planning and
TDM efforts is a convenient way for doing things smarter, better,
and faster.
 Information often used by retailers to market to their customers
offers an underexploited potential to assist solving many urban
planning and TDM problems.
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As demonstrated by the airports case
study:
BA played a crucial role for making possible the analysis
of 31 airports and their relationship to each other as a
system without the need of a single data collection trip or
data request to any state or local agency.
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Facilitates seeing beyond the data
 Represents an innovative, on-demand alternative to leverage tools and
datasets from multiple sources (e.g., collecting data from the ACS, appraisal
districts, MPOs).
 As demonstrated in the BRT case study, you can create quick site analyses by
simple ring, drive-time, or threshold trade areas, and produce demographic
reports as point and polygon features (e.g. the TDM case study).
 BA offers an optimized way to search and target areas that meet your specific
criteria, such areas are based on zip-codes, blocks, or any custom geography
level. For example:
For example, in the airports case study suppose you want to target moderately dense
populated areas with middle income families who tend to spend money on air travel.
You might want to search the following:
• Population between 10,000 and 30,000 people
• Avg household income of over $75,000
• Median age of 25–50 years
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Prevents the data lag problem
 The ACS is expected to provide a more frequent flow of information to the
transportation planning community, the process of inspecting, cleaning,
transforming
 However, modeling data at most agencies is often characterized by:
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Low and fragmented asset utilization
Duplication of datasets and efforts
Long procurement lead times.
 Until the change towards the cloud from state and local transportation and
planning agencies is complete, a significant amount of the data products
from state and local agencies would remain with limited access from the
transportation planning and research community.
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Promotes collaboration
 Conducting transportation planning projects distant from the regions of
study becomes a tedious process, often prone to errors or frequent data
collection trips from researchers and consultants to the study area.
 Cloud services allow access to background maps and additional data, and
share maps with the online community.
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Agenda







Objective
What is spatial intelligence and geoanalytics?
Data structure
Geoanalytic tools useful in transportation planning
Case studies
Assisting transportation planning efforts
Conclusion
34
Conclusion
 GIS is an essential tool for transportation planners in helping to collect,
process, and visualize data commonly used by transportation planners.
 Given the continually evolving advances in GIS technologies, this paper
serves only as a starting point documenting the capabilities of spatial
analytics to solve data, TDM, and similar transportation planning issues.
 This research explored the integration of SI and geoanalytics to streamline
workflows in TDM and transportation planning efforts highlighting its
benefits.
 Our six case studies explored in this paper demonstrated an innovative,
faster, and smarter alternative to integrate datasets from multiple sources.
 Until state and local transportation agencies complete their migration to the
cloud, SI and geoanalytic applications seem a logic alternative to streamline
data workflows.
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