Using Spatial Analytics to Streamline Data Workflows in Transportation Planning Transit, Freight,...
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Using Spatial Analytics to Streamline Data Workflows in Transportation Planning Transit, Freight, and Airports Case Studies By Arturo Bujanda 2014 Border
Using Spatial Analytics to Streamline Data Workflows in
Transportation Planning Transit, Freight, and Airports Case Studies
By Arturo Bujanda 2014 Border to Border Transportation Conference
November 19, 2014
Slide 2
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
Objectives 2
Slide 3
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. 3
Slide 4
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
What is spatial intelligence and geoanalytics? 4
Slide 5
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. 5
Slide 6
Spatial Intelligence and Geoanalytic Tools: Main Interface of
Esri Business Analyst (BA) 6
Slide 7
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
Data structure 7
Slide 8
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 20052009
data from the ACS is available in GIS- ready format 8
Slide 9
BA provides the following levels of geography for data
analysis: U.S. Sate Core-based statistical area (CBSA) Designated
market area (DMA) County County subdivision Place Zip code Tract
Block group Congressional districts 9
Slide 10
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
Geoanalytic tools useful in transportation planning 10
Slide 11
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. Enhancing Shopping Center Performance A Formula
for Revitalization ArcUser, Summer 2010 A Formula for
Revitalization PETCO Improves Location Selection Integrated
Solutions for Retailers, May 2010 PETCO Improves Location Selection
Finding Success in a Soft Economy ArcNews, Spring 2009 Finding
Success in a Soft Economy The Who, What, Where, and How About
Customers, Constituents, Donors ArcNews Online, Winter 2008/2009
The Who, What, Where, and How About Customers, Constituents, Donors
Nonetheless, we have found that some of such tools offer great
potential for their application in TDM and transportation planning
purposes 11
Slide 12
Settings for Data Apportionment Areas 12
Slide 13
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
Case studies 13
Slide 14
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. 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.
14
Slide 15
Original TAZs and AGEBs merged into resultant Super-zones and
were used to extract data from BA 15
Slide 16
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). 16 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.
Slide 17
Business centers in BA 2010 and BRT stops along the Las Vegas
MAX BRT line (Galicia, 2010) 1 17
Slide 18
BA Trade Area Creation Process Used to Extract Demographic Data
(Galicia, 2010) 1 18 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.
Slide 19
Service Coverage Area for Las Vegas MAX along the BRT Corridor
(Galicia, 2010) 1 19
Slide 20
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 PasoJuarez
binational region. 20
Slide 21
Identification of Freight Generation Clusters for Potential
Intermodal Terminal Locations 21
Slide 22
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. 22
Slide 23
Driving Distances from the Mexico Border System Airports Based
on Primary Highways 23
Slide 24
24
Slide 25
Real Influence (Cross-Border) Area of Texas Airports 25
Slide 26
Driving Times from the Texas Border Airports: 10, 20, and 40
minutes 26
Slide 27
27
Slide 28
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
Assisting transportation planning efforts 28
Slide 29
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.
29
Slide 30
As demonstrated by the airports case study: 30 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.
Slide 31
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:
31 Population between 10,000 and 30,000 people Avg household income
of over $75,000 Median age of 2550 years 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:
Slide 32
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:
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. 32
Slide 33
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. 33
Slide 34
Agenda Objective What is spatial intelligence and geoanalytics?
Data structure Geoanalytic tools useful in transportation planning
Case studies Assisting transportation planning efforts Conclusion
34
Slide 35
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. 35