This document summarizes research analyzing the airport service areas in the Midwest using the Huff model. The Huff model determines service areas based on an airport's attractiveness, measured by passenger enplanements, and distance from locations. The research objectives were to create a map of airport service areas in the Midwest and determine which airports Iowans tend to use. Airport and enplanement data from 25 major Midwest airports was analyzed using the Huff model with different parameter values to estimate service areas. Maps were produced showing each location's highest probability of using a particular airport based on attractiveness and distance.

1. Airport Service Areas in the Midwest
Joel Heilman
Airport Service Areas in the Midwest
Joel Heilman
Abstract
There are several factors that affect which airport
customers use. The biggest factors are the size and
travel time to the airport. The huff model uses
attractiveness and distance to determine the
service areas of particular services or businesses.
Using the size of the airports as attractiveness, it
was possible to determine the service area of each
airport.
Research Objectives
•Create a map of the service areas of airports in the
Midwest using the Huff model.
•What Airports do Iowans tend to use?
Data
•Airport Shapefile from MapCruzin.com joined
with 2010 Enplanement data from the Federal
Aviation Administration.
•Region of the Midwest selected and the
airports with the top 25 Enplanements
selected.
•Enplanements represent the relative size of
the airport
Methodology
Results/Maps
Conclusions
•Huff model is very effective at what it does
•There is some empirical estimation from
estimating the parameters
•Considers distance, and not pure travel time
Huff model:
P= AX
/ DY
Where:
P= Probability Consumer will use
location
A= Attractiveness (Enplanements)
D= Distance (Euclidian Distance)
X= Attractiveness Parameter
Y= Distance Decay Parameter
Attractiveness Parameter (X)= 1
Distance Decay Parameter (Y)= 1
Attractiveness Parameter (X)= 0.5
Distance Decay Parameter (Y)= 2
Highest Position Tool determines the
highest probability of each pixel