By Clement Zhang, Founder, FlightBI

Understanding an airport’s catchment area has always been central to planning, forecasting, and air service development. But as traveler behavior evolves—and competition among airports grows—traditional, static approaches to defining catchment areas are no longer enough.

Why Catchment Definition Matters

A catchment area helps airports understand where their passengers come from, how far travelers are willing to drive, and where they may be choosing competing airports instead. This information supports everything from infrastructure planning to targeted marketing and airline engagement.

When catchment areas are defined too broadly or too narrowly, airports risk overstating demand, missing leakage, or misaligning resources. A more accurate, behavior-driven definition enables stronger route proposals and better strategic decision-making.

Different Approaches, Different Insights

Airports have historically used geographic approaches—such as simple radius maps, drive-time isochrones, or split-line boundaries between neighboring airports—to outline their catchment area. These methods are easy to communicate, but they do not reflect how travelers actually choose airports.

Modeled approaches, including gravity or Huff models, introduce additional factors like flight frequency, connectivity, and fares. These can offer valuable forecasts, especially in regions with multiple competing airports.

Today, many airports are turning to behavioral approaches that examine where passengers truly originate. Using ZIP-level booking patterns, mobility data showing resident travel, and hotel distribution data for visitors, airports can identify “dominant” areas where they capture the majority of demand—and where they are losing travelers to competitors. Tools such as Fligence ZIP-OD are examples of platforms that help airports perform this type of analysis, but a variety of datasets and methods can be used.

Catchment Areas Are Dynamic, Not Fixed

One important shift in recent years is recognizing that a catchment area is not a single, static boundary. It often changes based on:

• Route type: International flights typically pull from a much broader area than short-haul domestic routes.
• Trip purpose: Business travelers prioritize convenience, while leisure travelers may prioritize price.
• Seasonality: Visitor markets expand and contract throughout the year.

Dynamic, behavior-based catchment definitions allow airports to reflect these differences, offering a more accurate view of demand for specific routes or time periods.

A More Nuanced Understanding

Combining geographic, modeled, and behavioral approaches gives airports a fuller picture of how their community interacts with the air transportation system. Traditional drive-time maps remain helpful for illustrating accessibility, while behavioral data provides insight into real-world choices and leakage patterns.

By embracing a more flexible, data-rich approach, airports can better understand their true market—and build stronger, more evidence-based cases when working with airline partners.

 

Clement Zhang has over 25 years of experience developing data and technology solutions for the travel and transportation industry. He is the founder of FlightBI and previously served as Director of Business Intelligence at Cirium, Vice President of Product Development at Diio, and Vice President at MergeGlobal. He holds an MBA from Georgetown University and a Ph.D. from Xi’an Jiaotong University. Clement can be reached at clement.zhang@flightbi.com.

 

 

 

 

DISCLAIMER

This article was provided by a third party and, as such, the views expressed therein and/or presented are their own and may not represent or reflect the views of Airports Council International-North America (ACI-NA), its management, Board, or members. Readers should not act on the basis of any information contained in the blog without referring to applicable laws and regulations and/or without appropriate professional advice.