National Academies Press: OpenBook

Toolkit for Establishing Airport Catchment Areas (2023)

Chapter: Post-Analysis Recommendations

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Page 87
Suggested Citation:"Post-Analysis Recommendations." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
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Suggested Citation:"Post-Analysis Recommendations." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
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Suggested Citation:"Post-Analysis Recommendations." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
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Suggested Citation:"Post-Analysis Recommendations." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
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Page 90

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87 Post-Analysis Recommendations Analytical tools introduced in the Tools for Catchment Area Analyses section can help users of this toolkit create a list of geographic entities representing airport passengers’ origins and the corresponding number of passengers from each geographic entity. Such data need to be plotted on maps so that airport catchment areas can be intuitively visualized. In this section, we recommend tools that can be used for catchment visualization, introduce different geographic entities that are appropriate for airport catchment area analysis, and provide guidance on how to maintain the currency of catchment area analysis (2022a). Catchment Visualization Tools Multiple tools are available to visualize catchment area analysis results. The results will be plotted in the form of a map, with each geographic entity colored differently based on the number of travelers from that entity. This visualization style is termed a choropleth map (Ingram & Rhodes, 2020). This section introduces popular tools that can be used to create choropleth maps. Microsoft Excel Excel can be used to show “categories across geographic regions” (Microsoft, 2022a). To create a choropleth map in Excel, users need to convert variables representing different geographic entities into geography data types. Detailed instructions on data conversion can be found at Microsoft (2022a). Once this is completed, then choropleth maps can be created by following these steps: Insert tab > Charts > Maps > Filled Map. Note this procedure may vary depending on the version of Microsoft Office and operating systems. Capabilities – Straightforward to deploy – Widely available in most workplaces – Capable of plotting high-level geographic details from countries/regions, states, counties, or postal codes – Does not support latitude/longitude, street address, census tracts, or census blocks – Choropleth maps may not be customizable Tableau Tableau is an interactive data visualization software capable of creating choropleth maps. The software allows users to connect the data file of airport catchment area analysis with various shapefiles or GeoJSON files, thus enabling the drawing last data on multiple geographic entity levels. Federal and state government agencies, professional organizations, and research institutions have made a large amount of historical and current shapefiles publicly available. Instructions for mapping in Tableau can be accessed via Tableau (2022a). Capabilities – Dedicated data visualization software – Capable of connecting with external shapefile and GeoJSON files

88 – Supports large data files – Can plot choropleth maps of all geographic entity levels – Has a monthly subscription cost – Has a number of requirements for data formats – Employees without prior experience may need extra training before adoption GIS Software (ArcGIS or QGIS) Dedicated GIS software, such as ArcGIS or QGIS can create choropleth maps and perform a wide range of spatial analysis. Both ArcGIS and QGIS provide tutorials in helping users with different experiences make and use choropleth maps, for instance, Esri (2022) and National Oceanic and Atmospheric Administration (NOAA) (2022). Capabilities – Preset tools for a wide range of GIS analysis – Able to handle a large amount of vector data – Functionality in building a dashboard to monitor events, make decisions, inform others, and see trends – ArcGIS has a subscription cost (QGIS is free-and-open-source) – GIS software normally has high requirements for hardware – Both ArcGIS and QGIS require dedicated training prior to use Programming Languages (Python, R, & JavaScript) There are several programming languages that are commonly adopted for in-depth GIS analysis, including creating choropleth maps. Due to their open-source ecosystem and great community contributions, these languages have a large number of libraries, packages, and extensions for various applications, including mapping and data analytics. For instance, Python has Matplotlib, Plotly, NumPy, Pandas, and Geopandas, and is incorporated into ArcGIS, QGIS, GRASS GIS, and gvSIG. JavaScript supports ArcGIS Web APIs, MapBox, CARTO, Google Maps API, OpenLayers, and Leaflet, making it a viable choice for the development of web mapping applications (Cioloboc, 2016). Meanwhile, R supports rgdal, rgeos, ggplot2, ggmap, mapview, and leaflet, which are popular choices for spatial analysis and visualization (R-project, 2022). Capabilities – Versatile, supported by an extended list of libraries – Has much community support – Open-source-and-free – Requires extensive training, and the learning curve can be steep for people with no prior programming experience – Can take much time to build initial analysis

89 Geographic Entities & Geographic Identifiers (GEOIDs) When it comes to mapping airport catchment areas, the geographic entity is a basic concept that researchers frequently come across. As its name suggests, a geographic entity represents an area with a certain shape and size. The Census Bureau uses different geographic entities to maintain and tabulates data (United States Census Bureau, 2021c). In general, geographic entities are categorized as either legal/administrative or statistical (United States Census Bureau, 2021c). Examples of legal/administrative geographic entities include states, counties, minor civil divisions, congressional districts, school districts, and incorporated places. And examples of statistical geographic entities are census tracts, metropolitan/micropolitan statistical areas, urban areas, and census-designated places. For airport catchment area analysis, the most frequently used geographic entities are ZIP Code Tabulation Areas (ZCTAs) (United States Census Bureau, 2022b) and census tracts, considering how data are collected and aggregated. Higher-level geographic entities, such as counties, are occasionally used due to the restrictive nature of collected data, for instance, in the case of license plate analysis. However, information summarized at the county level does not offer detailed insight for airports to examine how they interact with potential markets. On the opposite side, certain data are available at finer geographic entity levels, such as block groups or census blocks. Analysis conducted at such levels could potentially increase computational costs while contributing little incremental value for airports compared with studies on the census tract level. Another basic concept in airport catchment area analysis is geographic identifies, or GEOIDs. According to the United States Census Bureau (2021e), “GEOIDs are numeric codes that uniquely identify all administrative/legal and statistical geographic areas for which the Census Bureau tabulates data.” There are different types of GEOIDs maintained by different government agencies and organizations. We recommend using Federal Information Processing Series (FIPS) codes and Geographic Names Information System (GNIS) codes for catchment area analysis of US airports (United States Census Bureau, 2022a). Catchment Area Analysis Maintenance Air transportation is dynamic and competitive. Inside airports, new air services are being proposed and offered while existing services are axed constantly to optimize operational and financial performance. Outside airports, socioeconomic factors of the region where an airport is located may undergo significant changes over the years, thus causing temporary or permanent changes to the traveling passengers of an airport. We summarize a few scenarios here in this section that can trigger the airport to review their catchment area analysis to ensure the analysis results are still current and relevant. Scheduled maintenance • Minor checks – Airports conduct operations reviews frequently, e.g., quarterly and annually. Likewise, airports should also periodically examine their last catchment area analysis to check if input conditions to each analytical tool have any significant changes. For instance, the Travel Utility Analysis tool uses the value of travel time savings (VTTS) as key input to calculate the travel utility of different itineraries. If the Department of Transportation (2016) publishes the latest VTTS or updates its guidance on the valuation of travel time, then the airport should update its Travel Utility Analysis as well.

90 • Major checks – Considering the fast pace of the air transportation sector, airports should consider re-do their catchment areas every three to five years regardless. Such comprehensive reviews allow airports to systemically examine their markets, air services, and competitions. Not only will airports receive up- to-date catchment area maps, but they will also be able to use the analysis results as key inputs for other strategic plannings. Unscheduled maintenance In addition to scheduled minor checks and major checks, there are a few significant events that can trigger airports to review or re-do catchment area analysis. Such events include but are not limited to: • Significant enplanement change – If the subject airport has experienced significant passenger enplanement changes, either increase or decrease, while the enplanement numbers at nearby competing airports either remain stable or move in the opposite direction, this is a strong indicator that there may be undetected factors that have caused structural changes to the traveling population. The airport needs to re-examine its catchment areas and operations immediately. • Major capacity changes at the subject airport or competing airports – If there are any new airports constructed in the vicinity of the subject airport or major new airside projects planned and completed at the subject airport or competing airports, the subject airport needs to examine the induced demand by such projects as they may change how travelers choose department airport for their trips. • Major air services changes to the subject airport or competing airports – Though airports undergo air service changes often, there are some services that may cause a significant impact on the market composition. For instance, an airport becomes the hub or loses its hub status in airlines’ network; Low-cost carriers (LCC) or Ultra-low-cost carriers (ULCC) add or reduce services to an airport; An international carrier comes to the region for the first time, etc. Such air service changes will cause local travelers to re-think their travel plans and affect their itinerary choices. • External economic, climate, public health, or security shock events – External shock events, including economic/financial crisis, natural and climate diesters, public health crisis such as the COVID-19 Pandemic, and security-related policy updates such as new security check requirements after 9-11 could fundamentally affect how the public perceives and utilizes air transportation. While the impact of such events is more likely to be national or even international rather than local or regional, airports still need to re-investigate the effect on their own operations and update their practices and strategies accordingly.

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The catchment area of an airport encompasses areas where passengers are more likely to use the subject airport, even when there are other airport options in the vicinity.

ACRP Web-Only Document 56: Toolkit for Establishing Airport Catchment Areas, from TRB's Airport Cooperative Research Program, comprises various analytical tools, such as the Travel Utility Analysis tool, that enable airport industry practitioners to calculate the likely responses of travelers to different market and operational inputs, thus forecasting potential catchment areas for airports.

Supplemental to the report are three case studies: Case 1: Akron-Canton Airport (CAK), OH; Case 2: Ontario International Airport (ONT), CA; and Case 3: Albert J. Ellis Airport (OAJ), NC.

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