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Toolkit for Establishing Airport Catchment Areas (2023)

Chapter: Preliminary Analysis

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Page 13
Suggested Citation:"Preliminary Analysis." 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:"Preliminary Analysis." 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:"Preliminary Analysis." 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 16
Suggested Citation:"Preliminary Analysis." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
×
Page 16
Page 17
Suggested Citation:"Preliminary Analysis." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
×
Page 17
Page 18
Suggested Citation:"Preliminary Analysis." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
×
Page 18
Page 19
Suggested Citation:"Preliminary Analysis." National Academies of Sciences, Engineering, and Medicine. 2023. Toolkit for Establishing Airport Catchment Areas. Washington, DC: The National Academies Press. doi: 10.17226/27424.
×
Page 19
Page 20
Suggested Citation:"Preliminary Analysis." 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 20

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13 Preliminary Analysis Economic activities are the core driving force behind travel demand, including leisure traffic, business traffic, and cargo operations. As the nexus between airside activities and landside movements, airports function as critical infrastructure links connecting the air transportation network to local markets. Therefore, it is crucial to understand the local market, existing air services, and its geographic location of an airport before we can expect to establish the boundary of its catchment areas. This section summarizes key preliminary analyses that should be performed by airports prior to conducting the formal catchment area analysis. For a more detailed introduction of preliminary analysis, refer to Appendix B – Case Studies. Market Analysis Airports should consider acquire information provided by the United States Census Bureau (www.census.gov) to provide a comprehensive review of population, household, and their associated income for residents living in the vicinity of the airport. As this is one of the preliminary analyses, airports could use their Metropolitan Statistical Area (MSA), a formally defined geographic and statistical entity, as a proxy for airport catchment areas. For small airports that are not located in or near a MSA, they can use county-level data for the market study. Figure 1 and Table 1 present example of residential market analysis for Akron-Canton Airport (CAK) using information provided by the United States Census Bureau. Figure 1. Census tracts within the MSAs of Akron and Canton-Massillon

14 Table 1. Demographic and Economic Characteristics of Akron and Canton-Massillon MSAs Year Combined Population2 Combined Household2 Median Household Income3 Mean Household Income3 Akron Canton- Massillon Akron Canton- Massillon 2019 1,100,999 451,365 $57,158 $55,706 $80,800 $71,573 2018 1,103,500 450,670 $60,019 $51,624 $79,792 $66,980 2017 1,103,432 454,755 $56,106 $51,198 $75,838 $65,527 2016 1,103,502 447,873 $51,598 $50,811 $70,083 $66,227 2015 1,107,219 445,324 $51,580 $49,313 $70,288 $65,874 2014 1,107,748 442,968 $50,538 $47,729 $67,821 $62,048 2013 1,109,393 441,490 $49,984 $45,168 $67,507 $61,862 2012 1,105,717 442,650 $49,731 $45,157 $65,187 $57,113 2011 1,107,149 434,677 $47,032 $41,770 $62,438 $55,297 2010 1,106,189 440,944 $46,521 $42,365 $60,782 $55,183 Note: 1. Data are sourced from the American Community Survey (ACS) 1-year estimates data from 2010-2019 (United States Census Bureau, 2021e). 2. Population data are from American Community Survey Table DP05. 3. Household number and income data are from Table DP03. In addition to residential data, airports should also be aware of the travel demand created by businesses that are located near or around the subject airport. Statistics regarding local businesses can be accessed via the Statistics of US Businesses (SUSB) page, provided by the US Census Bureau, or through local counties or municipalities. See Table 2 for statistics of businesses located in MSAs around the Cleveland-Akron Airport. The results of the market analysis will later be used to estimate the number and purchasing power, which determines the air travel propensity (Gosling, 2014), of customers living within the airport catchment areas. Table 2. 2018 Enterprise Employment Size by Metropolitan Statistical Areas Near CAK Rank Metropolitan Statistical Areas Name Firms Employment Annual Payroll ($1,000) 30 Cleveland-Elyria, OH Metro Area 39,591 923,095 48,719,876 80 Akron, OH Metro Area 13,078 293,328 14,065,130 139 Canton-Massillon, OH Metro Area 7,091 150,596 6,108,802 Note: Data are sourced from the Annual Data Tables by Establishment Industry (United States Census Bureau, 2021b)

15 Air Services Analysis Understanding air services is particularly critical for airports located in a Multiple Airport Region (MAR) as the majority of travelers prioritize airline choice over airport choice (Ishii et al., 2009). For catchment areas of outbound traffic, the air service analysis will include an investigation of the popular destinations of outbound travelers and the associated passenger demand of each route. For inbound traffic, this task will address the origin and demand of popular routes. For US airports, the best available data sources are the Airline Origin and Destination Survey (DB1B) (Bureau of Transportation Statistics, 2019a) and U.S. Airline Traffic Databases (T100). Airports will be able to investigate top destinations for travelers who start their trips from the subject airports, either through direct flights or connecting via hub airports. The results of the air service analysis will later be used to construct different scenario-based catchment area analyses. Due to the bulk volume of DB1B and T100 data, airports are recommended to access such information through commercial data platforms/applications such as Cirium’s Diio Mi. By inquiring about historical Origin-Destination (OD) records, airports can quickly and conveniently establish top destinations preferred by outbound travelers and frequent origins for inbound visitors. Using the DB1B data, Figure 2 identifies the top outbound destinations (measured by annual passenger enplanements of flight legs leaving CAK) of CAK during 2010-2020. The results of air service analysis will later be used to estimate destination-based catchment area. Figure 2. Outbound traffic from CAK to top destinations during 2010 – 2020

16 Spatial Analysis In its essence, the airport catchment analysis determines the boundary of areas from which an airport is likely to pull traffic, either passenger or cargo. Therefore, the fundamental component of catchment analysis is spatial analysis. A refined spatial analysis would not only study the subject airport and its vicinity but also take into consideration the competing airports and ground transportation modes for accessing the airport. The spatial analysis provides key input for subsequent catchment area analysis. The spatial analysis calculates the travel distance/time from each geographic entity to the subject airport and nearby competing airports. Airports are recommended to use Geographic Information System (GIS) applications such as ArcGIS or QGIS for spatial analysis. In addition, Google Maps or Apple Maps also provide application programming interface (API) to support network analysis functions. The procedure of spatial analysis can be summarized as follows: • Select the appropriate geographic entity for analysis An introduction of geographic entities can be found in the Geographic Entities section of this document. Depending on the available resources and project objectives, airports can select either ZIP codes or census tracts as basic geographic entities. Airports need to note that the selection of geographic entity level will affect data collection requirements, the computation complexity, and the analysis results. • Determine the outer limit for analysis Though there could be travelers commuting extremely long distances to an airport to access commercial aviation, most travelers will only drive reasonable distances to airports. Airports should only focus on the majority of travelers by limiting the catchment area analysis to a certain range. This limit can be measured by travel time, such as 120 minutes from the subject airport. The limit can also be determined by competing airports. For instance, the catchment area of a smaller airport is unlikely to encroach into the vicinity of a larger airport nearby. This step needs to be completed by using the Create Buffer function (travel-time based) of GIS applications. All the geographic entities within this pre-determined outer limit will be retained for subsequent analysis. Figure 3 depicts a potential outer limit for analysis at Akron-Canton Airport by identifying census tracts located within a 150-minute drive of the airport. As shown, this area includes three other commercial airports potentially competing with CAK for airline passengers.

17 Source: Purdue University, generated using ArcGIS Figure 3. Census tracts within the 150-minute range from CAK  Find centroids of geographic entities within the pre-determined outer limit As each geographic entity represents a polygon on a map, it needs to be represented by a single point in order to calculate distances between the airports and different geographic entities. This step needs to be completed by using the Find Centroids function of GIS applications such as ArcGIS or QGIS. See Figure 4 for centroids of census tracts within the 150-minute driving time range to Akron-Canton Airport.

18 Source: Purdue University, generated using ArcGIS Figure 4. Centroids of census tracts within the 150-minute range from CAK  Calculate distances between centroids of included census tracts to the subject and competing airports This step will create a driving distance/time matrix between included census tracts and all airports involved in the analysis. Similar to Steps 2 and 3 in Spatial Analysis, this step can be completed using GIS applications such as ArcGIS Pro or QGIS. As we are considering generic situations rather than specific traffic conditions, we used the basemap in the ArcGIS Pro and the routing service provided by the software. To better simulate travelers’ decision-making process, the shortest driving time option should be used when calculating driving time/distances. Figure 5 shows driving paths between the centroids of three selected census tracts and CAK, Cleveland Hopkins International Airport (CLE), John Glenn Columbus International Airport (CMH), and Pittsburgh International Airport (PIT) airports using the fastest driving time option in routing planning. Driving distances and driving time will later be used as input data in computing the cost of ground access.

19 Source: Purdue University, generated using ArcGIS Figure 5. Driving paths from included census tracts to CAK and nearby airports (CMH, CLE, & PIT) Table 3 shows driving distances and driving times from census tracts that are within the pre-determined outer limit to CAK, CLE, CMH, and PIT, using the fastest driving time option in routing planning. Driving distances and driving time will later be used as input data in computing the cost of ground access. The results of spatial analysis will be later used as input data for several analytical tools.

20 Table 3. Driving Distance and Time from Included Census Tracts to CAK and Nearby Airports (CMH, CLE, & PIT) Census Tract GEOID Airport Driving Distance (miles) Driving Time (minutes) 39009973000 CMH 76.48 77.64 CAK 168.66 159.78 CLE 208.13 193.23 PIT 196.79 201.66 39009973300 CMH 81.12 81.31 CAK 167.95 156.36 CLE 212.76 196.90 PIT 196.08 198.25 39009973600 CMH 95.76 97.58 CAK 148.55 138.45 PIT 176.67 180.33 CLE 202.09 193.40 … … … …

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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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