Recent initiatives from the federal government, such as Justice40, assert the need to ensure equitable distribution of economic benefits of infrastructure investment. Yet, there is little empirical work that assesses spatial-economic outcomes in airport-adjacent communities. To inform these equity goals in the context of cargo airport development, this study proposed a strategy for discerning the economic clustering characteristics of airport-adjacent communities relative to their metropolitan areas. The study focused on the 10 U.S. airports with the most airfreight in 2017. We used the local spatial statistic, the Getis–Ord [Formula: see text], to identify grid-based spatial clusters of regionally significant transportation and logistics economic activity. We further explored the extent to which those clusters were consistent across economic attributes (businesses, employees, and sales volume). The results demonstrated that the presence of business hot spots in the airport-adjacent community was not necessarily matched by hot spots of employment or sales volume. The study recommends the following spatial terminology to describe patterns of spatial-economic hot spots near airports: Compacted aerotropolis, Fragmented aerotropolis, Sector aerotropolis, Airea, Corridor, and Outlying. The study found that two airports fit the Fragmented aerotropolis model; two, the Compacted aerotropolis model; one, the Airea; one, Outlying; and four were inconsistent across economic variables. By dividing the study airports into these categories, we were able to discern the significance of the economic impacts on the airport-adjacent community and provide a spatial rhetoric that would be meaningful and accessible to a variety of stakeholders in the participatory planning process.


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    Title :

    Cargo Airport Planning: Discerning Spatial Distributions of Freight Development in Airport-Adjacent Communities


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2023-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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