An ArcGIS Framework for Mapping Human-Centered Noise Annoyance for AAM Infrastructure Planning

Abstract

Advanced Air Mobility (AAM) represents a transformative shift in urban transportation; however, successful implementation depends strongly on public acceptance, with noise emerging as a major concern for low-altitude electric vertical takeoff and landing (eVTOL) operations. Existing studies commonly describe eVTOL noise using acoustic metrics such as A-weighted sound level and day-night average sound level. This study develops a Geographic Information System (GIS)-based framework that translates eVTOL acoustic outputs into maps representing the percentage of the population that is highly annoyed (%HA) for a representative medical delivery route in Northwest Arkansas. The results show that noise and annoyance generally decrease with distance from the route, while the highest annoyance occurs during descent, followed by climb and cruise. Census population data are integrated to estimate the number of highly annoyed individuals and identify spatial impact hotspots. Noise-annoyance results are then combined with route distance and airspace factors to evaluate alternative routes and identify balanced routing strategies. The proposed framework connects acoustic assessment with human response and supports the identification of noise-sensitive areas, comparison of route alternatives, and socially sustainable AAM infrastructure planning.