先进空中交通（Advanced Air Mobility, AAM）代表了城市交通的范式变革；然而，其成功实施高度依赖公众接受度，而低空电动垂直起降（electric vertical takeoff and landing, eVTOL）运行所产生的噪声已成为主要关切。现有研究通常采用A计权声级（LAeq）和昼夜平均声级（Ldn）等声学指标描述eVTOL噪声。本研究构建了一个基于地理信息系统（Geographic Information System, GIS）的框架，将eVTOL声学输出转化为表征高度烦恼人群比例（%HA）的空间分布图，案例为美国阿肯色州西北部一条典型医疗物资配送航线。结果表明，噪声与烦恼度总体随距航线距离增加而递减，其中下降阶段引发的烦恼度最高，其次为爬升阶段和巡航阶段。通过整合美国人口普查（Census）人口数据，估算高度烦恼个体数量并识别空间影响热点区域。进一步将噪声-烦恼度结果与航线距离及空域因素相结合，评估备选航线方案，识别兼顾多方需求的均衡路由策略。该框架将声学评估与人类主观响应相衔接，支持噪声敏感区域识别、航线方案比选以及社会可持续的AAM基础设施规划。

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.