The field of urban air mobility is rapidly advancing, with a focus on developing efficient and scalable infrastructure planning and optimization methods. Recent research has emphasized the need for integrated planning frameworks that account for spatial-temporal demand, heterogeneous user behaviors, and infrastructure capacity constraints. Novel optimization frameworks, such as those based on maximum covering location problems, have been proposed to address these challenges. Additionally, there is a growing interest in developing fair and distributed planning methods that can accommodate multiple stakeholders and competing goals. These advancements have the potential to enable the widespread adoption of urban air mobility systems, ensuring safe and efficient transportation in cities. Noteworthy papers include: The Maximum Coverage Model and Recommendation System for UAV Vertiports Location Planning, which proposes a novel optimization framework and integrated planning recommendation system for vertiport network design. Fair-CoPlan, which introduces a negotiated, semi-distributed flight planner that optimizes UAS flight lengths in a fair manner. FiReFly, which proposes a distributed fair motion planner that integrates fairness into multi-robot motion planning. Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring, which develops a decentralized vision-based multi-quadrotor system for wildlife monitoring.