Optimizing Low-Altitude Urban Airspace: Identifying Free Route Airspace and Control Points Through Spatial Analysis

Advancements in unmanned aerial vehicles (UAV) technologies have increased the need for effective urban low-altitude airspace management. Traditional Air Traffic Management (ATM), designed for manned aviation, cannot handle the high-density, high-traffic urban low-altitude operations. This paper proposes a novel approach to low-altitude airspace management by integrating the Alpha-Shape algorithm with spatial syntax theory. The method begins by constructing reachable airspace in complex urban environments using the Alpha-Shape algorithm, effectively excluding areas obstructed by buildings and terrain. Subsequently, at the 30-m altitude layer with Alpha set to 30 m, visibility and integration analyses are conducted to assess the accessibility, connectivity, and centrality of the airspace. Based on these analyses, free route airspace (FRA) and airspace control point (ACP) are identified. This framework allows UAV to operate freely within designated FRA, with strategically placed ACPs ensuring safe entry and exit. Case studies demonstrate that the proposed approach significantly enhances airspace capacity, traffic flow, and operational flexibility compared to traditional methods.