Traditional manual and satellite monitoring for unauthorized land-use parcels face limitations in timeliness, coverage, and efficiency. To address these challenges, this study proposes an automated full-process verification framework driven by an unmanned aerial vehicle (UAV) hangar system. Operating on a three-tier "cloud-edge-terminal" architecture, the framework seamlessly integrates five sequential links: intelligent scheduling, automatic data acquisition, real-time transmission, semantic interpretation, and result dissemination. Its core technical stack features direct georeferencing, parcel segmentation, and adaptive path planning. Specifically, a dynamic routing strategy combining an improved A* algorithm for local obstacle avoidance with Ant Colony Optimization (ACO) for global multi-target planning is introduced to accelerate inspection response speeds, achieving a closed-loop automation of parcel detection, verification, and evidence collection.</p> <p>To validate technical feasibility and adaptability, a field experiment was conducted in Shanghai, China, utilizing 6 UAV hangar base stations to inspect 120 target parcels (including 32 slender-shaped ones). Experimental results demonstrate that the system-generated routes achieved 100% coverage completeness—fully capturing all parcel boundaries within the camera’s effective field of view—while minimizing redundant traversal. Furthermore, the framework reduced manual operation time by 75% compared to traditional manual planning methods, requiring human intervention only for final result validation. Parametric configuration also enables rapid system adaptation to diverse regulatory scenarios, providing an efficient technical paradigm for targeted supervision in territorial governance.