To address the difficulties of unmanned aerial vehicle (UAV) nodes in networking on the same channel due to differences in available channels, especially under conditions of intense spectrum competition or dynamic electromagnetic environments, a multi-channel clustering algorithm for UAV Ad hoc networks based on adaptive node degree difference was proposed. Implementing a hierarchical clustering approach optimized for modularity, the algorithm calculated node similarity by including adaptive node degree difference under multi-channel conditions. The network modularity function was maximized to cluster large-scale UAV nodes, and network throughput was analyzed using the Bianchi model. Simulation results demonstrate that the proposed algorithm not only achieves a more balanced topology but efficiently increases network throughput compared to the Fast Unfolding, JS_CNC, and HVC_MCNC algorithms.