As urbanization accelerates, and the “low-altitude economy” progressively integrates unmanned aerial vehicles and air-ground-space information networks, profound transformations are occurring in how urban space is utilized. This paper offers a systematic review of recent advances in urban Unmanned Aerial Vehicle (UAV) mission-scheduling research, which presents a comprehensive systems architecture—comprising a scheduling platform, infrastructure and decision-making mechanisms—and examines urban environment modelling approaches from both static and dynamic perspectives. The core focus lies on the four critical technical issues within the “evaluation-layout-allocation-planning” technology chain: air-space planning, infrastructure siting, task allocation and route planning. We identify the research trajectories in terms of constraints, optimization objectives and solution methods, and summarize typical deployment scenarios for the three service-provider categories—government, industry and the public—particularly highlighting applications in emergency rescue, infrastructure inspection and last-mile logistics delivery. Findings indicate that hybrid decision-making frameworks and dynamic modelling are emerging as key research trends in urban UAV scheduling, aimed at maximizing mission-completion efficiency. Drawing on the systematic review of urban UAV task scheduling, this work serves as a foundation for constructing a unified framework, standardizing key technical modules and guiding the design and implementation pathways for real-world deployment.