With the rapid development of the urban low-altitude economy, unmanned aerial vehicles (UAVs) have been increasingly employed in logistics, infrastructure inspection, and urban surveillance. However, ensuring UAV flight safety in complex urban environments has become a growing concern, highlighting the importance of efficient and reliable path planning in low-altitude urban spaces. Most existing path planning approaches primarily focus on factors like population density and building obstacles, often overlooking the influence of wind, which can lead to deviations in UAV flight paths and even accidents. To address this issue, this study employs the PiFlow software. A complex model of New York City is first simplified to create a geometric representation of urban blocks. Wind field simulations are then performed by inputting urban terrain data and computational parameters into the model. These simulations provide wind information along the UAV’s flight path, enabling comprehensive assessment of its control performance. The results demonstrate that incorporating wind field analysis enhances real-time flight monitoring and offers a reliable foundation for developing effective UAV path planning strategies in urban low-altitude scenarios.