Fixed-wing drones, known for their superior energy efficiency and speed, are increasingly used in applications such as environmental monitoring and long-range missions. While they offer advantages over quadrotors in terms of distance and endurance, they remain underdeveloped in research due to the challenges they present. Precision in tasks like landing and altitude estimation relies heavily on accurate motion sensing and control, typically achieved through optical flow (OF) estimation. However, at high speeds, conventional cameras struggle with issues like motion blur and limited dynamic range, which can compromise the quality of OF data. To overcome these limitations, this work explores the use of neuromorphic cameras, which mimic biological vision by responding to brightness changes at the pixel level.