Abstract: Objectives: Nighttime light (NTL) remote sensing is a unique optical observation technique for assessing urban development, analyzing human activity intensity, and monitoring light pollution. However, traditional satellite-based NTL data are constrained by coarse spatial resolution and limited temporal coverage due to fixed overpass time. In contrast, unmanned aerial vehicle (UAV), with their high spatiotemporal resolution and flexible deployment capabilities, offer a promising alternative for acquiring high-quality NTL imagery. Nevertheless, due to the significantly lower illumination at night compared to daytime, UAV NTL images are more susceptible to external factors such as camera settings and flight attitudes. Accurately evaluating the quality of UAV NTL imagery is therefore critical for ensuring the scientific validity of UAV NTL data. Methods: To comprehensively evaluate imaging quality, a series of controlled acquisitions focused on three primary dimensions: camera parameters, flight altitude, and tilt angle. Specifically, 24 combinations of ISO sensitivity (100 to 3200) and exposure time (1/15 s to 1/2 s) were tested at a constant f/2.8 aperture. Additionally, images were captured across seven flight altitudes (200 m to 500 m at 50 m intervals) and 13 tilt angles (0° to 60° at 5° intervals). Given the absence of reference images, the blind/referenceless image spatial quality evaluator (BRISQUE) algorithm was applied to quantitatively assess spatial image quality, with the goal of determining the optimal imaging configuration. Results: The results indicate that the best imaging quality was achieved with ISO 800 and an exposure time of 1/15 s, offering superior performance in noise suppression, motion blur control, and brightness balance. Flight altitude had a relatively minor impact on image quality within the 200 to 500 m. In contrast, tilt angle had a significant influence on both geometric distortion and image brightness. The geometric deformation increased approximately linearly with larger tilt angles, while the impact on brightness was more complex. Greater tilt angles improved the visibility of building facades but also introduced occlusion effects, leading to dimmer recorded brightness values. Conclusions: The result systematically analyzed the mechanisms affecting UAV NTL imaging quality and identified optimal acquisition parameters, providing a theoretical insight for future UAV NTL remote sensing applications.