Angular reflectance effects are essential for radiometric calibration and the interpretation of remotely sensed data, yet remain difficult to characterize under realistic field conditions. This study presents a UAV-based approach for high-angular-resolution hyperspectral HDRF measurement over the Dunhuang Radiometric Calibration Site (DRCS). Six circular UAV flights were conducted at viewing zenith angles from 10° to 60° using a non-imaging hyperspectral sensor, with continuous ground-based irradiance measurements used to derive HDRF values in the 400–850 nm range. Ross–Li model fitting achieved high accuracy (R² > 0.968), while residual analysis identified systematic discrepancies associated with forward-scattering geometry and secondary illumination from nearby solar towers, with local residuals up to 4.5%. These results highlight the value of dense angular sampling and rapid UAV-based measurements for interpreting field-measured HDRF and for the informed application of reflectance models in calibration environments.

Unmanned aerial vehicles (UAVs) provide a flexible platform for surface reflectance measurement at spatial scales between ground observations and satellite remote sensing. This study develops a UAV-based spectroradiometric system for surface reflectance retrieval under natural illumination conditions using non-imaging hyperspectral sensors. The system integrates two stabilized spectroradiometers mounted on a UAV to simultaneously measure hemispherical downwelling irradiance and upwelling surface radiance at flight altitude, enabling reflectance retrieval through a radiance–irradiance ratio framework without relying on ground calibration targets or radiative transfer model inversion. Field experiments were conducted over agricultural plots, and the UAV-derived reflectance was quantitatively validated against ground-based dual-spectroradiometer measurements. The results demonstrate stable irradiance measurements during flight and good agreement between UAV- and ground-derived reflectance across the 400–900 nm spectral range. The proposed system offers a practical and reliable solution for hyperspectral reflectance retrieval using UAV platforms.