###### Abstract  
In unstable atmospheric conditions, using on-board irradiance sensors is one of the only robust methods to convert unmanned aerial vehicle (UAV)-based optical remote sensing data to reflectance factors. Normally, such sensors experience significant errors due to tilting of the UAV, if not installed on a stabilizing gimbal. Unfortunately, such gimbals of sufficient accuracy are heavy, cumbersome, and cannot be installed on all UAV platforms. In this paper, we present the FGI Aerial Image Reference System (FGI AIRS) developed at the Finnish Geospatial Research Institute (FGI) and a novel method for optical and mathematical tilt correction of the irradiance measurements. The FGI AIRS is a sensor unit for UAVs that provides the irradiance spectrum, Real Time Kinematic (RTK)/Post Processed Kinematic (PPK) GNSS position, and orientation for the attached cameras. The FGI AIRS processes the reference data in real time for each acquired image and can send it to an on-board or on-cloud processing unit. The novel correction method is based on three RGB photodiodes that are tilted 10\({}^{\circ}\) in opposite directions. These photodiodes sample the irradiance readings at different sensor tilts, from which reading of a virtual horizontal irradiance sensor is calculated. The FGI AIRS was tested, and the method was shown to allow on-board measurement of irradiance at an accuracy better than \(\pm\)0.8% at UAV tilts up to 10\({}^{\circ}\) and \(\pm\)1.2% at tilts up to 15\({}^{\circ}\). In addition, the accuracy of FGI AIRS to produce reflectance-factor-calibrated aerial images was compared against the traditional methods. In the unstable weather conditions of the experiment, both the FGI AIRS and the on-ground spectrometer were able to produce radiometrically accurate and visually pleasing orthomosaics, while the reflectance reference panels and the on-board irradiance sensor without stabilization or tilt correction both failed to do so. The authors recommend the implementation of the proposed tilt correction method in all future UAV irradiance sensors if they are not to be installed on a gimbal. d rone; unmanned aerial vehicle; UAV; irradiance; reflectance factor; tilt stabilization 2018 10.3390/rs10122068 10.3390/rs10122068 10.  
images of radiance or digital number (DN) level. The numeric values in such images are always affected by the varying illumination conditions, making it impossible to compare data acquired at different times, or to use it for quantitative analysis. To solve this, the radiance images need to be converted to reflectance factors and thus made invariant of the intensity of illumination i.e., irradiance. The reflectance factor conversion is done by normalizing the pixel radiance values (\(L\)) by irradiance of illumination (\(E\)) that was present at the target during the image exposure (\(R=\frac{1}{\pi}L/E\)) [2; 3]. In an idealized case, this is enough to characterize and normalize the illumination received by the target. In studies requiring the highest accuracy, e.g., reflectance anisotropy or bidirectional reflectance factor (BRF) analysis [4; 5; 6], the solar zenith angle and angular distribution (diffuse vs. direct) of illumination should also be known. However, usually this is not necessary and is left out, being too complicated to take into account. The current standard methods for the reflectance factor conversion can be distributed into roughly four categories: **(1)** The \"atmospheric model\"--methods where the irradiances are calculated using simulation or modeling of the atmosphere. These methods are the standard method for satellite applications [7; 8], and are also used commonly in airplane or high-altitude UAV-based remote sensing [9; 10]. Unfortunately, these methods work accurately only in stable blue-sky conditions and fail completely in the presence of broken clouds. In addition, in practice, too often the real atmospheric parameters are not used, but the simulation is based just on the generic atmospheric parameters for the applicable climate.