An analysis of the effect of the bidirectional reflectance distribution function on remote sensing imagery accuracy from Small Unmanned Aircraft Systems

Small Unmanned Aircraft Systems (SUASs) are increasingly being utilized for remote sensing applications due to their low-cost availability and potential for the collection of high-resolution on-demand aerial imagery. However, the field is still maturing, and there remains many questions on the accuracy and the validity of the data collected. While many researchers have investigated means of improving calibrations and data collection techniques, there are other sources of error that require investigation. In this paper, two unique characteristics of SUAS remote sensing are analyzed as potential sources of error: the use of wide field-of-view (FOV) imaging sensors and solar motion during one or more data collection flights. Both of these characteristics are related to the bidirectional reflectance distribution function (BRDF), a description of light reflection as a function of illumination direction and observer viewing angles. The wide FOV of many imaging equipment creates an inherent radial variation in viewing angle, and the solar motion creates a non-static illumination source. The results of this paper indicates that these two factors have significant contributions to errors and should not be assumed to be negligible.