The outcomes of remote sensing models are not always generalizable because the need for an efficient and trustworthy quantitative approach independent of the experiment circumstance has constrained the ability to translate them to another time and space.
There has been a significant expansion of UAS-based remote sensing in various industries, including agriculture and environmental research. However, the outcomes of remote sensing models are not generalizable because the ability to translate them to another time and space has been constrained by the lack of an efficient and trustworthy quantitative approach independent of the experiment circumstance. The sun-camera geometry is one of the most significant error factors degrading the UAS-based remote sensing data. This study analyzes how the geometry of the sun-camera affects the reflectance of a variety of specialized crops, such as citrus, almond, and grapes. It quantifies the size of the effect and presents a workable method to consider these effects. We discovered that for comparable canopies, a view angle shift of just 2° results in a noticeably different reflectance. The canopy reflectance measured from various view angles in the cameras' Field of View (FOV) could vary by more than 50% of the nadir view due to the directed solar radiation. Results reveal that these differences are not insignificant (contrary to commonly held beliefs in the literature) and that compensating for directional effects is necessary for the practical application of remote sensing data.
We created a model based on the Laplacian distribution function to estimate the intensity variation in aerial photographs in the major plane and cross-plane. Using the developed model, which has an r2 of up to 0.88 depending on the band, crop, and other variables, the nadir reflectance of each canopy may be determined from different view angles. The model's performance was assessed using the 4Sail radiative transfer model as a baseline.
The results of this study were used to calculate the ideal flight time as a function of the date, the FOV of the camera, and the latitude of the site. This will make it easier to adjust for the solar angle effect and prevent the acquisition of erroneous data.
Figure bellow shows the recommended flight time in the central valley of California to avoid darkspot and hotspot throughout the year. The times are without considering daylight saving times.
Recommended flight time in the central valley of California to avoid darkspot and hotspot throughout the year. The times are without considering daylight saving time.
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Media Resources Jafarbiglu, H., & Pourreza, A. (2023). Impact of sun-view geometry on canopy spectral reflectance variability. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 270-286.