Multi-Angular Reflectance Anisotropy Observed from UAV Multispectral Imagery
Researchers have developed a new workflow to extract multi-angular reflectance data from UAV multispectral imagery. This method accounts for radiometric variability caused by the drone's perspective and imaging system. Analysis of grassland data revealed significant reflectance anisotropy, particularly in red-edge and near-infrared bands, highlighting the impact of viewing geometry on radiometric consistency. AI
IMPACT Introduces a novel method for analyzing remote sensing data, potentially improving radiometric accuracy in multispectral imagery.