Forest structural information derived from multi-angular FIFEDOM (Frequent Image Frames Enhanced Digital Ortho-rectified Mapping) data

Information on the distribution of forest species is critical to sustainable management of the forest resources. However, forest species structure information accuracy remains low. Most of the current multi-angle data algorithms are based on the satellite-borne or simulated datasets. In this study, we exploited the use of structural information derived from airborne data to compare the signatures from the ground survey. This investigation was carried out by using FIFEDOM (frequent image frames enhanced digital ortho-rectified mapping) data. This study used FIFEDOM data collected over the Algoma forest, Ontario, Canada, which has four dominant species, jack pine, black spruce, poplar and white birch. The accuracy of the radiometric and geometric multi-angle signature results were assessed against CASI (compact airborne spectrographic imager) data, which were collected at the same time and also compared to SPRINT model simulation results.