Felling Outturn Assessment Using Earth Remote Sensing Data

Seismic exploration often demands forest clearing, thus making it important to assess the number of trees that must be cut down as the fieldwork proceeds. We suggest that remote sensing of the Earth’s surface with unmanned aircraft vehicles can be con-sidered as a new approach to solving this problem. To test its validity and potential utility, we installed a laser scanning system and a high-resolution camera on the unmanned aircraft vehicle. The data obtained were used to derive the digital terrain and elevation models of the area under study. The resulting models were processed with the help of a neural network developed as part of this work. They proved to be useful in identifying trees and their classes within the forest sites subjected to clearing. Additionally, a special algorithm was proposed and applied to assess the felling outturn for each tree class taken separately.