An Algorithm for Forest Stem Volume Retrieval Under the Condition of Limited Auxiliary Information

This paper presents an algorithm for retrieving the stem volume of forest stands on relatively flat ground. A forest backscatter model at the individual tree level is used to derive the algorithm. This model treats the trunk volumes as random quantities and employs a concept of random forest reflection coefficient. The algorithm is derived under the assumption that the only information on areal tree density and mean value of the forest reflection coefficient is available. Performance of the algorithm is investigated by means of Monte-Carlo simulation for different scenarios in terms of statistical distributions for the trunk volume and forest reflection coefficient. The results of simulation have shown that the algorithm exhibits robustness to the distributions and provides accurate stem volume estimation over a relatively wide range of the unknown variances of the distributions.