Inventory of small forest areas using an unmanned aerial system

Abstract

Acquiring high spatial and temporal resolution imagery from small unmanned aerial systems (sUAS) provides new opportunities for inventorying forests at small scales. Only a few studies have investigated the use of UASs in forest inventories, and the results are inconsistent and incomplete. The present study used three-dimensional (3D) variables derived from UAS imagery in combination with ground reference data to fit linear models for Lorey's mean height (h L), dominant height (h dom), stem number (N), basal area (G), and stem volume (V). Plot-level cross validation revealed adjusted R 2 values of 0.71, 0.97, 0.60, 0.60, and 0.85 for h L, h dom, N, G, and V, respectively, with corresponding RMSE values of 1.4 m, 0.7 m, 538.2 ha -1, 4.5 m 2 ·ha -1, and 38.3 m 3 ·ha -1. The respective relative RMSE values were 13.3%, 3.5%, 39.2%, 15.4%, and 14.5% of the mean ground reference values. The mean predicted values did not differ significantly from the reference values. The results revealed that the use of UAS imagery can provide relatively accurate and timely forest inventory information at a local scale. In addition, the present study highlights the practical advantages of UAS-assisted forest inventories, including adaptive planning, high project customization, and rapid implementation, even under challenging weather conditions.