Basal area and diameter distribution estimation using stereoscopic hemispherical images

In recent years, proximal sensing data has increasingly been used to optimize forest inventories. In this paper we present a forest inventory methodology based on stereoscopic hemispherical images. An automated pixel-based approach and a user-guided “region growing” approach have been developed for image matching. To estimate the basal area, number of trees and mean diameter, the sampling probability is determined for each tree. The accuracy and precision of the estimates derived from stereoscopic hemispherical images was analyzed for a set of National Forest Inventory plots. The results revealed that tree matching depends on the species, the distance to the target tree and the diameter. The Pearson correlation coefficient was 0.86 for the mean diameter and 0.89 for the basal area, whereas for the number of trees per hectare it was 0.59. The proposed methods may be used in large scale forest inventories as a cost-efficient way of obtaining data on diameter distribution and basal area from field surveys following a two-stage scheme combined with remote sensing techniques. © 2016 American Society for Photogrammetry and Remote Sensing.