Toward a comprehensive model for estimating diameter at breast height of Japanese cypress (Chamaecyparis obtusa) using crown size derived from unmanned aerial systems

Abstract Observing Forest attributes using small, weighted unmanned aerial systems (UASs) is increasing interest to forest ecologists and managers. Here, we provide a comprehensive model for estimating the relationship between diameter at breast height (DBH) and crown size for Japanese cypress (Chamaecyparis obtusa), intending to promote the use of UAS-acquired data. Aerial images were processed using Structure from Motion software to develop ortho-mosaicked imagery for the study sites. We also measured the DBH and height of 196 individual trees at these same sites. Crown size, estimated from the orthoimagery, was compared with DBH using multiple functional models. Model fit estimates has ranged from R2 = 0.6403–0.7584 and root mean square error (RMSE) = 6.34 cm–5.20 cm (relative RMSE (rRMSE) = 17.83–13.44%). Including tree height as a predictor improved model fit of both linear and Support Vector Regression (SVR) model, where the best result in Adjusted R2 = 0.834 and RMSE = 4.25 cm (rRMSE = 11.30%) for the SVR model. This study suggests the potential for accurately surveying forest attributes through UAS remote sensing, which has important implications for forest monitoring and management.