The comparison of airborne laser scanning-based probability layers as auxiliary information for assessing coarse woody debris

Abstract

During the past 15 years the assessment of biodiversity has become increasingly important in forestry. Dead wood (coarse woody debris, CWD) has been recognized as one of the strongest indicators of forest biodiversity, and therefore, much attention has been paid to CWD assessment. This study investigated whether airborne laser scanning (ALS)-based auxiliary information gathered from an independent study area is useful in guiding the sample-based field inventory of CWD. The auxiliary information was used in the design phase by implementing probability proportional to size (PPS) sampling with fixed-sized plots and initial sample units in adaptive cluster sampling (ACS). Furthermore, auxiliary information was used in the estimation phase in the form of ratio and regression estimations. ALS-based metrics and a logistic regression model were used in producing probability layers utilized as auxiliary data values. The sampling methods were compared based on the accuracy of mean volume (m3 ha−1) estimates for CWD with fixed input effort specified as field working hours. When ratio and regression estimation was used with fixed-sized plots, the increase in sampling efficiency was 4.6% and 6.0%, respectively. The use of auxiliary information in the design phase improved the efficiency considerably; the efficiency of ACS improved by 12.0% whereas the inventory of fixed-sized plots was as much as 16.7% more efficient when ALS data were used.