Effect of airborne laser scanning accuracy on forest stock and yield estimates

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Markus Holopainen Name of the doctoral dissertation Effect of airborne laser scanning accuracy on forest stock and yield estimates Publisher School of Engineering Unit Department of Surveying Series Aalto University publication series DOCTORAL DISSERTATIONS 6/2011 Field of research Real Estate Economics Manuscript submitted 16.06.2010 Manuscript revised 01.11.2010 Date of the defence 11.02.2011 Language English Monograph Article dissertation (summary + original articles) Abstract The main objective of the study was to assess the magnitude of uncertainty of airborne laser scanning (ALS) -based forest inventory data in forest net present value (NPV) computations. A starting point was the current state of change in operative forest-planning in which traditional standwise field inventories (SWFI) are being replaced by area-based ALS inventories (A_ALS). The more detailed objectives were as follows: 1) to investigate the significance of the accuracy of current (SWFI, A_ALS) and future (ALS individual tree detection (ITD)) forest inventory methodologies applied in the timing of simulated loggings and in NPV computations, 2) to compare the forest-planning inventory methods currently applied with respect to the accuracy of the timber assortment information derived, 3) to investigate the sources of uncertainty related to the estimation of timber assortment volumes and economic values in forest management-planning simulations and 4) to compare the uncertainty related to inventory accuracy, growth models and timber price development in NPV computations at the standand forest property-level, using various interest rates. The study was carried out, using empirical and simulated forest inventory data, forest management-planning calculations and Monte Carlo simulations.The main objective of the study was to assess the magnitude of uncertainty of airborne laser scanning (ALS) -based forest inventory data in forest net present value (NPV) computations. A starting point was the current state of change in operative forest-planning in which traditional standwise field inventories (SWFI) are being replaced by area-based ALS inventories (A_ALS). The more detailed objectives were as follows: 1) to investigate the significance of the accuracy of current (SWFI, A_ALS) and future (ALS individual tree detection (ITD)) forest inventory methodologies applied in the timing of simulated loggings and in NPV computations, 2) to compare the forest-planning inventory methods currently applied with respect to the accuracy of the timber assortment information derived, 3) to investigate the sources of uncertainty related to the estimation of timber assortment volumes and economic values in forest management-planning simulations and 4) to compare the uncertainty related to inventory accuracy, growth models and timber price development in NPV computations at the standand forest property-level, using various interest rates. The study was carried out, using empirical and simulated forest inventory data, forest management-planning calculations and Monte Carlo simulations. It was shown that forest inventory errors led to significant mistiming of simulated loggings and subsequent prominent losses in simulated NPV. The most significant source of error in the prediction of timber assortment outturns was SWFI and A_ALS inventory error. The errors related to stem distribution generation, stem form prediction and bucking simulation were significant but considerably lower in magnitude than the inventory error. A_ALS interpretation led to accuracy levels similar to or better than that of SWFI. At the stand-level the growth models used in forest-planning simulation computations were the greatest source of uncertainty with respect to NPVs computed throughout the rotation period. Uncertainty almost as great was caused by A_ALS and SWFI data uncertainty, while the uncertainty caused by fluctuation in timber prices was considerably lower in magnitude. Forest property level deals with a considerably lesser degree of NPV deviation than does stand-level: A_ALS inventory errors were the most prominent source of uncertainty, leading to a 5.1-7.5% relative deviation in property-level NPV when an interest rate of 3% was applied. A_ALS inventory error-related uncertainty resulted in significant bias in property-level NPV estimates. The study forms a basis for developing practical methodologies for taking uncertainty into account in forest property valuation.