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Research article2016Peer reviewedOpen access

Local pivotal method sampling design combined with micro stands utilizing airborne laser scanning data in a long term forest management planning setting

Saad, Rami; Wallerman, Jörgen; Holmgren, Johan; Lämås, Tomas


A new sampling design, the local pivotal method (LPM), was combined with the micro stand approach and compared with the traditional systematic sampling design for estimation of forest stand variables. The LPM uses the distance between units in an auxiliary space - in this case airborne laser scanning (ALS) data - to obtain a well-spread sample. Two sets of reference plots were acquired by the two sampling designs and used for imputing data to evaluation plots. The first set of reference plots, acquired by LPM, made up four imputation alternatives (varying number of reference plots) and the second set of reference plots, acquired by systematic sampling design, made up two alternatives (varying plot radius). The forest variables in these alternatives were estimated using the nonparametric method of most similar neighbor imputation, with the ALS data used as auxiliary data. The relative root mean square error (RelRMSE), stem diameter distribution error index and suboptimal loss were calculated for each alternative, but the results showed that neither sampling design, i.e. LPM vs. systematic, offered clear advantages over the other. It is likely that the obtained results were a consequence of the small evaluation dataset used in the study (n = 30). Nevertheless, the LPM sampling design combined with the micro stand approach showed potential for improvement and might be a competitive method when considering the cost efficiency.


local pivotal method (LPM); segmentation; most similar neighbor (MSN) imputation; forest management planning; suboptimal loss; Lidar; Heureka; decision support system

Published in

Silva Fennica
2016, Volume: 50, number: 2, article number: 1414
Publisher: Finnish Society of Forest Science, Finnish Forest Research Institute