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Predicting the occurrence of large-diameter trees using airborne laser scanning.

Authors :
Korhonen, Lauri
Salas, Christian
Østgård, Torgrim
Lien, Vegard
Gobakken, Terje
Næsset, Erik
Source :
Canadian Journal of Forest Research. 2016, Vol. 46 Issue 4, p461-469. 9p.
Publication Year :
2016

Abstract

Large-diameter trees are important for both ecological and economic reasons, but they have become increasingly rare. Thus, there is an interest in easily locating such trees, and for this purpose, the use of airborne laser scanning (ALS) seems suitable. Our objective was to assess the accuracy of area-based ALS estimation in predicting the number of large-diameter Scots pines ( Pinus sylvestris L.). A sample of 856 trees with a diameter >35 cm were measured from 1109 sample plots located in eastern Norway. We fitted negative binomial and zero-inflated negative binomial models for predicting large-diameter tree counts. ALS-derived and external variables were used as predictors when fitting the models. The accuracy was assessed based on the weighted kappa coefficient and cross validation. Our best model was based on three ALS height distribution variables, one horizontal ALS variable, and plot elevation. Its overall accuracy was 65.8% and the weighted kappa was 0.55. Although there was a clear relationship between the response and the proposed predictor variables, fairly large errors in the predicted large-diameter tree counts were common. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00455067
Volume :
46
Issue :
4
Database :
Academic Search Index
Journal :
Canadian Journal of Forest Research
Publication Type :
Academic Journal
Accession number :
114149188
Full Text :
https://doi.org/10.1139/cjfr-2015-0384