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Articles containing the keyword 'harvester data'

Category : Research article

article id 23023, category Research article
Lennart Noordermeer, Hans Ole Ørka, Terje Gobakken. (2023). Imputing stem frequency distributions using harvester and airborne laser scanner data: a comparison of inventory approaches. Silva Fennica vol. 57 no. 3 article id 23023. https://doi.org/10.14214/sf.23023
Keywords: forest inventory; airborne laser scanning; harvester data; inventory approaches
Highlights: We imputed stem frequency distributions using harvester reference data and predictor variables computed from airborne laser scanner data.; Stand-level distributions of stem diameter, tree height, volume, and sawn wood volume; (Enhanced) area-based and semi-individual tree crown approaches outperformed the individual tree crown method.
Abstract | Full text in HTML | Full text in PDF | Author Info
Stem frequency distributions provide useful information for pre-harvest planning. We compared four inventory approaches for imputing stem frequency distributions using harvester data as reference data and predictor variables computed from airborne laser scanner (ALS) data. We imputed distributions and stand mean values of stem diameter, tree height, volume, and sawn wood volume using the k-nearest neighbor technique. We compared the inventory approaches: (1) individual tree crown (ITC), semi-ITC, area-based (ABA) and enhanced ABA (EABA). We assessed the accuracies of imputed distributions using a variant of the Reynold’s error index, obtaining the best mean accuracies of 0.13, 0.13, 0.10 and 0.10 for distributions of stem diameter, tree height, volume and sawn wood volume, respectively. Accuracies obtained using the semi-ITC, ABA and EABA inventory approaches were significantly better than accuracies obtained using the ITC approach. The forest attribute, inventory approach, stand size and the laser pulse density had significant effects on the accuracies of imputed frequency distributions, however the ALS delay and percentage of deciduous trees did not. This study highlights the utility of harvester and ALS data for imputing stem frequency distributions in pre-harvest inventories.
  • Noordermeer, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID https://orcid.org/0000-0002-8840-0345 E-mail: lennart.noordermeer@nmbu.no (email)
  • Ørka, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID https://orcid.org/0000-0002-7492-8608 E-mail: hans-ole.orka@nmbu.no
  • Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: terje.gobakken@nmbu.no

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