Preharvest efficiency of Trestima, airborne laser scanning and forest management plan data validated by actual harvesting results and forest engineer preharvest estimations
Dunaeva, Tatiana (2017)
Dunaeva, Tatiana
Yrkeshögskolan Novia
2017
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201704054248
https://urn.fi/URN:NBN:fi:amk-201704054248
Tiivistelmä
The study compares the accuracy of forest attribute estimates, delivered by airborne laser scanning data, conventional stand-wise forest inventory in the form of Forest Management Plan and Trestima forest inventory app, in the context of real preharvesting situation in 2016, with the forest stock sold on stump. The measurements are validated by actual results of commercial harvesting, measured and registered by a harvester’s measurement system during logging. There were also available preharvesting estimations carried out by a forest engineer acting on behalf of the forest owner, who arranged the timber sale, which as well became a part of the study as an additional subjective element for comparison.
The aim of this study was to compare the accuracy of the three inventory methods and to find the most accurate and informative method of measurement in the preharvesting conditions from a forest owner’s point of view. The compared parameters were set according to the harvesting report, i.e. timber total volume, volumes per tree species, number of stems as well as timber assortment volumes. Trestima turned out to be the most accurate and effective in predicting preharvest stand characteristics, stand-level-wise.
The aim of this study was to compare the accuracy of the three inventory methods and to find the most accurate and informative method of measurement in the preharvesting conditions from a forest owner’s point of view. The compared parameters were set according to the harvesting report, i.e. timber total volume, volumes per tree species, number of stems as well as timber assortment volumes. Trestima turned out to be the most accurate and effective in predicting preharvest stand characteristics, stand-level-wise.