Abstract

In this article we introduce a new method for forest management inventories especially suitable for highly-valued timber where the precise estimation of stem parameters (diameter, form, and tapper) plays the key role for market purposes. The unmanned aerial system (UAS)-based photogrammetry is combined with terrestrial photogrammetry executed by walking inside the stand and the individual tree parameters are estimated. We compare two automatic methods for processing of the point clouds and the delineation of stem circumference at breast height. The error of the diameter estimation was observed to be under 1 cm root mean square error (RMSE) and the height estimation error was 1 m. Apart from the mentioned accuracy, the main advantage of the proposed work is shorter time demand for field measurement; we could complete both inventories of 1 hectare forest stand in less than 2 h of field work.

Highlights

  • IntroductionIncreasing demands for sustainable forestry require highly precise and fast forest inventories

  • Increasing demands for sustainable forestry require highly precise and fast forest inventories.Tree height and diameter at breast height (DBH) are the most important parameters in taking forest inventories

  • Based on the comparison of geodetic surveys, we found out that terrestrial photogrammetry (TP)-based tree positions reached the positional accuracy with root mean square error (RMSE) lower than 0.5 m with maximum of almost 1 m (Table 3)

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Summary

Introduction

Increasing demands for sustainable forestry require highly precise and fast forest inventories. Tree height and diameter at breast height (DBH) are the most important parameters in taking forest inventories. DBH is usually measured manually with a caliper or a measuring tape and it is recorded together with species during field inventories [1]. Tree height is usually measured by a height measuring instrument based on angle and distance measurements. The spatial information (horizontal structure of stand or tree positions) is difficult to obtain, it represents important information regarding the forest inventory itself (the stem density) as well as for studies of distance-dependent growth and dynamics of trees and stands [2]. Manual inventory methods for collecting forest information used nowadays are labor cost- and time-demanding and there is a need to find alternative methods.

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