Abstract
The potential of close-range photogrammetry (CRP) to compete with terrestrial laser scanning (TLS) to produce dense and accurate point clouds has increased in recent years. The use of CRP for estimating tree diameter at breast height (DBH) has multiple advantages over TLS. For example, point clouds from CRP are similar to TLS, but hardware costs are significantly lower. However, a number of data collection issues need to be clarified before the use of CRP in forested areas is considered effective. In this paper we focused on different CRP data collection methods to estimate DBH. We present seven methods that differ in camera orientation, shooting mode, data collection path, and other important factors. The methods were tested on a research plot comprised of European beeches (Fagus sylvatica L.). The circle-fitting algorithm was used to estimate DBH. Four of the seven methods were capable of producing a dense point cloud. The tree detection rate varied from 49% to 81%. Estimates of DBH produced a root mean square error that varied from 4.41 cm to 5.98 cm. The most accurate method was achieved using a vertical camera orientation, stop-and-go shooting mode, and a path leading around the plot with two diagonal paths through the plot. This method also had the highest rate of tree detection (81%).
Highlights
Forest inventory is the primary tool of forest management to collect data on various forest attributes that help managers make better decisions in consideration of multiple objectives
The tree identifications and estimates of diameter at breast height (DBH) were conducted for the successfully aligned meFtohuordosf(tmheetsheovedns m3 eatnhdod5s–w7)e.re successfully processed into dense point clouds
Overall accuracy varied from 49% tFoor81tr%ee. dTehteecctioomn wmiitshsiinotnheerprloort,wwaesapchrieesveendttwhehbeenstmreestuhlotsdws i5thaanndo6mwisesiroenuesrerodr; esqmualltotrees (DBH u13nduseirngsemveenthcoedn6t;imtheetehrigs)hecsatuosmediscsioomn merrisosriownaser3r4o(rms.ethod 7; Table 3)
Summary
Forest inventory is the primary tool of forest management to collect data on various forest attributes that help managers make better decisions in consideration of multiple objectives. Tree diameter at breast height (DBH) is one of the most important attributes in forestry. It provides fundamental information about trees and forest stands. Based on DBH, tree attributes, such as basal area, tree height, tree volume, and crown characteristics, can be estimated [1,2,3]. The DBH measurement is typically measured using a calliper or girth tape. Various non-contact dendrometers have been developed to measure DBH (e.g., optical callipers, Bitterlich’s relascope, dendrometers). Other tools have been developed to measure stem diameters at unreachable heights; their accuracy is typically lower compared to the contact dendrometers [4]. For forest inventory purposes, DBH is typically measured within sample plots.
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