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Use of Real‐Time GNSS‐RF Data to Characterize the Swing Movements of Forestry Equipment

Forest Operations Research Lab, College of Natural Resources, University of Idaho, 875 Perimeter Drive, Moscow, Idaho 83844‐3322, USA
Rocky Mountain Research Station, U.S. Forest Service, Missoula, Montana, 59801 USA
Author to whom correspondence should be addressed.
Forests 2017, 8(2), 44;
Received: 8 December 2016 / Accepted: 9 February 2017 / Published: 15 February 2017
The western United States faces significant forest management challenges after severe bark beetle infestations have led to substantial mortality. Minimizing costs is vital for increasing the feasibility of management operations in affected forests. Multi‐transmitter Global Navigation Satellite System (GNSS)‐radio frequencies (RF) technology has applications in the quantification and analysis of harvest system production efficiency and provision of real‐time operational machine position, navigation, and timing. The aim of this study was to determine the accuracy with which multi‐transmitter GNSS‐RF captures the swinging and forwarding motions of ground based harvesting machines at varying transmission intervals. Assessing the accuracy of GNSS in capturing intricate machine movements is a first step toward development of a real‐time production model to assist timber harvesting of beetle‐killed lodgepole pine stands. In a complete randomized block experiment with four replicates, a log loader rotated to 18 predetermined angles with GNSS‐RF transponders collecting and sending data at two points along the machine boom (grapple and heel rack) and at three transmission intervals (2.5, 5.0, and 10.0 s). The 2.5 and 5.0 s intervals correctly identified 94% and 92% of cycles at the grapple and 92% and 89% of cycles at the heel, respectively. The 2.5 s interval successfully classified over 90% of individual cycle elements, while the 5.0 s interval returned statistically similar results. Predicted swing angles obtained the highest level of similarity to observed angles at the 2.5 s interval. Our results show that GNSS‐RF is useful for realtime, model‐based analysis of forest operations, including woody biomass production logistics. View Full-Text
Keywords: forest operations; logistics; multi‐transmitter; accuracy; precision forestry forest operations; logistics; multi‐transmitter; accuracy; precision forestry
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MDPI and ACS Style

Becker, R.M.; Keefe, R.F.; Anderson, N.M. Use of Real‐Time GNSS‐RF Data to Characterize the Swing Movements of Forestry Equipment. Forests 2017, 8, 44.

AMA Style

Becker RM, Keefe RF, Anderson NM. Use of Real‐Time GNSS‐RF Data to Characterize the Swing Movements of Forestry Equipment. Forests. 2017; 8(2):44.

Chicago/Turabian Style

Becker, Ryer M., Robert F. Keefe, and Nathaniel M. Anderson. 2017. "Use of Real‐Time GNSS‐RF Data to Characterize the Swing Movements of Forestry Equipment" Forests 8, no. 2: 44.

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