# Use of Real-Time GNSS-RF Data to Characterize the Swing Movements of Forestry Equipment
## 1 Introduction
Real-time systems that communicate equipment and ground-worker locations among one another locally at remote logging sites are an important advancement because the technology opens the door to integrated, simultaneous analysis of data from multiple machines and ground workers interacting with one another within the framework of computer-augmented decision processes, with the objective of improving production logistics and safety [14; 15]. Past research has returned promising results related to the ability of GNSS receivers to monitor forestry equipment movements, though dense forest canopies are known to increase GNSS error and reduce the ability to collect precise and accurate measurements in dense stands [16; 17; 18; 19; 20]. Even when accuracy is reduced due to canopy closure, GNSS can be successful when high accuracy in monitoring object movements is not required [10]. For example, position accuracy to 10 m may be insufficient for safety applications, but acceptable for transportation routing. Landscape topography has also been an obstacle in the use of GNSS in forestry applications due to line of sight obstructions [21]. [PERSON] and [PERSON] used GNSS for elemental analysis of skidder cycles and found that GNSS locations could successfully be used to predict cycle durations and distinguish between different elements within those cycles (e.g., grapple, positioning, and travel), though the system was subject to large errors when compared to clock studies (i.e., manual timing by an observer) with regard to specific element durations [22]. Operational cycles measured with GNSS agreed with direct observation times 90% of the overall time studied [22]. Similar accuracies were found when using GNSS transponders to analyze the cycle times of forwarders and when using vibration sensors to assist in the determination of cycle times [23]. While GNSS data have been effective for capturing the location, movements, and overall cycle times of some forest machinery, researchers have encountered problems when attempting to acquire high levels of accuracy in the analysis of specific productive cycle elements [22; 23; 24; 25]. Additionally, there has been limited prior research evaluating the quality of productive cycle element characterization using positional information derived from GNSS-RF data. Understanding the accuracies and capabilities of commercially available, consumer-grade GNSS-RF transponders will facilitate development of their application in beetle-killed harvest logistics and in production analysis in forest operations more broadly. The objective of this study was to determine the effectiveness of multi-transmitter GNSS-RF units for characterizing the cycle elements of a log loader at three intervals of GNSS-RF signal transmission and two locations along the machine boom, using time and positional data sent by the transponders. GNSS-RF positional data were compared statistically to manually recorded time intervals for the same cycle elements. Our goals in determining the accuracy of the technology were two-fold: (1) to foster innovation in operations research, especially in the safe, efficient characterization of cycle elements and continued development of accurate, real-time model-assisted decision support and analysis; and (2) to facilitate the development and deployment of these technologies in the forest sector to improve productive efficiency and reduce costs. These goals are of particular interest and application in improving harvest logistics of beetle-killed timber harvests for biomass when product values are low, potential profit margins are narrow, and cost-minimization, even by small margins, can have large impacts on the financial viability of supply chains.