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Vol. 34, No. 8(3), S&M3042

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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Sensors and Materials, Volume 34, Number 12(4) (2022)
Copyright(C) MYU K.K.
pp. 4651-4668
S&M3135 Research Paper of Special Issue
https://doi.org/10.18494/SAM4214
Published: December 26, 2022

Application of Real-time Positioning Systems to a Forest Stand for Precision Forest Management [PDF]

Hyun-Min Cho, Jae-Heun Oh, Jin-Woo Park, Yun-Sung Choi, Jung-Soo Lee, and Sang-Kyun Han

(Received October 31, 2022; Accepted December 19, 2022)

Keywords: precision forestry, real-time positioning system, global navigation satellite system, inertial navigation system, positioning accuracy

There is an increasing demand for modern information and communications technologies (ICTs), such as light detection and ranging (LiDAR), photometric stereo, and mechanized forestry machines, for achieving more precise and efficient forest management. Simultaneously, the real-time positioning (RP) system has gained prominence as an essential peer technology. However, the conventional RP system, a single-band global navigation satellite system (GNSS), is inadequate for utilization with newly proposed precision forestry management systems. Therefore, we assessed the applicability of two alternative RP systems, GNSS real-time kinematic (GNSS-RTK) and embedded GNSS and inertial navigation system (INS), which can be applied to actual forest operations. We also analyzed the relationship between positioning error and various environmental factors. Consequently, the embedded GNSS/INS (EGI) showed better performance, with a root mean squared error (RMSE) of 1.42 m, than the GNSS-RTK (1.52 m), and its RMSE significantly decreased after sensor heading calibration (p <0.05) by 15 min of warm-up driving. In addition, both GNSS-RTK and EGI demonstrated a negative correlation between the RMSE and forest canopy coverage (p < 0.05). In this study, we identified the existing limitations and opportunities of proposed RP systems applied within the forestry industry, allowing for the development of a more suitable RP system for precision forestry management in future research.

Corresponding author: Sang-Kyun Han


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Cite this article
Hyun-Min Cho, Jae-Heun Oh, Jin-Woo Park, Yun-Sung Choi, Jung-Soo Lee, and Sang-Kyun Han, Application of Real-time Positioning Systems to a Forest Stand for Precision Forest Management, Sens. Mater., Vol. 34, No. 12, 2022, p. 4651-4668.



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