An examination of GNSS positioning under dense conifer forest canopy in the Pacific Northwest, USA
| Authors: | Jacob Strunk, Stephen E. Reutebuch, Robert J. McGaughey, Hans-Erik Andersen |
| Year: | 2025 |
| Type: | Scientific Journal |
| Station: | Pacific Northwest Research Station |
| DOI: | https://doi.org/10.1016/j.rsase.2024.101428 |
| Source: | Remote Sensing Applications: Society and Environment. 37(3): 101428. |
Abstract
Accurate positioning in the forest (e.g., less than 1–2 m horizontal error) is needed to leverage the potential of high-resolution auxiliary data sources such as airborne or satellite imagery, lidar, and photogrammetric heights used in forest monitoring. Unfortunately, typical short duration occupations in the forest with budget Global Navigation Satellite System (GNSS; GPS is the American constellation) receivers are generally inaccurate (horizontal errors >5–20 m). This study demonstrates that accurate GNSS positioning is feasible beneath 40 to 60 m-tall closed-canopy conifer forests of western Washington state, USA by using survey-grade receivers with at least 15-min occupations. We also demonstrate the effects of receiver height, occupation duration, base-station distance, and differential post-processing modes (e.g., autonomous, code, fixed-integer, and floating-point) on horizontal positioning accuracies in the forest.
A geodetic survey was our benchmark for accuracy estimation but is difficult to replicate by most other GNSS users in the forest. The difficulty in setting up a geodetic survey has led to common usage of naïve accuracy estimators based on within-occupation coordinate variation (e.g., the “accuracy” reported on the face of a handheld GNSS device). In this study we demonstrate the efficacy of two simple alternatives that outperform the naïve estimator; the naïve esimator was shown to perform poorly.
The findings in this study on GNSS performance and positioning accuracy estimation supports more effective use of GNSS technology in applications that require high-performance GNSS positioning in the forest.