GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies

Abstract

GNSS positioning under forest canopy remains challenging, as vegetation attenuates signals, promotes multipath propagation, and degrades satellite geometry. This paper presents a structured critical narrative review of the scientific literature published between 1996 and 2025, updated through a search to 2026. Autonomous GNSS, DGPS, RTK-GNSS, multi-GNSS and low-cost RTK, as well as GNSS–IMU, LiDAR, UAV, UWB, and SLAM approaches are compared. Evidence indicates a progressive deterioration in performance with canopy density. In the reviewed studies, autonomous GNSS errors frequently reach 15–30 m under dense canopy, while multi-GNSS RTK solutions report, under comparable conditions, approximately 0.5–2.03 m; ranges are indicative, not statistically aggregated estimates. GNSS integration with inertial sensors and LiDAR increases continuity and robustness, but operational validation remains limited. The main contribution is a decision-oriented framework that correlates canopy, degradation mechanisms, technology and mitigation strategies. Three priorities are highlighted: standardized reporting, forest-adapted corrections and comparative validation of multi-sensor systems.