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

Popovici, Bogdan; Pelorosso, Raffaele; Herbei, Mihai Valentin; Sala, Florin; Avădanei, Mihai

doi:10.67252/gl.2026.80.3.1

Geodetski list, Vol. 80 (103) No. 3, 2026.

Pregledni rad

https://doi.org/10.67252/gl.2026.80.3.1

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

Bogdan Popovici ; Ștefan cel Mare University of Suceava Faculty of Forestry Universității Street no. 13, 720229 Suceava, Romania *
Raffaele Pelorosso ; Tuscia University Department of Agriculture and Forest Sciences (DAFNE) 01100 Viterbo (VT), Italy
Mihai Valentin Herbei ; University of Life Sciences "King Mihai I" from Timișoara Faculty of Agriculture Calea Aradului no. 119, 300645 Timișoara, Romania
Florin Sala ; University of Life Sciences "King Mihai I" from Timișoara Faculty of Agriculture Calea Aradului no. 119, 300645 Timișoara, Romania
Mihai Avădanei ; University of Petroșani Faculty of Mines Universității Street no. 20, 332006 Petroșani, Romania

* Dopisni autor.

Puni tekst: engleski pdf 1.665 Kb

str. 207-226

preuzimanja: 0

citiraj

APA 6th Edition

Popovici, B., Pelorosso, R., Herbei, M.V., Sala, F. i Avădanei, M. (2026). GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies. Geodetski list, 80 (103) (3), 207-226. https://doi.org/10.67252/gl.2026.80.3.1

MLA 8th Edition

Popovici, Bogdan, et al. "GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies." Geodetski list, vol. 80 (103), br. 3, 2026, str. 207-226. https://doi.org/10.67252/gl.2026.80.3.1. Citirano 01.10.2026.

Chicago 17th Edition

Popovici, Bogdan, Raffaele Pelorosso, Mihai Valentin Herbei, Florin Sala i Mihai Avădanei. "GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies." Geodetski list 80 (103), br. 3 (2026): 207-226. https://doi.org/10.67252/gl.2026.80.3.1

Harvard

Popovici, B., et al. (2026). 'GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies', Geodetski list, 80 (103)(3), str. 207-226. https://doi.org/10.67252/gl.2026.80.3.1

Vancouver

Popovici B, Pelorosso R, Herbei MV, Sala F, Avădanei M. GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies. Geodetski list [Internet]. 2026 [pristupljeno 01.10.2026.];80 (103)(3):207-226. https://doi.org/10.67252/gl.2026.80.3.1

IEEE

B. Popovici, R. Pelorosso, M.V. Herbei, F. Sala i M. Avădanei, "GNSS Positioning Accuracy in Forest Environments: A Structured Critical Review of Canopy Effects and Mitigation Strategies", Geodetski list, vol.80 (103), br. 3, str. 207-226, 2026. [Online]. https://doi.org/10.67252/gl.2026.80.3.1

Sažetak

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.