SnowPole-GeoLoc: An open-source GNSS–LiDAR snow pole geo-localization framework
Year: 2026
Type: software-paper
Abstract: Reliable vehicle localization remains challenging in GNSS-limited and GNSS- denied environments, particularly under harsh Nordic winter conditions where road markings, traffic signs, and visual landmarks are often obscured by snow. This paper presents SnowPole-GeoLoc, an open-source software framework for snow pole geo-localization using GNSS and LiDAR data fusion. Snow poles are treated as stable, machine-perceivable road- side infrastructure landmarks that remain visible under heavy snowfall. The framework integrates deep learning–based snow pole detection from LiDAR- derived images with GNSS-assisted georeferencing to estimate absolute pole locations in map coordinates. The software supports ROS bag processing, visualization, coordinate transformation, and quantitative evaluation against ground-truth pole locations. SnowPole-GeoLoc is evaluated on real-world data collected along Norwegian highways using a 128-channel LiDAR sensor and continuous GNSS measurements. The software is modular, reproducible, and publicly released with pretrained models, datasets, and environment specifications, and can be used as a standalone snow pole geo-localization tool or as a core sub-module in end-to-end vehicle localization pipelines for winter-degraded sensing conditions.
Source: SoftwareX
Author: Durga Prasad Bavirisetti
Institution: University of Gävle
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Award: G1864946001
OpenAlex ID: W7140147188