Title: Mapping Trails and Tracks in the Boreal Forest using LiDAR and Convolutional Neural Networks
Citation: Terentieva, I. (2024). Supplementary: Mapping Trails and Tracks in the Boreal Forest using LiDAR and Convolutional Neural Networks (Version 1.0.0) [Graphic]. Zenodo. https://doi.org/10.5281/zenodo.11206113
Study Site: Kirby, Alberta
Purpose: This dataset consists of various geospatial layers and raster files used in the study of mapping trails and tracks in the boreal forest using LiDAR data and convolutional neural networks (CNNs). The layers include manually labeled training data, test polygons for accuracy assessment, trail density map, example of digital terrain model, original pixel-wise trail and track maps, and refined vectorized trail and track maps generated from both airborne and drone-based LiDAR data. Additionally, the dataset contains ancillary data such as industrial disturbance footprints, land cover maps, and random points for model performance evaluation.
Abstract: These data were collected and processed to develop and validate models capable of automatically mapping trails and tracks across diverse land-cover types. This dataset supports remote sensing and ecological research by providing detailed spatial data for automated trail and track mapping, enhancing understanding of human and wildlife movement patterns in the boreal forest.
Supplemental Information Summary: Our GitHub page, featuring tools and code for the trails and tracks mapping project, can be found here:
https://github.com/appliedgrg/trails-tracks-mapper
Research:
Further Info: McDermid, G. J., Terenteva, I., & Chan, X. Y. (2025). Mapping Trails and Tracks in the Boreal Forest Using LiDAR and Convolutional Neural Networks. Remote Sensing, 17(9), 1539. https://doi.org/10.3390/rs17091539
Status: Complete
Keywords:
mapping,
effects of disturbance,
seismic lines,
Geographical coordinates: North: 55.34, South: 55.34 East: -110.58 West: -110.58
Bounding Temporal Extent: Start Date: , End
Date:
