Abstract
Small-footprint airborne LiDAR scanning systems are effective in modelling forest structures and can also improve trail detection. We propose a trail detection method through a machine learning method from the LiDAR points. To do that, we analyze features for detecting a trail, digitize each feature and combine the results to distinguish between trail and non-trail areas. Our proposed method shows the feasibility of trail detection by using airborne LiDAR points gathered in dense mixed forest.
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Acknowledgment
This research was supported by Basic Science Research Program through the National Research Foundation of Ko-rea (NRF) funded by the Ministry of Education (NRF-2016R1D1A1B03932447).
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Kim, J., Lee, H., Kang, S. (2018). A Trail Detection Using Convolutional Neural Network. In: Lee, W., Choi, W., Jung, S., Song, M. (eds) Proceedings of the 7th International Conference on Emerging Databases. Lecture Notes in Electrical Engineering, vol 461. Springer, Singapore. https://doi.org/10.1007/978-981-10-6520-0_30
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DOI: https://doi.org/10.1007/978-981-10-6520-0_30
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