APA (7th ed.) Citation

Li, L., Mu, X., Chianucci, F., Qi, J., Jiang, J., Zhou, J., . . . Liu, S. (2022). Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach. International journal of applied earth observation and geoinformation, 107, 102686. https://doi.org/10.1016/j.jag.2022.102686

Chicago Style (17th ed.) Citation

Li, Linyuan, et al. "Ultrahigh-resolution Boreal Forest Canopy Mapping: Combining UAV Imagery and Photogrammetric Point Clouds in a Deep-learning-based Approach." International Journal of Applied Earth Observation and Geoinformation 107 (2022): 102686. https://doi.org/10.1016/j.jag.2022.102686.

MLA (9th ed.) Citation

Li, Linyuan, et al. "Ultrahigh-resolution Boreal Forest Canopy Mapping: Combining UAV Imagery and Photogrammetric Point Clouds in a Deep-learning-based Approach." International Journal of Applied Earth Observation and Geoinformation, vol. 107, 2022, p. 102686, https://doi.org/10.1016/j.jag.2022.102686.