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LiDAR remote sensing of forest structure
Abstract
Light detection and ranging (LiDAR) technology provides horizontal and vertical information at high spatial resolutions and vertical accuracies. Forest attributes such as canopy height can be directly retrieved from LiDAR data. Direct retrieval of canopy height provides opportunities to model above-ground biomass and canopy volume. Access to the vertical nature of forest ecosystems also offers new opportunities for enhanced forest monitoring, management and planning.
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Citations
Cited by
Development of a UAV-LiDAR System with Application to Forest Inventory
Wallace, L., Lucieer, A., Watson, C., & Turner, D. (2012) · Remote Sensing · doi:10.3390/rs4061519 · Cited by 710
Generating pit-free canopy height models from airborne lidar
Khosravipour, A., Skidmore, A. K., Isenburg, M., Wang, T., & Hussin, Y. A. (2014) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.80.9.863 · Cited by 347
Wang, K., Franklin, S. E., Guo, X., & Cattet, M. (2010) · Sensors · doi:10.3390/s101109647 · Cited by 320
Liu, X., Su, Y., Hu, T., Yang, Q., Liu, B., Deng, Y., Tang, H., Tang, Z., Fang, J., & Guo, Q. (2022) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112844 · Cited by 270
Adam, M., Urbazaev, M., Dubois, C., & Schmullius, C. (2020) · Remote Sensing · doi:10.3390/rs12233948 · Cited by 156
Metadata
- Authors
- Lim, K., Treitz, P., Wulder, M., St-Onge, B., & Flood, M.
- Venue
- Progress in Physical Geography: Earth and Environment
- Publisher
- SAGE Publications
- Published
- 2003-03
- Volume
- 27
- Issue
- 1
- Pages
- 88-106
- ISSN
- 0309-1333 (ISSN-L)
- 1477-0296
- OpenAlex
- W2098919237
- Cited by
- 1,103
- References
- 0
- FWCI
- 29.25
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: LiDAR remote sensing of forest structure. https://app.cochat.ai/papers/10.1191/0309133303pp360ra
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- Lim, K., Treitz, P., Wulder, M., St-Onge, B., & Flood, M. (2003). LiDAR remote sensing of forest structure. Progress in Physical Geography: Earth and Environment. https://doi.org/10.1191/0309133303pp360ra
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
