Leaf area index estimation in maize and soybean using UAV LiDAR data
Author:
Funder
Natural Science Foundation of Fujian Province, China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11119-024-10146-9.pdf
Reference50 articles.
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2. Ahmed, O. S., Franklin, S. E., Wulder, M. A., & White, J. C. (2015). Characterizing stand-level forest canopy cover and height using landsat time series, samples of airborne LiDAR, and the Random Forest algorithm. Isprs Journal of Photogrammetry and Remote Sensing : Official Publication of the International Society for Photogrammetry and Remote Sensing (Isprs), 101, 89–101.
3. Alonzo, M., Bookhagen, B., McFadden, J. P., Sun, A., & Roberts, D. A. (2015). Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry. Remote Sensing of Environment, 162, 141–153.
4. Bouvier, M., Durrieu, S., Fournier, R. A., & Renaud, J. P. (2015). Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data. Remote Sensing of Environment, 156, 322–334.
5. Cao, L., Coops, N. C., Sun, Y., Ruan, H., Wang, G., Dai, J., & She, G. (2019). Estimating canopy structure and biomass in bamboo forests using airborne LiDAR data. Isprs Journal of Photogrammetry and Remote Sensing : Official Publication of the International Society for Photogrammetry and Remote Sensing (Isprs), 148, 114–129.
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