Forest Aboveground Biomass Prediction by Integrating Terrestrial Laser Scanning Data, Landsat 8 OLI-Derived Forest Canopy Density and Spectral Indices

Author:

Bhandari Shes Kanta,Nandy SubrataORCID

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

Reference68 articles.

1. Abdollahnejad, A., Panagiotidis, D., & Surový, P. (2017). Forest canopy density assessment using different approaches—Review. Journal of Forest Science, 63(3), 107–116. https://doi.org/10.17221/110/2016-JFS

2. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. https://doi.org/10.1109/TAC.1974.1100705

3. Bhandari, S. K., & Chhetri, B. B. K. (2020). Individual-based modelling for predicting height and biomass of juveniles of Shorea robusta. Austrian Journal of Forest Science, 137(2), 133–160.

4. Bhandari, S. K., & Neupane, H. (2014). Allometric equations for estimating the above-ground biomass of Castanopsis indica at juvenile stage. Banko Janakari, 24(1), 14–22.

5. Bienert, A., Scheller, S., Keane, E., Mohan, F., & Nugent, C. (2007). Tree detection and diameter estimations by analysis of forest terrestrial laserscanner point clouds. In ISPRS workshop on laser scanning (Vol. 36, pp. 50–55). IAPRS.

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