In order to consider forest biomass as a real alternative for energy production, it is critical to obtain accurate estimates of its availability using non-destructive sampling methods. In this study, we estimate the biomass available in a Scots pine-dominated forest (Pinus sylvestris L.) located in Spain. The biomass estimates were obtained using LiDAR data combined with a multispectral camera and allometric equations. The method used to fuse the data was based on back projection, which assures a perfect match between both datasets. The results present estimates for each of the seven different biomass components: above ground, below ground, log, needles, and large, medium and small branches. The accuracy of the models varied between R2 values of 0.46 and 0.67 with RMSE% ranging from 15.72% to 35.43% with all component estimates below 20%, except for the model estimating biomass of big branches. The models in this study are suitable for the estimation of biomass and demonstrate that computation is possible at a fine scale for the different biomass components. These remote sensing methods are sufficiently accurate to develop biomass resource cartography for multiple energy uses.
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Citation
Hernando A, Puerto L, Mola-Yudego B, Manzanera JA, García-Abril A, Maltamo M, Valbuena R (2019). Estimation of forest biomass components using airborne LiDAR and multispectral sensors. iForest 12: 207-213. - doi: 10.3832/ifor2735-012
Academic Editor
Davide Travaglini
Paper history
Received: Jan 22, 2018
Accepted: Feb 06, 2019
First online: Apr 25, 2019
Publication Date: Apr 30, 2019
Publication Time: 2.60 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2019
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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