iForest - Biogeosciences and Forestry


Estimation of forest biomass components using airborne LiDAR and multispectral sensors

Ana Hernando (1)   , Luis Puerto (2), Blas Mola-Yudego (2), José Antonio Manzanera (1), Antonio García-Abril (1), Matti Maltamo (2), Rubén Valbuena (3-4)

iForest - Biogeosciences and Forestry, Volume 12, Issue 2, Pages 207-213 (2019)
doi: https://doi.org/10.3832/ifor2735-012
Published: Apr 25, 2019 - Copyright © 2019 SISEF

Research Articles

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.


Biomass Components, Forest Inventory, Airborne Laser Scanning, Multispectral Imagery, Data Fusion, Nearest Neighbor

Authors’ address

Ana Hernando
José Antonio Manzanera
Antonio García-Abril
Universidad Politécnica de Madrid, E.T.S.I. Montes, Research Group SILVANET, Ciudad Universitaria, 28040 Madrid (Spain)
Luis Puerto 0000-0002-9740-1972
Blas Mola-Yudego 0000-0003-0286-0170
Matti Maltamo
University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI80101, Joensuu (Finland)
Rubén Valbuena 0000-0003-0493-7581
University of Cambridge, Department of Plant Sciences, Forest Ecology and Conservation, Downing Street, CB2 3EA Cambridge (UK)
Rubén Valbuena 0000-0003-0493-7581
Bangor University, School of Natural Sciences, Thoday building, LL57 2UW Bangor (UK)

Corresponding author

Ana Hernando


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

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