학술논문

Estimation of forest biomass components using airborne LiDAR and multispectral sensors.
Document Type
Article
Source
iForest - Biogeosciences & Forestry. Apr2019, Vol. 12 Issue 2, p207-213. 7p.
Subject
*FOREST biomass
*BIOMASS estimation
*ALTERNATIVE fuels
*LIDAR
*SCOTS pine
*ALLOMETRIC equations
Language
ISSN
1971-7458
Abstract
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. [ABSTRACT FROM AUTHOR]