1. Estimation of forest biomass components using airborne LiDAR and multispectral sensors.
- Author
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Hernando, Ana, Puerto, Luis, Mola-Yudego, Blas, Manzanera, José Antonio, García-Abril, Antonio, Maltamo, Matti, and Valbuena, Rubén
- Subjects
FOREST biomass ,BIOMASS estimation ,ALTERNATIVE fuels ,LIDAR ,SCOTS pine ,ALLOMETRIC equations - 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]
- Published
- 2019
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