Estimation of forest biomass components using airborne LiDAR and multispectral sensors
| Autor: | Antonio García-Abril, Ana Hernando, Blas Mola-Yudego, Matti Maltamo, Ruben Valbuena, José Antonio Manzanera, Luis Puerto |
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| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
Mean squared error Multispectral image Tree allometry Biomass Forest Inventory 01 natural sciences Airborne Laser Scanning lcsh:Forestry Biomass Components Nature and Landscape Conservation Remote sensing Nearest Neighbor Multispectral Imagery Forest inventory Ecology Forestry Ranging 04 agricultural and veterinary sciences Data Fusion Lidar 040103 agronomy & agriculture lcsh:SD1-669.5 0401 agriculture forestry and fisheries Environmental science Scale (map) 010606 plant biology & botany |
| Zdroj: | iForest-Biogeosciences and Forestry, Vol 12, Iss 1, Pp 207-213 (2019) |
| ISSN: | 1971-7458 |
| DOI: | 10.3832/ifor2735-012 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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