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Título
Modelling stand biomass fractions in Galician Eucalyptus globulus plantations by use of different LiDAR pulse densities
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Forest Systems
Número de la revista
3
Datos de la obra
González Ferreiro, E., Miranda, D., Barreiro Fernandez, L., Buján, S., Garcia Gutierrez, J., & Diéguez Aranda, U. (2013). Modelling stands biomass fractions in Galician Eucalyptus globulus plantations by use of different LiDAR pulse densities. Forest systems, 22(3), 510-525. https://doi.org/10.5424/FS/2013223-03878
Editor
CSIC
Fecha
2013
ISSN
2171-5068
Abstract
[EN] Aims of study: To evaluate the potential use of canopy height and intensity distributions, determined by airborneLiDAR, for the estimation of crown, stem and aboveground biomass fractions.To assess the effects of a reduction in LiDAR pulse densities on model precision.Area of study: The study area is located in Galicia, NW Spain. The forests are representative of Eucalyptus globulusstands in NW Spain, characterized by low-intensity silvicultural treatments and by the presence of tall shrub.Material and methods: Linear, multiplicative power and exponential models were used to establish empiricalrelationships between field measurements and LiDAR metrics.A random selection of LiDAR returns and a comparison of the prediction errors by LiDAR pulse density factorwere performed to study a possible loss of fit in these models.Main results: Models showed similar goodness-of-fit statistics to those reported in the international literature. R2ranged from 0.52 to 0.75 for stand crown biomass, from 0.64 to 0.87 for stand stem biomass, and from 0.63 to 0.86for stand aboveground biomass. The RMSE/MEAN · 100 of the set of fitted models ranged from 17.4% to 28.4%.Models precision was essentially maintained when 87.5% of the original point cloud was reduced, i.e.a reductionfrom 4 pulses m–2to 0.5 pulses m–2.Research highlights: Considering the results of this study, the low-density LiDAR data that are released by theSpanish National Geographic Institute will be an excellent source of information for reducing the cost of forestinventories
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