Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference

Due to climate change, treelines are moving higher elevations and latitudes. The estimation of biomass trees shrubs advancing into alpine areas is necessary for carbon reporting. Remotely sensed (RS) data have previously been utilised extensively the forest variables such as tree height, volume, basal area, aboveground (AGB) in various types. Model-based inference found be efficient attributes using auxiliary RS data, this study focused on testing model-based estimations AGB treeline ecotone an area-based approach. Shrubs (Salix spp., Betula nana) (Betula pubescens ssp. czerepanovii, Sorbus aucuparia, Populus tremula, Pinus sylvestris, Picea abies) with heights up about five meters constituted components. was carried out a Hol, southern Norway, field plots point cloud obtained from airborne laser scanning (ALS) digital aerial photogrammetry (DAP). were acquired two different strata: tall short vegetation. Two separate models predicting constructed each stratum based metrics calculated ALS DAP clouds, respectively. From stratified predictions, mean estimated entire area. Despite prediction showing weak fit, indicated by their R2-values, 95% CIs relatively narrow, indicating adequate precision estimates. No significant difference between estimates either strata. Our results imply that can used ecotones.