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stat.AP2026
Evaluating LiDAR Data Sources, Predictor Resolution, and Spatial Random Effects in Bayesian Change-of-Support Models for Forest Inventory
Arthur Spitta, Andrew O. Finley, Christoph Gollob +4
Forest managers need timely stand-level information to support operational planning, particularly in mixed-species, structurally heterogeneous forests facing climate-related distur…
stat.AP2025
Small area estimation of growing stock timber volume, basal area, mean stem diameter, and stem density for mountain forests in Austria
Arne Nothdurft, Valentin Sarkleti, Tobias Ofner-Graff +8
Regression models were evaluated to estimate stand-level growing stock volume (GSV), quadratic mean diameter (QMD), basal area (BA), and stem density (N) in the Brixen im Thale for…
stat.AP2023
Spatial prediction of diameter distributions for the alpine protection forests in Ebensee, Austria, using ALS/PLS and spatial distributional regression models
Arne Nothdurft, Andreas Tockner, Sarah Witzmann +5
A spatial distributional regression model is presented to predict the forest structural diversity in terms of the distributions of the stem diameter at breast height (DBH) in the p…