17 citations · 17 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
Bayesian Modeling of Incompatible Spatial Data: A Case Study Involving Post-Adrian Storm Forest Damage Assessment
Lu Zhang, Andrew O. Finley, Arne Nothdurft +1
Modeling incompatible spatial data, i.e., data with different spatial resolutions, is a pervasive challenge in remote sensing data analysis. Typical approaches to addressing this c…
High-dimensional Multivariate Geostatistics: A Bayesian Matrix-Normal Approach
Lu Zhang, Sudipto Banerjee, Andrew O. Finley
Joint modeling of spatially-oriented dependent variables is commonplace in the environmental sciences, where scientists seek to estimate the relationships among a set of environmen…