2 citations · 3 across the 3 of their papers we have counts for
5 papers
Models to support forest inventory and small area estimation using sparsely sampled LiDAR: A case study involving G-LiHT LiDAR in Tanana, Alaska
Andrew O. Finley, Hans-Erik Andersen, Chad Babcock +3
A two-stage hierarchical Bayesian model is developed and implemented to estimate forest biomass density and total given sparsely sampled LiDAR and georeferenced forest inventory pl…
Remote sensing to reduce the effects of spatial autocorrelation on design-based inference for forest inventory using systematic samples
Chad Babcock, Andrew O. Finley, Timothy G. Gregoire +1
Systematic sampling is often used to select plot locations for forest inventory estimation. However, it is not possible to derive a design-unbiased variance estimator for a systema…
Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping
Daniel Taylor-Rodriguez, Andrew O. Finley, Abhirup Datta +5
Gathering information about forest variables is an expensive and arduous activity. As such, directly collecting the data required to produce high-resolution maps over large spatial…
Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations
Chad Babcock, Andrew O. Finley, Hans-Erik Andersen +9
The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip sampl…
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Andrew O. Finley, Abhirup Datta, Bruce C. Cook +3
We consider alternate formulations of recently proposed hierarchical Nearest Neighbor Gaussian Process (NNGP) models (Datta et al., 2016a) for improved convergence, faster computin…