4 citations · 5 across the 6 of their papers we have counts for
8 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…
Quantifying and correcting geolocation error in spaceborne LiDAR forest canopy observations using high spatial accuracy ALS: A Bayesian model approach
Elliot S. Shannon, Andrew O. Finley, Daniel J. Hayes +4
Geolocation error in spaceborne sampling light detection and ranging (LiDAR) measurements of forest structure can compromise forest attribute estimates and degrade integration with…
Conjugate Nearest Neighbor Gaussian Process Models for Efficient Statistical Interpolation of Large Spatial Data
Shinichiro Shirota, Andrew O. Finley, Bruce D. Cook +1
A key challenge in spatial statistics is the analysis for massive spatially-referenced data sets. Such analyses often proceed from Gaussian process specifications that can produce…
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…
Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables
Andrew O. Finley, Sudipto Banerjee, Yuzhen Zhou +2
Recent advancements in remote sensing technology, specifically Light Detection and Ranging (LiDAR) sensors, provide the data needed to quantify forest characteristics at a fine spa…
Dynamic spatial regression models for space-varying forest stand tables
Andrew O. Finley, Sudipto Banerjee, Aaron R. Weiskittel +2
Many forest management planning decisions are based on information about the number of trees by species and diameter per unit area. This information is commonly summarized in a sta…