Zobrazeno 1 - 10
of 413
pro vyhledávání: '"FINLEY, ANDREW O."'
Autor:
Shannon, Elliot S., Finley, Andrew O., May, Paul B., Domke, Grant M., Andersen, Hans-Erik, Gaines III, George C., Banerjee, Sudipto
National Forest Inventory (NFI) programs can provide vital information on the status, trend, and change in forest parameters. These programs are being increasingly asked to provide forest parameter estimates for spatial and temporal extents smaller t
Externí odkaz:
http://arxiv.org/abs/2407.09909
Autor:
May, Paul B., Finley, Andrew O.
Spatially explicit quantification of forest biomass is important for forest-health monitoring and carbon accounting. Direct field measurements of biomass are laborious and expensive, typically limiting their spatial and temporal sampling density and
Externí odkaz:
http://arxiv.org/abs/2407.07134
Model-assisted, two-stage forest survey sampling designs provide a means to combine airborne remote sensing data, collected in a sampling mode, with field plot data to increase the precision of national forest inventory estimates, while maintaining i
Externí odkaz:
http://arxiv.org/abs/2402.11029
The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar instrument that collects near-global measurements of forest structure. While expansive in scope, GEDI samples are spatially sparse and cover a small fraction of the land surface
Externí odkaz:
http://arxiv.org/abs/2401.01848
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 challenge aggregate information to a common coarse resolution, i.e., co
Externí odkaz:
http://arxiv.org/abs/2311.11256
Autor:
Nothdurft, Arne, Tockner, Andreas, Witzmann, Sarah, Gollob, Christoph, Ritter, Tim, Kraßnitzer, Ralf, Stampfer, Karl, Finley, Andrew O.
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 protection forests in Ebensee, Austria. In total 36,338 sample trees we
Externí odkaz:
http://arxiv.org/abs/2311.01893
Publikováno v:
Methods in Ecology and Evolution
Numerous modeling techniques exist to estimate abundance of plant and wildlife species. These methods seek to estimate abundance while accounting for multiple complexities found in ecological data, such as observational biases, spatial autocorrelatio
Externí odkaz:
http://arxiv.org/abs/2310.19446
Autor:
Doser, Jeffrey W., Finley, Andrew O., Saunders, Sarah P., Kery, Marc, Weed, Aaron S., Zipkin, Elise F.
Occupancy models are frequently used by ecologists to quantify spatial variation in species distributions while accounting for observational biases in the collection of detection-nondetection data. However, the common assumption that a single set of
Externí odkaz:
http://arxiv.org/abs/2308.02348
Autor:
Finley, Andrew O., Andersen, Hans-Erik, Babcock, Chad, Cook, Bruce D., Morton, Douglas C., Banerjee, Sudipto
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 plot measurements. The model is motivated by the United States Departmen
Externí odkaz:
http://arxiv.org/abs/2302.06410
Autor:
Doser, Jeffrey W., Kéry, Marc, Saunders, Sarah P., Finley, Andrew O., Bateman, Brooke L., Grand, Joanna, Reault, Shannon, Weed, Aaron S., Zipkin, Elise F.
Publikováno v:
Global Ecology and Biogeography, 33, e13814 (2024)
Species distribution models (SDMs) are increasingly applied across macroscales. Such models typically assume that a single set of regression coefficients can adequately describe species-environment relationships and/or population trends. However, suc
Externí odkaz:
http://arxiv.org/abs/2301.05645