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Keyword: random forest

Sagebrush scent identifies species and subspecies

Science Spotlights Posted on: August 24, 2016
Big sagebrush (Artemisia tridentata) is the dominant plant species across much of the Western U.S. and provide critical habitat and food for many endemic species, including the threatened greater sage-grouse. Sagebrush habitat is imperiled due to disturbances and increased wildfire frequency due to exotic annual grasses. Identification of big sagebrush subspecies is difficult, but critical for successful restoration. Researchers discover that volatiles emitted by sagebrush species and subspecies differ in consistent ways and can be used to accurately identify plants.

Signals of speciation: Volatile organic compounds resolve closely related sagebrush taxa, suggesting their importance in evolution

Publications Posted on: July 15, 2016
Volatile organic compounds (VOCs) play important roles in the environmental adaptation and fitness of plants. Comparison of the qualitative and quantitative differences in VOCs among closely related taxa and assessing the effects of environment on their emissions are important steps to deducing VOC function and evolutionary importance.

Vegetation, topography and daily weather influenced burn severity in central Idaho and western Montana forests

Publications Posted on: October 06, 2015
Burn severity as inferred from satellite-derived differenced Normalized Burn Ratio (dNBR) is useful for evaluating fire impacts on ecosystems but the environmental controls on burn severity across large forest fires are both poorly understood and likely to be different than those influencing fire extent.

Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance

Publications Posted on: October 06, 2015
As part of the development of the 2011 National Land Cover Database (NLCD) tree canopy cover layer, a pilot project was launched to test the use of high-resolution photography coupled with extensive ancillary data to map the distribution of tree canopy cover over four study regions in the conterminous US. Two stochastic modeling techniques, random forests (RF) and stochastic gradient boosting (SGB), are compared.

Field plot measures and predictive map products for "Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data"

Datasets Posted on: March 27, 2015
This data publication contains LiDAR data (for predictor variables) and plot tree data (for response variables) used in the modeling and mapping of species-level basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho.It also contains the Arc/INFO GRID raster maps for both study areas showing predicted species-level basal area and tree density.

Properties of Endogenous Post-Stratified Estimation using remote sensing data

Publications Posted on: April 22, 2014
Post-stratification is commonly used to improve the precision of survey estimates. In traditional poststratification methods, the stratification variable must be known at the population level. When suitable covariates are available at the population level, an alternative approach consists of fitting a model on the covariates, making predictions for the population and then stratifying on these predicted values.

Sickleweed on the Fort Pierre National Grasslands: An emerging threat

Publications Posted on: September 17, 2013
We report the first detailed field survey of sickleweed (Falcaria vulgaris L.) in the United States. Sickleweed is native to Europe, the Mediterranean, Asia Minor, and Iran and was first reported in the United States in 1922. It is listed by the Nebraska Invasive Species Council as a Category II invasive plant species.

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Publications Posted on: October 05, 2011
Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature loggers systematically distributed across 2 mountain ranges.

Evaluation of open source data mining software packages

Publications Posted on: January 27, 2010
Since 2001, the USDA Forest Service (USFS) has used classification and regression-tree technology to map USFS Forest Inventory and Analysis (FIA) biomass, forest type, forest type groups, and National Forest vegetation. This prior work used Cubist/See5 software for the analyses. The objective of this project, sponsored by the Remote Sensing Steering Committee (RSSC), was to evaluate other software packages, including R, SAS, WEKA, and Orange.

Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data

Publications Posted on: September 02, 2008
Meaningful relationships between forest structure attributes measured in representative field plots on the ground and remotely sensed data measured comprehensively across the same forested landscape facilitate the production of maps of forest attributes such as basal area (BA) and tree density (TD).