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Elizabeth Freeman


507 25th Street
Ogden, UT 84401
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Featured Publications


Cooke, Brian; Freeman, Elizabeth; Moisen, Gretchen; Frescino, Tracey, 2017. Painting a picture across the landscape with ModelMap
Schroeder, Todd A.; Schleeweis, Karen; Moisen, Gretchen; Toney, Chris; Cohen, Warren B.; Freeman, Elizabeth; Yang, Zhiqiang; Huang, Chengquan, 2017. Testing a Landsat-based approach for mapping disturbance causality in U.S. forests
Frescino, Tracey; Moisen, Gretchen; Patterson, Paul L.; Freeman, Elizabeth; Menlove, James S., 2016. Nevada Photo-Based Inventory Pilot (NPIP) resource estimates (2004-2005)
Moisen, Gretchen; Meyer, Mary C.; Schroeder, Todd A.; Liao, Xiyue; Schleeweis, Karen; Freeman, Elizabeth; Toney, Chris, 2016. Shape selection in Landsat time series: A tool for monitoring forest dynamics
Frescino, Tracey; Patterson, Paul L.; Moisen, Gretchen; Freeman, Elizabeth, 2015. FIESTA—An R estimation tool for FIA analysts
Schleeweis, Karen; Moisen, Gretchen; Schroeder, Todd A.; Toney, Chris; Freeman, Elizabeth, 2015. On the road to national mapping and attribution of the processes underlying U.S
Freeman, Elizabeth; Moisen, Gretchen; Coulston, John W.; Wilson, Barry T. (Ty), 2015. Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance
Meyer, Mary; Liao, Xiyue; Moisen, Gretchen; Freeman, Elizabeth, 2015. ShapeSelectForest: a new r package for modeling landsat time series
Schroeder, Todd A.; Moisen, Gretchen; Schleeweis, Karen; Toney, Chris; Cohen, Warren B.; Yang, Zhiqiang; Freeman, Elizabeth, 2015. Using an empirical and rule-based modeling approach to map cause of disturbance in U.S
Healey, Sean P.; Patterson, Paul L.; Saatchi, Sassan S.; Lefsky, Michael A.; Lister, Andrew J.; Freeman, Elizabeth, 2012. A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)
Healey, Sean P.; Patterson, Paul L.; Saatchi, Sassan; Lefsky, Michael A.; Lister, Andrew J.; Freeman, Elizabeth; Moisen, Gretchen, 2012. Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data
Frescino, Tracey; Patterson, Paul L.; Freeman, Elizabeth; Moisen, Gretchen, 2012. Using FIESTA , an R-based tool for analysts, to look at temporal trends in forest estimates
Moisen, Gretchen; Freeman, Elizabeth; Blackard, Jock A.; Frescino, Tracey; Zimmermann, Niklaus E.; Edwards, Thomas C. Jr., 2006. Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods
Shaw, David C.; Franklin, Jerry F.; Bible, Ken; Klopatek, Jeffrey; Freeman, Elizabeth; Greene, Sarah; Parker, Geoffrey G., 2004. Ecological setting of the Wind River old-growth forest.
A world map displaying the density of ModelMap downloads
Working in the Forest Inventory and Analysis (FIA) Program, we have access to a valuable collection of detailed information about forests on thousands of sample plots distributed across the country. This information is used to produce summaries of forestland characteristics for a variety of geographic areas such as states or individual national forests. We wanted a simple tool to extend this sample data and make detailed maps of forest characteristics for all the land in between the study locations.
Forest Inventory ESTimation & Analysis (FIESTA) is a research tool for analysts who use data from the Forest Inventory and Analysis program and work in the open-source, R statistical programming environment.

RMRS Science Program Areas: 
Inventory and Monitoring