Title: Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Author: Lister, Andrew; Riemann, Rachel; Westfall, James; Hoppus, Mike

Year: 2005

Publication: In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J., eds. Proceedings of the fourth annual forest inventory and analysis symposium; Gen. Tech. Rep. NC-252. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. 105-109

Abstract: The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered remotely sensed raster data were used to predict the basal area of deciduous trees at a spatial resolution of 30 m. Results varied, generally indicating that culling putatively unrelated variables did not improve estimates over those obtained using all the potential variables in the model.