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A comparison of small-area estimation techniques to estimate selected stand attributes using LiDAR-derived auxiliary variables

Creator:

Goerndt, Michael E., Monleon, Vicente J., and Temesgen, Hailemariam

Abstract:

One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and...

Resource Type:

Article

Full Text:

Michael Wing for his expertise with regard to GIS. We also thank Greg Latta, Matt Gregory, and Emilie
Comparison and analysis of small area estimation methods for improving estimates of selected forest attributes

Creator:

Goerndt, Michael E.

Abstract:

One of the most common practices regarding estimation of forest attributes is the partitioning of large forested subpopulations into smaller areas of interest to coincide with specific objectives of present and future forest management. New estimators are needed to improve estimation of selected forest attributes in small areas where the...

Resource Type:

Dissertation

Full Text:

well such as the generalized regression estimator (GREG), which are discussed in Rao (2003) and