Abstract
Small area estimation is a powerful modeling technique in which ancillary data can be utilized to “borrow” additional information, effectively increasing sample sizes in small spatial, temporal, or categorical domains. Though more commonly applied to biophysical variables within the study of forest inventory analyses, small area estimation can also be implemented in the context of understanding social values, behaviors, and trends among types of forest landowners within small domains. Here, we demonstrate a method for deriving a continuous fine-scale land cover and ownership layer for the state of Delaware, United States, and an application of that ancillary layer to facilitate small-area estimation of several variables from the USDA Forest Service’s National Woodland Owner Survey. Utilizing a proprietary parcel layer alongside the National Land Cover Database, we constructed a continuous layer with 10-meter resolution depicting land cover and land ownership classes. We found that the National Woodland Owner Survey state-level estimations of total acreage and total ownerships by ownership class were generally within one standard error of the population values calculated from the raster layer, which supported the direct calculation of several population-level summary variables at the county levels. Subsequently, we compare design-based and model-based methods of predicting commercial harvesting by family forest ownerships in Delaware in which forest ownership acreage, taken from the parcel map, was utilized to inform the model-based approach. Results show general agreement between the two modes, indicating that a small area estimation approach can be utilized successfully in this context and shows promise for other variables, especially if additional variables, e.g., United States Census Bureau data, are also incorporated.
Highlights
Of the approximate 816 million acres of forestland in the United States, private land ownership accounts for an estimated 56% (Butler et al, 2021)
We focused on forest ownerships owning one or more acres – and in particular on family forest ownerships owning one or more acres
This error metric only accounts for the specific variability introduced in this ownership classification phase and does not address the accuracy of the entire study as a whole
Summary
Of the approximate 816 million acres of forestland in the United States, private land ownership accounts for an estimated 56% (Butler et al, 2021). Understanding private land ownership attitudes and behaviors is fundamental to successfully cultivating socially positive land stewardship practices (Kumer and Štrumbelj, 2017; Mozgeris et al, 2017; Sotirov et al, 2019; Butler et al, 2021). Dynamic heterogeneity in attitudes and behaviors, both within and between private ownership classes, require robust datasets and appropriate models to accurately differentiate trends in ownership typologies (Kumer and Štrumbelj, 2017; Sotirov et al, 2019). Low sample sizes require that population estimates be calculated within relatively large spatial domains (nationwide, regional or state-level) in order to ensure sufficient levels of precision
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