Estimating Kentucky's Forest Inventory at the County Level with Improved Precision by Combining FIA Data with Remote Sensing, GIS, and Small-Area-Estimation Techniques

Our study will result in an improved understanding of the status of forest resources in Kentucky at the county level. Research outputs will include the tables summarizing the estimates of various forest inventory metrics (e.g., timberland acreage, tree density and volume at the species level) and their associated uncertainty for each county. The model outputs also include various thematic maps to show the spatial distribution of those forest attributes, because for certain SAE estimation techniques (e.g. nearest neighbor imputation), the estimation can be assessed at the pixel level. Those tables and maps can be used for many purposes, from developing management strategies to assessing potential impacts on other resources dependent on forests (e.g., wildlife). We will also provide a full appraisal of the major SAE techniques in estimating forest attributes at the county level for Kentucky’s forest, and outline an operational framework that could potentially be used in other states and regions. One or several scientific publications reporting the approach, results, and synthesis will provide strong scientific support for management decisions based on our results. The report of forest resources in Kentucky at the county level will be useful for various local stakeholders, further demonstrating the utility of the FIA data to the public.