Frontiers in Forests and Global Change · 2021 · 14 citations · 9 references
Natural ResourcesForestryRegional PlanningFire ManagementForest InventoryForest ManagementForest Disturbance DetectionForest PlanningForest Resource ManagementVegetation Change DetectionVegetation Cover AssessmentVegetation MonitoringCase Study EvaluationFire Impact AssessmentForest Attribute EstimationForest Fire MonitoringForest Inventory PlanningForest Landscape SimulationLandscape Scale AssessmentTransition Models
Forest Inventory and Analysis (FIA) data provides robust information for the United States Forest Service’s (USFS) mid-to-broad-scale planning and assessments, but ecological challenges (i.e., climate change, wildfire) necessitate increasingly strategic information without significantly increasing field sampling. Small area estimation (SAE) techniques could provide more precision supported by a rapidly growing suite of landscape-scale datasets. We present three Regional case studies demonstrating current FIA uses, how SAE techniques could enhance existing uses, and steps FIA could take to enable SAE applications that are user-friendly, comprehensive, and statistically appropriate. The Northern Region uses FIA data for planning and assessments, but SAE techniques could provide more specificity to guide vegetation management activities. State and transition simulation models (STSM) are run with FIA data in the Southwestern Region to predict effects of treatments and disturbances, but SAE could support model validation and more precision to identify treatable areas. The Southern Region used FIA to identify existing longleaf pine stands and evaluate condition, but SAE techniques within FIA tools would streamline analyses. Each case study demonstrates a desire to have FIA data on non-forested conditions and non-tree variables. Additional tools to measure statistical confidence would help maximize utility. FIA’s SAE techniques could add value to a widely used data set, if FIA can support key supplements to basic data and functionality.
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Small Area Estimation: An Appraisal
Malay Ghosh, J. N. K. Rao · Statistical Science · 1994 · 741 citations · Full text
New Important Developments in Small Area Estimation
Danny Pfeffermann · Statistical Science · 2013 · 420 citations · Full text