Title: Improving FIA trend analysis through model-based estimation using landsat disturbance maps and the forest vegetation simulator
Author: Healey, Sean P.; Moisen, Gretchen G.; Patterson, Paul L.
Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 427-431.
Description: The Forest Inventory and Analysis (FIA) Program's panel system, in which 10-20 percent of the sample is measured in any given year, is designed to increase the currency of FIA reporting and its sensitivity to factors operating at relatively fine temporal scales. Now that much of the country has completed at least one measurement cycle over all panels, there is an immediate need for estimation strategies which make the best use of this sampling schedule. A primary obstacle is that only a fraction of plots can be considered current in any particular year. This leaves the analyst with a choice of ignoring annual trends or creating estimates one panel at a time and suffering precision losses which may render apparent year-to-year differences uninterpretable. One option for increasing the temporal specificity of estimates is to update plot conditions for every year in a time series using the Forest Vegetation Simulator (FVS) and to use model-based estimation to create annual estimates using "observations" from every plot. The variance estimators used in such an approach would incorporate both sample and model uncertainty, the latter of which could be assessed at remeasured FIA plots. Disturbance maps created from time series of Landsat (or similar sensor) satellite imagery could be used to identify and appropriately alter FVS simulations for those plots which have been disturbed. Use of disturbance maps would allow sensitivity to year-to-year variation in the disturbance rate. FIA has recent experience in all of the components of the proposed approach including FVS, Landsat disturbance mapping, and model-based estimation. Further study to integrate these components into a production estimation system is warranted.
Keywords: statistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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Healey, Sean P.; Moisen, Gretchen G.; Patterson, Paul L. 2012. Improving FIA trend analysis through model-based estimation using landsat disturbance maps and the forest vegetation simulator. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 427-431.
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