Adding value to the FIA inventory: combining FIA data and satellite observations to estimate forest disturbanceThis article is part of a larger document. View the larger document here.
In addition to being one of the primary drivers of the net terrestrial carbon budget, forest disturbance also plays a critical role in regulating the surface energy balance, promoting biodiversity, and creating wildlife habitat. With climate change and an ever growing human population poised to alter the frequency and severity of disturbance regimes across the globe, improved monitoring of forest disturbance, especially at the landscape scale has taken on renewed importance. Because forest disturbance manifests at a variety of spatial and temporal scales and has varying impacts which affect the canopy, understory, and forest floor, effective monitoring will likely require a composite approach where localized field data collected by the Forest Inventory and Analysis (FIA) Program are combined with repeat observations from remote sensing satellites such as Landsat. As Landsat offers nearly 40 years of well calibrated and systematically collected imagery at no cost, it is now economically feasible to monitor year to year trends in forest disturbance over large areas. In addition to its use in mapping forest change, Landsat data can also serve as a valuable backdrop for collecting detailed human interpretations of disturbance. When collected over a design-based sample such as FIA plots, these manually derived interpretations offer a wealth of potential uses ranging from map validation to estimation of new disturbance-related attributes. Here satellite observations and FIA data are used to estimate the area impacted by several types of forest disturbance occurring in the Uinta Mountains of northern Utah. This study aims to evaluate two types of satellite observations in the context of FIA’s estimation procedure, including the use of human interpretations as an augmented response variable and the use of disturbance maps for stratified variance reduction.