USGS2009
The national forests (NFs) in the United States are protected areas managed for multiple purposes, and therefore are subject to both natural and anthropogenic disturbances. Monitoring forest changes arising from such disturbances and the post-disturbance recovery processes is essential for assessing the conditions of the NFs and the effectiveness of management approaches. In this study, we used time series stacks of Landsat images (LTSS) to evaluate the dynamics of seven NFs in eastern United States, including the De Soto NF, the Talladega NF, the Francis Marion NF, and the Uwharrie NF in southeastern U.S., and the Chequamegon NF, the Hiawatha NF, and the Superior NF in northern U.S. Each LTSS consisted of 12–14 Landsat images acquired for the same location, spanning from 1984 to 2006 with a nominal interval of one image every 2 years. Each LTSS was analyzed using a vegetation change tracker (VCT) algorithm to map forest disturbance. Accuracy assessments of the derived disturbance maps revealed that they had overall accuracy values of about 80%, with most of the disturbance classes having user's accuracies ranging from 70% to 95%. The producer's accuracies were generally lower, with the majority being in the range between 50% and 70%. While this may suggest that the disturbance maps could slightly underestimate disturbances, a more detailed assessment of the omission errors revealed that the majority of the disagreements were due to minor disturbances like thinning or storm damages that were identified by the image analysts but were not captured by the VCT algorithm. The derived disturbance year maps revealed that while each of the seven NFs consisted of 90% or more forest land, significant portions of the forests were disturbed since 1984. Mapped disturbances accounted for about 30%–45% of total land area in the four NFs in southeastern U.S. and about 10%–20% in the three NFs in northern U.S. The disturbance rates were generally higher in the buffer zones surrounding each NF, and varied considerably over time. The time series approach employed in this study represents a new approach for monitoring forest resources using the Landsat or similar satellite data records. The disturbance products derived using this approach were spatially explicit and contained much more temporal details than conventional bi-temporal change products, and likely will be found more useful by many users including ecologists and resources managers. The high disturbance rates found in the southeastern U.S. suggest that this region may have a more significant role in modulating the atmospheric carbon budget than currently recognized.
Remote Sensing of Environment↗