PROJECT OVERVIEW
Recent studies suggest that roughly one-quarter of global fossil fuel emissions (1-2 billion tons of carbon per year) are being absorbed each year by vegetation within the Northern Hemisphere. However, the nature, longevity, and variability of this biospheric carbon sink are poorly understood. In response the US Carbon Cycle Science Program has organized the North American Carbon Program (NACP), an integrated program of aircraft, satellite, and ground measurements and modeling to quantify the North American carbon budget and understand its mechanisms.
Forest-cover conversion, disturbance, and recovery have been proposed as primary mechanisms
for transferring carbon between the land surface and the atmosphere, but the area and timing of
these processes is still poorly quantified. Furthermore, the magnitude of fire, insect outbreaks, and logging vary significantly in time, which may translate to interannual variability in atmospheric carbon fluxes. Thus, quantifying the rate and geography of forest disturbance is a key element for understanding the continental carbon cycle. Remote sensing, particularly the 30+ year Landsat record, is well suited to detect recent disturbances and forest-cover change. Cloud-free, mid-summer, orthorectified Landsat datasets have already been assembled for epochs centered on 1975, 1990, 2000, and 2005 as part of the Global Land Survey (GLS) project.
The LEDAPS project is processing the North American GLS imagery to surface reflectance, using atmospheric correction routines developed for the Terra MODIS instrument, and then use change-detection techniques to map disturbance, regrowth, and permanent forest conversion across the continent. Phase I activities (2004-2008) focused on mapping disturbance from 1990-2000; Phase II (2009-2011) focuses on providing 5-year updates for the 1990-2005 period. LEDAPS is funded through the NASA Terrestrial Ecosystems Program and the NASA Applied Sciences Program.
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Landsat-5 image of Eastern Virginia, showing "patchwork" of land-cover types
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