HR: 11:50h
AN: B42A-07    [Abstracts]
TI: Classifying fire type based on MODIS vegetation time-series signal
AU: * Morisette, J T
EM: jeff.morisette@nasa.gov
AF: NASA's Goddard Space Flight Center, Terrestrial Information Systems Branch Mail code 923, Greenbelt, MD 20771 United States
AU: Morton, D
EM: morton@geog.umd.edu
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AU: Defries, R
EM: rd63@umail.umd.edu
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AU: Csiszar, I
EM: icsiszar@hermes.geog.umd.edu
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AU: Schroeder, W
EM: schroeder@geog.umd.edu
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AU: Giglio, L
EM: giglio@hades.gsfc.nasa.gov
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AU: Justice, C
EM: justice@hermes.geog.umd.edu
AF: University of Maryland, Geography Department 2181 LeFrak Hall, College Park, MD 20742 United States
AB: The importance of fire in tropical ecosystems is growing as both direct and indirect consequences of land use. Throughout the 80s and early 90s, constantly increasing human forcing and climate anomalies made forest fires in the Amazon Basin a major environmental issue. However, not all fires are equal. Some fires result in a major conversion of the landscape. While in other locations, fires are necessary to maintain the landscape. As land management and carbon science efforts continue to focus on the role of fire, it will be important to "filter" fire maps to differentiate between conversion and maintenance fires. To develop such a filter, we explore the MODIS vegetation signal before and after fires to establish the time series signal associated with different types of fire. In this work we present the time series signal for a set of prescribed burns, including recently deforested areas and grasslands managed for grazing. Results show that fires and land cover dynamics do influence the MODIS signal, but there is significant noise. To resolve complicated time series signatures, it is critical to utilize longer time series profiles and the MODIS quality assessment (QA) flags for proper interpretation of the data.
DE: 1615 Biogeochemical processes (4805)
DE: 0400 Biogeosciences
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting