HR: 11:20h
AN: GC22A-04    [Abstracts]
TI: Timber volume and biomass estimates in central Siberia from satellite data.
AU: * Ranson, J
EM: jon.ranson@nasa.gov
AF: NASA GSFC, Code 614.4, Greenbelt, MD 20771, United States
AU: Kimes, D
EM: daniel.s.kimes@nasa.gov
AF: NASA GSFC, Code 614.4, Greenbelt, MD 20771, United States
AU: Kharuk, V
EM: kharuk@ksc.krasn.ru
AF: V.N.Sukachev Institute of Forest, Academgorodok, Karsnoyarsk, 660036, Russian Federation
AU: Kharuk, V
EM: kharuk@ksc.krasn.ru
AF: University of Maryland- College Park, NASA GSFC Code 614.4, Greenbelt, MD 20771, United States
AU: Sun, G
EM: guoqing.sun@gmail.com>
AF: University of Maryland- College Park, NASA GSFC Code 614.4, Greenbelt, MD 20771, United States
AU: Montesanto, P
EM: pmontesano@pop600.gsfc.nasa.gov
AF: SSAI, Inc, NASA GSFC Code 614.4, Greenbelt, MD 20771, United States
AB: Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10˚x12˚ area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.
DE: 1632 Land cover change
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting