HR: 1340h
AN: B43A-0131 [Abstracts]
TI: Remotely Sensed Carbon and Water Variations at LBA Site to Amazon Regional Scales With Hyperion and
MODIS Data
AU: * Ratana, P
EM: piyachat@ag.arizona.edu
AF: Department of Soil, Water and Environmental Science, 429 Shantz Building #38
University of Arizona, Tucson, AZ 85721-0038
United States
AU: Huete, A R
EM: ahuete@ag.arizona.edu
AF: Department of Soil, Water and Environmental Science, 429 Shantz Building #38
University of Arizona, Tucson, AZ 85721-0038
United States
AU: Kim, Y
EM: ywkim@ag.arizona.edu
AF: Department of Soil, Water and Environmental Science, 429 Shantz Building #38
University of Arizona, Tucson, AZ 85721-0038
United States
AB:
We investigated the spatial and temporal variations in vegetation biologic activity at various LBA core and field sites with
carbon and water indices derived from fine resolution Hyperion data and moderate resolution MODIS observations. Leaf level
and canopy level surface moisture indices were computed over a range of climate conditions and land cover conversions with
hyperspectral Hyperion data. The moisture indices were combined with carbon measures, such as vegetation indices, to map
spatial and temporal patterns of above-ground net productivity and analyze ecosystem sensitivity to water availability. The
coupled water and carbon indices were scaled up to MODIS data for spatial and seasonal extension. MODIS water indices, land
surface temperature, vegetation indices, and LAI and FPAR products were extracted over both natural and converted areas and
over a climatic gradient of Amazon sites. Land surface moisture and carbon patterns behaved in an opposite manner between
natural and converted areas and exhibited significant seasonal variations. Our results show that these satellite datasets
can track vegetation activity in the Amazon region, including biologic responses to shifts in vegetation type and
disturbance. Remotely-sensed land surface water indices combined with the carbon products yield important information useful
in the prediction of vegetation health response to climate change and human land cover modifications.
DE: 1655 Water cycles (1836)
DE: 1620 Climate dynamics (3309)
DE: 1640 Remote sensing
DE: 0400 Biogeosciences
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting