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National Science Foundation Award #0534036

Artificial Neural Networks: A New Landscape Characterization Toolbox

 
Investigator(s): Audrey Huerta (PI) ; David Reusch (Co-PI)
Sponsor: Pennsylvania State Univ University Park, PA 16802 8148654700
Start Date/Expiration Date 2005-07-01 to 2006-06-30 (amended 2005-06-29)
Awarded Amount to Date: $75,509
Abstract: This project uses self-organizing maps, a form of artificial neural network techniques, to determine the role of glacial processes in uplift of the Transantarctic Mountains (TAM). The link between erosion and mountain building is known, but difficult to resolve because the processes are dynamically coupled. The TAM offer a unique opportunity to explore this relationship because they have been tectonically quiescent since the late Oligocene, but have undergone various forms of glaciation. Previous investigations of their landscape evolution have been based primarily on field inspection of landforms and surface features, a time intensive and logistically difficult undertaking. While these studies have documented the varying climatic influences on the TAM and the importance of fluvial, glacial, and desert processes in shaping the landscape, we are still left without an accounting of the impact of glacial erosion along the TAM as a whole. This project uses digital elevation models and self-organizing map analysis to provide quantitative metrics that characterize glacial landforms and determine the overall role of glaciation in mountain-building. The broader impacts of this work are improving society's understanding of global climate change by demonstrating links between climate and landform.
NSF Org: ANT - Antarctic Sciences Section
Award Number: 0534036
Award Instrument: Standard Grant
Program Manager: Thomas P. Wagner
ANT Antarctic Sciences Section
OPP Office of Polar Programs
NSF Program(s): ANTARCTIC GEOLOGY & GEOPHYSICS
Field Application(s): Polar Programs-Related
Program Reference Code(s): SMALL GRANTS-EXPLORATORY RSRCH, 9237
UNASSIGNED, 0000
Program Element Code(s): 5112