HR: 0800h
AN: NG41C-0667    [Abstracts]
TI: Integration of ASTER thermal infrared data and the Google Earth application to examine the relationship between sand transport pathways and dust emission hot-spots
AU: * Scheidt, S P
EM: sps11@pitt.edu
AF: Geology and Planetary Science University of Pittsburgh, SRCC 200 4107 O'Hara Street, Pittsburgh, PA 15260, United States
AU: Lancaster, N
EM: nick.lancaster@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, United States
AU: Ramsey, M
EM: mramsey@pitt.edu
AF: Geology and Planetary Science University of Pittsburgh, SRCC 200 4107 O'Hara Street, Pittsburgh, PA 15260, United States
AB: The identification and characterization of major mineral dust source areas from the Sahara Desert and the composition of these particulates are critical to our understanding of global dust production, models of atmospheric emission and transport, and determination of radiative properties of dust plumes from desert regions. The locations of many of these dust hot-spots have been determined using data such as the Total Ozone Mapping Spectrometer aerosol index (TOMS AI), showing that the largest sources of global dust are located in the Sahara Desert of west and central Africa. Studies using geochemical tracers, surface observations, analysis of meteorological data, and remote sensing have, however, arrived at different and sometimes conflicting delineations of Saharan dust sources. Geomorphic environment is a major control on dust emission source and process. Surface and remote sensing observations of the Bodele Depression, the largest dust source in the Sahara, show that sand saltation on the playa surface and the abrasion of material are the primary processes in generating dust. In order to test the hypothesis that other major natural global dust emission sources are linked to the interaction of sand transport along defined pathways and dust sources, multispectral thermal infrared (TIR) data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are integrated with the high resolution, mosaicked image data available from the Google Earth application. The geomorphic environment, surface composition and their relative importance as a control on dust emissions are assessed using high resolution data at dust hot-spots that were identified by the TOMS AI at the much lower spatial resolution of one pixel/degree.
DE: 1029 Composition of aerosols and dust particles
DE: 1625 Geomorphology and weathering (0790, 1824, 1825, 1826, 1886)
DE: 1640 Remote sensing (1855)
DE: 1824 Geomorphology: general (1625)
DE: 1843 Land/atmosphere interactions (1218, 1631, 3322)
SC: Nonlinear Geophysics [NG]
MN: 2007 Fall Meeting