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Figure 3. The Credo field site. 
  
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Figure 4. A time series of atmospherically corrected MODIS 
band 18 for 2009 representative of the Credo site. 
3.2 Reflectance Change-Based Dust Storm Detection 
As part of our AusCover work we are also extending the work 
of Broomhall et al (2009) in using atmospherically corrected 
MODIS surface reflectance data to detect dust storms. This 
work comes as bi-product of the need to devise new approaches 
to achieve accurate estimation of aerosol optical depth under 
Australian conditions. The typically bright land surface which 
exhibits sparse vegetation cover does not suits dark dense 
vegetation-based approaches to aerosol estimation (Broomhall 
et al, 2009). In this work we use the difference between the 
MODIS surface reflectance measurement and the surface 
reflectance predicted by the Bi-direction Reflectance 
Distribution Function (BRDF) to estimate aerosols. Such a 
‘reflectance change’ based approach also proves effective for 
detecting dust storms as shown in Figure 5. 
  
Figure 5. Dust storms detected from MODIS imagery using the 
reflectance change based methodology. 
4. CONCLUSION 
The AusCover project under the TERN program is compiling an 
archive of remotely sensed data linked to supporting in situ 
measurements with the aim of constructing a HPC-based 
research infrastructure towards a new era of ecological research 
and understanding. 
In this work we have concentrated on developments in MODIS 
processing that support well-quantified atmospheric correction 
of surface reflectance which we envisage will underpin new 
applications in ecological research and earth system science. 
5. REFERNCES 
Broomhall, M, McAtee, B., and Maier, S. 2009. An 
investigation of the remote sensing of aerosols based on 
MODIS data for Western Australia. Springer Verlag series on 
Geoinformation and Cartography, Series Editors: Cartwright, 
W., Gartner, G., Meng, L., & Peterson, M. ISSN:1863-2246. 
Justice, C., et al. 1998. The Moderate Resolution Imaging 
Spectroradiometer (MODIS): land remote sensing for global 
change research. IEEE transactions on Geoscience and Remote 
Sensing, 36, pp.1228-1249. 
McAtee, B and Maier, S., 2009. Improved near-real time 
atmospheric correction of MODIS data for Earth observation 
applications. Springer Verlag series on Geoinformation and 
Cartography, Series Editors: Cartwright, W., Gartner, G., 
Meng, L., & Peterson, M. ISSN:1863-2246.