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The Implementation of an Operational MODIS Aerosol Retrieval Algorithm at High Spatial Resolution

Heidary, Parisa | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48558 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Tajrishy, Masoud
  7. Abstract:
  8. Urmia Lake is one of the largest permanent hypersaline lakes in the world. Since Urmia Lake is faced with drying phenomena, the release of dust from its surface is expected. The most appropriate technique on dust storms is the remote sensing technique. One of the most popular parameter that provides the integrated information over a vertical column of unit cross section of this phenomenon is aerosol optical depth (AOD). Satellite remote sensing has been used to retrieve AOD over land and ocean at spatial resolutions of several to several tens of km. However, higher spatial resolution aerosol products for local scale areas have not been well-researched mainly due to the difficulty of differentiating aerosols from bright surfaces in local scales.
    This research, first presents the method to retrieve aerosol optical depth at 500 m resolution from MODIS data and compare it to Aerosol Robotic Network (AERONET) data, then analyzes the spatial and Frequency-of-Occurrence (FO) distributions of AOD. Eventually the sources according to high AOD and high FO are detected, and the resulting distribution is compared with MODIS 10 km AOD product. A simplified aerosol retrieval algorithm using the MODIS 500-m resolution bands is used, to retrieve aerosol optical depth over study basin which includes Lake Urmia as well. The 32 MODIS images in the dusty days of 2010–2013 were utilized in this study. Algorithm was applied directly to the MODIS data, with the aerosol properties derived from a local urban AERONET station at Zanjan Institute for Advanced Studies in Basic Sciences. The 500 m AOD retrieved from the algorithm showed a high consistency with ground-based AOD measurements, with average correlation coefficient ~0.726. Comparison results demonstrate that the simplified AOD algorithm is better able to represent aerosol conditions and hotspots over Urmia Lake than the MODIS standard product
  9. Keywords:
  10. Urumieh Lake ; Aerosol Optical Depth ; Dust Sources ; Remote Sensing ; MODIS Data ; Dust Source Detection

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