Analysis of VIIRS Aerosol and Land Surface Reflectance EDRs

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 Analysis of VIIRS Aerosol and Land Surface
Reflectance EDRs 

• Alexei Lyapustin, UMBC
• Nov 4-6, 2003 

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Analysis of VIIRS Aerosol and Land Reflectance
EDRs

• LIST OF EDRs
• (algorithms aerosol retrieval and atmospheric
  correction over land)
• Aerosol Optical Thickness and Particle Size
• Land Surface Albedo (spectral and shortwave
  broadband), BRDF and Vegetation Indices
• INVESTIGATORS
• PI Alexei Lyapustin (UMBC)
• (lead on synthetic data sets, algorithm
  development, and AGVN development)
• Co-I Yujie Wang (UMBC)
• (software development, MODIS MISR data
  processing for AGVN)
• Jeff Privette (GSFC)
• (land product validation, AGVN development)
• Collaborator Brent Holben (GSFC)
• (AERONET support, AGVN logistics)
• POTENTIAL COLLABORATIONS
• Geolocation Robert Wolf
• Albedo Validation Shunlin Liang

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APPROACH
Generate Synthetic Data Sets (SHARM-3D
non-homogeneous non-Lambertian surface,
atmo-spheric gaseous and water vapor absorption)
Self-consistent Accuracy Analysis
1.
VIIRS Aerosol Retrieval and Atmospheric
Correction
Accuracy Analysis based on Ground Data
Use MODIS Data to Emulate VIIRS
Measurements (will require recalculation of VIIRS
LUTs for MODIS channels)
Ground Validation AGVN
2.
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AGVN - AERONET-based Ground Validation Network
AGVN Products BRDF 1.
Point-wise in Observation Angles 2.
Best-fit MRPV (MISR) 3. Best-fit Kernel
(MODIS) Albedo 1. Spectral 2.
Shortwave Broadband (SB) 3. Spectral and SB
Fluxes Spectral Regression (for AOT retrieval)
1. 2.1 mkm -gt blue red
Expected Benefits 1. Validation
of surface albedo/BRDF 2. Development of global
surface climatology for aerosol
retrievals 3. Way to MODIS MISR data
fusion Calibration Analysis 4. Vicarious
calibration 5. Cross-calibration of different
sensors 6. Detection of calibration trend based
on a time series of surface reflectance
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Deliverables
We will contribute to

• Algorithm Analysis Report
• Government Cal/Val Plan
• NPP Team Algorithm Analysis
• by Sharing Synthetic Data Set