|
Activity Number:
|
321
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
| Abstract - #308496 |
|
Title:
|
Spatio-Temporal Processing of MISR's Aerosol Optical Depth Data
|
|
Author(s):
|
Tao Shi*+ and Noel Cressie
|
|
Companies:
|
The Ohio State University and The Ohio State University
|
|
Address:
|
317 Cockins Hall, 1958 Neil Ave., Columbus, OH, 43210,
|
|
Keywords:
|
data processing ; Kalman filtering ; kriging ; spatial heterogeneity
|
|
Abstract:
|
NASA's Multiangle Imaging Spectro Radiometer (MISR) provides level-2 data at 1.1km by 1.1km spatial resolution, and the satellite returns to its original location on the globe every 16 days. These level-2 data can be converted to level-3 data at a much lower spatial resolution by averaging those observations falling in lower-resolution pixels over a contiguous number of days; this results in a level-3 monthly data product at a resolution of 0.5 degree latitude by 0.5 degree longitude. Our goal is to fill in missing data and to de-noise the existing data, at level-3, in a statistically optimal way, where we exploit both the spatial and temporal dependencies in the data. We propose a method that combines elements of kriging and Kalman filtering to accomplish these goals, and we shall use the MISR Aerosol Optical Depth data to illustrate our approach.
|
