Abstract #302214

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JSM 2003 Abstract #302214
Activity Number: 368
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract - #302214
Title: A Comparison of Processing Approaches for Analyzing Spatial Covariance in Large Imagery Datasets
Author(s): James A. Shine*+
Companies: George Mason University
Address: 4218 Alcott St., Alexandria, VA, 22309-1302,
Keywords: spatial statistics ; large datasets ; distributed processing ; high performance computing
Abstract:

Analysis of spatial covariance structure in large imagery datasets produces results useful in optimal sampling design, compression capability, and estimation and classification of unknown data points. However, complete analysis of large imagery datasets is a computational challenge. Several approaches to this challenge are described and compared, including code optimization, parallel processing using clustered computers, and use of high-performance single processors.

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