Document Type

Thesis - University Access Only

Award Date


Degree Name

Master of Science (MS)

Department / School

Electrical Engineering

First Advisor

Dennis Helder


During the 1980’s researchers began to explore the use of relatively low resolution data sets to monitor large geographical areas. The primary interest was to improve mapping, resource analysis, and land management activities. One of the sources of this data is from the Advanced Very High Resolution Radiometer, AVHRR, carried aboard satellite platforms operated by the National Oceanic and Atmospheric Administration, NOAA. These sensors are capable of providing a maximum of 1.1 km resolution at the orbital subpoint. The corresponding size of the generated data set is about 100 million bytes for a five band multi-spectral observation covering 10 million square kilometers of Earth geography. One of the more challenging problems associated with the computer processing of these large data sets is how to detect data corruption that may occur due to electrical noise and hardware malfunctions in the complex electronics and communication systems used to transfer the data from satellite platforms to the ultimate end users. This paper examines several of the more common disruption situations and presents a technique to efficiently search for corrupted data. A single pass, two stage, data search procedure is presented which utilizes statistical methods to filter out the corrupted data. One stage of the process, based on global line statistics, is designed to detect large scale problems. If global testing is inconclusive, a more localized inspection is performed to isolate regions of statistically outlying data. Simple analysis methods are then used to determine if there is a spatial pattern present indicating a corrupted region. Promising results from the prototype code included with this paper have prompted the EROS Data Center to begin formal testing and implementation of the ideas presented here within the framework of their AVHRR Data Acquisition and Processing System, ADAPS.

Library of Congress Subject Headings

Remote sensing -- Data processing
Imaging systems in meteorology




South Dakota State University



Rights Statement

In Copyright