Document Type
Thesis - University Access Only
Award Date
2005
Degree Name
Master of Science (MS)
Department / School
Electrical Engineering and Computer Science
Abstract
The purpose of this research was to obtain an improved radiometric gain estimate for the Landsat 5 Thematic Mapper (TM) instrument over its operating lifetime. This investigation is important because the Landsat 5 TM instrument has operated more than 20 years. An estimate of the TM gain is acquired by the onboard Internal Calibrator (IC) as well as by ground-based vicarious calibration methods. The TM gain measured by the IC method depends on the performance of the internal calibrator, which can degrade over extended operation. On the other hand, ground based vicarious calibration primarily depends on surface reflectance estimation and atmospheric modeling. An improved radiometric gain of the TM was investigated considering both of these methods. The TM gain was estimated independently from both IC and vicarious methods. Gain estimation in each step was performed by using the forward-backward smoothing Kalman filter. The estimated lifetime gain by vicarious method illustrates the necessity of a correction for the IC gain model. After correction of the IC model, the estimated gain by the IC and vicarious methods were in better agreement. The relative difference between the estimated IC and vicarious gain is within 2% for the primary focal plane bands and 6% for the cold focal plane bands. Finally the estimated IC and vicarious gain were combined together to obtain an optimal radiometric gain of the instrument. The estimated vicarious gain has large error covariances and it was found that the optimum TM gain closely followed the estimated IC gain.
Library of Congress Subject Headings
Landsat satellites -- Calibration
Imaging systems -- Image quality
Format
application/pdf
Number of Pages
174
Publisher
South Dakota State University
Recommended Citation
Haque, Md. Obaidul, "Optimal Estimation of Landsat 5 Thematic Mapper Gain" (2005). Electronic Theses and Dissertations. 1191.
https://openprairie.sdstate.edu/etd2/1191