Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)


Electrical Engineering and Computer Science

First Advisor

Larry Leigh

Second Advisor

Dennis Helder


The primary objective of this project was to consistently calibrate the entire Landsat series to a common reflectance scale by performing cross-calibration corrections from Landsat-8 OLI to Landsat- 1 MSS. A consistent radiance-based calibration was already performed from Landsat-8 OLI through Landsat-1 MSS using bright targets and dark targets. The MSS radiance-based calibration results showed an uncertainty of about ±5%. Typically to convert from radiance to reflectance a solar model is used. Unfortunately, there are numerous solar models, all with various levels of accuracies. It was also seen that there is a data format inconsistency for different types of MSS data that impact the radiometric uncertainty of the products when compared to Landsat-8 OLI data. One of the advances Landsat-8 OLI has over to earlier missions is a solar model independent reflectance calibration. Hence, to reduce these uncertainties and remove the dependency on the solar model, direct reflectance-based calibration was performed for all previous missions using Landsat-8 OLI as the “standard”. A consistent cross-calibration of all Landsat sensors was achieved using coincident/near-coincident scene pairs. The work started from cross-calibration of Landsat-8 OLI to Landsat-7 ETM+ and continued through Landsat-1 MSS. Due to the fact each Landsat sensor measures slightly different parts of the electromagnetic spectrum, a spectral band adjustment factor (SBAF) was computed and used prior to the cross-calibration. To determine the significance of the bias derived from cross-calibration, a t-test was performed with a null hypothesis that the bias equals zero at a confidence interval of 95%. From the final calibration equations, it was found that for band 5 of Landsat-1 bias is significant. The effectiveness of these cross-calibration results is discussed by showing a significant improvement in the observed inconsistencies in the absolute calibration of all Landsat sensors for both bright and dark targets. The results show a significant improvement in reflectance calibration, and an overall uncertainty of less than ±3%.

Library of Congress Subject Headings

Landsat satellites -- Calibration.

Artificial satellites in remote sensing -- Calibration.

Reflectance -- Measurement.

Remote sensing -- Data processing.


Includes bibliographical references (pages 104-107)



Number of Pages



South Dakota State University


Copyright © 2016 Sandeep Kumar Chittimalli