Abstract

The Thermal Infrared Sensor (TIRS) onboard Landsat 8 was tasked with continuing thermal band measurements of Earth as part of the Landsat program. From first light in early 2013, there were obvious indications, such as nonuniform banding and varying absolute calibration errors, that stray light was contaminating the thermal image data collected from the instrument. Stray light in this case refers to unwanted radiance from outside the field-of-view entering the optical system and being recorded by the focal plane. Standard calibration techniques used to flat-field and radiometrically correct the data were not sufficient to adjust the image products to within the accuracy that the Landsat community has come to expect. The development of an operational technique to remove the effects of the stray light in the TIRS data has become a high priority. A methodology is presented that makes use of a stray light optical model developed for the instrument along with knowledge of the out-of-field area surrounding the TIRS earth scene. Two versions of the algorithm are proposed in which one method utilizes near-coincident image data from an external sensor while another novel method is proposed that makes use of TIRS image data itself without the need for external data. Preliminary results of the algorithm indicate that banding artifacts due to stray light are significantly reduced when the methods are applied. Additionally, initial absolute calibration error estimates of over 9K are reduced to within 2K when applying the correction methods. Although both variations of the proposed algorithm have significantly reduced the stray light effects, the fact that the latter method utilizing TIRS image data itself does not rely on any external data is a significant advantage toward the development of an operational stray light correction solution. Ongoing work is focused on operationalizing the algorithm and identifying and quantifying potential sources of error when applying the method.

© 2015 Optical Society of America

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