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Proceedings Paper

Using DIRSIG to identify uniform sites and demonstrate the utility of the side-slither calibration technique for Landsat's new pushbroom instruments
Author(s): Aaron D. Gerace; John R. Schott; Scott D. Brown; Michael G. Gartley
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Paper Abstract

The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are two new sensors being developed by the joint USGS-NASA Landsat Data Continuity Mission (LDCM) that will extend nearly 40 years of archived Landsat data once it achieves orbit in January of 2013. Previous efforts focused on using the DIRSIG (Digital Imaging and Remote Sensing Image Generation) tool to simulate all the phenomenology that can lead to non-uniformity variations in an LDCM image. This includes detector-to-detector and array-to-array non-uniformities due to variations in relative spectral response (RSR), gain, bias, and non-linearities. Synthetic images were generated to predict the LDCM performance pre-launch and to identify calibration concerns. In support of the calibration effort for LDCM, this work expands on an on-orbit calibration technique called side-slither. In this technique, a 90 degree yaw maneuver is performed over a uniform region in an effort to determine a flat-field correction. The first component of this research uses Landsat 5 radiance images as input to DIRSIG to evaluate potential sites for LDCM to perform side-slither once it achieves orbit. Relative gains are calculated and compared over desert regions, the Amazon, water bodies, and Antarctica in an effort to identify suitable sites for the maneuver. The second component of this work uses the DIRSIG tool to model all the non-uniformity variations from previous efforts and to perform the side-slither technique in an effort to calibrate the raw data. Synthetic image data is used and presented to measure the potential value of this calibration technique.

Paper Details

Date Published: 24 May 2012
PDF: 9 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83902A (24 May 2012); doi: 10.1117/12.919327
Show Author Affiliations
Aaron D. Gerace, Rochester Institute of Technology (United States)
John R. Schott, Rochester Institute of Technology (United States)
Scott D. Brown, Rochester Institute of Technology (United States)
Michael G. Gartley, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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