Radiometric Non-Uniformity Characterization and Correction of Landsat 8 OLI Using Earth Imagery-Based Techniques

Abstract

Landsat 8 is the first satellite in the Landsat mission to acquire spectral imagery of the Earth using pushbroom sensor instruments. As a result, there are almost 70,000 unique detectors on the Operational Land Imager (OLI) alone to monitor. Due to minute variations in manufacturing and temporal degradation, every detector will exhibit a different behavior when exposed to uniform radiance, causing a noticeable striping artifact in collected imagery. Solar collects using the OLI's on-board solar diffuser panels are the primary method of characterizing detector level non-uniformity. This paper reports on an approach for using a side-slither maneuver to estimate relative detector gains within each individual focal plane module (FPM) in the OLI. A method to characterize cirrus band detector-level non-uniformity using deep convective clouds (DCCs) is also presented. These approaches are discussed, and then, correction results are compared with the diffuser-based method. Detector relative gain stability is assessed using the side-slither technique. Side-slither relative gains were found to correct streaking in test imagery with quality comparable to diffuser-based gains (within 0.005% for VNIR/PAN; 0.01% for SWIR) and identified a 0.5% temporal drift over a year. The DCC technique provided relative gains that visually decreased striping over the operational calibration in many images.

Landsat-8 Operational Land Imager (OLI) Radiometric Performance On-Orbit

“…Using the Earth surface to characterize relative gains is challenging, as most, if not all, surfaces are not uniform or Lambertian enough to be used without additional knowledge. Some methods to make use of relatively large uniform targets are used to assess the uniformity of the OLI as shown in [8] though they are not mature enough to implement yet.…”

“…Performing these side slither maneuvers over uniform regions of the Earth enables individual detector calibration coefficients to be generated that can improve the pixel-to-pixel uniformity. These maneuvers are performed over desert or snow/ice regions about every three months to monitor and potentially improve the pixel-to-pixel uniformity [8].…”

A Relative Radiometric Calibration Method Based on the Histogram of Side-Slither Data for High-Resolution Optical Satellite Imagery

“…To more objectively evaluate the effects of the coefficients, different indices were proposed based on different validation datasets. The side-slither data for Group B described in Section 4.1 made use of the relative radiometric accuracy indices "root-mean-square deviation of the mean line" (RA) and "generalized noise" (RE), as well as streaking metrics [10], which could be treated as a uniform field because side-slither data have the same input radiance for each detector. The image data for Group C could be quantitatively evaluated using streaking metrics, the improvement factor (IF), and the structural similarity index (SSIM).…”

“…This new imaging mode has been applied to a satellite that can rotate its array 90 degrees on the yaw axis, which means that every detector is ideally aligned to image the same target as it moves along the velocity vector. Numerous satellites incorporate this imaging mode, including Landsat 8 [10], RapidEye [11], Pleiades-HR [12], and QuickBird [13]. Because the CCDs (charge-coupled device) or detectors are staggered, to ensure that the input of each detector is identical, the satellite needs to take images of a uniform field in the new mode used by Landsat 8, and QuickBird.…”

Landsat-8 Sensor Characterization and Calibration

“…Absolute calibration and stability using the on-board calibration devices is covered in the same paper [10] for TIRS, but in detail in a separate paper for OLI (Markham et al,[11]). Analysis of an alternate way to perform detector-to-detector relative radiometric calibration to reduce striping and banding artifacts in imagery is discussed in two papers: Pesta et al [12] which specifically examines OLI and Gerace et al [13], which examines strategies from a more theoretical standpoint using simulations. Validation of the OLI and TIRS radiometric calibrations by using surface measurements, also known as vicarious calibration and by comparison to other instruments, e.g., the Landsat-7 ETM+ is covered in five papers.…”