Matthew Montanaro

Stray Light Artifacts in Imagery from the Landsat 8 Thermal Infrared Sensor

The Thermal Infrared Sensor (TIRS) has been collecting imagery of the Earth since its launch aboard Landsat 8 in early 2013. In many respects, TIRS has been exceeding its performance requirements on orbit, particularly in terms of noise and stability. However, several artifacts have been observed in the TIRS data which include banding and absolute calibration discrepancies that violate requirements in some scenes. Banding is undesired structure that appears within and between the focal plane array assemblies. In addition, in situ measurements have shown an error in the TIRS absolute radiometric calibration that appears to vary with season and location within the image. The source of these artifacts has been determined to be out-of-field radiance that scatters onto the detectors thereby adding a non-uniform signal across the field-of-view. The magnitude of this extra signal can be approximately 8% or higher (band 11) and is generally twice as large in band 11 as it is in band 10. A series of lunar scans were obtained to gather information on the source of this out-of-field radiance. Analyses of these scans have produced a preliminary map of stray light, or ghost, source locations in the TIRS out-of-field area. This dataset has been used to produce a synthetic TIRS scene that closely reproduces the banding effects seen in actual TIRS imagery. Now that the cause of the banding has been determined, a stray light optics model is in development that will pin-point the cause of the stray light source. Several methods are also being explored to correct for the banding and the absolute calibration error in TIRS imagery.

The Thermal Infrared Sensor (TIRS) on Landsat 8: Design Overview and Pre-Launch Characterization

The Thermal Infrared Sensor (TIRS) on Landsat 8 is the latest thermal sensor in that series of missions. Unlike the previous single-channel sensors, TIRS uses two channels to cover the 10–12.5 micron band. It is also a pushbroom imager; a departure from the previous whiskbroom approach. Nevertheless, the instrument requirements are defined such that data continuity is maintained. This paper describes the design of the TIRS instrument, the results of pre-launch calibration measurements and shows an example of initial on-orbit science performance compared to Landsat 7.

Radiometric Calibration Methodology of the Landsat 8 Thermal Infrared Sensor

The science-focused mission of the Landsat 8 Thermal Infrared Sensor (TIRS) requires that it have an accurate radiometric calibration. A calibration methodology was developed to convert the raw output from the instrument into an accurate at-aperture radiance. The methodology is based on measurements obtained during component-level and instrument-level characterization testing. The radiometric accuracy from the pre-flight measurements was estimated to be approximately 0.7%. The calibration parameters determined pre-flight were updated during the post-launch checkout period by utilizing the on-board calibration sources and Earth scene data. These relative corrections were made to adjust for differences between the pre-flight and the on-orbit performance of the instrument, thereby correcting large striping artifacts observed in Earth imagery. Despite this calibration correction, banding artifacts (low frequency variation in the across-track direction) have been observed in certain uniform Earth scenes, but not in other uniform scenes. In addition, the absolute calibration performance determined from vicarious measurements have revealed a time-varying error to the absolute radiance reported by TIRS. These issues were determined to not be caused by the calibration process developed for the instrument. Instead, an investigation has revealed that stray light is affecting the recorded signal from the Earth. The varying optical stray light effect is an ongoing subject of evaluation and investigation, and a correction strategy is being devised that will be added to the calibration process.

On-Orbit Radiometric Performance of the Landsat 8 Thermal Infrared Sensor

The Thermal Infrared Sensor (TIRS) requirements for noise, stability, and uniformity were designed to ensure the radiometric integrity of the data products. Since the launch of Landsat 8 in February 2013, many of these evaluations have been based on routine measurements of the onboard calibration sources, which include a variable-temperature blackbody and a deep space view port. The noise equivalent change in temperature (NEdT) of TIRS data is approximately 0.05 K @ 300 K in both bands, exceeding requirements by about a factor of 8 and Landsat 7 ETM+ performance by a factor of 3. Coherent noise is not readily apparent in TIRS data. No apparent change in the detector linearization has been observed. The radiometric stability of the TIRS instrument over the period between radiometric calibrations (about 40 min) is less than one count of dark current and the variation in terms of radiance is less than 0.015 \(W/m^2/sr/\mu m\) (or 0.13 K) at 300 K, easily meeting the short term stability requirements. Long term stability analysis has indicated a degradation of about 0.2% or less per year. The operational calibration is only updated using the biases taken every orbit, due to the fundamental stability of the instrument. By combining the data from two active detector rows per band, 100% detector operability is maintained for the instrument. No trends in the noise, operability, or short term radiometric stability are apparent over the mission life. The uniformity performance is more difficult to evaluate as scene-varying banding artifacts have been observed in Earth imagery. Analyses have shown that stray light is affecting the recorded signal from the Earth and inducing the banding depending on the content of the surrounding Earth surface. As the stray light effects are stronger in the longer wavelength TIRS band11 (12.0 \(\mu m\)), the uniformity is better in the shorter wavelength band10 (10.9 \(\mu m\)). Both bands have exceptional noise and stability performance and band10 has generally adequate uniformity performance and should currently be used in preference to band11. The product uniformity will improve with the stray light corrections being developed.

Toward an operational stray light correction for the Landsat 8 Thermal Infrared Sensor

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.

Performance of the QWIP focal plane arrays for NASA's Landsat Data Continuity Mission

The focal plane assembly for the Thermal Infrared Sensor (TIRS) instrument on NASAs Landsat Data Continuity Mission (LDCM) consists of three 512 x 640 GaAs Quantum Well Infrared Photodetector (QWIP) arrays. The three arrays are precisely mounted and aligned on a silicon carrier substrate to provide a continuous viewing swath of 1850 pixels in two spectral bands defined by filters placed in close proximity to the detector surfaces. The QWIP arrays are hybridized to Indigo ISC9803 readout integrated circuits (ROICs). QWIP arrays were evaluated from four laboratories; QmagiQ, (Nashua, NH), Army Research Laboratory, (Adelphi, MD), NASA/ Goddard Space Flight Center, (Greenbelt, MD) and Thales, (Palaiseau, France). All were found to be suitable. The final discriminating parameter was the spectral uniformity of individual pixels relative to each other. The performance of the QWIP arrays and the fully assembled, NASA flight-qualified, focal plane assembly will be reviewed. An overview of the focal plane assembly including the construction and test requirements of the focal plane will also be described.

An Analysis of the Side Slither On-Orbit Calibration Technique Using the DIRSIG Model

Pushbroom-style imaging systems exhibit several advantages over line scanners when used on space-borne platforms as they typically achieve higher signal-to-noise and reduce the need for moving parts. Pushbroom sensors contain thousands of detectors, each having a unique radiometric response, which will inevitably lead to streaking and banding in the raw data. To take full advantage of the potential exhibited by pushbroom sensors, a relative radiometric correction must be performed to eliminate pixel-to-pixel non-uniformities in the raw data. Side slither is an on-orbit calibration technique where a 90-degree yaw maneuver is performed over an invariant site to flatten the data. While this technique has been utilized with moderate success for the QuickBird satellite [1] and the RapidEye constellation [2], further analysis is required to enable its implementation for the Landsat 8 sensors, which have a 15-degree field-of-view and a 0.5% pixel-to-pixel uniformity requirement. This work uses the DIRSIG model to analyze the side slither maneuver as applicable to the Landsat sensor. A description of favorable sites, how to adjust the maneuver to compensate for the curvature of “linear” arrays, how to efficiently process the data, and an analysis to assess the quality of the side slither data, are presented.

The Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) on the Landsat Data Continuity Mission (LDCM)

The Landsat Data Continuity Mission (LDCM), a partnership between the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) / United States Geological Survey (USGS), is scheduled for launch in December, 2012. It will be the eighth mission in the Landsat series. The LDCM instrument payload will consist of the Operational Land Imager (OLI), provided by Ball Aerospace and Technology Corporation (BATC) under contract to NASA and the Thermal Infrared Sensor (TIRS), provided by NASAs Goddard Space Flight Center (GSFC). This paper outlines the present development status of the two instruments.

Preliminary on-orbit performance of the Thermal Infrared Sensor (TIRS) on board Landsat 8

The Thermal Infrared Sensor (TIRS) on board Landsat 8 continues thermal band measurements of the Earth for the Landsat program. TIRS improves on previous Landsat designs by making use of a pushbroom sensor layout to collect data from the Earth in two spectral channels. The radiometric performance requirements of each detector were set to ensure the proper radiometric integrity of the instrument. The performance of TIRS was characterized during pre-flight thermal-vacuum testing. Calibration methods and algorithms were developed to translate the raw signal from the detectors into an accurate at-aperture spectral radiance. The TIRS instrument has the ability to view an on-board variable-temperature blackbody and a deep space view port for calibration purposes while operating on-orbit. After TIRS was successfully activated on-orbit, checks were performed on the instrument data to determine its image quality. These checkouts included an assessment of the on-board blackbody and deep space views as well as normal Earth scene collects. The calibration parameters that were determined pre-launch were updated by utilizing data from these preliminary on-orbit assessments. The TIRS on-orbit radiometric performance was then characterized using the updated calibration parameters. Although the characterization of the instrument is continually assessed over the lifetime of the mission, the preliminary results indicate that TIRS is meeting the noise and stability requirements while the pixel-to-pixel uniformity performance and the absolute radiometric performance require further study.

The development of a DIRSIG simulation environment to support instrument trade studies for the SOLARIS sensor

NASA Goddard’s SOLARIS (Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer) sensor is the calibration demonstration system for CLARREO (Climate Absolute Radiance and Refractivity Observatory), a mission that addresses the need to make highly accurate observations of long-term climate change trends. The SOLARIS instrument will be designed to support a primary objective of CLARREO, which is to advance the accuracy of absolute calibration for space-borne instruments in the reflected solar wavelengths. This work focuses on the development of a simulated environment to facilitate sensor trade studies to support instrument design and build for the SOLARIS sensor. Openly available data are used to generate geometrically and radiometrically realistic synthetic landscapes to serve as input to an image generation model, specifically the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Recent enhancements to DIRSIG’s sensor model capabilities have made it an attractive option for performing sensor trade studies. This research takes advantage of these enhancements to model key sensor characteristics (e.g., sensor noise, relative spectral response, spectral coverage, etc.) and evaluate their impact on SOLARIS’s stringent 0.3% error budget for absolute calibration. A SOLARIS sensor model is developed directly from measurements provided by NASA Goddard and various synthetic landscapes generated to identify potential calibration sites once the instrument achieves orbit. The results of these experiments are presented and potential sources of error for sensor inter-calibration are identified.