Landsat 9 Cross Calibration Under-Fly of Landsat 8: Planning, and Execution
Abstract
:1. Background
Previous Landsat Missions
2. Planning Goals and Strategy
2.1. Goals
2.2. Strategy
2.2.1. Planning Constraints
2.2.2. Ascent Planning
2.2.3. Scene Acquisition Ramp up to Tandem Flying
- D34–36: 200 scenes;
- D37–38: 500 scenes;
- D39–40: 700 scenes;
- D41-onwards: 740 scenes.
2.2.4. Calibration Site Identification
- OLI-2Acquisition priority was given to cover three different approaches for radiometric evaluation; simulations of the under-fly period for cross calibration, various Pseudo Invariant Calibration Sites (PICS) based approaches for trending and cross calibration, and vicarious calibration team field measurements for absolute and cross calibration. For the under-fly, the following criteria were met; acquire all images within +/− 45 degrees latitude (excluding 0 and -10 degrees), for all land cover types classes derived by SDSU [2] that exhibited less than 1% uncertainty impacts due to spectral and angular corrections, and for similar view angles and solar angles. “Sand” classification targets included PICS and Extended PICS sites (EPICS), e.g., North Africa desert, given their temporal and spectral stability characteristics and broad coverage providing worldwide trending information. Sites were also identified and measured by CalVal members from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and international collaborators. USGS EROS coordinated this effort that included Australia and South Africa sites.
- TIRS-2Considering the utility of the open-ocean and near-shore data acquired during the Landsat 8/Landsat 7 under-flight (i.e., these data were critical for the development of the TIRS stray-light mitigation algorithm), an emphasis was placed on identifying similar scenes for the Landsat 9/Landsat 8 under flight. Roughly 75% of the image data acquired by TIRS during the Landsat 8/Landsat 7 under flight were contaminated with clouds. As such, a simple geographic information system (GIS) tool was developed here to better identify potential cloud-free scenes for acquisition, see Figure 2.A 20-year temporal average of the Moderate Resolution Imaging Spectroradiometer (MODIS) monthly cloud product (MODIS Standard Atmosphere Level-3 MCD06COSP product) for November was obtained (Figure 2, left) and a threshold of 50% set to identify areas where cloud coverage would be less likely. Figure 2 (right) shows the thresholded image where black represents areas with less than 50% cloud probability based on the MODIS product. (Note that a 25% threshold nearly eliminates all the favorable (black) regions in Figure 2, right). The orbital model “WRS2DATA” file developed by Flight Dynamics System (discussed later) was used to predict where Landsat 9 would be during commissioning and, for this study, the under-flight period from ~13 November 2021 to 17 November 2021. The orange dotted lines in Figure 2 (right) shows where the orbital model and low cloud regions intersect for the first day of the under flight.Recommendations for favorable intervals were made based on this analysis with a ‘highest’ priority given to nearshore continental United States (CONUS) path/rows due to the availability of reference data. (Note that the National Oceanic and Atmospheric Administration (NOAA) nearshore buoy network is extensive, and a ground campaign was conducted across the United States by RIT using Tidbit temperature sensors to expand the availability of reference data to support TIRS-2 calibration efforts.) ‘High’ priority was given to world-wide nearshore scenes as the contrast between hot land and cooler water provides potential scenarios where effects due to stray light can be observed in the image data. Near-shore image data acquired with TIRS during the Landsat 8/Landsat 7 under-fly were critical to the development of its stray light correction algorithm. Finally, open ocean scenes were assigned a ‘medium’ priority because reference data are typically not available, and land-geometries are not present to inform on the presence of stray light. In the context of calibration, open ocean scenes also have significant utility for flat-field assessment.
3. Execution
3.1. Launch and Ascent
3.2. Acquisition Scheduling
3.2.1. Scheduling Constraints
- Maximum number of night acquisitions per orbit is limited to 24 scenes;
- Maximum off-nadir angle is limited to +/− 15 degrees;
- Maximum number of scenes within an off-nadir collect is limited to 18 scenes;
- Maximum number of off-nadir acquisitions per orbit is limited to two;
- For simultaneous day earth collects, point Landsat 9 off-nadir keeping Landsat 8 nadir to minimize the loss of science acquisitions of the operational satellite;
- For simultaneous day ocean collects, point Landsat 9 off-nadir keeping Landsat 8 nadir, or point Landsat 8 off-nadir keeping Landsat 9 nadir, whichever is desired depending on the target;
- For simultaneous night collects, point Landsat 9 off-nadir keeping Landsat 8 nadir, or point Landsat 8 off-nadir keeping Landsat 9 nadir, whichever is desired depending on the target.
3.2.2. Flight Dynamics Products
3.2.3. UPE (User Portal Elements)
4. Data Collection
5. Lessons Learned
- The SCR scene rejection criteria differed based upon the solar zenith angle. As noted previously, there were two scheduling systems (i.e., Landsat 8 MOC and Landsat 8 and Landsat 9 LMOC) that required inputs and SCR evaluations. As such, each system was found to calculate the solar angle zenith angle differently with Landsat 9 derived from earth-center, and Landsat 8 derived from the earth-surface. This resulted in the loss of some coincident images.
- Landsat 9 scenes were not acquired due to the overriding priority given to calibration collects (scheduled by SCR) over routine earth collects (scheduled by the Landsat 9 LTAP). Due to a flaw in the Landsat 9 scheduling process, the SCR calibration collects for a given path were scheduled while routine LTAP Earth collects were rejected. Note in Figure 9, in particular, the lack of coverage over Europe and Canada due to the large number of calibration-collects requested over the United States and Africa. By contrast, in the Landsat 8 scheduling system, calibration collects were automatically scheduled based upon a list of predefined acquisition constraints including instrument and/or calibrator configuration, cadence, and location defined to avoid affecting Earth collects.
- Landsat 9 scenes were missed due to a different (smaller) scene gap size between intervals versus Landsat 8.
- Incorrect scene PATH reporting information derived for SCR versus LCR acquisitions attributed to an error in the LMOC system. Note that this did not lead to a loss of scenes but rather, a skewed reporting of scenes acquired.
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
References
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Instrument | Guidelines for Acquiring Data |
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OLI | 1. Uniform targets of sufficient size (~300 × 300 m). (10 IFOV (Instantaneous Field of View) × 10 IFOV).
3. View zenith angle differences of less than 5 degrees. |
TIRS | 1. Uniform targets of sufficient size (~1 × 1 km). (10 IFOV × 10 IFOV).
3. View zenith angle differences of less than 20 degrees. |
Type | Constraints and Guidelines |
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Science |
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Operational |
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Coordination with other missions |
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Collision Avoidance |
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Kaita, E.; Markham, B.; Haque, M.O.; Dichmann, D.; Gerace, A.; Leigh, L.; Good, S.; Schmidt, M.; Crawford, C.J. Landsat 9 Cross Calibration Under-Fly of Landsat 8: Planning, and Execution. Remote Sens. 2022, 14, 5414. https://doi.org/10.3390/rs14215414
Kaita E, Markham B, Haque MO, Dichmann D, Gerace A, Leigh L, Good S, Schmidt M, Crawford CJ. Landsat 9 Cross Calibration Under-Fly of Landsat 8: Planning, and Execution. Remote Sensing. 2022; 14(21):5414. https://doi.org/10.3390/rs14215414
Chicago/Turabian StyleKaita, Edward, Brian Markham, Md Obaidul Haque, Donald Dichmann, Aaron Gerace, Lawrence Leigh, Susan Good, Michael Schmidt, and Christopher J. Crawford. 2022. "Landsat 9 Cross Calibration Under-Fly of Landsat 8: Planning, and Execution" Remote Sensing 14, no. 21: 5414. https://doi.org/10.3390/rs14215414
APA StyleKaita, E., Markham, B., Haque, M. O., Dichmann, D., Gerace, A., Leigh, L., Good, S., Schmidt, M., & Crawford, C. J. (2022). Landsat 9 Cross Calibration Under-Fly of Landsat 8: Planning, and Execution. Remote Sensing, 14(21), 5414. https://doi.org/10.3390/rs14215414