Background

The U.S. Department of the Interior is directed to ensure that U.S. land imaging needs are met in the future and to maintain U.S. leadership in civil land imaging and land science. Those directives come in the context of the Future of Land Imaging Interagency Working Group’s report titled “A Plan for a U.S. National Land Imaging Program” (Executive Office of the President of the United States, 2007) and two recent Earth observation (EO) publications (Executive Office of the President of the United States, 2014, 2016). These reports identified Landsat and other key USGS EO assets as critical components in the national EO structure, where several assets were ranked in the top 10 of more than 300 assets. Among them, Landsat ranked third or higher.

Continuity with the past is key to meeting future land imaging science needs. The Landsat program, operated by the USGS, is the longest continuous record of satellite-based Earth imaging. Landsat data quality is viewed by the remote-sensing user community as a gold standard (National Geospatial Advisory Committee, 2020).

To ensure the continued excellent quality of Landsat data, the USGS EROS Center has identified (1) maintaining a well-calibrated multidecade remote-sensing archive for science and (2) developing and understanding land remote-sensing requirements and land imaging solutions as key strategic pillars. Understanding the land imaging requirements of current and future users, along with an ability to assess the capabilities of current and future systems for meeting those requirements, is key to meeting future land imaging science needs. In the past, Cal/Val activities at the EROS Center addressing the previously mentioned pillars were spread across multiple groups. The USGS EROS Center strategically brought the multiple groups together and formed a single team in a unified project called the ECCOE to enable the USGS to more efficiently address national and global land remote-sensing needs.

Purpose and Scope

The primary purpose of this report is to provide the latest geometric and radiometric performance results for all active Landsat missions. This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 4 (October–December), 2022. All data used to compile the results presented in this report are available from the USGS EarthExplorer website: https://earthexplorer.usgs.gov (USGS, 2021a).

Processing Level Definitions

This report frequently references Landsat processing levels. Descriptions of these processing levels are in the following subsections.

Landsat Collection Definitions

This report frequently references Landsat collections. In 2016, the USGS reorganized the Landsat archive into a tiered-collection management structure. This structure ensures that all Landsat L1 products provide a consistent archive of known data quality while controlling continuous improvement of the archive and access to all data as they are acquired. The implementation of collections represents a substantial change in the management of the Landsat archive by ensuring consistent quality over time and across all instruments.

Operational Land Imager Signal-to-Noise Ratio

The signal-to-noise ratio (SNR) for each of the OLI spectral bands is characterized at a prescribed band-specific typical radiance (L_typical) level, as described in table 3. The SNR of a detector at a given radiance level is defined as the mean of the measured pixel radiances acquired over a homogenous target divided by their standard deviation. A curve is fit to the SNR at the measured radiance levels and is evaluated at the prescribed L_typical level. The SNR is characterized at multiple stages of the instrument build, culminating in the testing of the fully integrated instrument.

The OLI SNR is evaluated on orbit each month. It remains consistently two to three times better than requirements and about eight times better than the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) SNR. The Collection 2 SNR slightly increased because of improvement in the bias calculation, further exceeding requirement thresholds. The per-band OLI median SNR at the L_typical level (yellow bars) for December 2022, which for all bands easily exceeds the OLI SNR requirements (blue bars) by more than 50 percent, is shown in figure 1. Lifetime SNR stability at L_typical for each OLI band is represented in figures 2, 3, 4, 5, 6, 7, 8, 9, and 10; monthly SNR values (for the detectors that have median SNRs for all bands) are denoted by the diamonds, and the uncertainties in the monthly SNR model are denoted by the error bars. The SNR for each band has remained stable over time (within the uncertainty of the models and much greater than the required levels).

Thermal Infrared Sensor Noise Performance

Noise can be defined as variation in detected signal over time when observing a stable source of radiation. For thermal sensors, noise is usually expressed in terms of a change in brightness temperature (that is, the noise equivalent change in temperature [NEΔT]). NEΔT is estimated as the standard deviation of detector data acquired over a uniform radiance source and then converted to temperature. Noise performance is completed on blackbody and deep space TIRS data (Montanaro and others, 2014).

All TIRS detectors have similar NEΔT. At 300 Kelvin (K), band-average noise performance for both thermal bands is about eight times better than the requirement (less than 0.4 K) and about four times better than the NEΔT of the Landsat 7 ETM+ thermal band at that same temperature. Lifetime averages of NEΔT at 300 K for TIRS band 10 are shown in figure 11, and the same averages for TIRS band 11 are shown in figure 12. In both figures, colored diamonds are used to indicate the observed NEΔT values as measured over time.

Radiometric Stability

Radiometric stability of an instrument is fundamental to low uncertainty in the radiometric calibration of data products generated from its measurements. The radiometric response stability is characterized for all OLI and TIRS bands using the instruments’ responses to signals from the onboard calibration devices collected over time (USGS, 2021d). The bias and gain stability of an instrument are contributing factors to variability within a radiometrically calibrated product.

The per-band OLI radiometric stability over the lifetime of the instrument is shown in figures 13, 14, 15, 16, 17, 18, 19, 20, and 21. Within each figure, the x-axis represents years since launch (February 11, 2013) and the y-axis represents the response relative to mission day 75. The solid brown line (figs. 13 and 14) represents the gain model used over time, which is derived from the OLI response to the stimulation lamps, solar panels, and lunar collects; it is only shown for the bands with responsivity (gain) determined to be slowly changing over time (coastal/aerosol [CA] and blue bands). For the remaining bands, response changes were minuscule until the safehold events in November 2020. More information about the Landsat 8 safehold events is available at https://www.usgs.gov/landsat-missions/november-19-2020-landsat-8-data-availability-update-recent-safehold-events. These observations indicate high radiometric stability of the instrument over its lifetime. Data derived from bands that have changed responsivity are corrected during product generation, so final products are not affected.

The long-term stability of the TIRS side A electronics that were used for the first approximately (~) 700 days of the mission is shown in figures 22 and 23. During that period, TIRS gains changed by about 0.2 and 0.1 percent per year for bands 10 and 11, respectively. These trends reduced on the side B electronics to about 0.05 and 0.01 percent until the two safehold events in November 2020, as seen in figures 24 and 25, respectively. After the safehold events, TIRS responsivity has gradually decreased ~3.0 and ~6.0 percent for bands 10 and 11, respectively. Note that the response degradation is modeled and corrected to within 0.5-percent uncertainty in the L1 products.

Since January 2021, TIRS onboard calibrator acquisitions have been collected on a weekly basis (instead of once every ~2 weeks) to better monitor the degradation in response observed after the safehold events. Weekly calibration acquisitions are planned into the future if the response degradation trend continues, and if geometric and radiometric accuracies are not negatively affected by the increased acquisition frequency.

Updates to Absolute Radiometric Calibration

Absolute radiometric calibration is established on the ground before launch and transferred to orbit using the solar diffuser for OLI and the blackbody for TIRS. Onboard calibrators and pseudoinvariant calibration sites (PICS; Committee on Earth Observation Satellites, 2021) are used to monitor changes in absolute calibration, and vicarious methods are used to check absolute calibration over time (USGS, 2021d). Updates can be made to the calibration parameters used in processing the data to L1 when a substantial change is detected in the calibrator trends.

The lifetime effect of OLI gain updates is shown in figure 26. A slow decay in CA and blue band calibration response was observed (figs. 13 and 14). The absolute radiometric calibration for the CA band has been actively modeled since April 2015, and an update to the calibration parameters was implemented for the blue band in April 2017. In April 2018, it was determined that the response to the working stimulation lamp was diverging from the other calibrators, and the working stimulation lamp was removed from the model that generates the gain updates. Similarly, in October 2019, the working diffuser was removed from the gain model because of diverging trends. In both cases, the new estimates of the radiometric gain were only applied to newly acquired data. When the archive was reprocessed for Collection 2, the updated gains were applied to all data, which changed the calibrated response in the CA and blue bands by as much as 0.15 percent compared to the Collection 1 products. The safehold events in November 2020 caused small changes to the OLI response, as reflected in figure 26 by the small, systematic error adjustments that were made to the gain models. In July 2021, the calibration parameter file (CPF) was updated to account for as much as a 0.12-percent step change in OLI responsivity caused by the November 2020 safehold events.

The effect of change in average gain for TIRS bands 10 and 11 since the safehold event on November 1, 2020, is shown in figure 27. The orange line is a modeled gain trend for band 10 based on the internal calibrator data (fig. 23), and the blue line is the gain trend sampled into calibration parameters that ensure there is no more than a 0.5-percent band-average radiometric gain change over the CPF period in the L1 products. Likewise, for band 11, the magenta line is a modeled gain trend based on the internal calibrator data (fig. 25), and the yellow line is the gain trend sampled into calibration parameters. Because of the relatively sharp decrease in response shortly after the safehold events, when compared with the response before the safehold events, calibration parameters were issued more frequently to ensure high quality L1 products. As the rate of degradation has slowed, updated calibration parameters have returned to quarterly issuance.

Relative Gains

Relative gains account for the differences in responsivity between detectors within a spectral band. OLI relative gains are monitored using solar diffuser acquisitions, side slither acquisitions (which entail a 90-degree yaw maneuver over an invariant site to flatten the data), and scene statistics. Quarterly updates are completed using data from the solar diffuser acquisitions from quarter 3 (July–September), 2022. Starting with the release of Collection 2, TIRS relative gain calibration updates also were completed quarterly using blackbody collects from the previous quarter. These calibration updates removed detector-to-detector striping (USGS, 2021d).

Typical per-detector changes in relative gains between the previous quarter and this quarter for several bands are shown in figures 28, 29, 30, and 31 by analyzing data from within each quarter. In each figure, the x-axis indicates the detector number, and the y-axis indicates the change in relative gain between the quarters as a ratio. These changes in responsivity are accounted for in the L1 product by updating the following quarter’s CPF.

The OLI detectors that have indicated a sudden change in responsivity of 0.5 percent or greater in the shortwave infrared (SWIR) 1 and SWIR 2 bands since launch are shown in figures 32 and 33. The x-axis indicates the date of the jump in responsivity, and the y-axis signifies the detector number. The observed responsivity jumps seem to be randomly scattered in time and location on the focal plane so do not seem to be associated with an instrument event or failure. These jumps are only seen in the SWIR bands (SWIR 1, SWIR 2, and cirrus); the visible and near infrared band detectors have not indicated any jump behavior over the whole mission.

Geometric Performance Summary

The Landsat 8 on-orbit geometric performance for the reporting quarter (quarter 4, October–December 2022) meets all requirements as outlined in USGS (2019b). The quarterly results summary is provided in table 4.

Band Registration Accuracy

Internal band registration measures how accurately the various Landsat 8 spectral bands are geometrically aligned to each other. The assessment provides a numerical evaluation of the accuracy of the band registration within an image using automated cross-correlation techniques between the bands to be assessed (USGS, 2021d).

OLI band registration performance has been stable over time. Quarterly band-to-band maximum registration accuracy for each band combination except for the cirrus band is shown in figure 34. Within the figure, blue bars indicate maximum registration accuracy in the line direction, and green bars indicate maximum registration accuracy in the sample direction. Lifetime OLI band registration accuracy for all bands is 4.3 meters (not shown), and lifetime OLI band registration accuracy for all bands, excluding cirrus, is 3.3 meters, which is well within the instrument specification accuracy. OLI band registration accuracy for all bands during quarter 4, 2022, is 4.8 meters (not shown), and OLI band registration accuracy for all bands, excluding cirrus, during quarter 4, 2022, is 3.2 meters.

TIRS band registration performance has been stable throughout the instrument’s lifetime, including after changes in scene select mechanism operation beginning in December 2014. Behavior is well within specification, as shown in figure 35, and quarter 4, 2022, results are consistent with past performance. Within the figure, blue bars indicate maximum registration accuracy in the line direction, and green bars indicate maximum registration accuracy in the sample direction. Lifetime TIRS band registration accuracy is 9.0 meters, and during quarter 4, 2022, the accuracy is 8.0 meters. Since quarter 3 (July–September), 2020 (Collection 2 data), registration bias between the line and sample directions has reduced, which may be because of better scene select mechanism pointing stability, the TIRS relative gain update, or both.

Lifetime TIRS to OLI band registration accuracy by quarter is shown in figure 36. Before the Collection 2 CPF update, seasonal effects are noticeable but leveled off after the release of Collection 2 in December 2020, as indicated by the closely aligned line (blue bars) and sample (green bars) accuracies. Lifetime TIRS to OLI registration accuracy (excluding the cirrus band) is 19.9 meters in the line direction and 18.2 meters in the sample direction. Quarter 4, 2022, TIRS to OLI registration accuracy (excluding the cirrus band) is 19.8 meters in the line direction and 19.0 meters in the sample direction.

Operational Land Imager to Thermal Infrared Sensor Alignment

OLI to TIRS alignment knowledge is critical to ensure that the L1 product accuracy requirements can be met. The alignment between OLI and TIRS instruments is periodically measured using correlation-based methods to ensure that the band-to-band alignment requirements for all Landsat 8 bands can be met (USGS, 2021d). The alignment estimates are used to update the calibration parameters in the CPFs when the observed changes are determined to affect the performance requirements.

TIRS to OLI pitch alignment measurements over instrument lifetimes are shown in figure 37. The November 2020 safehold events did substantially affect pitch alignment, but the ECCOE Landsat Cal/Val Team continues to monitor pitch alignment. Recently (in quarter 4, 2021), a small change in the TIRS to OLI pitch alignment was observed, which is similar to the seasonal trend observed in previous years. However, the magnitude of this trend was not the same as before, so it was unclear whether this new trend would continue or not. The trend continued in quarter 1, 2022, so a CPF update was issued in quarter 2, 2022, for residual corrections to the alignment parameters. At this point in time, predictive estimates based on previous quarters, not knowing if the seasonal trend will be observed or not, made the CPF inconsistent with the seasonal pattern. With an intention to align the CPF more with the seasonal pattern for better prediction, subsequent predictive CPF updates for quarter 3, 2022, and quarter 4, 2022, were not changed. The lifetime TIRS to OLI roll alignment is shown in figure 38, and the lifetime TIRS to OLI yaw alignment is shown in figure 39. Each light blue symbol on these figures represents one calibration scene, the dark blue solid lines indicate quarterly alignment averages, and the orange dashed lines indicate applied Collection 2 CPF correction values.

Geometric Accuracy

Landsat 8 geometric assessment evaluates the absolute positional accuracy of the image products with respect to a ground (geometric) reference. The geometric accuracy assessment estimates the geometric error between the L1TP products and GCPs using automated cross-correlation techniques (USGS, 2021d).

Based on analysis results, relative accuracy of the Collection 2 GCPs is comparable to the digital orthophoto quadrangle (DOQ) supersites, which are sites created from a mosaic of highly accurate high-resolution terrain-corrected aerial data. Comparatively, relative accuracy of the Collection 2 GCPs is substantially better than the internal consistency of the Collection 1 GCPs. Overall, cloud contaminated scene-based results are the primary contributor to poor geometric accuracy from L1TP products. Lifetime quarterly geometric accuracy at a circular error with 90-percent confidence (CE90) is shown in figure 40. Blue bars indicate the geometric accuracy estimated over supersite paths/rows (calibration sites) with a strong constraint of cloud-free scenes, yellow bars indicate geometric accuracy estimated over supersite paths/rows (calibration site’s scenes subsetting from all the L1TP scenes with no cloud constraints) using Collection 2 GCPs, and green bars indicate geometric accuracy estimated over all L1TP scenes processed in Collection 2 using Collection 2 GCPs (no cloud constraints). All results for this quarter are within the accuracy specification.

Lifetime and quarter 4, 2022, geometric accuracies for L1TP products are 3.8 and 4.5 meters when compared against cloud-free scenes over supersite paths/rows, 5.2 and 6.6 meters when compared against all L1TP scenes over supersite paths/rows only, and 10.3 and 11.2 meters when analyzing all the L1TP scenes processed in Collection 2, respectively. Note that seasonal effect is a factor in accuracy results.

Geodetic Accuracy

The purpose of the geodetic accuracy assessment is to ensure that the Landsat 8 L0Rp data can be successfully processed into L1 systematic products that meet the system requirement of 65 meters at a CE90 horizontal accuracy. To measure the accuracy, calibration scenes are automatically correlated with data from the panchromatic band to measure the discrepancy between the known ground location and the position predicted by the OLI geometric model (USGS, 2021d).

Based on analysis results, absolute accuracy of the Collection 2 GCPs is comparable to the DOQ supersites and is substantially better compared to the Collection 1 GCPs (Rengarajan and others, 2020). Lifetime quarterly geodetic accuracy (CE90) is shown in figure 41. Blue bars indicate the accuracy estimated using DOQ supersite paths/rows (calibration site), and green bars indicate accuracy estimated from all L1TP scenes processed in Collection 2 using Collection 2 GCPs. As in the case with the geometric accuracy, a wide variety of scene types (cloud contaminated, islands, desert, snow covered, ice sheets, and so on) are the primary contributor to the poor geodetic accuracy for Collection 2 GCP-based results.

Although quarters 1, 2, and 3, 2021, indicated a slight increase in the geodetic accuracy offset, the lifetime results have been consistently well within the accuracy specification. The recent increase in the geodetic accuracy is because of a systematic bias in the along-track direction observed since the November 2020 safehold events. After the bias stabilized, an update to the sensor alignment parameters in the CPF was released in quarter 4, 2021, resulting in a decrease in the observed geodetic offsets. An additional sensor alignment update was released in quarter 2, 2022, in response to an along-track offset that was greater than 10 meters and continuing to increase. Geodetic accuracy has been within 10 meters (considering both along-track and across-track directions) since then, and no sensor alignment update was necessary. Lifetime geodetic accuracies for systematic products are 16.4 meters when compared using DOQ GCPs over supersites and 25.6 meters when compared using Collection 2 GCPs over all the scenes processed in Collection 2, respectively.

Landsat 8 to Sentinel-2 Registration Accuracy

The USGS Landsat Collection 2 release included an update to the Landsat ground reference dataset by harmonizing with the Sentinel-2 Global Reference Image (GRI) dataset. The objective of using the GRI dataset in Landsat ground reference was to improve the absolute and relative accuracies of the Landsat products across all missions and to improve the coregistration between Landsat and Sentinel-2 terrain-corrected products. The Cal/Val Team plans to continue to assess the coregistration error between the two sensors over a select number of sites that are globally distributed.

The European Space Agency began using GRI as reference in their Sentinel-2 Level-1C (L1C) processing in March/April 2021, but global coverage (excluding Antarctica and small islands) was limited to scenes over Europe and Africa until August 2021. Sentinel-2 L1C products generated before GRI availability are planned to be reprocessed with GRI as a ground reference at a future date. The observed coregistration error between Landsat 8 L1TP products and Sentinel-2 L1C products without the use of GRI (as indicated with the magenta dots) is shown in figure 42, as well as coregistration errors with Sentinel-2 L1C products where GRI was used (as indicated with the yellow dots). Coregistration errors without the use of GRI are expected to be less than 15 meters; coregistration errors with GRI are expected to be less than 8 meters. For reference, observed coregistration errors between Landsat 8 L1TP products also are included in the figure as indicated with the orange dots. With global availability of Sentinel-2 L1C products using GRI as the geospatial reference, the number of characterized sites has been expanded to a couple of tiles from each continent while also using the growing temporal inventory. Based on analysis results, continent specific GRI differences have not been observed.

Onboard Calibrator Trends

The ETM+ has three onboard calibration devices: the Internal Calibrator, the Partial Aperture Solar Calibrator, and the Full Aperture Solar Calibrator. These calibration devices have been used to monitor radiometric stability since launch (April 15, 1999; Markham and others, 1994; Barsi and others, 2016; USGS, 2019a).

The responsivity of the ETM+ as determined from the onboard calibrators is shown in figure 43 for the blue band and figure 44 for the SWIR 1 band. The three calibrators all indicate degradation over time, although at varying rates that changed at different times. The degradation shown here is thought to be primarily within the calibrators and not because of the ETM+ detectors or electronics (Markham and others, 2012). Furthermore, preliminary analyses indicate no significant change in response after the orbit-lowering maneuvers.

Coherent Noise

Coherent noise in the ETM+ has been monitored since launch using a Fast Fourier transform on dark nighttime data (Barsi and others, 2016). The Landsat 7 lifetime coherent noise results for specific band and detector combinations at designated frequencies are shown in figure 45. Magnitudes of most coherent noise components remain low, but a positive trend in coherent noise power of SWIR 1 (band 5) detector 12 (orange circles) has been observed. In this SWIR 1 detector 12 case, noise power decreases with instrument ontime along an interval, so scenes acquired earlier in an interval are subject to stronger coherent noise features. In 2010, only the first few scenes acquired in an interval were affected by the coherent noise, but by 2015, the noise was strong enough that it was still present as many as 15 minutes later (fig. 45).

Pseudoinvariant Calibration Sites Trending

PICS also are used to monitor the ETM+ radiometric stability. Several of the PICS regions (Committee on Earth Observation Satellites, 2021) defined by Centre National D’Etudes Spatiales (CNES) were used to develop a new gain model for ETM+, which was applied starting in 2013 (USGS, 2021c). The Cal/Val Team uses multiple PICS for monitoring radiometric changes because of the temporal stability of those sites (Tuli and others, 2019). PICS trending calculates basic statistics from geographic regions of interest (ROIs) extracted from geometrically corrected Landsat products. The primary purpose for trending is to repeatedly characterize PICS, save results to the database, and thus enable an automatic monitoring of ETM+ temporal stability.

The lifetime top of atmosphere reflectance values observed over the Libya 4 PICS site (lat 28.55° N., long 23.39° E.) using the CNES ROI are shown in figure 46. The long-term temporal trends show seasonal effects, which are more substantial in the higher wavelength SWIR bands. After removal of the seasonal effect, there is a slight indication of deviation from current trends; the deviation is in the negative direction for the blue, green, and red bands and in the positive direction for the near infrared, SWIR, and panchromatic bands.

Geometric Performance Summary

The Landsat 7 on-orbit geometric performance for this quarter (quarter 4, October–December 2022) meets all requirements as outlined in USGS (2019a). The quarterly results summary is provided in table 5.

Geodetic Accuracy

The purpose of the geodetic accuracy assessment is to ensure that the Landsat 7 L0Rp data can be successfully processed into L1 systematic products that meet the system requirement of 250-meter (1σ) accuracy, excluding terrain effects and without the use of GCPs. Geodetic accuracy is monitored using calibration supersites containing GCPs derived from the DOQ aerial photography (U.S. supersites) and SPOT satellite imagery (Australian supersites).

The lifetime quarterly mean offsets for Landsat 7 are shown in figure 47. Within the figure, the blue bars indicate the across-track accuracy, and the green bars indicate the along-track accuracy. As of quarter 4 (October–December), 2022, this across-track offset has exceeded 89 meters.

The lifetime quarterly geodetic accuracy for Landsat 7 is shown in figure 48. The figure shows the expected geodetic accuracy of a systematic product. Magenta bars indicate the across-track root mean square error (RMSE), and light blue bars indicate the along-track RMSE.

Band Registration Accuracy

Internal band registration measures how accurately the various Landsat 7 spectral bands are aligned to each other. The assessment provides a numerical evaluation of the accuracy of the band registration within an image using automated cross-correlation techniques between the bands to be assessed (USGS, 2021d).

The per-band average RMSE since launch is shown in figure 49. Blue bars indicate band registration accuracy in the line direction, and green bars indicate band registration accuracy in the sample direction. This figure also shows the specification offsets, which each band easily outperforms.

Orbital Drift from Worldwide Reference System-2

Landsat 7 is nearing the end of its fuel supply. To conserve fuel, satellite inclination maneuvers have been eliminated, causing the satellite to slowly drift off the nominal WRS–2 orbit. The Cal/Val Team continues to monitor Northern and Southern Hemisphere sites to quantify the amount of WRS–2 displacement. Stakeholders use this information to determine the usability of the data. From April 6 to May 5, 2022, Landsat 7 went through several orbital maneuvers to lower the orbit by 8 kilometers, which has resulted in substantial differences in scene center easting when compared with the displacement before the orbital maneuvers.

The observed orbital drift from WRS–2 for path 39, row 37 (lat 33°10′37″ N., long 115°38′05″ W.), which is a Northern Hemisphere scene, is shown in figure 50. Magenta diamonds in the figure indicate the scene center location converted to easting and, for historical trending purposes, the measurements begin in 2015. The difference between the first 2015 observation and the most extreme observation from September 2022 is about 73.6 kilometers, at a westward drift, with a significant displacement observed after the orbit-lowering maneuvers. The most recent observation from December 2022 more closely aligns with previous observations, indicating westward and eastward drift fluctuations.

The observed orbital drift from WRS–2 for path 100, row 73 (lat 18°47′14″ S., long 138°22′13″ E), which is a Southern Hemisphere scene, is shown in figure 51. Again, magenta diamonds indicate the scene center location converted to easting, and the figure has measurements from 2015 to the current quarter. The difference between extreme measurements is about 120.6 kilometers. The drift for this Southern Hemisphere scene was to the east until the orbit-lowering maneuvers, after which significant westward and eastward drift fluctuations were observed.

Level 2 Surface Reflectance Pseudoinvariant Calibration Site Trending

In addition to L1 products, Landsat 7 and Landsat 8 surface reflectance PICS trending is completed by the Cal/Val Team. The primary purpose of Level 2 surface reflectance PICS trending is to repeatedly characterize the temporal stability of the ETM+ and OLI sensors. The CNES ROI has been chosen for completing the analysis.

The Collection 2, Level 2 lifetime surface reflectance trends for six Landsat 7 spectral bands for the Libya 4 PICS are provided in figure 52. The x-axis represents years since launch, and the y-axis represents surface reflectance. For this analysis, cloud-free data were used. A strong seasonal effect was noted in the higher wavelength (SWIR) bands (not shown). This seasonal effect has been reduced using appropriate linear models. After reducing seasonality from all bands, drift was estimated for each band from the slope and intercept of line fits. A small negative drift was noticeable in the blue, green, and red bands, and a positive drift was noticeable for the near infrared, SWIR 1, and SWIR 2 bands.

The Collection 2, Level 2 lifetime surface reflectance trends for seven Landsat 8 spectral bands for the Libya 4 PICS are provided in figure 53. Drift estimate results indicate small decay in responsivity for all bands. The x-axis represents years since launch, and the y-axis represents surface reflectance. The seasonal effect has been reduced from all bands using appropriate models.

Overall, OLI and ETM+ indicated stability for Level 2 surface reflectance based on the analysis completed. No significant instability was monitored in any band, according to the lifetime drift estimate results.