Landsat Level-1 products are delivered as quantized and calibrated scaled Digital Numbers (DN). The Level-1 DN data can be rescaled to Top-of-Atmosphere (TOA) reflectance applying radiometric rescaling coefficients. Currently, the Level-1 product is the standard data product of the Landsat sensors. The more recent Level-2 data products contain surface reflectance values, i.e., reflectance as it would be measured at ground level in the absence of atmospheric effects; in the near future, these products are anticipated to become the standard products of the Landsat sensors. The purpose of this paper is to present a radiometric performance evaluation of Level-1 and Level-2 data products for the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) sensors. TOA reflectance and derived surface reflectance values from both data products were evaluated and compared to in situ measurements from eight test sites located in Turkey, Brazil, Chile, the United States, France, and Namibia. The results indicate an agreement between the ETM+ and OLI Level-1 TOA reflectance data and the in situ measurements of 3.9% to 6.5% and 3.9% to 6.0%, respectively, across all spectral bands. Agreement between the in situ measurements and both Level-2 surface reflectance data products were consistently decreased in the shorter wavelength bands, and slightly better in the longer wavelength bands. The mean percent absolute error for Level-2 surface reflectance data ranged from 3.3% to 10% for both Landsat sensors. The significant decay in agreement with the data collected in situ in the short wavelength spectral bands with Level-2 data suggests issues with retrieval of aerosol concentration at some sites. In contrast, the results indicate a reasonably accurate estimate of water vapor in the mid-infrared spectrum. Lastly, despite the less reliable performance of Level-2 data product in the visible spectral region (compared with Level-1 data) in both sensors, the Landsat-8 OLI Level-2 showed an improvement of surface reflectance product over all spectral bands in common with the Landsat-7 ETM+ Level-2 data.

In 2013, the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Infrared and Visible Optical Sensors Subgroup (IVOS) established the Radiometric Calibration Network (RadCalNet), consisting of four international test sites providing automated in situ measurements and estimates of propagated top-of-atmosphere (TOA) reflectance. This work evaluates the ‘reliability’ of RadCalNet TOA reflectance data at three of these sites—RVUS, LCFR, and GONA—using Landsat 7 ETM+, Landsat 8 operational land imager (OLI), and Sentinel 2A/2B (S2A/S2B) MSI TOA reflectance data. This work identified a viewing angle effect in the MSI data at the RVUS and LCFR sites; when corrected, the overall standard deviation in relative reflectance differences decreased by approximately 2% and 0.5% at the RVUS and LCFR sites, respectively. Overall, the relative mean differences between the RadCalNet surface data and sensor data for the RVUS and GONA sites are within 5% for ETM+, OLI, and S2A MSI, with an approximately 2% higher difference in the S2B MSI data at the RVUS site. The LCFR site is different from the other two sites, with relative mean differences ranging from approximately -10% to 1%, even after performing the viewing angle effect correction on the MSI data. The data from RadCalNet are easy to acquire and use. More effort is needed to better understand the behavior at LCFR. One significant improvement on the accuracy of the RadCalNet data might be the development of a site-specific BRDF characterization and correction.

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process.

Brazil and China have a long-term joint space based sensor program called China-Brazil Earth Resources Satellite (CBERS). The most recent satellite of this program (CBERS-4) was successfully launched on 7 December 2014. This work describes a complete procedure, along with the associated uncertainties, used to calculate the in-flight absolute calibration coefficients for the sensors Multispectral Camera (MUX) and Wide-Field Imager (WFI) on-board CBERS-4. Two absolute radiometric calibration techniques were applied: (i) reflectance-based approach and (ii) cross-calibration method. A specific site at Algodones Dunes region located in the southwestern portion of the United States of America was used as a reference surface. Radiometric ground and atmospheric measurements were carried out on 9 March 2015, when CBERS-4 passed over the region. In addition, a cross-calibration between both MUX and WFI on-board CBERS-4 and the Operational Land Imager (OLI) on-board Landsat-8 was performed using the Libya-4 Pseudo Invariant Calibration Site. The gain coefficients are now available: 1.68, 1.62, 1.59 and 1.42 for MUX and 0.379, 0.498, 0.360 and 0.351 for WFI spectral bands blue, green, red and NIR, respectively, in units of (W/(m²·sr·μm))/DN. These coefficients were determined with uncertainties lower than 3.5%. As a validation of these radiometric coefficients, cross-calibration was also undertaken. An evaluation of radiometric consistency was performed between the two instruments (MUX and WFI) on-board CBERS-4 and with the well calibrated Landsat-7 ETM+. Results show that the reflectance values match in all the analogous spectral bands within the specified calibration uncertainties.

The remote sensing community has extensively used Pseudo-Invariant Calibration Sites (PICS) to monitor the long-term in-flight radiometric calibration of Earth-observing satellites. The use of the PICS has an underlying assumption that these sites are invariant over time. However, the site’s temporal stability has not been assured in the past. This work evaluates the temporal stability of PICS by not only detecting the trend but also locating significant shifts (change points) lying behind the time series. A single time series was formed using the virtual constellation approach in which multiple sensors data were combined for each site to achieve denser temporal coverage and overcome the limitation of dependence related to a specific sensor. The sensors used for this work were selected based on radiometric calibration uncertainty and availability of the data: operational land imager (Landsat-8), enhanced thematic mapper (Landsat-7), moderate resolution imaging spectroradiometer (Terra and Aqua), and multispectral instrument (Sentinel-2A). An inverse variance weighting method was applied to the Top-of-Atmosphere (TOA) reflectance time series to reveal the underlying trend. The sequential Mann–Kendall test was employed upon the weighted TOA reflectance time-series recorded over 20 years to detect abrupt changes for six reflective bands. Statistically significant trends and abrupt changes have been detected for all sites, but the magnitude of the trends (maximum of 0.215% change in TOA reflectance per year) suggest that these sites are not changing substantially over time. Hence, it can be stated that despite minor changes in all evaluated PICS, they can be used for radiometric calibration of optical remote sensing sensors. The new approach provides useful results by revealing underlying trends and providing a better understanding of PICS’ stability.

Cross-calibration is one of the various methods applied for Earth Observation Satellites sensor calibration. In the cross-calibration procedure, one sensor is calibrated against another sensor, in which the radiometric calibration is better known, via near-simultaneous imaging of a common ground target. One of the most important steps during the cross-calibration is the Spectral Band Adjustment Factor (SBAF) assessment. The SBAF is used to compensate the differences in the spectral responses of the sensors, avoiding large uncertainties in cross-calibration results. The investigation described in this work focussed on the evaluation of the SBAF’s inherent uncertainties using Monte Carlo Simulation method. Basically, the Monte Carlo approach is based on calculating multiple integral by random sampling. The SBAFs were developed for analogous Landsat 8 Operational Land Imager and CBERS 4 Multispectral Camera spectral bands. The Hyperion hyperspectral sensor on-board Earth Observing-1 was utilized to understand the spectral profile of the target and to derive the SBAF. This study was performed over two pseudo invariant calibration sites: Algodones Dunes and Libya-4. The spectral uncertainty of the SBAFs using Monte Carlo was found to be within 0.01–1.79%. The results suggested that the uncertainty of the SBAFs is dependent on the correlation between the input variables: the higher the correlation, the lowest is the SBAF uncertainty.