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On-orbit absolute radiometric calibration is not only a prerequisite for the quantitative application of optical remote sensing satellite data but also a key step in ensuring the accuracy and reliability of satellite observation data. Due to the diversity of imaging conditions for optical remote sensing satellite sensors, on-orbit absolute radiometric calibration usually requires a large number of imaging tasks and manual labor to calibrate each imaging condition. This seriously limits the timeliness of on-orbit absolute radiometric calibration and is also an urgent problem to be solved in the context of the explosive growth of satellite numbers. Based on this, we propose a general on-orbit absolute radiometric calibration method compatible with multiple imaging conditions. Firstly, we use a large amount of laboratory radiometric calibration data to explore the mathematical relationship between imaging conditions (row transfer time, integration level and gain), radiance, and DN, and successfully build an imaging condition compatibility model. Secondly, we combine the imaging condition compatibility model with cross calibration to achieve a general on-orbit absolute radiometric calibration method. We use cross calibration to obtain the reference radiance and corresponding DN of the target satellites, which calculates the general coefficient by using row transfer time, integration level, and gain, and use the general coefficient to calibrate all imaging conditions. Finally, we use multiple imaging tasks of the JL1GF03D11 satellites to verify the effectiveness of the proposed method. The experiments show that the average relative difference was reduced to 2.79% and the RMSE was reduced to 1.51, compared with the laboratory radiometric calibration method. In addition, we also verify the generality of the proposed method by using 10 satellites of the Jilin-1 GF03D series. The experiment shows that the goodness of fit of the general coefficient is all greater than 95%, and the average relative difference between the reference radiance and the calibrated radiance of the proposed method is 2.46%, with an RMSE of 1.67. To sum up, by using the proposed method, all imaging conditions of optical remote sensing satellite sensor can be calibrated in one imaging task, which greatly improves the timeliness and accuracy of on-orbit absolute radiometric calibration. [ABSTRACT FROM AUTHOR]

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The on-orbit radiometric calibration of spaceborne sensors is the foundation of quantitative remote sensing, and the calibration accuracy directly affects the quality of quantitative remote sensing products. The wide swath of the Chinese Ocean Color and Temperature Scanner (COCTS) onboard the HY-1C satellite makes it difficult to ignore errors caused by viewing angles during calibration. Thus, this article proposes a cross-calibration method based on the bottom-of-atmosphere (BOA) and top-of-atmosphere (TOA) spectral band adjustment factors (SBAFs). This method cross calibrates the COCTS sensor after correcting viewing geometry and radiometric differences. It is based on the Sentinel-3/ocean and land color instrument (OLCI) sensor. First, time-series data from the OLCI sensor were used to select calibration points in the Dunhuang area. Subsequently, the bidirectional reflectance distribution function (BRDF) for each corresponding spectral band of the OLCI sensor was constructed point by point. Next, the BOA and TOA SBAFs were calculated using the interpolated continuous spectra obtained from MOD09GA products. After correcting for the BRDF and SBAF, cross calibration between COCTS and OLCI was achieved. The results showed that the BOA SBAF model achieved higher precision calibration coefficients than the TOA SBAF model, with errors in each band below 5.76%. The proposed method can provide technical support for the cross calibration of wide-swath sensors.

SDGSAT-1, the inaugural Earth science satellite commissioned by the Chinese Academy of Sciences, successfully lifted off from China's Taiyuan Satellite Launch Center on 5 November 2021. Cross calibration has emerged as an indispensable methodology, providing an effective means for quality assessment, stability monitoring, and uncertainty analysis. This is achieved through the meticulous selection of an appropriate reference instrument. In our investigation, we conducted a comprehensive evaluation of the absolute radiometric calibration accuracy of the thermal infrared spectrometer (TIS), a pivotal component aboard SDGSAT-1. Our evaluation centered on a meticulous comparative analysis, where we juxtaposed the brightness temperature (BT) values recorded by TIS with the BT values derived from TIRS-2, computed following the spectral alignment with TIS. Our findings reveal that the current absolute BT bias for the B2 channel of TIS is less than 0.52 K. Meanwhile, the B3 channel exhibits a slightly larger fluctuation in absolute BT bias, yet remains within acceptable parameters, registering at less than 1 K. Notably, B3 emerges as the more dependable option for accurately gauging the temperature of the target region. Specifically, when the BT of B3 surpasses 290 K, the BT bias remains consistently below 0.3 K. In light of the approximately 40-min time difference in the water surface data utilized in our study, we conducted simulations to assess the channel BT of TIS under the scenario of a 0.25 °C water temperature variation. Our simulations conclusively demonstrate that the corresponding change in BT does not exceed 0.25 K.

Launched in November 2021, the sustainable development science satellite-1 carries the thermal infrared spectrometer (TIS) as a pivotal payload. Achieving precise radiometric calibration for geophysical parameter accuracy is crucial. Leveraging the frequent cross-calibration capability of the geostationary satellite FY-4A/advanced geostationary radiation imager (AGRI), this study addresses observational geometry challenges. The proposed radiance correction model for FY-4A/AGRI effectively reduces radiance discrepancies caused by differences in satellite zenith angles between TIS and AGRI. After integrating the corrected data into nadir-observed statistics, the long-term brightness temperature (BT) bias of TIS and AGRI was monitored. The results show that the daytime and nighttime BT bias exhibit similar trends, with the B2 band mainly showing negative bias. Overall, the BT bias for the B2 and B3 bands is within 1 K. The standard deviation of the BT bias for approximately 2250 sample points was calculated, revealing the values of 0.22 K and 0.40 K during the daytime, and 0.31 K and 0.57 K at night. The introduced model error remains below 0.31 K. Regarding the uncertainty of the BT bias introduced by spectral matching, when the spectral broadening is 1.15 times the wavelength interval, the uncertainty is less than 0.29 K for B2 and less than 0.38 K for B3. This work enhances our understanding of radiometric calibration challenges, providing insights into satellite-based geophysical parameter accuracy.

The very high resolution commercial satellite constellation of Maxar offers unique opportunities for a wide range of Earth science research and applications. The key to their widespread and effective use is stable and consistent calibration. In this article, we characterized the long-term calibration trends and cross-calibration coefficients for the four Maxar satellites (GeoEye-1, QuickBird-2, WorldView-2, and WorldView-3) using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) processing technique. Utilizing MAIAC Moderate Resolution Imaging Spectroradiometer (MODIS) atmosphere and surface products, we calculated top-of-atmosphere (TOA) reflectance for the Blue, Green, Red, and near-infrared, or “NIR1” (NIR) bands over the Libya-4 desert site. To ensure data consistency, we applied geometric normalization to account for variations in TOA reflectance arising from different view geometries. In addition, a spatial transfer technique was employed to increase the number of samples and yield more robust statistical trend analysis. Our analysis revealed that half of the bands exhibited statistically significant calibration trends. These trends were found to be 2–3 times higher in magnitude compared with those observed in the early Collection 6 MODIS. After detrending, Maxar sensors were cross-calibrated to MODIS Aqua, considered as a calibration standard. In this process, German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer hyperspectral measurements were used for spectral conversion required to align Maxar with MODIS bands. The cross-calibration analysis shows that GeoEye-1, WorldView-2, and WorldView-3 were systematically higher than MODIS Aqua by 2%–4% in the Blue, Green, and NIR bands, and by 7%–8% in the Red band. Detrending and cross-calibration to MODIS Aqua effectively transforms the Maxar constellation into a common sensor system enhancing spatiotemporal coverage and broadening the potential range of applications.

On-orbit absolute radiometric calibration is not only a prerequisite for the quantitative application of optical remote sensing satellite data but also a key step in ensuring the accuracy and reliability of satellite observation data. Due to the diversity of imaging conditions for optical remote sensing satellite sensors, on-orbit absolute radiometric calibration usually requires a large number of imaging tasks and manual labor to calibrate each imaging condition. This seriously limits the timeliness of on-orbit absolute radiometric calibration and is also an urgent problem to be solved in the context of the explosive growth of satellite numbers. Based on this, we propose a general on-orbit absolute radiometric calibration method compatible with multiple imaging conditions. Firstly, we use a large amount of laboratory radiometric calibration data to explore the mathematical relationship between imaging conditions (row transfer time, integration level and gain), radiance, and DN, and successfully build an imaging condition compatibility model. Secondly, we combine the imaging condition compatibility model with cross calibration to achieve a general on-orbit absolute radiometric calibration method. We use cross calibration to obtain the reference radiance and corresponding DN of the target satellites, which calculates the general coefficient by using row transfer time, integration level, and gain, and use the general coefficient to calibrate all imaging conditions. Finally, we use multiple imaging tasks of the JL1GF03D11 satellites to verify the effectiveness of the proposed method. The experiments show that the average relative difference was reduced to 2.79% and the RMSE was reduced to 1.51, compared with the laboratory radiometric calibration method. In addition, we also verify the generality of the proposed method by using 10 satellites of the Jilin-1 GF03D series. The experiment shows that the goodness of fit of the general coefficient is all greater than 95%, and the average relative difference between the reference radiance and the calibrated radiance of the proposed method is 2.46%, with an RMSE of 1.67. To sum up, by using the proposed method, all imaging conditions of optical remote sensing satellite sensor can be calibrated in one imaging task, which greatly improves the timeliness and accuracy of on-orbit absolute radiometric calibration.