Calibration Sites Research Articles

Comparison of MyRTKnet Performance with Various Real-Time Corrections Based on Different Time

Virtual Reference Station (VRS), Master-Auxiliary Corrections (MAX), Individualised Master-Auxiliary Corrections (IMAX), Nearest Base, and Network D-GNSS are among the Network Real-Time Kinematic (NRTK) techniques supported by the Malaysia Real-Time Kinematic GNSS Network (MyRTKnet) in providing network-based solutions to users. However, different network corrections have different limits due to different characters, thus offering a variety of position accuracy. Therefore, this study evaluated the accuracy of real-time corrections, VRS, MAX, IMAX, D-GNSS, and Nearest Base, for the coordinates at two different times, morning and evening. The study was conducted at two different times to make it easier for users to choose a suitable and quality time to conduct observations. This research was implemented on the pillars at the calibration site of Politeknik Sultan Haji Ahmad Shah (POLISAS) in Kuantan, Pahang. The coordinates in the pillar become a benchmark to differentiate with real-time correction coordinates. The result of that difference can be used to analyse the level of accuracy for real-time corrections. The study’s findings show that the real-time correction accuracy of the VRS type is the most stable and has the highest accuracy. Nearest Base and MAX corrections also give relatively good accuracy and can be improved by increasing observation time and depending on the area. IMAX produces inconsistent results with relatively low accuracy, but some techniques can be applied to obtain good accuracy. D-GNSS type corrections give inconsistent results and low position accuracy as it utilises code measurement only. The research concludes that the best correction is VRS. The Nearest Base and MAX produce acceptable accuracy and can be safely chosen over IMAX and D-GNSS.

Nouméa: a new multi-mission calibration and validation site for past and future altimetry missions?

Abstract. Today, monitoring the evolution of sea level in coastal areas is of importance, since almost 11 % of the world's population lives in low-lying areas. Reducing uncertainties in sea level estimates requires a better understanding of both altimetry measurements and local sea level dynamics. In New Caledonia, the Nouméa lagoon is an example of this challenge, as altimetry, coastal tide gauge, and vertical land motions from global navigation satellite systems (GNSSs) do not provide consistent information. The GEOCEAN-NC 2019 field campaign addresses this issue with deployments of in situ instruments in the lagoon (GNSS buoy, pressure gauge, etc.), with a particular focus on the crossover of one Jason-series track and two Sentinel-3A missions tracks. In this study, we propose a method to virtually transfer the Nouméa tide gauge at the altimetry crossover point, using in situ data from the field campaign. Following the philosophy of calibration and validation (Cal/Val) studies, we derive absolute altimeter bias time series over the entire Jason and Sentinel-3A periods. Overall, our estimated altimeter mean biases are slightly larger by 1–2 cm compared to Corsica and Bass Strait results, with inter-mission biases in line with those of Bass Strait site. Uncertainties still remain regarding the determination of our vertical datum, only constrained by the three days of the GNSS buoy deployment. With our method, we are able to re-analyse about 20 years of altimetry observations and derive a linear trend of −0.2 ± 0.1 mm yr−1 over the bias time series. Compared to previous studies, we do not find any significant uplift in the area, which is more consistent with the observations of inland permanent GNSS stations. These results support the idea of developing Cal/Val activities in the lagoon, which is already the subject of several experiments for the scientific calibration phase of the SWOT wide-swath altimetry mission.

Recalibrating the Pennsylvania pre‐sidedress soil nitrate test recommendations for modern corn production

AbstractThe pre‐sidedress soil nitrate test (PSNT) was developed over 30 years ago to determine sidedress nitrogen (N) fertilizer recommendations for corn (Zea mays L.). Since the original PSNT calibrations were developed, changes in production practices such as no‐till and cover cropping and increases in corn yields and N use efficiency could affect the accuracy of PSNT recommendations. To update the PSNT recommendations in Pennsylvania and demonstrate the test's efficacy, we compiled a dataset of 32 calibration sites and 13 demonstration sites where the PSNT was conducted, and the economically optimum N rate (EONR) for corn was determined from an N fertilizer yield response curve. We recalibrated the PSNT recommendation algorithm and compared its accuracy to the original calibration. The new calibration resulted in a single long‐term manure history factor that interacted with the PSNT result to adjust the sidedress N recommendation (−5.7 kg N ha−1 [mg NO3‐N kg−1]−1). The new calibration also included a term for a mixed species cover crop, which increased the sidedress N recommendation 56.2 kg N ha−1. Finally, the coefficient that scales the N fertilizer recommendation based on yield goal decreased by 29% from the original calibration to 12.9 kg N Mg−1 grain. The new algorithm for predicting EONR reduced the error of the sidedress N recommendation by one‐half compared to the original calibration. The new PSNT calibration will allow users to accurately determine sidedress N recommendations in sites with a long‐term manure history and underscores the importance of updating soil fertility recommendation algorithms with modern data.

Improved On-Orbit MTF Measurement Method Based on Point Source Arrays

The modulation transfer function (MTF) is a key characteristic used to assess the performance of optical remote sensing satellite sensors. MTF detection can directly measure a sensor’s two-dimensional (2D) point spread function (PSF); therefore, it has been applied to various high-resolution remote sensing satellites (e.g., Pleiades) using point sources. However, current point source methods mainly use 2D Gaussian functions to fit the discrete digital number (DN) of the point source on the image to extract the center of the point source and fit the PSF after encrypting multiple point sources; thus, noise robustness is poor and measurement accuracy varies widely. In this study, we developed a noise-resistant on-orbit MTF detection method based on the object space constraint among point source arrays. Utilizing object space constraint relationships among points in a point source array, a homography transformation model was established, enabling accurate extraction of sub-pixel coordinates for each point source response. Subsequently, aligning the luminosity distribution of all point sources concerning a reference point source, the encrypted PSF was obtained and then fitted to obtain the MTF. To validate the method, Gaofen-2 (GF-2) satellite images were used to conduct an in-orbit imaging experiment on the point source array of the Chinese Zhongwei remote sensing satellite calibration site. Compared with the Gaussian model methods, the proposed method yielded more accurate peak positions for each point source. Standard deviations of peak position constant ratios in along- and cross-track directions improved by 2.8 and 4.8 times, respectively. The root-mean-square error (RMSE) of the collinearity test results increased by 92%, and the noise resistance of the MTF curve improved by two times. Dynamic MTF values at the Nyquist frequency for the GF-2 panchromatic band in along- and cross-track directions were 0.0476 and 0.0705, respectively, and MTF values in different directions were well distinguished.

A Survey Method for Drift Ice Characteristics of the Yellow River Based on Shore-Based Oblique Images

Acquisition of continuous drift ice characteristic parameters such as ice size, shape, concentration, and drift velocity are of great importance for understanding river freezing and thawing processes. This study acquired hourly oblique images captured by a shore-based camera in the winter of 2021–2022 on the Yellow River, China. The pixel point scale method for correcting oblique images is provided. The 61 lines were measured at the calibration site and the absolute error between the measured value and the calculated value was in the range of 0.009–0.850 m, with a mean error of 0.236 m. After the correction of oblique images, the true equivalent diameter of drift ice during the freezing period ranged from 0.52–13.10 m with a mean size of 3.36 m, which was larger than that of 2.30 m during the thawing period which ranged from 0.20–12.54 m. It was found that the size of drift ice increased with time during the freezing period and decreased with time during the thawing period. The fractal dimension and roundness were used to represent drift ice shape. The fractal dimension ranged from 1.0–1.3 and the roundness ranged from 0.1–1.0. A Gaussian distribution was used to estimate drift ice size and shape distributions. There is a nonlinear relationship between ice concentration and drift velocity, which can be well expressed by the logistic function. In the future, drift ice parameters for more years and hydrometeorological data for the same time need to be accumulated, which helps to analyze the freezing and thawing patterns of river ice.

Evaluation of the Radiometric Calibration of ZY1-02E Thermal Infrared Data

Following the launch of the ZY1-02E satellite, the thermal infrared sensor aboard the satellite experienced alterations in the space environment, leading to varying degrees of attenuation in some components. The laboratory calibration accuracy could not satisfy the demands of quantitative production, and a certain degree of deviation was observed in on-orbit calibration. To accurately characterize the on-orbit radiation properties of thermal infrared remote sensing payloads, an absolute radiometric calibration campaign was carried out at the Ulansuhai Nur and Baotou calibration sites in Inner Mongolia in July 2022. This paper outlines the processes of onboard calibration and vicarious calibration for the ZY1-02E satellite, comparing the outcomes of onboard calibration with those of vicarious calibration. The onboard calibration method involved internal calibration, while the vicarious calibration method utilized an on-orbit absolute radiometric calibration technique based on various natural features that were not constrained by satellite–Earth spectrum matching requirements. Calibration coefficients were acquired, and the absolute radiometric calibration results of on-orbit vicarious and onboard calibration were compared, analyzed, and verified using the radiance computed from measured data and the reference sensor data. The accuracy of on-orbit absolute vicarious calibration was determined, and the causes for the decline in the radiation calibration accuracy on the orbiting satellite were examined. The findings revealed that the vicarious calibration results exhibited a lower percentage of radiance deviation compared with the onboard calibration results, meeting the quantitative requirements of remote sensing data. These results were significantly better than those obtained from onboard blackbody calibration, offering a data foundation for devising satellite calibration plans and enhancing calibration algorithms. In the future, the developmental trend of on-orbit radiometric calibration technology will encompass high-precision and slow-attenuation onboard calibration techniques, as well as high-frequency and simplified-step vicarious calibration methods.

Implementation Possibilities of Standard Site Method Sub-cases for EMC Antenna Calibrations in Non-ideal Site Conditions

Today, a number of engineering issues require electromagnetic compatibility (EMC) tests, in turn triggering the need for EMC-antenna calibrations. In this framework, experimenters seek accurate and time-saving solutions. Basically, standard site method (SSM) ANSI C63.5-2006 stipulates the near-to-ideal conditions on an empty and vast land, where three antennas are used for antenna factor determination. In our previous work, we investigated the suitability of narrow test sites for antenna calibration according to three-antenna SSM-ANSIC-63.5-2006, whose usability was validated under certain conditions. In the present study, we expand our research by applying the sub-cases of using a known antenna and identical antennas specified in the standard in order to shorten the calibration process. The results reveal that the methods for various calibrations are useful for successfully running the process even in non-ideal sites and help significantly reduce the experimentation time, considering the uncertainty limits specified in EMC test standards.

Benefits of hierarchical predictions for digital soil mapping—An approach to map bimodal soil pH

Maps of soil pH are an important tool for making decisions in sustainable forest management. Accurate pH mapping, therefore, is crucial to support decisions by authorities or forest companies. Soil pH values typically exhibit a distinct distribution characterized by two frequently encountered pH ranges, wherein aluminium oxides (Al2O3) and carbonates (CaCO3) act as the primary buffer agents. Soil samples with moderately acid pH values (pH CaCl2 of 4.5-6) are less commonly observed due to their weaker buffering capacity. The different strength of buffer agents results in a distinct bimodal distribution of soil pH values with peaks at pH of around 4 and 7.5. Commonly used approaches for spatial mapping neglect this often observed characteristic of soil pH and predict unimodal distributions with too many moderately acid pH values. For ecological map applications this might result in misleading interpretations.This article presents a novel approach to produce pH maps that are able to reproduce pedogenic processes. The procedure is suitable for bimodal responses where the response distribution is naturally inherent and needs to be reproduced for the predictions. It is model-agnostic, namely independent from the used statistical prediction method. Calibration data is optimally split into two parts corresponding each to a data culmination, i.e. for soil pH values belonging to the ranges of the two principal buffer agents (Al2O3 and CaCO3). For each subset a separate model is then built. In addition, a binary model is fitted to assign every new prediction location a probability to belong either to Al2O3 or CaCO3 buffer range. Predictions are combined by weighted mean. Weights are derived from probabilities predicted by the binary model. Degree of smoothness is chosen by sigmoid transform which allows for optimal continuous transition of the pH values between Al2O3 and CaCO3 buffer ranges. For each location uncertainty distributions may be combined by using the same weights.We illustrated application of the new approach to a medium and strong bimodal distributed response (1) pH in 0–5 cm and (2) pH in 60–100 cm of forest soils in Switzerland (2530 calibration sites). While model performance measured at 354 validation sites slightly dropped compared to a common modelling approach (drop of R2 of 0.02–0.03) distributional properties of the predictions are much more meaningful from a pedogenic point of view. We were able to demonstrate the benefits of considering specific distributional properties of responses within the prediction process and expanded model assessment by comparing observed and predicted distributions.

Efficient Super-Resolution Method for Targets Observed by Satellite SAR.

This study presents an efficient super-resolution (SR) method for targets observed by satellite synthetic aperture radar (SAR). First, a small target image is extracted from a large-scale SAR image and undergoes proper preprocessing. The preprocessing step is adaptively designed depending on the types of movements of targets. Next, the principal scattering centers of targets are extracted using the compressive sensing technique. Subsequently, an impulse response function (IRF) of the satellite SAR system (IRF-S) is generated using a SAR image of a corner reflector located at the calibration site. Then, the spatial resolution of the IRF-S is improved by the spectral estimation technique. Finally, according to the SAR signal model, the super-resolved IRF-S is combined with the extracted scattering centers to generate a super-resolved target image. In our experiments, the SR capabilities for various targets were investigated using quantitative and qualitative analysis. Compared with conventional SAR SR methods, the proposed scheme exhibits greater robustness towards improvement of the spatial resolution of the target image when the degrees of SR are high. Additionally, the proposed scheme has faster computation time (CT) than other SR algorithms, irrespective of the degree of SR. The novelties of this study can be summarized as follows: (1) the practical design of an efficient SAR SR scheme that has robustness at a high SR degree; (2) the application of proper preprocessing considering the types of movements of targets (i.e., stationary, moderate motion, and complex motion) in SAR SR processing; (3) the effective evaluation of SAR SR capability using various metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), focus quality parameters, and CT, as well as qualitative analysis.

Baseline Calibration of L-Band Spaceborne Bistatic SAR TwinSAR-L for DEM Generation

The Terrain Wide-swath Interferometric L-band Synthetic Aperture Radar (TwinSAR-L) mission is a spaceborne bistatic synthetic aperture radar (SAR) mission to derive a high-quality global digital elevation model (DEM). The prerequisite of the high-accuracy DEM is knowing the interferometric baseline with high precision. The challenging problem is that the baseline of the bistatic system is highly dynamic due to the fast relative motion between the two satellites. In this paper, a pixel-related baseline model based on the geometrical shift is proposed to accurately reflect the position change of satellites. The baseline error is then calibrated using height gradient information and a small number of point targets with a slight incidence angle difference, eliminating the need for low-frequency corner reflectors and avoiding the difficulty of selecting a calibration site. The proposed method has been successfully exploited during the initial Commissioning Phase of TwinSAR-L, demonstrating its effectiveness in evaluating the precise baseline and supporting the generation of high-precision DEM.

Improving hydrodynamic modeling of river networks by incorporating data assimilation using a particle filter

Numerical modeling is a well-recognized method for studying the hydrodynamic processes in river networks. Multi-source measurements also offer abundant information on the patterns and mechanisms within the processes. Therefore, improving hydrodynamic modeling of river networks through the use of data assimilation techniques has become a hot research topic in recent years. The particle filter (PF) is a commonly used data assimilation method and has been proven to be applicable to various nonlinear and non-Gaussian models. In the current study, an improved numerical hydrodynamic model for large-scale river networks is established by incorporating the advanced PF algorithm. Furthermore, the PF method based on the Gaussian likelihood function (GLF) and the method based on the Cauchy likelihood function (CLF) are compared for a complex river network scenario. The feasibility of the PF-based methods was evaluated through application to the Yangtze-Dongting River-lake Network (YDRN) by assimilating water stage data collected at six hydrometric stations during the entire hydrodynamic process in 2003. Additionally, the parameters used in the likelihood function, which affect the assimilation performance, also were explored in the current study. The study results found that the accuracy of the model-derived water stage data was improved when the PF-based methods are utilized, with improvement not only at the data assimilation (calibration) sites but also at three hydrometric stations not used in the data assimilation (i.e., verification sites). The highest average Nash-Sutcliffe Efficiency result for the six assimilation sites were 0.98 while the lowest summed root-mean-square-error result was 1.801 m. The comparison results also indicated that the CLF-based PF outperformed the GLF-based PF when high-accuracy observed data are available. Specifically, the CLF can effectively resolve the filtering failure problem and the dispersion problem of PFs, and further improve the accuracy of the filtering results for a river network scenario. In summary, the CLF-based PF method along with high-accuracy observation data shows promise to provide reliable reference and technical support for hydrodynamic modeling of large-scale river networks.

Evaluation of Temporal Stability in Radiometric Calibration Network Sites Using Multi-Source Satellite Data and Continuous In Situ Measurements

The radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require high spatiotemporal stability. However, some studies have found that PICS are not invariable. Previous studies used top-of-atmosphere (TOA) data without verifying site data, which could affect the accuracy of their results. In this study, we analyzed the short- and long-term radiometric trends of RadCalNet sites using bottom-of-atmosphere (BOA) data, and verified the trends revealed by the TOA data from Landsat 7, 8, and Sentinel-2. Besides the commonly used methods (e.g., nonparametric Mann–Kendall and sequential Mann–Kendall tests), a more robust Sen’s slope method was used to estimate the magnitude of the change. We found that (1) the trends based on TOA reflectance contrasted with those based on BOA reflectance in certain cases, e.g., the reflectance trends in the red band of BOA data for La Crau in summer and autumn and Baotou were not significant, while the TOA data showed a significant downward trend; (2) the temporal trends showed statistically significant and abrupt changes in all PICS, e.g., the SWIR2 band of La Crau in winter and spring changed by 1.803% per year, and the SWIR1 band of Railroad Valley Playa changed by >0.282% per year, indicating that the real changes in sensor performance are hard to detect using these sites; (3) spatial homogeneity was verified using the coefficient of variation (CV) and Getis statistic (Gi*) for each PICS (CV < 3% and Gi* > 0). Overall, the RadCalNet remains a highly reliable tool for vicarious calibration; however, the temporal stability should be noted for radiometric performance monitoring of sensors.

Vicarious Radiometric Calibration of the Multispectral Imager Onboard SDGSAT-1 over the Dunhuang Calibration Site, China

The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world’s first Earth science satellite to serve the United Nations 2030 Sustainable Development Agenda. A vicarious radiometric calibration experiment was conducted at the Dunhuang calibration site (Gobi Desert, China) on 14 December 2021. In-situ measurements of ground reflectance, aerosol optical depth (AOD), total columnar water vapor, radiosonde data, and diffuse-to-global irradiance (DG) ratio were performed to predict the top-of-atmosphere radiance by the reflectance-, irradiance-, and improved irradiance-based methods using the moderate resolution atmospheric transmission model. The MII calibration coefficients were calculated by dividing the top-of-atmosphere radiance by the average digital number value of the image. The radiometric calibration coefficients calculated by the three calibration methods were reliable (average relative differences: 2.20% (reflectance-based vs. irradiance-based method) and 1.43% (reflectance-based vs. improved irradiance-based method)). The total calibration uncertainties of the reflectance-, irradiance-, and improved irradiance-based methods were 2.77–5.23%, 3.62–5.79%, and 3.50–5.23%, respectively. The extra DG ratio measurements in the latter two methods did not improve the calibration accuracy for AODs ≤ 0.1. The calibrated MII images were verified using Landsat-8 Operational Land Imager (OLI) and Sentinel-2A MultiSpectral Instrument (MSI) images. The retrieved ground reflectances of the MII over different surface types were cross-compared with those of OLI and MSI using the FAST Line-of-sight Atmospheric Analysis of Hypercubes software. The MII retrievals differed by <0.0075 (7.13%) from OLI retrievals and <0.0084 (7.47%) from MSI retrievals for calibration coefficients from the reflectance-based method; <0.0089 (7.57%) from OLI retrievals and <0.0111 (8.65%) from MSI retrievals for the irradiance-based method; and <0.0082 (7.33%) from OLI retrievals and <0.0101 (8.59%) from MSI retrievals for the improved irradiance-based method. Thus, our findings support the application of SDGSAT-1 data.

Inter-Comparison of Landsat-8 and Landsat-9 during On-Orbit Initialization and Verification (OIV) Using Extended Pseudo Invariant Calibration Sites (EPICS): Advanced Methods

Three advanced methodologies were performed during Landsat-9 on orbit and initialization and verification (OIV): Extended Pseudo Invariant Calibration Sites Absolute Calibration Model Double Ratio (ExPAC Double Ratio) and Extended Pseudo Invariant Calibration Sites (EPICS)-based cross-calibration utilizing stable regions in Northern African desert sites (EPICS-NA) and a global scale (EPICS-Global). The development of these three techniques was described using uncertainties analysis. The ExPAC Double Ratio was derived based on the ratio between ExPAC model prediction and satellite measurements for Landsat-8 and Landsat-9. The ExPAC Double Ratio can be performed to determine differences between sensors ranging from visible, red edge, near-infrared, to short-wave infrared wavelengths. The ExPAC Double Ratio and EPICS-based inter-comparison ratio uncertainties were determined using the Monte Carlo Simulation. It was found that the uncertainty levels of 1–2% can be achieved. The EPICS-based cross-calibration results were derived using two targets: EPICS-NA and EPICS-Global, with uncertainties of 1–2.2% for all spectral bands. The inter-comparison results between Landsat-9 and Landsat-8 during the OIV period using the three advanced methods were well within 0.5% for all spectral bands except for the green band, which showed sub 1% agreement.

Radiometric Calibration of GF5-02 Advanced Hyperspectral Imager Based on RadCalNet Baotou Site

In this study, an on-orbit radiometric calibration campaign of the GF5-02 AHSI was performed at the RadCalNet Baotou site, based on the automated observation of reflectance and atmospheric parameters of a 300 m × 300 m homogeneous desert area. The consistency of the radiometric calibration coefficients was validated both at the Dunhuang calibration site and the Baotou site. The average relative difference between the calibrated top-of-atmospheric (TOA) radiance and the predicted TOA radiance were less than 7%. The R2 of these two TOA radiances were all higher than 0.99. These results showed that the accuracy of calibration coefficients could meet the requirements of hyperspectral quantification applications. The uncertainty of GF5-02 AHSI radiometric calibration was 6.18%. This study also demonstrated that automated observation data of the Baotou site were reliable for high-frequency radiometric calibration and radiometric performance monitoring of GF5-02 AHSI.

Validation of EMI-2 Radiometric Performance with TROPOMI over Dome C Site in Antarctica

(1) The Environmental Trace Gases Monitoring Instrument-2(EMI-2) is a high-quality spaceborne imaging spectrometer that launched in September 2021. To evaluate its radiometric calibration performance in-flight, the UV2 and VIS1 bands of EMI-2 were cross-calibrated by the corresponding bands (band3 and band4) of TROPOMI over the pseudo-invariant calibration site Dome C. (2) After angle limitation and cloud filtering of the Earth radiance data measured by EMI-2 and TROPOMI over Dome C, the top of atmosphere (TOA) reflectance time series were calculated. The spectral adjustment factors (SAF) were derived from the solar spectrum measured by the sensor to minimize the uncertainties caused by the different spectral response functions (SRF) of sensors. In addition, a correction method based on the radiative transfer model (RTM) SCIATRAN was used to suppress unaccounted angular dependence of atmospheric scattering. The radiation performance of EMI-2 is evaluated using the TOA reflectance ratio of EMI-2 and TROPOMI, combining the SAF correction and RTM-based correction methods. (3) It was shown that the time series trending of the TOA reflectance ratio between EMI-2 measurements and TROPOMI demonstrate flat characteristics and strong correlation. The mean reflectance ratios range from 0.998 to 1.09. The standard deviation of the reflection ratio is less than 3%. For 328 nm, 335 nm, 340 nm, 460 nm, and 490 nm, the mean values are close to one, and the relative radiometric bias estimated through EMI-2 and TROPOMI intercalibration is less than 3%, and for other wavelengths, the biases are less than 6%, except for 416 nm, which behaves higher than 7%. The cross-calibration results show that the radiometric calibration of EMI-2 is within the relative accuracy requirement.

Radiometric and Polarimetric Quality Validation of Gaofen-3 over a Five-Year Operation Period

GaoFen-3 was the first Chinese civilian C-band synthetic aperture radar (SAR) satellite, launched in August 2016. The need for monitoring the satellite’s image quality has been boosted by its widespread applications in various fields. The efficient and scientific assessment of the system’s radiometric and polarimetric performance has been essential in its more than five years of service. The authors collected 90 images of the Inner Mongolia calibration site, 888 images of the Amazon rainforest, and 39,929 images of the Chinese mainland from 2017 to 2021. This was achieved whilst covering the leading imaging modes, such as the spotlight mode, stripmap mode, ultra-fine mode, wave imaging mode, etc. In this study, we derive a framework that incorporates the man-made corner reflectors (CRs) in Mongolia, the traditional Amazon rainforest datasets, and even the long-strip data in the Chinese mainland (known as CRAS) for the purposes of GaoFen-3 radiometric quality analysis and polarimetric validation over its five years of operation. Polarimetric calibration without recourse to the CRs is utilized to measure the polarimetric distortions regardless of the region, and thus requires a higher calibration accuracy for the GaoFen-3 polarimetric monitoring task. Consequently, the modified Quegan method is developed by relaxing the target azimuth symmetry constraint with the Amazon forest datasets. The experiments based on the CRAS demonstrate that the main radiometric characteristics could reach the international level, with an estimated noise-equivalent sigma zero of approximately −30 dB, a radiometric resolution that is better than 2.9 dB, and a single-imagery relative radiation accuracy that is better than 0.51 dB. For polarimetric validation, the modified Quegan method was utilized to measure the crosstalk for quad-pol products to ensure that it was than −40 dB. Meanwhile, non-negligible channel imbalance errors were found in the QPSII and WAV modes, and they were effectively well-calibrated with strip estimators to satisfy the system design.

Radiometric Re-Compensation of Sentinel-1 SAR Data Products for Artificial Biases due to Antenna Pattern Changes

SAR data products for Sentinel-1 have been freely available and delivered operationally on behalf of the European Space Agency since the routine operation of Sentinel-1A in 2014. These products were delivered using the best knowledge at their processing time, in particular with respect to the radiometric calibration. As reprocessing of SAR data products is not foreseen in the nominal processing chain of Sentinel-1, changes of applied processing parameters impact the SAR data quality and can be a disturbing factor for long-term monitoring of radiometric features. In particular, antenna pattern updates produce artificial radiometric steps which are visible in radar backscatter time series, especially in case of monitoring radiometric stable reference targets. This paper introduces a method for correcting changes due to such updates without the need of reprocessing SAR data products. The method was applied to long-lasting time series of data acquisitions which are used to monitor the radiometric performance with reference targets at the DLR calibration site. It has been shown that artificial steps due to antenna pattern updates disappear in backscatter timelines after correct application. Furthermore, the derived absolute radiometric accuracy was improved for the joint observation period of S1A and S1B for almost five years until December 2021.

Chang’E-5 samples—New “ground truth” for the quantitative inversion of lunar remote sensing

<p indent="0mm">The Chang’E-5 (CE-5) mission successfully returned <sc>1731 g</sc> of lunar soil samples from the northeast of the Oceanus Procellarum. The newly returned lunar soil can provide a new ground truth for the quantitative inversion of lunar remote sensing data. In this study, the mineral and chemical compositions (FeO, TiO₂, Th) of the landing region were obtained from the remote sensing data and compared with the laboratory analysis results of the CE-5 lunar soil samples. The differences between them (especially the olivine content) indicate that there is still room for improvement in the methods for retrieving the elemental and mineral abundances using remote sensing data. Through a systematic comparative analysis, we discovered that: (1) the geochemical characteristics of high FeO, medium TiO₂, and abundant Th in the CE-5 lunar soil are significantly different from the existing Apollo lunar soil, which can provide unique ground truth for remote sensing research; (2) The CE-5 lunar soil represents mature lunar soil developed on the young basalt unit on the moon, with a small proportion of distantly sourced ejecta, representing the mare basalt composition characteristics of the landing region; (3) The CE-5 lunar soil is very fine, which meets the sample standard <sc>(&lt;45 μm)</sc> of the Lunar Soil Characterization Consortium for providing ground truth. Notably, the CE-5 landing region also exhibits unique characteristics: (1) it is located in the mid-latitude region on the western hemisphere of the moon, different from the low-latitude region where the United States and the Soviet Union sample return missions landed; (2) it is located on the late-stage lunar basalt unit; it is different from the existing spectral calibration area. Therefore, the construction of the CE-5 landing area as a new remote sensing calibration site based on the measured data of its lunar soil can significantly expand the geographical scope and global representation of the lunar calibration sites. Based on the results of the remote sensing and sample studies, we delineate the calibration area in the unit where the CE-5 landing site is located (Em4), thus providing a reference for establishing a remote sensing calibration area in the future.

On-Orbit Absolute Radiometric Calibration and Uncertainty Analysis of OCM2 Sensor onboard Oceansat-2 Satellite

ABSTRACT This study describes On-Orbit absolute radiometric calibration for the Ocean Colour Monitor2 (OCM2) onboard Oceansat-2 satellite through a vicarious calibration experiment performed at the Great Rann of Kutch calibration site in Gujarat, India, in February 2022. To achieve accurate and consistent calibration for the OCM2 channels, a reflectance-based calibration method was used which relies on synchronous in-situ measurements of surface reflectance and atmospheric parameters at the time of satellite overpass. In this exercise, the 6 SV (Second Simulation of a Satellite Signal in the Solar Spectrum Vector) radiative transfer (RT) model was used to simulate the Top Of Atmosphere (TOA) spectral radiance for the OCM2 channels. The on-orbit radiometric performance/changes were derived by comparing the 6 SV simulated TOA radiance with those of the OCM2 Level 1B (L1B) data product. The results indicate that the average gain for band 1 to band 8 was found in the range from 0.88 to 1.23 and the relative error from 1.58% to 18.79% for the OCM2 sensor. However, the Root-Mean-Square-Error (RMSE) between the OCM2 measured and the 6 SV simulated TOA radiance data range from 0.17 (µW cm−2 sr−1 nm−1) at 443 nm to 2.04 (µW cm−2 sr−1 nm−1) at 620 nm. Furthermore, we analysed in detail the various uncertainties in this approach emanating from surface reflectance, atmospheric conditions (ozone, water vapour and aerosol optical depth), aerosol-type assumption in the RT model, BRDF, and inherent accuracy of the 6 SV RT model. The overall uncertainty was within 6% estimated using the reflectance-based calibration method.