Cross-calibration Method Research Articles

Radiometric Calibration of the Near-Infrared Bands of GF-5-02/DPC for Water Vapor Retrieval

The GaoFen (GF)-5-02 satellite is one of the new generations of hyperspectral observation satellites launched by China in 2021. The directional polarimetric camera (DPC) is an optical sensor onboard the GF-5-02 satellite. The precipitable water vapor (PWV) is a key detection parameter of DPC. However, the existing PWV data developed using DPC data have significant errors due to the lack of the timely calibration of the two bands (865, 910 nm) of DPC used for PWV retrieval. In order to acquire DPC PWV data with smaller errors, a calibration method is developed for these two bands. The method consists of two parts: (1) calibrate the 865 nm band of the DPC using the cross-calibration method, (2) calibrate the 910 nm band of the DPC according to the calibrated 865 nm band of the DPC. This method effectively addresses the issue of the absence of a calibration method for the water vapor absorption band (910 nm) of the DPC. Regardless of whether AERONET PWV data or SuomiNET PWV data are used as the reference data, the accuracy of the DPC PWV data developed using calibrated DPC data is significantly superior to that of the DPC PWV data retrieved using data before recalibration. This means that the calibration method for the NIR bands of the DPC can effectively enhance the quality of DPC PWV data.

Polarimetric SAR cross-calibration method based on stable distributed targets

ABSTRACT Polarimetric calibration is essential for the pre-processing of Polarimetric Synthetic Aperture Radar (PolSAR) data because it effectively mitigates polarimetric distortions in the measured PolSAR data. Traditional methods of polarimetric calibration employ man-made calibrators that offer high accuracy. However, the frequency of calibration is often limited due to the labor-intensive and time-consuming nature of deploying such calibrators. Some polarimetric calibration methods based on distributed targets in nature enable more frequent calibration. Nevertheless, these methods are constrained by the availability of specific distributed targets with known polarimetric properties for estimating parameters related to co-polarization channel imbalance (co-pol-imba) parameters. If distributed targets are not appropriately selected or suitable targets are absent within the image scene, the accuracy of calibration will be compromised. To address this challenge, this paper introduces the idea of cross-calibration, which uses calibrated PolSAR data to determine the real polarimetric property of distributed targets and cross-estimates co-pol-imba parameters for uncalibrated PolSAR data. Furthermore, considering the disparities in imaging geometry between calibrated and uncalibrated PolSAR data, the Cross-Co-Polarization Ratio (CCPR) coefficients are proposed to select stable distributed targets in both the calibrated PolSAR data and the uncalibrated PolSAR data. This approach not only takes into account the impact of co-pol-imba on feature extraction but can also be applied in a broader range of scenes. The real data experiments on the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data show that the estimated results of the cross-calibration method for co-pol-imba are comparable to the polarimetric calibration method based on man-made calibrators, with an amplitude difference of 0.17 dB and a phase difference of 0.69°.

Cross-Calibration of HY-1D/COCTS Thermal Emissive Bands in the South China Sea

Haiyang-1D (HY-1D) is the second operational satellite in China’s Haiyang-1 series of satellites, carrying the Chinese Ocean Color and Temperature Scanner (COCTS) to provide ocean color and temperature observations. The radiometric calibration is a prerequisite to guarantee the quality of the satellite observations and the derived products, and the radiometric calibration of the thermal emissive bands of HY-1D/COCTS can effectively improve the accuracy of sea surface temperature (SST) derived from the thermal infrared data. In this paper, a study on the regional cross-calibration of the COCTS thermal emissive bands is conducted for high-accuracy SST observations in the South China Sea. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the NOAA-20 satellite launched by the National Oceanic and Atmospheric Administration (NOAA) is selected as the calibration reference sensor, and a double-difference cross-calibration method is used for HY-1D/COCTS thermal infrared brightness temperature (BT) evaluation. The results show that the bias of the 11 µm and 12 µm thermal emissive bands of COCTS and VIIRS in the South China Sea are 0.101 K and 0.892 K, respectively, and the differences in BTs between the two sensors show temperature dependence. The cross-calibration coefficients are obtained and used to correct the BT of the COCTS thermal emissive bands. The bias of the BT of the 11 µm and 12 µm bands of COCTS are about 0.01 K after cross-calibration. To further validate the results, COCTS post-calibration data were examined using the NOAA-20 Cross-track Infrared Sounder (CrIS) data as a third-party source. The BT is calculated with the spectral response functions of the COCTS thermal emissive bands using the convolution calculation of the CrIS hyperspectral region observations. The comparison shows a small bias between the post-calibration COCTS thermal emissive band observations and CrIS, which is consistent with the comparison between VIIRS and CrIS. The accuracy of the post-calibration COCTS thermal emissive band BT data in the South China Sea has been significantly improved.

A new method for cross-calibration between LIBS systems based on a domain adaptive fully connected network

This paper proposes a domain-adaptive fully connected neural network (DADNN) that is capable of transferring prior knowledge between ChemCam and SDU-LIBS.

Improved SAR Radiometric Cross-Calibration Method Based on Scene-Driven Incidence Angle Difference Correction and Weighted Regression

Improved SAR Radiometric Cross-Calibration Method Based on Scene-Driven Incidence Angle Difference Correction and Weighted Regression

On the use of solid 133Ba sources as surrogate for liquid 131I in SPECT/CT calibration: a European multi-centre evaluation

IntroductionCommissioning, calibration, and quality control procedures for nuclear medicine imaging systems are typically performed using hollow containers filled with radionuclide solutions. This leads to multiple sources of uncertainty, many of which can be overcome by using traceable, sealed, long-lived surrogate sources containing a radionuclide of comparable energies and emission probabilities. This study presents the results of a quantitative SPECT/CT imaging comparison exercise performed within the MRTDosimetry consortium to assess the feasibility of using 133Ba as a surrogate for 131I imaging.Materials and methodsTwo sets of four traceable 133Ba sources were produced at two National Metrology Institutes and encapsulated in 3D-printed cylinders (volume range 1.68–107.4 mL). Corresponding hollow cylinders to be filled with liquid 131I and a mounting baseplate for repeatable positioning within a Jaszczak phantom were also produced. A quantitative SPECT/CT imaging comparison exercise was conducted between seven members of the consortium (eight SPECT/CT systems from two major vendors) based on a standardised protocol. Each site had to perform three measurements with the two sets of 133Ba sources and liquid 131I.ResultsAs anticipated, the 131I pseudo-image calibration factors (cps/MBq) were higher than those for 133Ba for all reconstructions and systems. A site-specific cross-calibration reduced the performance differences between both radionuclides with respect to a cross-calibration based on the ratio of emission probabilities from a median of 12–1.5%. The site-specific cross-calibration method also showed agreement between 133Ba and 131I for all cylinder volumes, which highlights the potential use of 133Ba sources to calculate recovery coefficients for partial volume correction.ConclusionThis comparison exercise demonstrated that traceable solid 133Ba sources can be used as surrogate for liquid 131I imaging. The use of solid surrogate sources could solve the radiation protection problem inherent in the preparation of phantoms with 131I liquid activity solutions as well as reduce the measurement uncertainties in the activity. This is particularly relevant for stability measurements, which have to be carried out at regular intervals.

Multi-stage multi-criteria group decision making method based on hierarchical criteria interaction and trust rejection threshold under uncertain preference information

In the face of complex and changeable group decision-making problems, making satisfactory decisions is always difficult, which is deeply affected by information such as different stages, criteria, experts and alternatives. Thus, this study aims to develop an effective multi-stage multi-criteria group decision making (MSMCGDM) method to solve the multi-stage group decision making problems with various information. Firstly, through the introduction of trust rejection threshold, a Cross Calibration method is proposed to calculate experts' weights, considering the social influence of experts in the same stage as well as different stages. Then, based on the extend DEMATEL and Shapley approaches, the DE-Shapley method is constructed to obtain criteria weights considering the hierarchical criteria interaction according to the evaluation information on criteria. Furthermore, inspired by the adjacency matrix, the relationship matrix on alternatives and the concept of alternative sets are proposed to consider the acceptability of alternatives in different stages. Afterwards, elastic mechanism in proposed framework is put forward to deal with the unexpected situations when implementing the optimal alternative set. Finally, two scenarios on snowmelt flood are presented to demonstrate the application of the proposed method, sensitive analysis and comparative analyses are conducted to highlight the advantages of our proposed method.

In-orbit cross-calibration of millimeter conically scanning spaceborne radars

Abstract. The planned and potential introduction in global satellite observing systems of conically scanning Ka- and W-band atmospheric radars (e.g., the radars in the Tomorrow.IO constellation, https://www.tomorrow.io/space/, last access: 1 June 2022, and the Wivern (WInd VElocity Radar Nephoscope) radar, https://www.wivern.polito.it, last access: 1 July 2022) calls for the development of methodologies for calibrating and cross-calibrating these systems. Traditional calibration techniques pointing at the sea surface at about 11∘ incidence angle are in fact unfeasible for such fast rotating systems. This study proposes a cross-calibration method for conically scanning spaceborne radars based on ice cloud reflectivity probability distribution functions (PDFs) provided by reference radars like the Global Precipitation Measurement (GPM) Ka-band radar or the W-band radars planned for the ESA-JAXA EarthCARE or for the NASA Atmosphere Observing System missions. In order to establish the accuracy of the methodology, radar antenna boresight positions are propagated based on four configurations of expected satellite orbits so that the ground-track intersections can be calculated for different intersection criteria, defined by cross-over instrument footprints within a certain time and a given distance. The climatology of the calibrating clouds, derived from the W-band CloudSat and Ka-band GPM reflectivity records, can be used to compute the number and the spatial distribution of calibration points. Finally, the mean number of days required to achieve a given calibration accuracy is computed based on the number of calibration points needed to distinguish a biased reflectivity PDF from the sampling-induced noisiness of the reflectivity PDF itself. Findings demonstrate that it will be possible to cross-calibrate, within 1 dB, a Ka-band (W-band) conically scanning radar like that envisaged for the Tomorrow.io constellation (Wivern mission) every few days (a week). Such uncertainties are generally meeting the mission requirements and the standards currently achieved with absolute calibration accuracies.

The Uncertainty of SNO Cross-Calibration for Satellite Infrared Channels

The on-orbit radiometric calibration is a fundamental task in quantitative remote sensing applications. A widely used calibration method is the cross-calibration based on Simultaneous Nadir Observation (SNO), which involves using high-precision reference instruments to calibrate lower-precision onboard instruments. However, despite efforts to match the observation time, spatial location, field geometry, and instrument spectra, errors can still be introduced during the matching processes and linear regression analysis. This paper focuses on the error generated by sample matching and the error fitting method generated by the sample fitting method. An error propagation analysis is performed to develop a generic model for assessing the uncertainty of the SNO cross-calibration method itself in meteorological satellite infrared channels. The model is validated using the payload parameters of the Hyperspectral Infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) instruments aboard the FengYun-3D (FY-3D). Simulation experiments are performed considering typical bright temperatures, different background fields, and varying matching threshold conditions. The results demonstrate the effectiveness of the proposed model in capturing the error propagation chain in the SNO cross-calibration process. The model provides valuable insight into error analysis in the SNO cross-calibration method and can assist in determining the optimal sample matching threshold for achieving radiometric calibration accuracy.

Characterization of the INFN proton CT scanner for cross-calibration of x-ray CT

Objective. The goal of this study was to assess the imaging performances of the pCT system developed in the framework of INFN-funded (Italian National Institute of Nuclear Physics) research projects. The spatial resolution, noise power spectrum (NPS) and RSP accuracy has been investigated, as a preliminary step to implement a new cross-calibration method for x-ray CT (xCT). Approach. The INFN pCT apparatus, made of four planes of silicon micro-strip detectors and a YAG:Ce scintillating calorimeter, reconstructs 3D RSP maps by a filtered-back projection algorithm. The imaging performances (i.e. spatial resolution, NPS and RSP accuracy) of the pCT system were assessed on a custom-made phantom, made of plastic materials with different densities ((0.66, 2.18) g cm−3). For comparison, the same phantom was acquired with a clinical xCT system. Main results. The spatial resolution analysis revealed the nonlinearity of the imaging system, showing different imaging responses in air or water phantom background. Applying the Hann filter in the pCT reconstruction, it was possible to investigate the imaging potential of the system. Matching the spatial resolution value of the xCT (0.54 lp mm−1) and acquiring both with the same dose level (11.6 mGy), the pCT appeared to be less noisy than xCT, with an RSP standard deviation of 0.0063. Concerning the RSP accuracy, the measured mean absolute percentage errors were (0.23+−0.09)% in air and (0.21+−0.07)% in water. Significance. The obtained performances confirm that the INFN pCT system provides a very accurate RSP estimation, appearing to be a feasible clinical tool for verification and correction of xCT calibration in proton treatment planning.

Cross-calibration method based on an automated observation site.

Cross-calibration methods are widely used in high-precision remote sensor calibrations and ensure observational consistency between sensors. Because two sensors must be observed under the same or similar conditions, the cross-calibration frequency is greatly reduced; performing cross-calibrations on Aqua/Terra MODIS, Sentinel-2A/Sentinel-2B MSI and other similar sensors is difficult due to synchronous-observation limitations. Additionally, few studies have cross-calibrated water-vapor-observation bands sensitive to atmospheric changes. In recent years, standard automated observation sites and unified processing technology networks, such as an Automated Radiative Calibration Network (RadCalNet) and an automated vicarious calibration system (AVCS), have provided automatic observation data and means for independently, continuously monitoring sensors, thus offering new cross-calibration references and bridges. We propose an AVCS-based cross-calibration method. By limiting the observational-condition differences when two remote sensors transit over wide temporal ranges through AVCS observation data, we improve the cross-calibration opportunity. Thereby, cross-calibrations and observation consistency evaluations between the abovementioned instruments are realized. The influence of AVCS-measurement uncertainties on the cross-calibration is analyzed. The consistency between the MODIS cross-calibration and sensor observation is within 3% (5% in SWIR bands); that for the MSI is within 1% (2.2% in the water-vapor-observation band); and for the cross-calibration of Aqua MODIS and the two MSI, the consistency between the cross-calibration-predicted TOA reflectance and the sensor-measured TOA reflectance was within 3.8%. Thus, the absolute AVCS-measurement uncertainty is also reduced, especially in the water-vapor-observation band. This method can be applied to cross-calibrations and measurement consistency evaluations of other remote sensors. Later, the spectral-difference influences on cross-calibrations will be further studied.

Radiometric cross-calibration of Sentinel-2B MSI with HY-1C SCS based on the near simultaneous imaging of common ground targets.

To simplify the cross-calibration process and improve calibration frequency and accuracy, this paper proposes a cross-calibration method for the multispectral remote sensor Multi-Spectral Instrument (MSI) carried by Sentinel-2B using the hyperspectral remote sensor, that is, the satellite calibration spectrometer (SCS) carried by Hai Yang (HY)-1C, as the reference sensor and establishes the calibration process. Precise spectral response matching between SCS and MSI spectral channels is performed by the interpolation and iteration of hyperspectral data to eliminate the difference in band settings and significantly improve the accuracy of cross-calibration coefficients. The SNO-x inherited from the simultaneous nadir overpass (SNO) method is used as a prediction method to carry out cross-calibration imaging in mid- and low-latitude regions, which improves the cross-calibration frequency and broadens the dynamic range of calibration. The cross-calibration coefficients and offsets of MSI B1∼B7 and B8a were obtained by processing the earth observation images of the MSI and SCS on January 24, 2019. Then, the cross-calibration coefficients and offsets are applied to the ocean, farmland and other ground objects with different reflectance, and the reliability and accuracy of the cross-calibration results are evaluated with the Moderate-resolution Imaging Spectroradiometer (MODIS) carried by Terra as a reference. To improve the accuracy of the evaluation, the spectral band adjustment factor between the corresponding channels of MSI and MODIS is used to correct the measured reflectance of MODIS based on the satellite calibration coefficient. The reflectance directly obtained by processing the MSI image is used as the MSI-measured reflectance, the reflectance obtained based on the cross-calibration coefficient is used as the MSI-calculated reflectance, and the reflectance corrected by the spectral band adjustment factor (SBAF) is used as the MODIS-calculated reflectance. The results show that the mean root-mean-square relative error (RMSRE) between the MODIS-calculated reflectance and the MSI-calculated reflectance is 2.16% and that the mean RMSRE between the MODIS-calculated reflectance and the MSI-measured reflectance is 3.05%, indicating that the reflectance corrected based on calibration coefficients is closer to the MODIS-calculated reflectance. Finally, each uncertainty source in the cross-calibration is analyzed, and the comprehensive uncertainty is found to be 4.03%, indicating that SCS can be used as a reference for MSI cross-calibration.

Cross Calibration Method Based on the Multi-angle Apparent Reflectance Model

Cross Calibration Method Based on the Multi-angle Apparent Reflectance Model

Bilateral independent cross-calibration method of the satellite-borne imaging altimeter

Bilateral independent cross-calibration method of the satellite-borne imaging altimeter

Towards a continent-wide ecological site condition database using calibrated expert evaluations.

A cost-effective way of undertaking comprehensive, continental-scale, assessments of ecological condition is needed to support large-scale conservation planning, monitoring, reporting, and decision-making. Currently, cross-jurisdictional inconsistency in assessment methods limits the capacity to scale-up monitoring. Here we present a novel way to build a coherent continent-wide site-level ecological condition dataset, using cross-calibration methods to integrate assessments from many observers. We focus on the use of condition assessments from individual expert observers, a currently untapped resource. Our approach has two components: (1) a simple online tool that captures expert assessments at specific locations; (2) a process of calibrating and rescaling disparate expert evaluations that can be applied to the data to provide a consistent dataset for use in conservation assessments. We describe a pilot study, involving 28 experts, who contributed 314 individual site condition assessments across a wide range of ecosystems and regions throughout continental Australia. A correction factor for each expert was used to rescale the contributed site condition assessment scores, based on a set of 77 photographic images, each scored for their condition by multiple experts, using a linear mixed model. Our approach shows strong promise for delivering the volumes of data required to develop continental-scale reference libraries of site condition assessments. Although developed from expert elicitation, the approach could also be used to harmonize the collation of existing condition datasets. The process we demonstrate can also facilitate online citizen scientists to make site condition assessments that can be cross-calibrated using contributed images.

Image-based cross-calibration method for multiple spectrometer-based OCT.

A fast and practical computational cross-calibration of multiple spectrometers is described. A signal correlation matrix (CM) can be constructed from paired B-scans in a multiple-spectrometer optical coherence tomography (OCT), where the wavelength-corresponding pixels are indicated by high cross correlation. The CM can be used to either guide the physical alignment of spectrometers or to numerically match the spectra in the post-process. The performance is comparable to the previously reported optimization approach, as demonstrated by the mirror tests, qualitative comparison of OCT and optical coherence tomography angiography (OCTA) images, and quantitative comparison of image metrics.

Radiometric Cross-Calibration of GF-6/WFV Sensor Using MODIS Images With Different BRDF Models

The wide field of view (WFV) imaging system of the GaoFen-6 (GF-6) satellite processes four popular spectral bands [blue, green, red, and near-infrared (NIR)] and four new spectral bands (costal, yellow, and two red edges). However, the corresponding reference spectral bands for these eight spectral bands from one reference sensor are insufficient in the cross-calibration process of the WFV; therefore, current cross-calibration methods should be improved. To address this problem, the Moderate-Resolution Imaging Spectroradiometer (MODIS), which has high radiometric performance with the aid of an onboard calibration system, is used as a reference sensor, and cross-calibration methods using the top of atmosphere (TOA) and the bottom of atmosphere (BOA) bidirectional reflectance distribution function (BRDF) models are developed and compared. The results reveal that the cross-calibration results in eight spectral bands with the BOA BRDF model that can obtain higher consistency with the official calibration coefficients (OCCs) compared with the TOA BRDF model. In addition, after various influencing factors are comprehensively analyzed, the spectral band adjustment factor (SBAF) correction in the shortwave infrared (SWIR) spectral bands can be neglected; moreover, by using five spectral bands (blue, green, red, NIR, and SWIR) of the MODIS sensor, the BOA BRDF model and the cubic polynomial interpolation method provide optimal cross-calibration schemes for WFV sensor. The total radiometric cross-calibration uncertainties of the proposed cross-calibration methods with the BOA BRDF model and the TOA BRDF model are less than 5.73% and 6.32%, respectively.

Spectral Reflectance Estimation of UAS Multispectral Imagery Using Satellite Cross-Calibration Method

This paper introduces a satellite-based cross-calibration (SCC) method for spectral reflectance estimation of unmanned aircraft system (UAS) multispectral imagery. The SCC method provides a low-cost and feasible solution to convert high-resolution UAS images in digital numbers (DN) to reflectance when satellite data is available. The proposed method is evaluated using a multispectral data set, including orthorectified KHawk UAS DN imagery and Landsat 8 Operational Land Imager Level-2 surface reflectance (SR) data over a forest/grassland area. The estimated UAS reflectance images are compared with the National Ecological Observatory Network's imaging spectrometer (NIS) SR data for validation. The UAS reflectance showed high similarities with the NIS data for the near-infrared and red bands with Pearson's r values being 97 and 95.74, and root-mean-square errors being 0.0239 and 0.0096 over a 32-subplot hayfield.

Optimization of cross-calibration factor for quantitative bone SPECT without attenuation and scatter correction in the lumbar spine: head-to-head comparison with attenuation and scatter correction.

Quantitative single-photon emission computed tomography (SPECT) with computed tomography (SPECT/CT) is known to improve diagnostic performance. Although SPECT-alone systems are used widely, accurate quantitative SPECT using these systems is challenging. This study aimed to improve the accuracy of quantitative bone SPECT of the lumbar spine with the SPECT-alone system. The cross-calibration factor (CCF) was measured using three kinds of phantoms and the optimal values were determined. The recovery coefficient with and without attenuation and scatter correction (ACSC) were compared. Bone SPECT/CT was performed on 93 consecutive patients with prostate cancer, and the standardized uptake values (SUVs) were compared using the respective CCFs. The first 60 patients were classified according to body weight, and the correlation coefficient between SUVs with and without ACSC were calculated; the slopes were defined as body weight-based coefficients (BWCs). In the remaining 33 patients, the SUV was adjusted according to BWC, and the accuracy of the adjustment was verified. The quantitative SPECT values obtained from the CCF using SIM2 bone phantom showed nearly accurate radioactivity concentrations, even without ACSC. The recovery coefficients with and without ACSC were similar. Unadjusted SUVs with and without ACSC were strongly correlated; however, SUVs without ACSC were significantly higher than those with ACSC (P < 0.0001). The mean difference between the SUVs with and without ACSC disappeared when the SUVs without ACSC were adjusted by BWC (P = 0.9814). Our cross-calibration method for quantitative bone SPECT enables interpretation with a harmonized SUV even in SPECT-alone systems.

An Automatic Radiometric Cross-Calibration Method for Wide-Angle Medium-Resolution Multispectral Satellite Sensor Using Landsat Data

Radiometric calibration of the medium-resolution satellite data is critical for monitoring and quantifying changes in the Earth's environment and resources. Many medium-resolution satellite sensors have irregular revisits and, sometimes, have a large difference in illumination viewing geometry compared with a reference sensor, posing a great challenge for routine cross-calibration practices. To overcome these issues, this study proposed a cross-calibration method to calibrate medium-resolution multispectral data. The Chinese Gaofen-4 (GF-4) panchromatic and multispectral sensor (PMS) data with large viewing angles were used as the test data, and Landsat-8 operational land imager (OLI) data were used as the reference data. A bidirectional reflectance distribution function (BRDF) correction method was proposed to eliminate the effects of differences in illumination viewing geometry between GF-4 and Landsat-8. The validation using concurrent image shows that the mean relative error (MRE) of cross calibration is less than 6.65%. Validation using ground measurements shows that our calibration results have an improvement of around 14.8% compared with the official released calibration coefficients. The time series cross calibration reveals that, without the requirements of simultaneous nadir observations (SNOs), our calibration activities can be carried out more often in practice. Gradual and continuous radiometric sensor degradation is identified with the monthly updated calibration coefficients, demonstrating the reliability and importance of the timely cross calibration. Besides, the cross-calibration approach does not rely on any specific calibration site, and the difference in illumination viewing geometry can be well considered. Thus, it can be easily adapted and applied to other optical satellite data.