Cross-calibration Coefficients Research Articles

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.

Cross-Radiometric Calibration and NDVI Application Comparison of FY-4A/AGRI Based on Aqua-MODIS

To enhance the accuracy and stability of FY-4A/AGRI detection data, the MODIS, with highly accurate onboard calibration, is selected as the reference sensor for cross-radiation calibration calculations. The following are the data selection conditions: full considered time, observation geometries, field angles, cloud cover, etc. FY-4A/AGRI and Aqua-MODIS image data are selected as matching sample region locations, where the time difference between the observations for the same ground object is less than 15 min, the satellite zenith angle is less than 30°, and the field angle difference is less than 0.01. The 245 collected reflectance spectral curves are convolved with the spectral response functions of the two sensors, and the spectral band adjustment factors of the corresponding bands are calculated for spectral correction purposes. The cross-calibration coefficients for the red and near-infrared bands are calculated by linearly fitting the simulated top of the atmosphere reflectance values and digital number values from the AGRI sensor in a homogeneous area. In this paper, 16 cross-calibration calculations are performed on FY-4A/AGRI image data from August 2018 to September 2020, and the results are compared with the original calibration coefficients to test the feasibility of the proposed method. Additionally, 31 cross-calibration calculations are performed on image data from October 2020 to December 2022 to study the resulting AGRI sensor quality and performance changes. The NDVI of the FY-4A/AGRI image data was calculated before and after the cross-radiometric calibration using the maximum synthesis method. Additionally, the NDVI of the MODIS image data was compared and analyzed from three aspects: time, space, and the change trend. The results show that the spectral band adjustment factor calculated using the reflectance spectral curves of the ground objects in this paper can effectively correct for the spectral differences between the two sensors. Sixteen cross-calibration coefficients are less than 5.2% different from the original calibration coefficients, which fully proves the feasibility of the method used in this paper. All of the cross-calibration results show that the AGRI sensors have a certain degree of attenuation in the red and near-infrared bands, and the annual attenuation rates are approximately 1.37% and 2.55%, respectively. Cross-radiometric calibration has further improved the quality of the NDVI in FY-4A/AGRI imagery, enhancing the precision of its data application.

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.

Dosimetric accuracy of a cross-calibration coefficient for plane-parallel ionization chamber obtained in low-energy electron beams using various cylindrical dosimeters

Abstract Introduction: The accuracy of the cross-calibration procedure depends on ionization chamber type, both used as reference one and under consideration. Also, the beam energy and phantom medium could influence the precision of cross calibration coefficient, resulting in a systematic error in dose estimation and thus could influence the linac beam output checking. This will result in a systematic mismatch between dose calculated in treatment planning system and delivered to the patient. Material and methods: The usage of FC65-G, CC13 and CC01 thimble reference chambers as well as 6, 9, and 15 MeV electron beams has been analyzed. A plane-parallel PPC05 chamber was calibrated since scarce literature data are available for this dosimeter type. The influence of measurement medium and an effective point of measurement (EPOM) on obtained results are also presented. Results: Dose reconstruction precision of ~0.1% for PPC05 chamber could be obtained when cross-calibration is based on a thimble CC13 chamber. Nd,w,Qcross obtained in beam ≥ 9MeV gives 0.1 – 0.5% precision of dose reconstruction. Without beam quality correction, 15 MeV Nd,w,Qcross is 10% lower than Co-60 Nd,w,0. Various EPOM shifts resulted in up to 0.6% discrepancies in Nd,w,Qcross values. Conclusions: Ionization chamber with small active volume and tissue-equivalent materials supplies more accurate cross-calibration coefficients in the range of 6 – 15 MeV electron beams. In the case of 6 and 9 MeV beams, the exact position of an effective point of measurement is of minor importance. In-water cross-calibration coefficient can be used in a solid medium without loss of dose accuracy.

The Assessment of Cross Calibration/Validation Accuracy for KOMPSAT-3 Using Landsat 8 and 6S

In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.

Radiometric Cross-Calibration of GF-4/IRS Based on MODIS Measurements

GaoFen-4 (GF-4) infrared spectrum (IRS) camera has a special spectral band located in the mid-wave infrared spectrum with the wavelength ranging from 3.50 to 4.10 μm. It is very important for forest fire-detection and other quantitative remote sensing applications at a high spatial resolution of 400 m. Due to the similarity of the spectral characteristics, the thermal emissive band 20 (3.660-3.840 μm) and 22 (3.929-3.989 μm) of medium resolution imaging spectrometer (MODIS) are taken as the reference bands for the radiometric cross-calibration of the GF-4/IRS camera. The time difference between selected GF-4/IRS and MODIS images at the Qinghai Lake and Se lincuo Lake test sites is less than one hour. After spatial matching, single-band and dual-band spectral matching methods are proposed in this article. Then, the DN value of GF-4 image is linearly fitted to the radiance of the corresponding MODIS image to obtain the radiometric calibration coefficients of GF-4/IRS camera. The validation results show that the cross-calibration coefficients calculated by integrating the measurement of two MODIS bands with the mean value spectral matching approach has the highest radiometric calibration consistency with the official calibration coefficients.

Characterization of the PTW-34089 type 147 mm diameter large-area ionization chamber for use in light-ion beams

A newly-designed large-area plane-parallel ionization chamber (of type PTW 34089), denoted BPC150, with a nominal active volume diameter of 147 mm is characterized in this study. Such chambers exhibit benefits compared to smaller chambers in the field of scanned light-ion beam dosimetry because they capture a larger fraction of the laterally-spread beam fragments and ease positioning with respect to small fields. The chamber was characterized in 60Co, 200 kV x-ray, proton and carbon ion beams. The chamber-specific beam-quality correction factor kQ,Q0 was determined. To investigate the homogeneity of the chamber’s response, a radial response map was acquired. An edge correction was applied when the proton beam only partly impinged on the chamber’s active surface. The measured response map showed that the response in the chamber’s center is 3% lower than the average response over the total active area. Furthermore, percentage depth dose (PDD) curves in carbon ions were acquired and compared to those obtained with smaller-diameter chambers (i.e. 81.6 mm and 39.6 mm) as well as with results from Monte Carlo simulations. The measured absorbed dose to water cross calibration coefficients resulted in a kQ,Q0 of 0.981 ± 0.020. Regarding carbon ion PDD curves, relative differences between the BPC150 and smaller chambers were observed, especially for higher energies and in the fragmentation tail. These differences reached 10%–22% in the fragmentation tail (compared to the 81.6 mm diameter chamber). Differences increased when comparing to a chamber with 39.6 mm diameter. The provided results characterize the BPC150 thoroughly for usage in scanned light-ion beam dosimetry and demonstrate its advantage of capturing a larger fraction of the laterally-integrated dose in the fragmentation tail.

Combination of Cross- and Inter-Band Radiometric Calibrations for a Hyperspectral Sensor Using Model-Based Spectral Band Adjustment

Recently, the growing number of hyperspectral satellite sensors have increased the demand for a flexible and robust approach to their calibration. This paper proposes an operational method for the simultaneous correction of inter-sensor and inter-band biases in hyperspectral sensors via the soil line concept for spectral band adjustment. Earth Observing-1 Hyperion was selected as an example, with the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference. The results over the Railroad Valley Playa calibration site indicated that the discrepancy in the analogous bands between Hyperion and MODIS during 2001–2008 was approximately 4–6% and 7–9% of the root-mean-square error in the top-of-atmosphere (TOA) radiance at the visible and near-infrared region and shortwave infrared region, respectively. For all Hyperion bands, the relative cross-calibration coefficients during this period were calculated (typically ranging from 0.9 to 1.1) to correct the Hyperion TOA radiance to be consistent with the MODIS and the other Hyperion bands. The application of the proposed approach could allow for more flexible cross-calibration of irregular-orbit sensors aboard the International Space Station.

Radiometric Calibration and Uncertainty Analysis of KOMPSAT-3A Using the Reflectance-Based Method.

In recent years, Korea has sustained consistent access to remote sensed data by launching Korea Multi-Purpose Satellite-3A (KOMPSAT-3A, K3A)—an updated version of the high-resolution KOMPSAT series. This KOMPSAT-3A required calibration and validation (Cal/Val) before and after its launch to enable proper functional characterization and to maintain the veracity of data collected. The Korea Aerospace Research Institute (KARI) executed the initial prelaunch calibration in the laboratory and we performed the Cal/Val of KOMPSAT-3A during the Launch and Early Operation Phase (LEOP) in the field. Two suitable sites in Korea and Mongolia with stable weather, almost uniform terrain, and near Lambertian diffusion, provided the necessary tarp reflectance to calculate the absolute radiometric calibration coefficients. The surface reflectance was determined using 12 and four well-calibrated reference reflectance tarps employing the FieldSpec® 3(Analytical Spectral Devices Inc., Boulder, CO, USA) Spectroradiometer. Subsequently, the top of atmosphere (TOA) radiance was estimated using radiative transfer code (RTC) software based on the Atmospheric and Topographic Correction (ATCOR). In addition, cross calibration was simultaneously performed at the Libya-4 pseudo invariant calibration site (PICS) for KOMPSAT-3A TOA radiance, using the spectral band adjustment factor (SBAF) compensated Landsat 8 reflectance and the Second Simulation of Satellite Signal in the Solar Spectrum (6S) to compute cross calibration coefficients. The results of the KOMPSAT-3A absolute calibration coefficient show that the R2 values were over 0.99, implying a significant correlation for almost all bands between the TOA radiance and the KOMPSAT-3A spectral band response at both campaign sites. However, this study reveals a difference of less than 5% calibration gains for all bands compared to the prelaunch values, while the cross calibration gain is below 5% in visible bands and above 5% in the near infrared band. An effort to optimize the reliability of the absolute calibration coefficients resorted to the rigorous quantification of uncertainties amongst atmospheric conditions, the digital number (DN), the reflectance tarp, the bidirectional reflectance distribution function (BRDF), and ozone levels. Therefore, we presumed that the total uncertainty was 4.27%, which conforms to some published results.

Cross calibration of GF-4 visible and near-infrared sensor with CE-3 VNIS sensor based on lunar

In space-borne remote sensing, the accuracy of radiometric calibration is a key issue for image quality and further data applications. According to the relationship between GF-4 visible and near-infrared (VNIR) sensor and CE-3 VNIS sensor, an applicable cross radiometric calibration method is proposed here based on the observation data of lunar. The cross calibration generates a set of radiometric calibration coefficients for GF-4 VNIR sensor. Two validation experiments are implemented to verify the authenticity and accuracy of cross calibration coefficients: the proposed approach shows a high consistency than previous coefficients by comparing the retrieved reflectance of three calibration sites on lunar, and gets the accuracy of 5.34 %, 3.42 %, 3.49 % and 5.96 % with blue, green, red and near infrared bands of GF-4 by ground-based experiments.

Radiometric Cross-Calibration of GF-4/VNIR Sensor With Landsat8/OLI, Sentinel-2/MSI, and Terra/MODIS for Monitoring Its Degradation

Optical satellite sensor generally suffers from drifts and biases relative to their prelaunch calibration, caused by launch and the space environment. Radiometric cross-calibration is valuable for calibrating sensors without coincident surface measurements through transferring radiometric values between satellite sensors via a stable target. The data quality of visible and near-infrared (VNIR) sensor onboard Gaofen-4 (GF-4) satellite seriously depends on vicarious calibration, which is performed once every year, thus, a cross-calibration approach is proposed for monitoring its radiometric performance much more frequently. In this study, the GF-4/VNIR is cross-calibrated by Landsat8/OLI, Sentinel-2/MSI, and Terra/MODIS with the aid of the tandem scenes during 2017 and 2018 after correcting the discrepancy on viewing geometries and spectrum. The results show that there is test site dependency and sensor dependency, and cross-calibration coefficients in the four bands roughly have similar variation trend as a sinusoidal function during 2017 and 2018, varying from 0.00023 to 0.00079. Furthermore, uncertainty analysis of the cross-calibration is carried out to analyze the uncertainty contributions affecting the cross-calibration accuracy. Note that the calibration accuracy of referenced sensors, the uncertainty of the MODTRAN model, BRDF uncertainty are the three main factors affecting the cross-calibration accuracy, the total uncertainty is approximately 3.9%–6.64%.

Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.

Radiometric Cross-Calibration of Landsat-8/OLI and GF-1/PMS Sensors Using an Instrumented Sand Site

The panchromatic and multispectral (PMS1/PMS2) sensors designed with one panchromatic band and four multispectral bands are two optical cameras on-board the Gao Fen 1 (GF-1) satellite launched on April 26, 2013. The spatial resolution of PMS1/PMS2 are 2 and 8 m of pan and multispectral, respectively. The vicarious calibration of GF-1/PMS was performed by China Centre for Resource Satellite Data and Application, and the calibration coefficients were released once a year. Due to the lack of on-board calibrator, the on-orbit radiometric performance evaluation of the PMS sensors is very important for the further quantitative application of the data. To evaluate the radiometric performance of PMS1 sensor on-board GF-1 satellite, this paper attempts to calibrate PMS1 sensor against the well-calibrated OLI sensor on-board Landsat-8. An instrumented sand site was used, which is located in the national high resolution remote sensing comprehensive calibration site, Baotou, China. The cross-calibration coefficients of PMS1 on October 5, 2015 and August 20, 2016 are calculated and compared with the official calibration coefficients published in 2015 and 2016. The results show that the cross-calibration of PMS sensor using other sensors is necessary, due to the low updating frequency of calibration coefficient for GF-1/PMS sensor. The uncertainty estimation results show that the total uncertainties associated with the cross-calibration of Landsat-8/OLI and GF-1/PMS sensors over a desert site are within 5.5%.

RADIOMETRIC CROSS-CALIBRATION OF GAOFEN-1 WFV CAMERAS WITH LANDSAT-8 OLI AND MODIS SENSORS BASED ON RADIATION AND GEOMETRY MATCHING

Abstract. Cross-calibration has the advantages of high precision, low resource requirements and simple implementation. It has been widely used in recent years. The four wide-field-of-view (WFV) cameras on-board Gaofen-1 satellite provide high spatial resolution and wide combined coverage (4 × 200 km) without onboard calibration. In this paper, the four-band radiometric cross-calibration coefficients of WFV1 camera were obtained based on radiation and geometry matching taking Landsat 8 OLI (Operational Land Imager) sensor as reference. Scale Invariant Feature Transform (SIFT) feature detection method and distance and included angle weighting method were introduced to correct misregistration of WFV-OLI image pair. The radiative transfer model was used to eliminate difference between OLI sensor and WFV1 camera through the spectral match factor (SMF). The near-infrared band of WFV1 camera encompasses water vapor absorption bands, thus a Look Up Table (LUT) for SMF varies from water vapor amount is established to estimate the water vapor effects. The surface synchronization experiment was designed to verify the reliability of the cross-calibration coefficients, which seem to perform better than the official coefficients claimed by the China Centre for Resources Satellite Data and Application (CCRSDA).

Radiometric Cross-Calibration of GF-4 PMS Sensor Based on Assimilation of Landsat-8 OLI Images

Earth observation data obtained from remote sensors must undergo radiometric calibration before use in quantitative applications. However, the large view angles of the panchromatic multispectral sensor (PMS) aboard the GF-4 satellite pose challenges for cross-calibration due to the effects of atmospheric radiation transfer and the bidirectional reflectance distribution function (BRDF). To address this problem, this paper introduces a novel cross-calibration method based on data assimilation considering cross-calibration as an optimal approximation problem. The GF-4 PMS was cross-calibrated with the well-calibrated Landsat-8 Operational Land Imager (OLI) as the reference sensor. In order to correct unequal bidirectional reflection effects, an adjustment factor for the BRDF was established, making complex models unnecessary. The proposed method employed the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm to find the optimal calibration coefficients and BRDF adjustment factor through an iterative process. The validation results revealed a surface reflectance error of <5% for the new cross-calibration coefficients. The accuracy of calibration coefficients were significantly improved when compared to the officially published coefficients as well as those derived using conventional methods. The uncertainty produced by the proposed method was less than 7%, meeting the demands for future quantitative applications and research. This method is also applicable to other sensors with large view angles.

Absolute calibration of sniffer probes on Wendelstein 7-X.

Here we report the first measurements of the power levels of stray radiation in the vacuum vessel of Wendelstein 7-X using absolutely calibrated sniffer probes. The absolute calibration is achieved by using calibrated sources of stray radiation and the implicit measurement of the quality factor of the Wendelstein 7-X empty vacuum vessel. Normalized absolute calibration coefficients agree with the cross-calibration coefficients that are obtained by the direct measurements, indicating that the measured absolute calibration coefficients and stray radiation levels in the vessel are valid. Close to the launcher, the stray radiation in the empty vessel reaches power levels up to 340 kW/m(2) per MW injected beam power. Furthest away from the launcher, i.e., half a toroidal turn, still 90 kW/m(2) per MW injected beam power is measured.

Radiometric cross-calibration of Gaofen-1 WFV cameras using Landsat-8 OLI images: A solution for large view angle associated problems

Abstract Four wide-field-of-view (WFV) instruments are onboard the Gaofen-1 (or GF-1) satellite, providing a combined swath of ~ 800 km. However, observations with large view angles pose new challenges for radiometric cross-calibration with a simple image-based method when using Landsat-8 Operational Land Imager (OLI) data as a reference. Based on radiative transfer modeling, a novel radiometric cross-calibration method has been proposed in this study to solve large view angle-associated problems. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products were used to simulate the top of atmosphere (TOA) signal of the reference and target instruments, and the unequal bidirectional effects were corrected using MODIS bi-directional reflectance distribution function (BRDF) products. Extensive validations with both satellite data and in situ measurements revealed an uncertainty of ~ 8% for the newly produced cross-calibration coefficients when they were used to calibrate TOA reflectance for both close-nadir and off-nadir instruments. The improvements are discernable when compared with the official provided coefficients and that were derived using the image-based cross-calibration method. This study demonstrated not only the usefulness of Landsat-8 OLI data in sensor radiometric calibration but also the impressive accuracy of the MODIS BRDF and aerosol products in radiative transfer simulations. The proposed method can be used in the future to monitor and correct potential radiometric degradations of the GF-1 WFV instruments, and it also can be easily extended to other similar satellite missions to conduct radiometric cross-calibrations.

Cross-Calibration of the HSI Sensor Reflective Solar Bands Using Hyperion Data

This paper describes a methodology that uses Hyperion imagery as reference data to calibrate the Chinese Hyperspectral Imager (HSI) onboard the HJ-1A satellite. Two test sites near Dunhuang in Gansu and in Inner Mongolia were used for the cross-calibration. To account for the uncertainties in the top of atmosphere (TOA) reflectance due to the bidirectional reflectance distribution function (BRDF) and relative spectral response (RSR) differences between the two sensors, a model is adopted to transfer the Hyperion TOA reflectance to the effective HSI TOA reflectance. The influence of BRDF is analyzed, and two BRDF correction approaches are applied to the two test sites, respectively. For the Dunhuang test site, the ground synchronously measured reflectance in different solar zenith angles is used for BRDF correction. For the Inner Mongolia test site, a kernel-driven model is applied. The influence of RSR mismatch is computed using a spectral profile adjustment factor (SPAF), which takes into account the spectral profile of the target and the RSR of each sensor. The SPAF is calculated according to the TOA reflectance simulated using moderate resolution atmospheric transmission. One-point calibration and multipoint calibration coefficients are computed, respectively. Ground reflectance data measured in June 2010 at the Inner Mongolia test site were used to validate the cross-calibration coefficients based on the Hyperion image. The results support the proposal that the cross-calibration method between two hyperspectral sensors is effective, and the use of multipoint calibration coefficient with nonzero offset has great potential for hyperspectral sensor calibration.

Multi-points cross calibration and validation of HJ-1B and AIRS thermal infrared channels

On orbit radiometric calibration of thermal infrared sensors in China is mainly based on the single-point method with insitu measurements of large uniform targets and cross calibration with moderate resolution sensors which have high calibration accuracy. The single-point method is time-consuming and laborious, and the intercept can not be calculated. Accuracy of cross calibration with the moderate resolution sensors is restricted by the matching algorithm of entrance pupil radiances. Both of this two methods' insufficients have been affected the accuracy of on orbit radiometric calibration in China. According to the characteristics of AIRS hyperspectral data, multi-points cross calibration is performed between the AIRS and HJ-1B thermal infrared channles. The time and spatial varieties are eliminated through the similar imaging times and homogeneous regions. At the same time, radiative transfer calculation by MODTRAN is used for each pixel to normalize the observation geometry. Times series multi-points method with the single target, various times and homogeneous targets multi-points method with the single time, various targets are performed to obtain the calibration coefficients of HJ-1B thermal infrared channel. Onboard calibration coefficients calculated by the Look-up table method is used to validate the multi-points cross calibration results. After the elimination of abnormal points from the time series multi-points method and regulation of match factor with homogeneous targets multi-points method, the differences between the equivalent brightness temperature retrieved by the multi-points cross calibration and onboard calibration coefficients are 1.81 and 0.92 K, respectively. The results indicate that the homogeneous targets multi-points method for cross calibration of AIRS and HJ-1B thermal infrared channels has higher accurate.

Multicenter cross-calibration of I-123 metaiodobenzylguanidine heart-to-mediastinum ratios to overcome camera-collimator variations

BackgroundThe heart-to-mediastinum ratio (HMR) of 123I-metaiodobenzylguanidine (MIBG) showed variations among institutions and needs to be standardized among various scinticamera-collimator combinations. MethodsA total of 225 phantom experiments were performed in 84 institutions to calculate cross-calibration coefficients of HMR. Based on phantom studies, a conversion coefficient for each camera-collimator system was created, including low-energy (LE, n = 125) and a medium-energy (ME, n = 100) collimators. An average conversion coefficient from the most common ME group was used to calculate the standard HMR. In clinical MIBG studies (n = 52) from three institutions, HMRs were standardized from both LE- and ME-type collimators and classified into risk groups of <1.60, 1.60-2.19, and ≥2.20. ResultsThe average conversion coefficients from the individual camera-collimator condition to the mathematically calculated reference HMR ranged from 0.55 to 0.75 for LE groups and from 0.83 to 0.95 for ME groups. The conversion coefficient of 0.88 was used to unify HMRs from all acquisition conditions. Using the standardized HMR, clinical studies (n = 52) showed good agreement between LE and ME types regarding three risk groups (κ = 0.83, P < .0001, complete agreement in 90%, 42% of the patients reclassified into the same risk group). ConclusionBy using the reference HMR and conversion coefficients for the system, HMRs with various conditions can be converted to the standard HMRs in a range of normal to low HMRs.