Radiometric Calibration Accuracy of GOES Sounder Infrared Channels

2013 ◽  
Vol 51 (3) ◽  
pp. 1187-1199 ◽  
Author(s):  
Fangfang Yu ◽  
Xiangqian Wu
2019 ◽  
Vol 11 (6) ◽  
pp. 707 ◽  
Author(s):  
Qiyue Liu ◽  
Tao Yu ◽  
Hailiang Gao

On-orbit radiometric calibration of a space-borne sensor is of great importance for quantitative remote sensing applications. Cross-calibration is a common method with high calibration accuracy, and the core and emphasis of this method is to select the appropriate reference satellite sensor. As for the cross-calibration of high-spatial resolution and narrow-swath sensor, however, there are some scientific issues, such as large observation angles of reference image, and non-synchronization (or quasi-synchronization) between the imaging date of reference image and the date of sensor to be calibrated, which affects the accuracy of cross-calibration to a certain degree. Therefore, taking the GaoFen-1 (GF-1) Panchromatic and Multi-Spectral (PMS) sensor as an example in this research, an innovative radiometric cross-calibration method is proposed to overcome this bottleneck. Firstly, according a set of criteria, valid MODIS (Moderate Resolution Imagine Spectroradiometer) images of sunny day in one year over the Dunhuang radiometric calibration site in China are extracted, and a new and distinctive bidirectional reflectance distribution function (BRDF) model based on top-of-atmosphere (TOA) reflectance and imaging angles of the sunny day MODIS images is constructed. Subsequently, the cross-calibration of PMS sensor at Dunhuang and Golmud radiation calibration test sites is carried out by using the method presented in this paper, taking the MODIS image with large solar and observation angles and Landsat 8 Operational Land Imager (OLI) with different dates from PMS as reference. The validation results of the calibration coefficients indicate that our proposed method can acquire high calibration accuracy, and the total calibration uncertainties of PMS using MODIS as reference sensor are less than 6%.


2008 ◽  
Author(s):  
Thomas S. Pagano ◽  
Hartmut H. Aumann ◽  
Rudolf Schindler ◽  
Denis Elliott ◽  
Steve Broberg ◽  
...  

2021 ◽  
Vol 15 (04) ◽  
Author(s):  
Fangfang Yu ◽  
Xiangqian Wu ◽  
Hyelim Yoo ◽  
Haifeng Qian ◽  
Xi Shao ◽  
...  

2008 ◽  
Author(s):  
Ryoichi Imasu ◽  
Naoko Saitoh ◽  
Yosuke Niwa ◽  
Hiroshi Suto ◽  
Akihiko Kuze ◽  
...  

2021 ◽  
Vol 217 (2) ◽  
Author(s):  
Alexander G. Hayes ◽  
P. Corlies ◽  
C. Tate ◽  
M. Barrington ◽  
J. F. Bell ◽  
...  

AbstractThe NASA Perseverance rover Mast Camera Zoom (Mastcam-Z) system is a pair of zoomable, focusable, multi-spectral, and color charge-coupled device (CCD) cameras mounted on top of a 1.7 m Remote Sensing Mast, along with associated electronics and two calibration targets. The cameras contain identical optical assemblies that can range in focal length from 26 mm ($25.5^{\circ }\, \times 19.1^{\circ }\ \mathrm{FOV}$ 25.5 ∘ × 19.1 ∘ FOV ) to 110 mm ($6.2^{\circ } \, \times 4.2^{\circ }\ \mathrm{FOV}$ 6.2 ∘ × 4.2 ∘ FOV ) and will acquire data at pixel scales of 148-540 μm at a range of 2 m and 7.4-27 cm at 1 km. The cameras are mounted on the rover’s mast with a stereo baseline of $24.3\pm 0.1$ 24.3 ± 0.1  cm and a toe-in angle of $1.17\pm 0.03^{\circ }$ 1.17 ± 0.03 ∘ (per camera). Each camera uses a Kodak KAI-2020 CCD with $1600\times 1200$ 1600 × 1200 active pixels and an 8 position filter wheel that contains an IR-cutoff filter for color imaging through the detectors’ Bayer-pattern filters, a neutral density (ND) solar filter for imaging the sun, and 6 narrow-band geology filters (16 total filters). An associated Digital Electronics Assembly provides command data interfaces to the rover, 11-to-8 bit companding, and JPEG compression capabilities. Herein, we describe pre-flight calibration of the Mastcam-Z instrument and characterize its radiometric and geometric behavior. Between April 26$^{th}$ t h and May 9$^{th}$ t h , 2019, ∼45,000 images were acquired during stand-alone calibration at Malin Space Science Systems (MSSS) in San Diego, CA. Additional data were acquired during Assembly Test and Launch Operations (ATLO) at the Jet Propulsion Laboratory and Kennedy Space Center. Results of the radiometric calibration validate a 5% absolute radiometric accuracy when using camera state parameters investigated during testing. When observing using camera state parameters not interrogated during calibration (e.g., non-canonical zoom positions), we conservatively estimate the absolute uncertainty to be $<10\%$ < 10 % . Image quality, measured via the amplitude of the Modulation Transfer Function (MTF) at Nyquist sampling (0.35 line pairs per pixel), shows $\mathrm{MTF}_{\mathit{Nyquist}}=0.26-0.50$ MTF Nyquist = 0.26 − 0.50 across all zoom, focus, and filter positions, exceeding the $>0.2$ > 0.2 design requirement. We discuss lessons learned from calibration and suggest tactical strategies that will optimize the quality of science data acquired during operation at Mars. While most results matched expectations, some surprises were discovered, such as a strong wavelength and temperature dependence on the radiometric coefficients and a scene-dependent dynamic component to the zero-exposure bias frames. Calibration results and derived accuracies were validated using a Geoboard target consisting of well-characterized geologic samples.


2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 139
Author(s):  
Shengli Chen ◽  
Xiaobing Zheng ◽  
Xin Li ◽  
Wei Wei ◽  
Shenda Du ◽  
...  

To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried out in August 2018. The lake surface and atmospheric parameters were mainly measured by advanced observation instruments, and the MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4.0) was used to simulate the multiple scattering radiance value at the altitude of the sensor. The results showed that the relative deviations between bands 9 and 12 are within 5.0%, while the relative deviations of bands 8, and 13 are 17.1%, and 12.0%, respectively. The precision of the calibration method was verified by calibrating the Aqua/Moderate-resolution Imaging Spectroradiometer (MODIS) and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer (VIIRS), and the deviation of the calibration results was evaluated with the results of the Dunhuang RCS calibration and lunar calibration. The results showed that the relative deviations of NPP/VIIRS were within 7.0%, and the relative deviations of Aqua/MODIS were within 4.1% from 400 nm to 600 nm. The comparisons of three on-orbit calibration methods indicated that band 8 exhibited a large attenuation after launch and the calibration results had good consistency at the other bands except for band 13. The uncertainty value of the whole calibration system was approximately 6.3%, and the uncertainty brought by the field surface measurement reached 5.4%, which might be the main reason for the relatively large deviation of band 13. This study verifies the feasibility of the vicarious calibration method at the Lake Qinghai RCS and provides the basis and reference for the subsequent on-orbit calibration of FY-3D/MERSI-II.


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