Dr. Yuan Li Profile

Dr. Yuan Li

at National Satellite Meteorological Ctr

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Publications (6)

Proceedings Article | 5 November 2020 Paper

Research on prediction algorithm of solar activity base on MgII index for FY-3/OMS

Guo-chao Pei, Yuan Li, Ting-zhu Bai, Li-hui Chen

Proceedings Volume 11566, 115660B (2020) https://doi.org/10.1117/12.2575958

KEYWORDS: Calibration, Satellites, Spectroscopy, Spectral calibration, Climatology, Solar processes

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Proceedings Article | 18 December 2019 Paper

Modeling and seasonal analysis of ozone content in field automatic calibration

Yanqiu Li, Yuan Li, Tingzhu Bai

Proceedings Volume 11341, 113410F (2019) https://doi.org/10.1117/12.2541625

KEYWORDS: Data modeling, Calibration, Satellites, Remote sensing, Humidity, Meteorology, Ozone, Atmospheric modeling, Visibility

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Proceedings Article | 9 September 2019 Presentation + Paper

Solar reflection band site automatic calibration by the Dunhuang site automatic observation radiometric calibration operational system

Yuan Li, Zhiguo Rong, Yanqiu Li, Yong Zhang, Xiutian Ba, Yanna Zhang, Lin Chen, Lijun Zhang, Wei Wei, Ling Sun

Proceedings Volume 11127, 111271M (2019) https://doi.org/10.1117/12.2528375

KEYWORDS: Reflection, Calibration, Satellites, Remote sensing, Reflectivity, Satellite navigation systems, Meteorological satellites, Bidirectional reflectance transmission function, Algorithm development, Environmental sensing

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Proceedings Article | 26 November 2014 Paper

FY-3C/MERSI pre-launch calibration for reflective solar bands

Lin Chen, Na Xu, Yuan Li, Ronghua Wu, Xiuqing Hu, Peng Zhang

Proceedings Volume 9264, 92640Z (2014) https://doi.org/10.1117/12.2070397

KEYWORDS: Optical sensors, Sun, Sensors, Calibration, Satellites, Spectrometers, Reflectivity, Satellite imaging, Meteorological satellites, Radiometry

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Medium Resolution Spectral Imager (MERSI) is the key imaging sensor on board Fengyun-3 (FY-3), the second generation polar-orbiting meteorological satellites in China, currently operating on both FY-3A, FY-3B and FY-3C satellites. It has 20 spectral bands, including 19 reflective solar bands (RSBs) with center wavelengths from 0.41μm to 2.1μm and 1 thermal emissive band (TEB) with center wavelength 12μm, making observations at two spatial resolutions: 250 m (bands 1-5) and 1km (bands 6-20). The FY-3C has been launched in 23, Sept., 2013. The MERSI doesn't carry on-board calibration standards. To obtain RSBs radiometric responses, pre-launched field radiometric calibration test which is called Solar Radiation Based Calibration(SRBC) was taken in Dali in 27, Feb. to 2, Mar., 2013. For the SRBC measurement which the sun was the source of irradiance, MERSI viewed the reflected solar irradiance from a set of the sixteen reference spectral on panels with different reflective level. The uniformity, reflectivity and BRDF (Bidirectional reflection of distribution function) of sixteen reference panels were tested in advance. There are two kinds of calibration coefficient generation methods used in SRBC. One is similar as the Sea-WiFS pre-launch calibration method by Langley calibration. Besides this, we use a portable spectrometers produced by Analytical Spectral Devices inc. (ASD inc.) named FieldSpec 3 to measure the absolutely reflected radiance simultaneously. The calibrated spectrometers measured radiance could be as the reference radiance and the the calibration coefficient of the MERSI can be calculated. We called this method Calibration Based on Reference Instrument(CBRI). The results of these two methods are comparable. The CBRI results are less then 6% difference with Langley calibration method in most channels except water-vapor channels and channel 15. An non-linear feature of the most FY-3C/MERSI detectors was found for the first time. This phenomenon is even more obvious for the water-vapor channels. The second order coefficient determined by pre-launched calibration is quite useful to improve the on-obit calibration accuracy.

Proceedings Article | 19 November 2014 Paper

The comparison of BRDF model and validation of MCD43 products by the 2013 Dunhuang Gobi experiments

Yuan Li, Zhi-guo Rong, Li-jun Zhang, Ling Sun, Na Xu

Proceedings Volume 9264, 926415 (2014) https://doi.org/10.1117/12.2067763

KEYWORDS: Visible radiation, Data modeling, Sensors, Calibration, Satellites, Remote sensing, Reflectivity, Meteorological satellites, Bidirectional reflectance transmission function, Atmospheric modeling

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Proceedings Article | 30 August 2013 Paper

Multi-satellites normalization of the FengYun-2s visible detectors by the MVP method

Yuan Li, Zhi-guo Rong, Li-jun Zhang, Ling Sun, Na Xu

Proceedings Volume 8910, 89100O (2013) https://doi.org/10.1117/12.2032758

KEYWORDS: Visible radiation, Lithium, Sun, Sensors, Calibration, Satellites, Remote sensing, Reflectivity, Meteorological satellites, Bidirectional reflectance transmission function

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After January 13, 2012, FY-2F had successfully launched, the total number of the in orbit operating FengYun-2 geostationary meteorological satellites reached three. For accurate and efficient application of multi-satellite observation data, the study of the multi-satellites normalization of the visible detector was urgent. The method required to be non-rely on the in orbit calibration. So as to validate the calibration results before and after the launch; calculate day updating surface bidirectional reflectance distribution function (BRDF); at the same time track the long-term decay phenomenon of the detector's linearity and responsivity. By research of the typical BRDF model, the normalization method was designed. Which could effectively solute the interference of surface directional reflectance characteristics, non-rely on visible detector in orbit calibration. That was the Median Vertical Plane (MVP) method. The MVP method was based on the symmetry of principal plane, which were the directional reflective properties of the general surface targets. Two geostationary satellites were taken as the endpoint of a segment, targets on the intersecting line of the segment's MVP and the earth surface could be used as a normalization reference target (NRT). Observation on the NRT by two satellites at the moment the sun passing through the MVP brought the same observation zenith, solar zenith, and opposite relative direction angle. At that time, the linear regression coefficients of the satellite output data were the required normalization coefficients. The normalization coefficients between FY-2D, FY-2E and FY-2F were calculated, and the self-test method of the normalized results was designed and realized. The results showed the differences of the responsivity between satellites could up to 10.1%(FY-2E to FY-2F); the differences of the output reflectance calculated by the broadcast calibration look-up table could up to 21.1%(FY-2D to FY-2F); the differences of the output reflectance from FY-2D and FY-2E calculated by the site experiment results reduced to 2.9%(13.6% when using the broadcast table). The normalized relative error was also calculated by the self-test method, which was less than 0.2%.

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