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Remote Sensing Technology and Application  2020, Vol. 35 Issue (1): 153-162    DOI: 10.11873/j.issn.1004-0323.2020.1.0153
    
Validation of Narrow-band Surface Albedo Retrieved from FY-3C MERSI Satellite Data
Chunliang Zhao1,2(),Wenbo Xu3,Jinlong Fan1()
1. National Satellite Meteorological Center, Beijing 100081, China
2. Chinese Academy of Agricultural Sciences, Institute of Agricultural Resources and Regional Planning, Beijing 100081, China
3. University of Electronic Science and Technology of China, School of Resources and Environment, Chengdu 611731, China
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Abstract  

Surface albedo is one of the driving factors in surface radiant energy balance and surface-atmosphere interaction.It is widely used in surface energy balance, medium and long-term weather forecasting and global change research.This study aims to validate the surface albedo retrieved from FY-3C MERSI. This paper selected four regions in Africa and North America as study areas to validate the retrieved albedo from the reflectance data and angle data of FY-3C MERSI at 250 m resolution in 2014. The semi-empirical kernel-driven BRDF(bidirectional reflectance distribution function) model RossThick-LiSparseR and least squares fitting method were used to calculate the parameter of BRDF. Then four narrow-band black-sky albedos and four narrow-band white-sky albedos can be obtained by angle integration. Finally, the cross-validation of FY-3C surface narrow-band albedo products with MODIS albedo products (MCD43A3) was carried out. The results show that theRoot Mean Square Error(RMSE) between the FY-3C narrow-band albedo and the corresponding MODIS narrow-band albedo is in the range of 0.01 ~ 0.04, and the Mean Bias (MBIAS) is 0.09. FY-3C narrow-band albedo has good consistency with the corresponding MODIS narrow-band albedo in the visible and near-infrared bands. So, the methodologyof using the BRDF model to invert the surface albedo of FY-3C medium resolution imaging spectrometer data is feasible and reliable. The further improvement of the inversion accuracy of FY3C-MERSI surface albedo also depends on the improvement of basic data processing quality, including image geometric correction, calibration, and strict data quality control.
Key words:  Surface Albedo      FY-3C      MERSI      MODIS     
Received:  09 October 2018      Published:  01 April 2020
ZTFLH:  TP75  
Corresponding Authors:  Jinlong Fan     E-mail:  zcluestc@163.com;fanjl@cma.gov.cn
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Chunliang Zhao
Wenbo Xu
Jinlong Fan

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Chunliang Zhao,Wenbo Xu,Jinlong Fan. Validation of Narrow-band Surface Albedo Retrieved from FY-3C MERSI Satellite Data. Remote Sensing Technology and Application, 2020, 35(1): 153-162.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2020.1.0153     OR     http://www.rsta.ac.cn/EN/Y2020/V35/I1/153

区域 经度/° 纬度/°
BurkinaFaso Koumbia -6.14，-1.14 8.72，13.72
Ethiopia WestShewa 35.30，40.30 6.60，11.60
Tanzania Rungwe 31.68，36.68 -11.55，-6.55
USA Fresno -122.32，-117.32 34.28，39.28
Table 1  Geographical location of the study area
Fig.2  The reflectance image of FY-3C in the study area(composed of band 3、4、1)
通道序号

中心波长

/μm

光谱带宽

/μm

空间分辨率

/m

噪声等效反射率ρ/%

或噪声等效温差

动态范围

(最大反射率ρ、最大温度K)
1 0.470 0.05 250 0.45 100%
2 0.550 0.05 250 0.40 100%
3 0.650 0.05 250 0.40 100%
4 0.865 0.05 250 0.45 100%
Table 2  The 250 m resolution channel specification of MERSI
Fig.1  The angle data of FY-3C
Fig.3  The Black Sky Albedo(BSA) and White Sky Albedo(WSA) in the study area
Fig.4  The spectral response function of FY-3C and MODIS
地表反照率 研究区 TanzaniaRungwe BurkinaFasoKoumbia USAFresno EthiopiaWestShewa
BSA FY3C_band1-MODIS_band3 0.7381 0.5294 0.8854 0.8709
FY3C_band2-MODIS_band4 0.8394 0.7398 0.9362 0.8732
FY3C_band3-MODIS_band1 0.8909 0.8776 0.9402 0.9092
FY3C_band4-MODIS_band2 0.9320 0.8944 0.8801 0.9004
WSA FY3C_band1-MODIS_band3 0.6271 0.5055 0.8543 0.8388
FY3C_band2-MODIS_band4 0.7460 0.7350 0.8961 0.8295
FY3C_band3-MODIS_band1 0.8345 0.8690 0.8942 0.8770
FY3C_band4-MODIS_band2 0.9074 0.8592 0.7588 0.8682
Table 3  Correlation of verification points in study area
地表反照率 研究区 TanzaniaRungwe BurkinaFasoKoumbia USAFresno EthiopiaWestShewa
BSA FY3C_band1-MODIS_band3 0.081 0.014 0.033 0.055
FY3C_band2-MODIS_band4 0.018 0.007 0.041 0.016
FY3C_band3-MODIS_band1 0.009 0.023 0.032 0.008
FY3C_band4-MODIS_band2 0.005 0.103 0.023 0.018
WSA FY3C_band1-MODIS_band3 0.098 0.080 0.034 0.080
FY3C_band2-MODIS_band4 0.021 0.007 0.038 0.020
FY3C_band3-MODIS_band1 0.011 0.005 0.027 0.011
FY3C_band4-MODIS_band2 0.008 0.029 0.027 0.027
Table 4  RMSE of validation in study areas
地表反照率 研究区 TanzaniaRungwe BurkinaFasoKoumbia USAFresno EthiopiaWestShewa
BSA FY3C_band1-MODIS_band3 0.009 0.006 0.249 0.008
FY3C_band2-MODIS_band4 0.004 0.185 0.249 0.005
FY3C_band3-MODIS_band1 0.005 0.243 0.243 0.025
FY3C_band4-MODIS_band2 0.048 0.245 0.212 0.043
WSA FY3C_band1-MODIS_band3 0.009 0.009 0.247 0.008
FY3C_band2-MODIS_band4 0.004 0.025 0.243 0.005
FY3C_band3-MODIS_band1 0.006 0.097 0.204 0.031
FY3C_band4-MODIS_band2 0.095 0.234 0.134 0.049
Table 5  Bias of validation in study areas
Fig.5  scatter plot of BSA and WSA in Rungwe_Tanzania
Fig.6  scatter plot of BSA and WSA in Koumbia_BurkinaFaso
Fig.7  scatter plot of BSA and WSA in Fresno_USA_MODIS
Fig.8  Scatter plot of BSA and WSA in WestShewa_Ethiopia
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