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Remote Sensing for Natural Resources    2021, Vol. 33 Issue (3) : 27-35     DOI: 10.6046/zrzyyg.2020330
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LST reversion and downscaling based on FY-3D/MWRI L1B brightness temperature data
ZHU Yuxin1(), WU Menxin2(), BAO Yansong3, LI Xinchuan1, ZHANG Jinzong1
1. School of Urban and Environmental Sciences, Huaiyin Normal University, Huaian 223300, China
2. National Meteorological Centre, Beijing 100081, China
3. School of Atmospheric Physics,Nanjing University of Information Science & Technology, Nanjing 210044, China
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Abstract  

Based on FY-3C VIRR LST and FY-3D/MWRI L1B brightness temperature data of February 1, 2020 and taking the area with geographical coordinates of 18°~54°N, 73°~135°E as an example, the LST reversion and downscaling based on the FY-3D/MWRI L1B data were studied using a statistical regression model and a hierarchical Bayesian fusion model. As a result, two models were constructed, namely a LST binary linear regression inversion model based on FY-3D single-channel horizontal and vertical polarization-corrected brightness temperature data and a hierarchical Bayesian fusion downscaling model based on FY-3D retrieved LST and FY-3C VIRR LST. They were verified with the LST on the day of MYD11A1 as reference data, obtaining the following results. As for the reversion statistical model, the mean bias, error standard deviation, and root mean square error were -1.28 K, 8.85 K, and 8.85 K, respectively for the FY-3D descending data and were -0.81 K, 6.74 K, and 6.78 K, respectively for the FY-3D ascending data. As for the hierarchical Bayesian fusion downscaling model, the mean bias, error standard deviation, and root mean square error were 0.50 K, 5.45 K, and 5.41 K, respectively for the FY-3D descending data and were 0.25 K, 5.54 K, and 5.54 K, respectively for the FY-3D ascending data. This study will provide a novel idea for the LST inversion and downscaling of passive microwaves.

Keywords FY-3D MWRI      VIRR LST      hierarchical Bayesian      statistical regression      downscaling     
ZTFLH:  TP79  
Corresponding Authors: WU Menxin     E-mail: zhuyuxin_402@163.com;wumx@cma.gov.cn
Issue Date: 24 September 2021
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Yuxin ZHU
Menxin WU
Yansong BAO
Xinchuan LI
Jinzong ZHANG
Cite this article:   
Yuxin ZHU,Menxin WU,Yansong BAO, et al. LST reversion and downscaling based on FY-3D/MWRI L1B brightness temperature data[J]. Remote Sensing for Natural Resources, 2021, 33(3): 27-35.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2020330     OR     https://www.gtzyyg.com/EN/Y2021/V33/I3/27
Fig.1  Technology roadmap
6060 6070 6080 6090
5050 5060 5070 5080 5090 50A0 50B0
4060 4070 4080 4090 40A0 40B0 40C0
3060 3070 3080 3090 30A0 30B0 30C0 30D0
2070 2080 2090 20A0 20B0 20C0 20D0
1070 1080
Tab.1  Longitude and latitude number and relative position of sample area of FY-3C VIRR LST
h25v03 h26v03
h23v04 h24v04 h25v04 h26v04 h27v04
h23v05 h24v05 h25v05 h26v05 h27v05 h28v05
h25v06 h26v06 h27v06 h28v06 h29v06
h28v07 h29v07
h28v08 h29v08
Tab.2  Tile and relative position of sample area of MYD11A1 LST
Fig.2  Scatter plot of VIRR LST against MODIS LST before bias correction
Fig.3  Scatter plot of VIRR LST against MODIS LST after bias correction
Fig.4  Spatial distribution of bias corrected VIRR LST
波段 1 2 3 4 5 6 7 8 9 10
回归系数 0.325 1 0.150 0 0.580 6 0.393 9 0.734 1 0.592 0 0.815 8 0.727 8 0.797 6 0.782 6
Tab.3  Correlation coefficient between FY-3D MWRI orbit dropping data and FY-3C VIRR LST
波段 1 2 3 4 5 6 7 8 9 10
回归系数 0.583 7 0.333 1 0.734 4 0.497 1 0.813 2 0.632 3 0.830 7 0.721 4 0.802 3 0.779 8
Tab.4  Correlation coefficient between FY-3D MWRI orbit lifting data and FY-3C VIRR LST
降轨 升轨
平均
偏差
误差标
准差
均方根
误差
相关
系数
平均
偏差
误差标
准差
均方根
误差
相关
系数
-1.28 8.85 8.85 0.81 -0.81 6.74 6.78 0.91
Tab.5  Validation results between FY-LST and MYD11A1 LST(K)
Fig.5  Retrieval LST of FY-3D on February 1, 2020
Fig.6  Scatter plot between FY LST and MODIS LST
node mean sd MC error 2.5% median 97.5% start sample
mu1[1,1] 274.8 0.54 0.03 273.9 274.8 275.9 1 001 500
mu1[1,2] 274.6 0.65 0.03 273.3 274.7 276.0 1 001 500
mu1[1,3] 274.6 0.54 0.03 273.5 274.6 275.7 1 001 500
mu1[1,4] 274.7 0.66 0.02 273.2 274.7 276.1 1 001 500
mu1[1,5] 274.7 0.62 0.04 273.3 274.7 276.0 1 001 500
mu1[1,6] 274.7 0.66 0.03 273.5 274.7 276.1 1 001 500
mu1[1,7] 274.7 0.62 0.03 273.5 274.8 276.0 1 001 500
mu1[1,8] 274.7 0.59 0.03 273.5 274.7 275.9 1 001 500
mu1[1,9] 274.2 0.64 0.08 272.7 274.3 275.2 1 001 500
mu1[1,10] 274.3 0.68 0.08 272.7 274.4 275.5 1 001 500
Tab.6  Sample statistics of partial nodes (orbit lifting)
node mean sd MC error 2.5% median 97.5% start sample
mu1[1,1] 273.1 0.52 0.02 272.1 273.1 274.1 1 001 500
mu1[1,2] 273.0 0.52 0.03 272.0 273.0 274.0 1 001 500
mu1[1,3] 273.0 0.54 0.03 271.8 273.0 273.9 1 001 500
mu1[1,4] 273.0 0.51 0.03 271.9 273.0 273.9 1 001 500
mu1[1,5] 273.0 0.51 0.03 271.9 273.0 274.0 1 001 500
mu1[1,6] 273.2 0.54 0.02 272.1 273.1 274.3 1 001 500
mu1[1,7] 273.2 0.50 0.02 272.3 273.2 274.2 1 001 500
mu1[1,8] 273.2 0.51 0.03 272.2 273.2 274.2 1 001 500
mu1[1,9] 273.1 0.50 0.02 272.2 273.1 274.2 1 001 500
mu1[1,10] 273.3 0.55 0.03 272.3 273.3 274.5 1 001 500
Tab.7  Sample statistics of part nodes (orbit dropping)
Fig.7  Spatial distribution of FY-3D MWRI downscaling LST
Fig.8  Scatter plot between FY downscaling LST and MODIS LST
降轨 升轨
平均
偏差
误差标
准差
均方根
误差
相关
系数
平均
偏差
误差标
准差
均方根
误差
相关
系数
0.50 5.45 5.41 0.94 0.25 5.54 5.54 0.94
Tab.8  Validation results between FY downscaling LST and MYD11A1 day LST (K)
Fig.9  Spatial distribution of posterior standard deviation
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