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Remote Sensing for Land & Resources    2021, Vol. 33 Issue (1) : 145-151     DOI: 10.6046/gtzyyg.2020102
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The evaluation of FY-3C snow products in the Tibetan Plateau
MIN Wenbin1(), PEN Jun1, Li Shiying2
1. Institute of Plateau Meteorology, CMA /Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Chengdu 610071, China
2. Sichuan Meteorological Sounding Data Center, Chengdu 610071, China
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Abstract  

In order to understand the regional reliability of the Fengyun-3C(FY-3C) satellite snow products, the authors used the snow cover data of 118 meteorological stations in the Tibetan Plateau from October 1, 2018 to April 30, 2019 to evaluate the snow cover (MULSS_SNC) and snow water equivalent (MWRIX_SWE) products. The results show that, for snow cover pixels of MULSS_SNC and MWRIX_SWE, the accuracy rate is 87.18% and 72.32% respectively, the recall rate is 66.67% and 49.63% respectively, the false rate is 12.81% and 27.68% respectively, and the missing rate is 33.33% and 50.37% respectively. In terms of mixed pixels or pixels with snow depth less than 0.5 cm, both MULSS_SNC and MWRIX_SWE tend to identify with no snow, and the missing rate of snow depth less than 1cm is up to 60%. When the snow depth of MULSS_SNC is more than 2cm, the recall rate can reach 89.09%. However, for MWRIX_SWE, only when the snow depth is more than 5cm can the snow recall rate reach 63.37%. The snow depth in the Tibetan Plateau from MWRIX_SWE has a large error with ground observations, and there is no linear positive correlation, so it is not recommended to use it directly.

Keywords MULSS_SNC      MWRIX_SWE      evaluation      Tibetan Plateau     
ZTFLH:  TP79  
Issue Date: 18 March 2021
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Wenbin MIN
Jun PEN
Shiying Li
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Wenbin MIN,Jun PEN,Shiying Li. The evaluation of FY-3C snow products in the Tibetan Plateau[J]. Remote Sensing for Land & Resources, 2021, 33(1): 145-151.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020102     OR     https://www.gtzyyg.com/EN/Y2021/V33/I1/145
Fig.1  Distribution of snow observation stations in Qinghai-Tibet Plateau
地面观测样本数/个 MULSS_SNC像元数 /个
积雪 陆地 云及其他 参与评估
积雪 3 147 864 432 1851 1 296
陆地 1 548 127 847 574 974
部分积雪 20 321 353 13 091 6 877 13 444
合计 25 016 1 344 14 370 9 302 15 714
Tab.1  The identification results of MULSS_SNC
地面观测样本数/个 MWRIX_SWE像元数/个
积雪 陆地 缺数据 参与评估
积雪 3 147 998 1 013 1 136 2 011
陆地 1 548 382 613 553 995
部分积雪 20 321 2 705 10 184 7 432 12 889
合计 25 016 4 085 11 810 9 121 15 895
Tab.2  The identification results of MWRIX_SWE
积雪深度/cm [0.5,1] (1,2] (2,3] (3,4] (4,5] (5,6] (6,8] (8,10] >10 >2 合计
MULSS_SNC判识结果
地面积雪像元数/个 460 185 118 103 69 50 77 48 186 651 1 296
判识正确像元数/个 168 116 99 83 61 44 71 41 181 580 864
召回率/% 36.52 62.70 83.90 80.58 88.41 88.00 92.21 85.42 97.31 89.09 66.67
漏判像元数/个 292 69 19 20 8 6 6 7 5 71 432
漏判率/% 63.48 37.30 16.10 19.42 11.59 12.00 7.79 14.58 2.69 10.91 33.33
漏判百分比/% 67.59 15.97 4.40 4.63 1.85 1.39 1.39 1.62 1.16 16.44 100
MWRIX_SWE反演结果
地面积雪像元数/个 723 286 214 154 119 67 110 72 266 1 002 2 011
判识正确像元数/个 238 125 101 85 75 48 85 49 192 635 998
SWE召回率/% 32.92 43.71 47.20 55.19 63.03 71.64 77.27 68.06 72.18 63.37 49.63
SWE漏判像元数/个 485 161 113 69 44 19 25 23 74 367 1 013
SWE漏判率/% 67.08 56.29 52.80 44.81 36.97 28.36 22.73 31.94 27.82 36.63 50.37
SWE漏判百分比/% 47.88 15.89 11.15 6.81 4.34 1.88 2.47 2.27 7.31 36.23 100
Tab.3  The evaluation results of FY3C snow cover products with different snow depth
地面观测样本数/个 合成产品像元数/个
积雪 陆地 MWRIX
无数据
参与评估
积雪 3 147 1 419 887 841 2 306
陆地 1 548 289 751 508 1 040
部分积雪 20 321 1 332 11 694 7 295 13 026
合计 25 016 3 040 13 332 8 644 16 372
Tab.4  The identification results of synthetic products of MULSS_SNC and MWRIX_SWE
Fig.2  The missing rate of FY3C snow cover products with different snow depth
Fig.3  The scatter map of snow depth from ground observation and MWRIX_SWE
Fig.4  The scatter map of snow depth from ground observation and satellite inversion below 60cm
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