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Remote Sensing Technology and Application  2022, Vol. 37 Issue (6): 1339-1349    DOI: 10.11873/j.issn.1004-0323.2022.6.1339
Evaluation of Passive Microwave Snow-Depth Retrieval Algorithm in Selin Co and Nam Co
Junfei Wu1(),Tandong Yao1,2(),Yufeng Dai2,Wenfeng Chen2
1.College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China
2.Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China
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The passive microwave snow-depth retrieval algorithm is an important method to obtain the surface snow depth information of the Tibetan Plateau on a large scale. In order to evaluate the applicability of the current passive microwave snow-depth retrieval algorithms in the Selin Co and Nam Co regions of the Tibetan Plateau, AMSR2 brightness temperature data and snow depth data of ground stations are used, while R, Bias and RMSE are used as evaluation indicators. Five algorithms including Chang2 algorithm, Che algorithm, SPD algorithm, AMSR2 algorithm and Jiang algorithm are chosen. The results show that the Jiang algorithm has the best overall performance, with the highest R value of 0.68 at Nam Co station. The Che algorithm has a good retrieval effect on shallow snow, and its Bias at Bangor Station is -0.66 cm. The Chang2 algorithm performed well for the deep snow of Nam Co station and Selin Co station, with R values of 0.63 and 0.50 in the two places respectively. The retrieval effect of SPD algorithm is the most unsatisfactory, and the snow depth is overestimated obviously, among which shallow snow is overestimated by nearly 20 cm. The performance of AMSR2 algorithm differs greatly between regions, and the retrieved results at Namco Station are better than those at Selin Co Station and Bangor Station. Except for the SPD algorithm, all other algorithms underestimate snow depth in the study area, which is consistent with previous research results.

Key words:  Nam Co      Selin Co      Passive microwave      Snow depth retrieval      AMSR2     
Received:  10 May 2021      Published:  15 February 2023
ZTFLH:  TP426.635  
Corresponding Authors:  Tandong Yao     E-mail:;
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Junfei Wu
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Yufeng Dai
Wenfeng Chen

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Junfei Wu,Tandong Yao,Yufeng Dai,Wenfeng Chen. Evaluation of Passive Microwave Snow-Depth Retrieval Algorithm in Selin Co and Nam Co. Remote Sensing Technology and Application, 2022, 37(6): 1339-1349.

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Chang1算法SD = 1.59×(Tb18H-Tb37H )
Chang 2算法SD = 2.0(Tb18H- Tb37H ) -8
Foster算法SD = 0.78×(Tb18H-Tb37H )/(1-f)

SPD = (Tb18V-Tb37V ) + (Tb18V-Tb18H )

SD = 0.68×SPD + 0.67

Cao算法SD = 1.59×(Tb18H-Tb37H ) – 8
Che算法SD = 0.66× (Tb19H-Tb37H ) + b

SD = ffarmland × SD farmland + fgrass × SD grass +

fbaresoil × SD baresoil + fforest × SD forest

ASMR2算法SD = f(SD f ) + (1-f)*(SD0)
Table 1  Retrieval algorithms description
Fig.1  Spatial distribution of snow depth observation stations in the study area
Fig. 2  Theoretical description of SR50A
中心频率/ GHz极化波束宽度/MHz灵敏度/K



6.93V, H3500.335×62
7.3V, H3500.335×62
10.65V, H1000.624×42
18.7V, H2000.614×22
23.8V, H4000.615×26
36.5V, H10000.67×12
89.0V, H30001.13×5
Table 2  Instrument information of AMSR2
Table 3  Land cover of instantaneous field of view
Fig.3  Retrieved and observed snow depth
Fig.4  Scatter plot of retrieved and observed snow depth in study area. The dashed line represents the 1∶1 line
Table 4  Evaluation of retrieval algorithms in Dangxiong station
Chang2算法0.63 **16.25-12.84
Table 5  Evaluation of retrieval algorithms in Nam Co station
Table 6  Evaluation of retrieval algorithms in Bangor station
Table 7  Evaluation of retrieval algorithms in Selin Co station
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