Cloud detection algorithm over Ice-Snow Based on Polarization Sensor of Gaofen-5(02) Satellite

Ying Fang; Xiaobing Sun; Rufang Ti; Honglian Huang; Xiao Liu; Yuyao Wang

doi:10.3788/AOS230494

Acta Optica Sinica, Volume. 43, Issue 24, 2428004(2023)

Cloud detection algorithm over Ice-Snow Based on Polarization Sensor of Gaofen-5(02) Satellite

Ying Fang^1,2, Xiaobing Sun^1,3、*, Rufang Ti¹, Honglian Huang^1,3, Xiao Liu^1,3, and Yuyao Wang^1,2

¹Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Heifei Institutes of Pysical Science, Chinese Academy of Sciences, Hefei 230031, Anhui , China

²University of Science and Technology of China, Hefei 230026, Anhui , China

³Hefei Chief Expert Studio of Agricultural Industry, Hefei 230012, Anhui , China

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Figures & Tables(15)

Fig. 1. Reflection characteristics of DPC for cloudy pixels in different wavelengths. (a) 1-8 angles; (b) 9-17 angles

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Fig. 2. Relationship between proportional coefficient X and $m P^{2}$ of 6S radiative transfer fitting

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Fig. 3. Statistical results of apparent pressure

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Fig. 4. Variation of 865 nm polarization reflectance with scattering angle. (a) Water cloud; (b) ice-snow; (c) ice cloud

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Fig. 5. Statistics of 865 nm polarized reflectance based on DPC data

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Fig. 6. Variation of reflectivities of cirrus cloud and ice-snow with wavelength based on POSP data

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Fig. 7. Variation of reflectivities of ice cloud, water cloud, and ice-snow with wavelength based on POSP data

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Fig. 8. Flow chart of cloud detection algorithm over ice-snow

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Fig. 9. Reliability verification of cloud detection algorithm in Greenland region on February 19, 2022. (a) True color picture of DPC; (b) DPC/POSP detection results; (c) MODIS detection results

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Fig. 10. Reliability verification of cloud detection algorithm in Antarctic region on November 15, 2021. (a) True color picture of DPC; (b) DPC/POSP detection results; (c) MODIS detection results

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Table 1. Band parameters of DPC and POSP

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Table 1. Band parameters of DPC and POSP

Band	DPC		POSP		Main application	Article application
Band	Central wavelength /nm	Polarization I/Q/U	Central band /nm	Polarization I/Q/U	Main application	Article application
Ultraviolet band	—	—	380	Y	Absorbent aerosol
Visible and near-infrared band	—	—	410	Y	Absorbent aerosol
	443	N	443	Y	Aerosol optical depth
	490	Y	490	Y	Aerosol，surface albedo，and cloud reflectance
	565	N	—	—	Surface albedo
	670	Y	670	Y	Aerosol properties	NDSI and cloud
	763	N	—	—	Cloud and aerosol layer height	Cloud and apparent pressure
	765	N	—	—	Cloud and aerosol layer height	Cloud and apparent pressure
	865	Y	865	Y	Aerosol and cloud	Water cloud
	910	N	—	—	Water vapor
Shortwave infrared band	—	—	1380	Y	Cirrus cloud	Cirrus cloud
	—	—	1610	Y	Dust aerosol	NDSI and cloud
	—	—	2250	Y	Surface-atmosphere decoupling	Cloud

Table 2. Characteristic bands and main application fields of MODIS cloud detection

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Table 2. Characteristic bands and main application fields of MODIS cloud detection

Band number	Spectral range /nm	Signal-to-noise ratio	Central wavelength /nm	Resolution /m	Main application
1	620-670	128	645	250	Land/Cloud boundary
2	841-876	201	858.5	250
4	545-565	228	555	500
6	1628-1652	275	1640	500	Cloud/Snow and vegetation cover
20	3660-3840	0.05	3750	1000	Surface/Cloud temperature
21	3929-3989	2.00	3959	1000
22	3929-3989	0.07	3959	1000
23	4020-4080	0.07	4060	1000
26	1360-1390	150	1375	1000	Cirrus cloud and water vapor
31	10780-11280	0.05	110300	1000	Surface/Cloud temperature
32	11770-12270	0.05	120200	1000	Surface/Cloud temperature
33	13185-13485	0.25	133350	1000	Cloud top height
35	13785-14085	0.25	139350	1000
36	14085-14385	0.35	142350	1000

Table 3. Fitting related parameters of Eqs. (3) and (4)
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Table 3. Fitting related parameters of Eqs. (3) and (4)
Parameter Value
$P_{0}$ 1013.25
A 151.44038
B $-$ 456.49618
C 461.90846
D $-$ 156.97163

Table 4. Monthly average statistical results of parameters in study area

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Table 4. Monthly average statistical results of parameters in study area

	Greenland		Antarctic
Month	$R_{1380}$	NDSI	$R_{1380}$	NDSI
11	0.02944	0.49304	0.11060	0.54372
12	0.09366	0.57571	0.08932	0.59624
01	0.03887	0.73313	0.07490	0.49718
02	0.08560	0.53212	0.09882	0.51374
03	0.06825	0.46872	—	—
04	0.01138	0.46165	—	—
05	0.01147	0.48687	—	—
06	0.09810	0.42454	—	—
07	0.04122	0.55549	—	—
08	0.09939	0.42723	—	—

Table 5. Comparison of reflectivity parameters of cloud and snow in Greenland
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Table 5. Comparison of reflectivity parameters of cloud and snow in Greenland
Category Minimum Maximum Average Standard deviation
$R_{1380}$ Snow 0.05009 0.12897 0.08333 0.02362
Cloud 0.33228 0.36951 0.33228 0.01363
NDSI Snow 0.53700 0.62265 0.57469 0.02351
Cloud 0.33972 0.35694 0.34795 0.00501

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Ying Fang, Xiaobing Sun, Rufang Ti, Honglian Huang, Xiao Liu, Yuyao Wang. Cloud detection algorithm over Ice-Snow Based on Polarization Sensor of Gaofen-5(02) Satellite[J]. Acta Optica Sinica, 2023, 43(24): 2428004

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