Research on emissivity directionality of radiometric calibration sites for optical sensors

Jia-Xin LIU; Zhi-Wei YANG; Cai-Xia GAO; Hui-Ya MA; En-Yu ZHAO; Si-Bo DUAN

doi:10.11972/j.issn.1001-9014.2023.05.014

Journals >Journal of Infrared and Millimeter Waves >Volume 42 >Issue 5 >Page 687 > Article

Journal of Infrared and Millimeter Waves
Vol. 42, Issue 5, 687 (2023)

Research on emissivity directionality of radiometric calibration sites for optical sensors

Jia-Xin LIU^1、3, Zhi-Wei YANG², Cai-Xia GAO^1、*, Hui-Ya MA^1、3, En-Yu ZHAO⁴, and Si-Bo DUAN⁵

Author Affiliations

¹National Engineering Laboratory for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

²Xinjiang Transportation Planning Survey and Design Institute，Urumqi 830006，China

³University of Chinese Academy of Science，Beijing 100049，China

⁴College of Information Science and Technology，Dalian Maritime University，Dalian 116026，Liaoning，China

⁵Key Laboratory of Agri-informatics，Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning，Chinese Academy of Agricultural Sciences，Beijing 100081，China

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DOI: 10.11972/j.issn.1001-9014.2023.05.014 Cite this Article

Jia-Xin LIU, Zhi-Wei YANG, Cai-Xia GAO, Hui-Ya MA, En-Yu ZHAO, Si-Bo DUAN. Research on emissivity directionality of radiometric calibration sites for optical sensors[J]. Journal of Infrared and Millimeter Waves, 2023, 42(5): 687 Copy Citation Text

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Fig. 1. MODIS images over Algeria3, Algeria5, Libya1, Mauritania1 and Mauritania2 areas (study area is shown in red square)

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Fig. 2. Spectrum function of MODIS/29/31/32 and SEVIRI 7/9/10 channels

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Fig. 3. ECMWF /ERA5 atmospheric profile data over Algeria3_1 km

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Fig. 4. Technical flow chart

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Fig. 5. Multi-source sensor method/MYD21 directional emissivity results and comparison

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Fig. 6. Uncertainty tree of emissivity directional model

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Fig. 7. Model uncertainty caused by initial emissivity value

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Fig. 8. Model uncertainty caused by atmospheric temperature and humidity profiles

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Fig. 9. Model uncertainty caused by MODIS sensor calibration

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Fig. 10. Uncertainty caused by SEVIRI sensor calibration

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Fig. 11. Uncertainty caused by radiative transfer model

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Fig. 12. Total uncertainty of radiance directional model at each viewing zenith angle

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场地名称	经度/°	纬度/°	区域面积/Km²
Algeria3_1km	7.74	30.37	75×75
Algeria5_1km	2.13	31.37	75×75
Libya1_1km	13.35	24.12	50×50
Mauritania1_1km	-9.20	19.60	50×50
Mauritania2_1km	-8.63	20.70	75×75

Table 1. Geographic information of the regions of interest

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载荷	波段序号	中心波长/μm	光谱范围/μm	信噪比/NE∆T
MODIS	29	8.55	8.4~8.7	0.05 K
	30	9.73	9.58~9.88	0.25 K
	31	11.03	10.78~11.28	0.05 K
	32	12.02	11.77~12.27	0.05 K
	33	13.335	13.185~13.485	0.25 K
	34	13.635	13.485~13.785	0.25 K
	35	13.935	13.785~14.085	0.25 K
	36	14.235	14.085~14.385	0.35 K
SEVIRI	6	6.25	5.35~7.15	0.75 K
	7	8.7	8.3~9.1	0.28 K
	8	9.66	9.38~9.94	1.5 K
	9	10.8	9.8~11.8	0.25 K
	10	12	11~13	0.37 K
	11	13.4	12.4~14.4	1.80 K

Table 2. AQUA/MODIS and MSG-2/SEVIRI thermal infrared bands parameters

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观测天顶角	0°~10°	10°~20°	20°~30°	30°~40°	40°~50°	50°~60°	60°~65°
Algeira3_1km	1 294	1 382	845	1 617	2 364	2 695	2 695
Algeira5_1km	1 286	1 450	686	2 940	2 342	2 940	2 574
Libya1_1km	1 372	837	833	1 519	2 058	1 323	2 842
Mauritania1_1km	637	476	927	827	1 323	1 862	1 519
Mauritania2_1km	637	619	670	815	1 315	1 503	1 911

Table 3. Number of samples under different viewing zenith angle intervals in each study area

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目标区域	波段	经验性模型	RMSE
Algeria3_1 km	29	$ε (θ) = 0.000 61 θ - 2.758 e - 05 θ^{2} + 0.765 7$	0.002 3
	31	$ε (θ) = 8.857 e - 05 θ - 9.889 e - 06 θ^{2} + 0.957 7$	0.001 7
	32	$ε (θ) = 0.00055 θ - 1.705 e - 05 θ^{2} + 0.973$	0.000 3
Algeria5_1 km	29	$ε (θ) = 0.710 2 + 0.032 17 \times c o s (w θ) + 0.016 26 \times s i n (w θ) (w = 0.043 25)$	0.003 4
	31	$ε (θ) = 0.815 9 + 0.136 2 \times c o s (w θ) - 0.010 05 \times s i n (w θ) (w = 0.009 1)$	0.001 9
	32	$ε (θ) = 0.966 + 0.007 8 \times c o s (w θ) + 0.002 4 \times s i n (w θ) (w = 0.048 17)$	0.001 1
Libya1_1 km	29	$ε (θ) = 0.001 1 θ - 3.194 e - 05 θ^{2} + 0.722 3$	0.003 4
	31	$ε (θ) = 0.000 95 θ - 2.771 e - 05 θ^{2} + 0.961 7$	0.003
	32	$ε (θ) = 0.943 3 + 0.027 0 \times c o s (w θ) + 0.025 48 \times s i n (w θ) (w = 0.034 2)$	0.003
Mauritania1_1 km	29	$ε (θ) = 0.000 29 θ - 2.721 e - 05 θ^{2} + 0.771 4$	0.002 9
	31	$ε (θ) = 0.000 21 θ - 1.293 e - 05 θ^{2} + 0.954 3$	0.000 8
	32	$ε (θ) = 0.944 1 + 0.035 7 \times c o s (w θ) + 0.011 8 \times s i n (w θ) (w = 0.031 05)$	0.000 7
Mauritania2_1 km	29	$ε (θ) = 0.001 14 θ - 4.677 e - 05 θ^{2} + 0.767 2$	0.007 1
	31	$ε (θ) = 0.000 66 θ - 2.262 e - 05 θ^{2} + 0.951 7$	0.003 4
	32	$ε (θ) = 0.000 28 θ - 1.397 e - 05 θ^{2} + 0.976 2$	0.001 5