GF-6 WFV Data Cloud Detection Based on Improved LCCD Algorithm

Yongji Wang; Yanfang Ming; Tianchen Liang; Xueying Zhou; Chen Jia; Quan Wang

doi:10.3788/AOS202040.2128001

Acta Optica Sinica, Volume. 40, Issue 21, 2128001(2020)

GF-6 WFV Data Cloud Detection Based on Improved LCCD Algorithm

Yongji Wang¹, Yanfang Ming^1、*, Tianchen Liang¹, Xueying Zhou², Chen Jia¹, and Quan Wang¹

Author Affiliations

¹College of Geomatics, Shandong University of Science and Technology, Qingdao, Shandong 266590, China

²School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei 430072, China

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Figures & Tables(12)

Fig. 1. Surface reflectance characteristics of non-spatiotemporal series. (a) Water; (b) wetland; (c) bareland; (d) impervious surface

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Fig. 2. Surface reflectance characteristics of spatiotemporal series. (a) Forest; (b) grassland; (c) shrubland

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Fig. 3. Flow chart of cloud detection

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Fig. 4. Cloud detection results above water. (a) Thick cloud; (b) broken cloud; (c) thin cloud

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Fig. 5. Cloud detection results above vegetation. (a) Thick cloud; (b) thin cloud; (c) broken cloud

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Fig. 6. Cloud detection results above bright surfaces. (a) Thin cloud; (b) thick cloud; (c) broken cloud

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Fig. 7. Landsat8 cloud detection results above bright surfaces. (a) Broken cloud; (b) thick cloud; (c) thin cloud

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Fig. 8. Accuracy index for each sample. (a) β_CRT; (b) β_CRC; (c) β_CRS

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Fig. 9. Error rate index of each sample. (a) β_CER; (b) β_OER

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Table 1. Introduction of GF-6 WFV data
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Table 1. Introduction of GF-6 WFV data
Band number Spectral range /μm Spatial resolution /m
B01 0.45-0.52 16
B02 0.52-0.59 16
B03 0.63-0.69 16
B04 0.77-0.89 16
B05 0.69-0.73 16
B06 0.73-0.77 16
B07 0.40-0.45 16
B08 0.59-0.63 16

Table 2. Thresholds of forests, grasslands and shrublands

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Table 2. Thresholds of forests, grasslands and shrublands

Parameter	Forest	Bareland	Tropical	Frigid zone	Temperate zone
Parameter	Forest	Bareland	Tropical	Frigid zone	Spring	Summer	Autumn	Winter
N_s/N_f			0.1/0.9	0.3/0.7	0.6/0.4	0.1/0.9	0.4/0.6	0.9/0.1
T_B	0.12	0.18	0.126	0.138	0.156	0.126	0.144	0.174
T_G	0.18	0.20	0.182	0.186	0.192	0.182	0.188	0.198
T_R	0.13	0.25	0.142	0.166	0.202	0.142	0.178	0.238
Parameter	Grassland	Bareland	Tropical	Frigid zone	Temperate zone
Parameter	Grassland	Bareland	Tropical	Frigid zone	Spring	Summer	Autumn	Winter
N_s/N_g			0.1/0.9	0.7/0.3	0.6/0.4	0.1/0.9	0.4/0.6	0.9/0.1
T_B	0.20	0.18	0.198	0.186	0.188	0.198	0.192	0.182
T_G	0.23	0.20	0.227	0.209	0.212	0.227	0.218	0.203
T_R	0.30	0.25	0.295	0.265	0.270	0.295	0.280	0.255
Parameter	Shrubland	Bareland	Tropical	Frigid zone	Temperate zone
Parameter	Shrubland	Bareland	Tropical	Frigid zone	Spring	Summer	Autumn	Winter
N_s/N_b			0.1/0.9	0.4/0.6	0.6/0.4	0.1/0.9	0.4/0.6	0.9/0.1
T_B	0.16	0.18	0.162	0.168	0.172	0.162	0.168	0.178
T_G	0.18	0.20	0.182	0.188	0.192	0.182	0.188	0.198

Table 3. Overall accuracy evaluation of cloud detection
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Table 3. Overall accuracy evaluation of cloud detection
Accuracy Vegetation Water Bright surface Average
β_CRT /% 96.36 96.43 94.01 95.60
β_CRC /% 93.09 95.60 88.70 92.46
β_CRS /% 97.38 96.35 96.67 96.80
β_CER /% 2.59 3.46 2.72 2.92
β_OER /% 6.91 3.77 10.79 7.16

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Yongji Wang, Yanfang Ming, Tianchen Liang, Xueying Zhou, Chen Jia, Quan Wang. GF-6 WFV Data Cloud Detection Based on Improved LCCD Algorithm[J]. Acta Optica Sinica, 2020, 40(21): 2128001

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