TY - JOUR
T1 - Determining switching threshold for NIR-SWIR combined atmospheric correction algorithm of ocean color remote sensing
AU - Liu, Huizeng
AU - ZHOU, Qiming
AU - Li, Qingquan
AU - Hu, Shuibo
AU - Shi, Tiezhu
AU - Wu, Guofeng
N1 - Funding Information:
This study was supported by the National Key R&D Program of China (No. 2017YFC0506200 ), Natural Science Foundation of China (No. 41471340 ), Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20151117105543692 ), and Shenzhen Future Industry Development Funding Program (No. 201507211219247860 ). We thank NASA OBPG for providing MODIS products, and thank NASA GSFC and Principal investigators of AERONET-OC stations for providing AERONET data. We are grateful to the two anonymous reviewers for their helpful comments and constructive suggestions.
Funding Information:
This study was supported by the National Key R&D Program of China (No. 2017YFC0506200), Natural Science Foundation of China (No. 41471340), Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20151117105543692), and Shenzhen Future Industry Development Funding Program (No. 201507211219247860). We thank NASA OBPG for providing MODIS products, and thank NASA GSFC and Principal investigators of AERONET-OC stations for providing AERONET data. We are grateful to the two anonymous reviewers for their helpful comments and constructive suggestions.
PY - 2019/7
Y1 - 2019/7
N2 - Accurate atmospheric correction is decisive for ocean color remote sensing applications. Near infrared (NIR)-based algorithm performs well for clear waters; while shortwave infrared (SWIR)-based algorithm can obtain good results for turbid waters, however, it tends to produce noisy patterns for clear waters. A practical strategy is to apply NIR- and SWIR-based algorithm for clear and turbid waters, respectively, which is called NIR-SWIR combined atmospheric correction algorithm. However, the currently applied switching scheme for the NIR-SWIR algorithm undermines the atmospheric correction performance. This study aimed to find an applicable switching scheme for NIR-SWIR algorithm. Four MODIS land bands were used to switch the NIR- and SWIR-based algorithms. A simulated dataset was used to evaluate atmospheric performance of NIR- and SWIR-based algorithm. The switching threshold for each MODIS land band was determined as an Rrs value at which SWIR-based algorithm performed better than NIR-based algorithm. The switching scheme was evaluated using matchups of simultaneous MODIS Aqua images and AERONET-OC data, and then tested with a MODIS Aqua image over the western Pacific Ocean. Results showed that the switching threshold for Rrs(469), Rrs(555), Rrs(645)and Rrs(859)were 0.009, 0.016, 0.009 and 0.0006 sr−1, respectively; Rrs(645)with a threshold of 0.009 sr−1 and Rrs(555)with a threshold of 0.016 sr−1 worked well for NIR-SWIR algorithm, while Rrs(469)and Rrs(859)produced worse performance. Therefore, Rrs(555)> 0.016 sr−1 or Rrs(645)> 0.009 sr−1 was recommended as the switching scheme for NIR-SWIR algorithm. Considering contrasted estuarine, coastal and some inland waters, combining NIR- and SWIR-based atmospheric correction algorithm with the proposed switching scheme should be useful for remote sensing monitoring over these waters.
AB - Accurate atmospheric correction is decisive for ocean color remote sensing applications. Near infrared (NIR)-based algorithm performs well for clear waters; while shortwave infrared (SWIR)-based algorithm can obtain good results for turbid waters, however, it tends to produce noisy patterns for clear waters. A practical strategy is to apply NIR- and SWIR-based algorithm for clear and turbid waters, respectively, which is called NIR-SWIR combined atmospheric correction algorithm. However, the currently applied switching scheme for the NIR-SWIR algorithm undermines the atmospheric correction performance. This study aimed to find an applicable switching scheme for NIR-SWIR algorithm. Four MODIS land bands were used to switch the NIR- and SWIR-based algorithms. A simulated dataset was used to evaluate atmospheric performance of NIR- and SWIR-based algorithm. The switching threshold for each MODIS land band was determined as an Rrs value at which SWIR-based algorithm performed better than NIR-based algorithm. The switching scheme was evaluated using matchups of simultaneous MODIS Aqua images and AERONET-OC data, and then tested with a MODIS Aqua image over the western Pacific Ocean. Results showed that the switching threshold for Rrs(469), Rrs(555), Rrs(645)and Rrs(859)were 0.009, 0.016, 0.009 and 0.0006 sr−1, respectively; Rrs(645)with a threshold of 0.009 sr−1 and Rrs(555)with a threshold of 0.016 sr−1 worked well for NIR-SWIR algorithm, while Rrs(469)and Rrs(859)produced worse performance. Therefore, Rrs(555)> 0.016 sr−1 or Rrs(645)> 0.009 sr−1 was recommended as the switching scheme for NIR-SWIR algorithm. Considering contrasted estuarine, coastal and some inland waters, combining NIR- and SWIR-based atmospheric correction algorithm with the proposed switching scheme should be useful for remote sensing monitoring over these waters.
KW - Aerosol
KW - NIR-SWIR
KW - Ocean color atmospheric correction
KW - Water quality
UR - http://www.scopus.com/inward/record.url?scp=85065424050&partnerID=8YFLogxK
U2 - 10.1016/j.isprsjprs.2019.04.013
DO - 10.1016/j.isprsjprs.2019.04.013
M3 - Journal article
AN - SCOPUS:85065424050
SN - 0924-2716
VL - 153
SP - 59
EP - 73
JO - ISPRS Journal of Photogrammetry and Remote Sensing
JF - ISPRS Journal of Photogrammetry and Remote Sensing
ER -