Publications

Chen, Jun; Zhu, Yuanli; Wu, Yongsheng; Cui, Tingwei; Ishizaka, Joji; Ju, Yongtao (2015). A Neural Network Model for K(lambda) Retrieval and Application to Global K-par Monitoring. PLOS ONE, 10(6), UNSP e0127514.

Abstract
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths K-d(lambda) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability of a semi-analytical K-d(lambda) retrieval model (SAKM) and Jamet's neural network model (JNNM), and then develop a new neural network K-d(lambda) retrieval model (NNKM). Based on the comparison of K-d(lambda) predicted by these models with in situ measurements taken from the global oceanic and coastal waters, all of the NNKM, SAKM, and JNNM models work well in K-d(lambda) retrievals, but the NNKM model works more stable and accurate than both SAKM and JNNM models. The near-infrared band-based and shortwave infrared band-based combined model is used to remove the atmospheric effects on MODIS data. The K-d(lambda) data was determined from the atmospheric corrected MODIS data using the NNKM, JNNM, and SAKM models. The results show that the NNKM model produces <30% uncertainty in deriving K-d(lambda) from global oceanic and coastal waters, which is 4.88-17.18% more accurate than SAKM and JNNM models. Furthermore, we employ an empirical approach to calculate K-par from the NNKM model-derived diffuse attenuation coefficient at visible bands (443, 488, 555, and 667 nm). The results show that our model presents a satisfactory performance in deriving K-par from the global oceanic and coastal waters with 20.2% uncertainty. The K-par are quantified from MODIS data atmospheric correction using our model. Comparing with field measurements, our model produces similar to 31.0% uncertainty in deriving K-par from Bohai Sea. Finally, the applicability of our model for general oceanographic studies is briefly illuminated by applying it to climatological monthly mean remote sensing reflectance for time ranging from July, 2002-July 2014 at the global scale. The results indicate that the high K-d(lambda) and K-par values are usually found around the coastal zones in the high latitude regions, while low K-d(lambda) and K-par values are usually found in the open oceans around the low-latitude regions. These results could improve our knowledge about the light field under waters at either the global or basin scales, and be potentially used into general circulation models to estimate the heat flux between atmosphere and ocean.

DOI:
10.1371/journal.pone.0127514

ISSN:
1932-6203