Paper Info
Title
An Improved Empirical Model for Retrieving Bottom Reflectance in Optically Shallow Water
Abstract
Satellite remote sensing has become an essential observing system to obtain comprehensive information on the status of coastal habitats. However, a significant challenge in remote sensing of optically shallow water is to correct the effects of the water column. This challenge becomes particularly difficult due to the spatial and temporal variability of water optical properties. In order to model the light distribution for optically shallow water and retrieve the bottom reflectance, a parameterized model was proposed by introducing an important adjusted factor g. The synthetic data sets generated by HYDROLIGHT were utilized to train a neural network (NN) and then to derive the adjustable parameter values. The parameter g was found to vary with water depth, water optical properties, and bottom reflectance. Specifically, it revealed two obvious patterns among the different benthic habitat types. In coral reef, seagrass, and macrophyte habitats, g exhibited a remarkable peak at about 550 nm. The peak has a value of about 2.47-2.49. In white sand or hardpan habitats, g spectra are relatively flat. The semi-empirical model was applied to calculate the bottom reflectance from the new weighting factor, the downward diffuse attenuation coefficient, and the irradiance reflectance just below the sea surface collected in Sanya Bay in 2008 and 2009. Good agreement between the predicted and measured values demonstrated that the weighting factor g is an effective tool to modify the model for interpreting and predicting bottom reflectance without the need for any localized input (R2 > 0.79).
Year
DOI
Venue
2015
10.1109/JSTARS.2015.2398898
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  
Keywords
DocType
Volume
underwater optics,ad 2008,ad 2009,hydrolight,sanya bay,benthic habitat types,bottom reflectance,coastal habitats,coral reef,diffuse attenuation coefficient,empirical model,macrophyte habitats,neural network,optically shallow water,satellite remote sensing,seagrass,water column effects,water optical properties,water column correction,attenuation,adaptive optics,optical scattering,mathematical model,remote sensing
Journal
8
Issue
ISSN
Citations 
3
1939-1404
1
PageRank 
References 
Authors
0.35
3
2
Name
Order
Citations
PageRank
Chaoyu Yang123.07
Dingtian Yang210.35