LS2 is a bulk inversion model for estimating the seawater inherent optical properties of the spectral absorption, a(λ), and backscattering, bb(λ), coefficients as well as their non-water components anw(λ) and bbp(λ) from measurements of remote-sensing reflectance, Rrs(λ). The model avoids assumptions about the spectral shapes of a(λ) and bb(λ) and can be implemented as the first step in a multi-step semianalytical approach with additional absorption partitioning models to derive absorption coefficients of seawater constituents either from in situ or remote-sensing observations of Rrs(λ). The complete development and validation of the LS2 model is described in [Loisel et al. 2018] (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JC013632). The LS2 model builds upon and extends the previous version of inverse reflectance model described in Loisel and Stramski 2000 (https://doi.org/10.1364/AO.39.003001). The LS2 model code was originally written by our collaborators from France led by Dr. Hubert Loisel. The presented version of LS2 model source code is in MATLAB file format. In this version of LS2 code we introduced a number of changes with a primary purpose to streamline the structure of the code and facilitate its application by users.
This README document provides information about the files within the LS2_Distribution repository.
The main function that runs LS2 model for a single input Rrs(λ), i.e., at a single light wavelength λ. The function calculates a(λ), bb(λ), anw(λ), and bbp(λ), from input solar zenith angle, Rrs(λ), Kd(λ), bw(λ), aw(λ), and bp(λ), at the given Rrs(λ) input wavelength. Note that input Kd(λ) can be obtained either from direct measurements (if available) or, in the context of remote-sensing applications, from a separate algorithm that uses Rrs(λ) as input such as neural network model as described in Loisel et al. 2018. See supporting documentation for further details.
Look-up tables (LUTs) necessary to run LS2_main.m. The structure contains five fields, each of which is necessary to run LS2. See LS2_main.m function documentation for further details about the .mat file.
Script which tests LS2 on ten sample inputs at six different wavelengths corresponding to center wavelengths of spectral bands available on ocean color sensor SeaWiFS.
Excel spreadsheet containing the input and resulting output parameters obtained from the application of LS2 on ten samples at six different wavlengths. The file is the original output file generated by LS2_test_run.m.
Function that calculates the particulate scattering coefficient, bp(λ), at a user defined wavelength from the empirical relationship using chlorophyll-a concentration (Chla) as a predictor of bp(λ), as described in Morel and Maritorena (2001). This relationship is used to produce input bp(λ), which is a second-order parameter of LS2 model used to calculate the ratio of the pure seawater (molecular) scattering coefficient to the total scattering coefficient, and is provided for the convenience of the user. Furthermore, the approach utilized in Morel and Maritorena (2001) to calculate bp(λ) was deemed adequate for the performance of LS2 model as demonstrated in Loisel et al. (2018). Note that in order to use bp_from Chla.m function in conjuction with LS2_main.m the user is required to provide Chla input to bp_from Chla.m function. For example, if LS2 model is used in satellite ocean color application, the satellite-derived Chla product can be used as input to bp_from Chla.m. Note also that bp_from Chla.m function and Chla which is used by this function are not needed to run the LS2 model if bp(λ) is known or can be estimated by other means and provided as input to LS2_main.m.
Contributors: Matthew Kehrli, Aster Taylor, Rick A. Reynolds, and Dariusz Stramski
Contacts: Matthew Kehrli1 (mdkehrli@ucsd.edu | mdkehrli@gmail.com), Rick Reynolds1 (rreynolds@ucsd.edu), Dariusz Stramski1 (dstramski@ucsd.edu), Hubert Loisel2 (hubert.loisel@univ-littoral.fr)
1 Ocean Optics Research Laboratory, Scripps Institution of Oceanography, University of California San Diego
2 Laboratoire d’Oceanologie et de Geosciences, Universite du Littoral Cote d’Opale, Universite Lille, CNRS, Wimereux, France