Title
A Spectral-Unmixing Approach to Estimate Water–Mass Concentrations in Case 2 Waters
Abstract
In this work, we study the estimation of water-quality parameters from the water-leaving reflectance by means of spectral unmixing. Our starting point is the provision of an analytic model relating the reflectance of water to its masses/bodies or constituents, as specified by their specific inherent optical properties (SIOP) and concentrations. The main objective is to reformulate the estimation of these concentrations as a spectral unmixing problem. We perform this by employing the linear mixing model (LMM), while suitably defining the endmembers (EMs) as representations of different water types dominated by one or more constituents. Each EM is then calculated by substituting the in situ-measured SIOP and combinations of utmost concentrations of each constituent into the water-reflectance model. Such use of unmixing practically enables to maintain an implicitly nonlinear relation between the water reflectance and constituents' concentrations, without resorting to the use of nonlinear mixing models. Furthermore, we present a method to automatically extract the EMs from the reflectance image. We validate the entire unmixing-based take using the state-of-the-art method as reference that inverts the water reflectance via comparisons (curve matching) with spectra from a lookup table. This validation is done using simulated data derived from the water-reflectance model and real hyperspectral data acquired over coastal waters of a shallow sea.
Year
DOI
Venue
2014
10.1109/JSTARS.2014.2345562
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  
Keywords
Field
DocType
geophysical image processing,hydrological techniques,oceanographic techniques,water quality,case 2 waters,linear mixing model,nonlinear mixing models,specific inherent optical properties,spectral unmixing problem,spectral-unmixing approach,water reflectance,water-leaving reflectance,water-mass concentrations,water-quality parameter estimation,Case 2 waters,image processing,remote sensing,spectral unmixing,water quality retrieval
Lookup table,Nonlinear system,Curve matching,Remote sensing,Hyperspectral imaging,Spectral line,Reflectivity,Analytic model,Water mass,Mathematics
Journal
Volume
Issue
ISSN
7
8
1939-1404
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Burazerovic, D.100.34
Rob Heylen226923.24
Dries Raymaekers332.36
Els Knaeps453.53