The inherent optical properties (IOPs) of natural waters are the most significant factors affecting light propagation within water columns, and thus play indispensable roles on estimation of aquatic biomass, primary production, and carbon pools. Despite its importance, no IOPs retrieval model was specifically developed for inland water bodies, although significant efforts were made on oceanic inversion models. In addition, for inland waters, an IOPs-based model is often preferred for estimating chlorophyll-a (Chl-a) concentration, an application of IOPs, over empirical and some semi-empirical algorithms. Then developing a model for estimating both IOPs and Chl-a is of significance for understanding the bio-optical properties and occurrence of algal blooms in eutrophic reservoirs, lakes and estuaries. In this paper, an IOPs Inversion Model of Inland Waters (IIMIW) for deriving natural water IOPs and estimating Chl-a is proposed and validated. The results indicate that this model can be used to accurately retrieve absorption coefficients at 443 nm and 665 nm with R2 = 0.8347 and R2 = 0.7550 respectively for Indiana study sites, and to estimate Chl-a from the derived absorption coefficients at high accuracies (R2 = 0.9292 and a mean relative error 21.65%) with samples collected from eight different study sites in the world and in different seasons. The model was also applied on Airborne Imaging Spectrometer for Application (AISA) images to map IOPs and Chl-a. Through validation by in situ measured Chl-a, results directly show that IIMIW can predict Chl-a with good accuracy even using the AISA bands, to as well indirectly prove that non-water absorption coefficients are retrieved accurately, at least within red and near-infrared region. Further biogeochemical information can be derived from these maps as well. These promising mapping results reveal possible remote routine surveillance of bio-optical states of inland waters.
An inversion model for deriving inherent optical properties of inland waters: Establishment, validation and application
Remote Sensing of Environment ; 135 ; 150-166
2013
17 Seiten, 95 Quellen
Article (Journal)
English
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