Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29590
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: A global approach for chlorophyll-a retrieval across optically complex inland waters based on optical water types
Author(s): Neil, Claire
Spyrakos, Evangelos
Hunter, Peter D
Tyler, Andrew N
Contact Email: evangelos.spyrakos@stir.ac.uk
Keywords: Algorithm validation
Chlorophyll-a
water quality
inland waters
case 2 waters
remote sensing
optical water type
Issue Date: 1-Aug-2019
Citation: Neil C, Spyrakos E, Hunter PD & Tyler AN (2019) A global approach for chlorophyll-a retrieval across optically complex inland waters based on optical water types. Remote Sensing of Environment, 229, pp. 159-178. https://doi.org/10.1016/j.rse.2019.04.027
Abstract: Numerous algorithms have been developed to retrieve chlorophyll-a (Chla) concentrations (mg m−3) from Earth observation (EO) data collected over optically complex waters. Retrieval accuracy is highly variable and often unsatisfactory where Chla co-occurs with other optically active constituents. Furthermore, the applicability and limitations of retrieval algorithms across different optical complex systems in space and time are often not considered. In the first instance, this paper provides an extensive performance assessment for 48 Chla retrieval algorithms of varying architectural design. The algorithms are tested in their original parametrisations and are then retuned using in-situ remote sensing reflectance (Rrs(λ), sr−1) data (n = 2807) collected from 185 global inland and coastal aquatic systems encompassing 13 different optical water types (OWTs). The paper then demonstrates retrieval performance across the full dataset of observations and within individual OWTs to determine the most effective model(s) of those tested for retrieving Chla in waters with varying optical properties. The results revealed significant variability in retrieval performance when comparing model outputs to in-situ measured Chla for the full in-situ dataset in its entirety and within the 13 distinct OWTs. Importantly, retuning an algorithm to optimise its parameterisation for each individual OWT (i.e. one algorithm, multiple parameterisations) is found to improve the retrieval of Chla overall compared to simply calibrating the same algorithm using the complete in-situ dataset (i.e. one algorithm, one parameterisation). This resulted in a 25% improvement in retrieval accuracy based on relative percentage difference errors for the best performing Chla algorithm. Improved performance is further achieved by allowing model type and specific parameterisation to vary across OWTs (i.e. multiple algorithms, multiple parameterisations). This adaptive framework for the dynamic selection of in-water algorithms is shown to provide overall improvement in Chla retrieval across a continuum of bio-geo-optical conditions. The final dynamic ensemble algorithm produces estimates of (log10-transformed) Chla with a correlation coefficient of 0.89 and a mean absolute error of 0.18 mg m−3. The OWT framework presented in this study demonstrates a unified approach by bringing together an ensemble of algorithms for the monitoring of inland waters at a global scale from space.
DOI Link: 10.1016/j.rse.2019.04.027
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Neil C, Spyrakos E, Hunter PD & Tyler AN (2019) A global approach for chlorophyll-a retrieval across optically complex inland waters based on optical water types. Remote Sensing of Environment, 229, pp. 159-178. DOI: https://doi.org/10.1016/j.rse.2019.04.027 © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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