Retrieval of Chlorophyll-a concentration and associated product uncertainty in optically diverse lakes and reservoirs



Liu X, Steele C, Simis S, Warren M, Tyler A, Spyrakos E, Selmes N & Hunter P (2021) Retrieval of Chlorophyll-a concentration and associated product uncertainty in optically diverse lakes and reservoirs. Remote Sensing of Environment, 267, Art. No.: 112710.

Satellite product uncertainty estimates are critical for the further development and evaluation of remote sensing algorithms, as well as for the user community (e.g., modelers, climate scientists, and decision-makers). Optical remote sensing of water quality is affected by significant uncertainties stemming from correction for atmospheric effects as well as a lack of algorithms that can be universally applied to waterbodies spanning several orders of magnitude in non-covarying substance concentrations. We developed a method to produce estimates of Chlorophyll-a (Chla) satellite product uncertainty on a pixel-by-pixel basis within an Optical Water Type (OWT) classification scheme. This scheme helps to dynamically select the most appropriate algorithms for each satellite pixel, whereas the associated uncertainty informs downstream use of the data (e.g., for trend detection or modeling) as well as the future direction of algorithm research. Observations of Chla were related to 13 previously established OWT classes based on their corresponding water-leaving reflectance (Rw), each class corresponding to specific bio-optical characteristics. Uncertainty models corresponding to specific algorithm - OWT combinations for Chla were then expressed as a function of OWT class membership score. Embedding these uncertainty models into a fuzzy OWT classification approach for satellite imagery allows Chla and associated product uncertainty to be estimated without a priori knowledge of the biogeochemical characteristics of a water body. Following blending of Chla algorithm results according to per-pixel fuzzy OWT membership, Chla retrieval shows a generally robust response over a wide range of class memberships, indicating a wide application range (ranging from 0.01 to 362.5 mg/m3). Low OWT membership scores and high product uncertainty identify conditions where optical water types need further exploration, and where biogeochemical satellite retrieval algorithms require further improvement. The procedure is demonstrated here for the Medium Resolution Imaging Spectrometer (MERIS) but could be repeated for other sensors, atmospheric correction methods and optical water quality variables.

Chlorophyll-a; Optical water types; Uncertainty; Inland waters; Remote sensing

Remote Sensing of Environment: Volume 267

FundersNERC Natural Environment Research Council
Publication date15/12/2021
Publication date online02/10/2021
Date accepted by journal16/09/2021

People (3)


Dr Peter Hunter
Dr Peter Hunter

SIEC/Forth-ERA Science Director, Scotland's International Environment Centre

Dr Evangelos Spyrakos
Dr Evangelos Spyrakos

Associate Professor, Biological and Environmental Sciences

Professor Andrew Tyler
Professor Andrew Tyler

Scotland Hydro Nation Chair, Scotland's International Environment Centre

Projects (1)