Validation of Envisat MERIS algorithms for chlorophyll retrieval in a large, turbid and optically-complex shallow lake

Abstract

The 10-year archive of MEdium Resolution Imaging Spectrometer (MERIS) data is an invaluable resource for studies on lake system dynamics at regional and global scales. MERIS data are no longer actively acquired but their capacity for global scale monitoring of lakes from satellites will soon be re-established through the forthcoming Sentinel-3 Ocean and Land Colour Instrument (OLCI). The development and validation of in-water algorithms for the accurate retrieval of biogeochemical parameters is thus of key importance if the potential of MERIS and OLCI data is to be fully exploited for lake monitoring. This study presents the first extensive validation of algorithms for chlorophyll-a (chl-a) retrieval by MERIS in the highly turbid and productive waters of Lake Balaton, Hungary. Six algorithms for chl-a retrieval from MERIS over optically complex Case 2 waters, including band-difference and neural network architectures, were compared using the MERIS archive for 2007-2012. The algorithms were locally-tuned and validated using in situ chl-a data (n = 289) spanning the five year processed image time series and from all four lake basins. In general, both band-difference algorithms tested (Fluorescence Line Height (FLH) and Maximum Chlorophyll Index (MCI)) performed well, whereas the neural network processors were generally found to much less accurately retrieve in situ chl-a concentrations. The Level 1b FLH algorithm performed best overall in terms of chl-a retrieval (R2 = 0.87; RMSE = 4.19 mg m - 3; relative RMSE = 30.75%) and particularly at chl-a concentrations of ≥ 10 mg m- 3 (R2 = 0.85; RMSE = 4.81 mg m- 3; relative RMSE = 20.77%). However, under mesotrophic conditions (i.e., chl-a < 10 mg m- 3) FLH was outperformed by the locally-tuned FUB/WeW processor (relative FLH RMSE < 10 mg m- 3 = 57.57% versus relative FUB/WeW RMSE < 10 mg m- 3 = 46.96%). An ensemble selection of in-water algorithms is demonstrated to improve chl-a retrievals

Evaluation of MERIS Chlorophyll-a Retrieval Processors in a Complex Turbid Lake Kasumigaura over a 10-Year Mission

“…The algorithms that were compared within the two studies were both based on the neural network and their results revealed that the EUL processor was the most accurate algorithm. Inter-comparison between the band height and neural network algorithms showed that the band height algorithms outperformed the neural network as reported by Binding et al [36] and Lankester et al [37].…”

“…In addition, the upper limit of Chla concentrations during the above-mentioned studies were less than 70 mg·m −3 [35][36][37], which does not represent highly turbid water bodies. The aim of the current study was to investigate the performance of the seven algorithms over a complex water body (i.e., Lake Kasumigaura), which is characterized by a trophic environment covering broad statuses (i.e., mesotrophic to hypertrophic).…”

Sensitivity analysis of a bio-optical model for Italian lakes focused on Landsat-8, Sentinel-2 and Sentinel-3

“…Pahlevan et al [2014] analysed the radiometric performance of Operational Land Imager (OLI), on board Landsat 8 [Irons et al, 2012], for water quality applications [e.g., Vanhellemont and Ruddick, 2014].They identified local gain factors for radiance and reflectance to improve the retrieval of in-water products by considering in situ measurements and other ocean colour satellites as a benchmark. The Ocean and Land Colour Instrument (OLCI), an improved continuation of Medium Resolution Imaging Spectrometer (MERIS) [Donlon et al, 2012], on-board Sentinel-3, is a useful satellite for monitoring waters environments which leaves the moderate spatial scale unchanged (300 m) [Aschbacher et al, 2012;Malenovsky et al, 2013;Palmer et al, 2014]. The Multi Spectral Instrument (MSI) on board Sentinel-2 has fewer bands and a wider bandwidth than OLCI [Drusch et al, 2012].…”

A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu

“…These blooms have Compared to Landsat TM/ETM+ , MERIS, and MODIS imagery provide advantages for large lakes due to their short overpass period and good spatial resolution [72,73]. MERIS, accessible until April 2012, provided important insights into the concentrations of optically active substances in large lakes [45,74]. MODIS (1999-present for Terra, 2002-present for Aqua) provides frequent (daily) and synoptic global observations and is equipped with several medium-resolution bands ("sharpening" bands designed for land use), and is also the prototype for VIIRS (the Visible Infrared Imager/Radiometer Suite) [75,76], allowing MODIS algorithms to inform algorithm development for VIIRS.…”