Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10years of MERIS observations

Palmer, Stephanie C.; Odermatt, Daniel; Hunter, Peter; Brockmann, Carsten; Présing, Mátyås; Balzter, Heiko; Tóth, Viktor R.

doi:10.1016/j.rse.2014.11.021

Cited by 103 publications

(66 citation statements)

References 65 publications

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“…Suitable sensors must deploy bands in the visible and near-infrared (VNIR) wavelengths with high radiometric sensitivity such as ocean colour sensors (e.g., MODIS and MERIS). Owing to their spatial resolution (≥300 m), studies conducted with these sensors focus mainly on large lakes such as Lake Balaton [15], Lake Geneva [16], Lake Taihu [17][18][19], or Great Lakes [20], but rarely on small lakes [21,22]. Studies on smaller lakes refer to less sensitive Landsat data [23] or to high spatial resolutions from commercial sensors such as WorldView [24] or Quickbird [25].…”

Section: Introductionmentioning

confidence: 99%

Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake

et al. 2016

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Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr −1 ). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (a CDOM (440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and a CDOM (440) were modelled in optically shallow water. In deep water, SPM and a CDOM (440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m −1 ) showed an underestimation of S2-A derived a CDOM (440) (mean: 0.14 m −1 ); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m −1 vs. 0.019 m −1 ). Chlorophyll-a concentrations (~1 mg·m −3 ) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.

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Section: Introductionmentioning

confidence: 99%

Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake

et al. 2016

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“…It is composed of several processors for the ESA BEAM Toolbox (Fomferra and Brockmann, 2005), which has recently evolved into the Sentinel Application Platform (SNAP). The same input and auxiliary data and pre-and post-processing modules were also used to create 10-day aggregates for the investigation of phenological cycles in Lake Balaton (Palmer et al, 2015), and corresponding CaLimnos v1 L2 intermediate outputs were used for assessing the spatio-temporal variability of chl-a in Lake Geneva (Kiefer et al, 2015).…”

Section: Data Processing Methodsmentioning

confidence: 99%

Diversity II water quality parameters from ENVISAT (2002–2012): a new global information source for lakes

Odermatt

Danne

Philipson

et al. 2018

Earth Syst. Sci. Data

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Abstract. The use of ground sampled water quality information for global studies is limited due to practical and financial constraints. Remote sensing is a valuable means to overcome such limitations and to provide synoptic views of ambient water quality at appropriate spatio-temporal scales. In past years several large data processing efforts were initiated to provide corresponding data sources. The Diversity II water quality dataset consists of several monthly, yearly and 9-year averaged water quality parameters for 340 lakes worldwide and is based on data from the full ENVISAT MERIS operation period (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Existing retrieval methods and datasets were selected after an extensive algorithm intercomparison exercise. Chlorophyll-a, total suspended matter, turbidity, coloured dissolved organic matter, lake surface water temperature, cyanobacteria and floating vegetation maps, as well as several auxiliary data layers, provide a generically specified database that can be used for assessing a variety of locally relevant ecosystem properties and environmental problems. For validation and accuracy assessment, we provide matchup comparisons for 24 lakes and a group of reservoirs representing a wide range of bio-optical conditions. Matchup comparisons for chlorophyll-a concentrations indicate mean absolute errors and bias in the order of median concentrations for individual lakes, while total suspended matter and turbidity retrieval achieve significantly better performance metrics across several lake-specific datasets. We demonstrate the use of the products by illustrating and discussing remotely sensed evidence of lake-specific processes and prominent regime shifts documented in the literature. The Diversity II data are available from https://doi.pangaea.de/10.1594/PANGAEA.871462, and Python scripts for their analysis and visualization are provided at https://github.com/odermatt/diversity/.

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“…Reprocessed time series, by contrast, can be used to find the interannual variability for an area (Kopelevich et al, 2013), to detect anomalous events (e.g. -Gollop et al, 2008), changes in phenology (Palmer et al, 2015b) …”

Section: Special Issue Science Of the Total Environmentmentioning

confidence: 99%

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

Tyler

Hunter

Spyrakos

et al. 2016

Science of The Total Environment

130

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The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production.Despite this, the Earth's surface waters are impacted by multiple natural and anthropogenic pressures and drivers of environmental change. The complex interaction between physical, chemical and biological processes in surface waters poses significant challenges for in situ monitoring and assessment and often limits our ability to adequately capture the dynamics of aquatic systems and our understanding of their status, functioning and response to pressures. Here we explore the opportunities that Earth observation (EO) has to offer to basin-scale monitoring of water quality over the surface water continuum comprising inland, transition and coastal water bodies, with a particular focus on the Danube and Black Sea region. This review summarises the technological advances in EO and the opportunities that the next generation satellites offer for water quality monitoring. We provide an overview of algorithms for the retrieval of water quality parameters and demonstrate how such models have been used for the assessment and monitoring of inland, transitional, coastal and shelfsea systems. Further, we argue that very few studies have investigated the connectivity between these systems especially in large river-sea systems such as the Danube-Black Sea. Subsequently, we describe current capability in operational processing of archive and near real-time satellite data. We conclude that while the operational use of satellites for the assessment and monitoring of surface waters is still developing for inland and coastal waters and more work is required on the development and validation of remote sensing algorithms for these optically complex waters, the potential that these data streams offer for developing an improved, potentially paradigm-shifting understanding of physical and biogeochemical processes across large scale river-sea continuum including the Danube-Black Sea is considerable.

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Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10years of MERIS observations

Cited by 103 publications

References 65 publications

Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake

Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake

Diversity II water quality parameters from ENVISAT (2002–2012): a new global information source for lakes

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

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