Remote sensing of euphotic depth in shallow tropical inland waters of Lake Naivasha using MERIS data

Majozi, Nobuhle P.; Salama, Mhd. Suhyb; Bernard, Stewart; Harper, David M.; Habte, Mussie Ghirmai

doi:10.1016/j.rse.2014.03.025

Cited by 66 publications

(30 citation statements)

References 65 publications

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“…Therefore, the commonly used parameter K d is the vertical mean value of a certain layer of water [4]. K d is a basic parameter that characterizes underwater light fields [5] and plays a vital role in studying water turbidity [6], sediment transport and resuspension [7,8], heat transfer within the upper water [9,10], the photosynthesis of phytoplankton [11,12], and the net primary productivity of natural waters [13,14].…”

Section: Introductionmentioning

confidence: 99%

Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI

et al. 2017

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Abstract:The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400-1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (K d (490)) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available K d (490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R 2 ) = 0.81, root-mean-square error (RMSE) = 0.99 m −1 and mean absolute percentage error (MAPE) = 19.55%) and validation accuracy (N = 14, R 2 = 0.83, RMSE = 1.06 m −1 and MAPE = 27.30%), making it more suitable for turbid inland waters; (2) A comparison of the OLCI K d (490) product and a similar Moderate Resolution Imaging Spectroradiometer (MODIS) product reveals a high consistency between the OLCI and MODIS products in terms of the spatial distribution of K d (490). However, the OLCI product has a smoother spatial distribution and finer textural characteristics than the MODIS product and contains notably higher-quality data; (3) The K d (490) values for Lake Taihu exhibit notable spatial and temporal variations. K d (490) is higher in seasons with relatively high wind speeds and in open waters that are prone to wind-and wave-induced sediment resuspension. Finally, the Sentinel-3A-OLCI has a higher spatial resolution and is equipped with a relatively wide dynamic range of spectral bands suitable for inland waters. The Sentinel-3B satellite will be launched soon and, together with the Sentinel-3A satellite, will form a two-satellite network with the ability to make observations twice every three days. This satellite network will have a wider range of application and play an important role in the monitoring of inland waters with complex optical properties.

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Section: Introductionmentioning

confidence: 99%

Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI

et al. 2017

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“…The complex relationships between K d and inherent optical properties developed in earlier studies were not capable of providing accurate estimation of K d from ocean color remote sensing [ Lee et al , ]. Therefore, empirical algorithms, which either suggest a direct relationship between remote sensing reflectance ( R rs or normalized water‐leaving radiance, n L w ) and K d or an indirect relationship with intermediate levels of chlorophyll a concentration [ Austin and Petzold , ; Mueller , ; Zhang et al , , ; Majozi et al , ], were applied to estimate K d .…”

Section: Introductionmentioning

confidence: 99%

Wind and rainfall regulation of the diffuse attenuation coefficient in large, shallow lakes from long‐term MODIS observations using a semianalytical model

et al. 2017

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Knowledge of the variation and regulation of the diffuse attenuation coefficient is important for management of lake water quality and ecological environments. Data were collected seven times (378 samples) from 2006 to 2011 in Lake Taihu to improve the existing semianalytical model of diffuse attenuation coefficient at 490 nm (Kd(490)) by measuring in situ Kd(490) and remote sensing reflectance (Rrs). This semianalytical model was applied to determine the long‐term variation of Kd(490) and its driving factors from Moderate Resolution Imaging Spectroradiometer (MODIS) images. Our semianalytical model of Kd(490) improves the retrieval accuracy of Kd(490) from 29.60% to 22.58% (root‐mean‐square percentage error) and 24.28 ± 18.54% (mean value ± standard deviation) to 19.29 ± 14.34% (mean absolute relative error). The Kd(490) from maps produced from MODIS images clearly present the temporal and spatial variations of Kd(490). This indicates the suitability of using the improved semianalytical model and MODIS to observe Kd(490) in turbid shallow inland waters. Long‐term MODIS observation of Kd(490) shows distinct seasonal and spatial variations. Temporally, the highest and the lowest Kd(490) were found in winter and in summer, respectively. Spatially, high Kd(490) values were primarily distributed in the southwestern and northwestern Lake Taihu, and relatively low Kd(490) values were distributed in Meiliang Bay and Gonghu Bay (the eastern part of the lake and East Bay were excluded in this study due to invalid retrieval results of Kd(490)). Many covarying points were found between Kd(490) and maximum wind speed from long‐term observations, suggesting that wind‐induced sediment resuspension is the principal driver of high Kd(490). Correlation was also observed between Kd(490) and heavy rainfall events, suggesting the regulating effect of heavy rainfall.

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“…Several sensor‐specific algorithms for atmospheric correction and constituent retrieval have been implemented in the Basic ERS & Envisat (A) ATSR and MERIS Toolbox (BEAM). Among these, the neural networks C2R, EUL, FUB, have been developed for specific water types and have been compared and applied in the last years [ Attila et al ., ; Kallio et al ., ; Majozi et al ., ; Odermatt et al ., ]. In the framework of the Coastcolour project (http://www.coastcolour.org), a newer neural network‐based processor has also been developed.…”

Section: Introductionmentioning

confidence: 99%

Evaluation and reformulation of the maximum peak height algorithm (MPH) and application in a hypertrophic lagoon

Pitarch

Ruiz‐Verdú

Sendra

et al. 2017

J. Geophys. Res. Oceans

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We studied the performance of the MERIS maximum peak height (MPH) algorithm in the retrieval of chlorophyll‐a concentration (CHL), using a matchup data set of Bottom‐of‐Rayleigh Reflectances (BRR) and CHL from a hypertrophic lake (Albufera de Valencia). The MPH algorithm produced a slight underestimation of CHL in the pixels classified as cyanobacteria (83% of the total) and a strong overestimation in those classified as eukaryotic phytoplankton (17%). In situ biomass data showed that the binary classification of MPH was not appropriate for mixed phytoplankton populations, producing also unrealistic discontinuities in the CHL maps. We recalibrated MPH using our matchup data set and found that a single calibration curve of third degree fitted equally well to all matchups regardless of how they were classified. As a modification to the former approach, we incorporated the Phycocyanin Index (PCI) in the formula, thus taking into account the gradient of phytoplankton composition, which reduced the CHL retrieval errors. By using in situ biomass data, we also proved that PCI was indeed an indicator of cyanobacterial dominance. We applied our recalibration of the MPH algorithm to the whole MERIS data set (2002–2012). Results highlight the usefulness of the MPH algorithm as a tool to monitor eutrophication. The relevance of this fact is higher since MPH does not require a complete atmospheric correction, which often fails over such waters. An adequate flagging or correction of sun glint is advisable though, since the MPH algorithm was sensitive to sun glint.

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Remote sensing of euphotic depth in shallow tropical inland waters of Lake Naivasha using MERIS data

Cited by 66 publications

References 65 publications

Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI

Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI

Wind and rainfall regulation of the diffuse attenuation coefficient in large, shallow lakes from long‐term MODIS observations using a semianalytical model

Evaluation and reformulation of the maximum peak height algorithm (MPH) and application in a hypertrophic lagoon

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