Calibration and Validation of Algorithms for the Estimation of Chlorophyll-A in Inland Waters with Sentinel-2

Pereira-Sandoval, Marcela; Ruiz‐Verdú, Antonio; Tenjo, Carolina; Delegido, Jesús; Urrego, Patricia; Peña, Ramón; Vicente, Eduardo; Soria, Juan M.; Soria, Javier; Moreno, José

doi:10.1109/igarss.2018.8517371

Cited by 14 publications

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“…The measurement procedure for obtaining the Z sd is to lower it slowly in the water until it disappears from sight. When that happens, it is possible to obtain the Z sd [9]. Table 2 describes the in situ minimum and maximum values of the Chl-a and Z sd parameters, together with other statistics.…”

Section: Study Areamentioning

confidence: 99%

Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data

et al. 2019

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The atmospheric contribution constitutes about 90 percent of the signal measured by satellite sensors over oceanic and inland waters. Over open ocean waters, the atmospheric contribution is relatively easy to correct as it can be assumed that water-leaving radiance in the near-infrared (NIR) is equal to zero and it can be performed by applying a relatively simple dark-pixel-correction-based type of algorithm. Over inland and coastal waters, this assumption cannot be made since the water-leaving radiance in the NIR is greater than zero due to the presence of water components like sediments and dissolved organic particles. The aim of this study is to determine the most appropriate atmospheric correction processor to be applied on Sentinel-2 MultiSpectral Imagery over several types of inland waters. Retrievals obtained from different atmospheric correction processors (i.e., Atmospheric correction for OLI 'lite' (ACOLITE), Case 2 Regional Coast Colour (here called C2RCC), Case 2 Regional Coast Colour for Complex waters (here called C2RCCCX), Image correction for atmospheric effects (iCOR), Polynomial-based algorithm applied to MERIS (Polymer) and Sen2Cor or Sentinel 2 Correction) are compared against in situ reflectance measured in lakes and reservoirs in the Valencia region (Spain). Polymer and C2RCC are the processors that give back the best statistics, with coefficients of determination higher than 0.83 and mean average errors less than 0.01. An evaluation of the performance based on water types and single bands-classification based on ranges of in situ chlorophyll-a concentration and Secchi disk depth values-showed that performance of these set of processors is better for relatively complex waters. ACOLITE, iCOR and Sen2Cor had a better performance when applied to meso-and hyper-eutrophic waters, compare with oligotrophic. However, other considerations should also be taken into account, like the elevation of the lakes above sea level, their distance from the sea and their morphology.

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Section: Study Areamentioning

confidence: 99%

Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data

et al. 2019

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“…Ecuación con la misma forma matemática que la (2) con un ligero cambio en los coeficientes. Para comparar la ecuación 2, obtenida en este trabajo con espectros de S2, con la ecuación 3 o 5 de Pereira-Sandoval et al (2019a), y que fue obtenida con los mismos datos, pero simulando S2 a partir de radiometría de campo, en la figura 3 se ha representado en color rojo la ecuación 3. La gráfica muestra que ambas curvas siguen la tendencia de los puntos experimentales.…”

Section: Resultados Y Discusiónunclassified

“…En cada píxel se han calculado los índices R 490 /R 560 , R 490 /R 705 y R 560 /R 705 que fueron los mejores índices para la estimación de SD a partir de imágenes simuladas de S2 según Pereira-Sandoval et al (2019a). Además, se han calculado los índices R 665 /R 490 y R 490 /R 665 , cocientes entre el azul y el rojo que han sido muy utilizados por diferentes autores para la estimación de SD (Matthews, 2011).…”

Section: Calibración De íNdices Y Bandasunclassified

“…Los satélites Sentinel-2 (S2) de la ESA ofrecen imágenes de buena calidad radiométrica y adecuada resolución espacial y temporal, muy útiles en los estudios de calidad del agua, principalmente en aguas continentales debido al pequeño tamaño de muchos lagos y embalses. Por ello, diferentes investigaciones llevadas a cabo en los últimos años están desarrollando métodos operativos para la estimación de la calidad del agua con S2 (Ansper y Alikas, 2019;Toming et al, 2016;Pahlevan et al, 2019;Page et al, 2019), como el proyecto llevado a cabo por los autores de este artículo Ecological Status of AQuatic Systems with Sentinel Satellites (ESAQS, https://ipl.uv.es/esaqs/), cuyo objetivo principal fue desarrollar y validar algoritmos para la estimación de indicadores ecológicos de calidad en aguas continentales, entre ellos la concentración de clorofila-a [Chl-a], la transparencia, la materia orgánica disuelta y los sólidos en suspensión, a partir de imágenes S2 en diferentes lagos y embalses de la cuenca del Júcar (Pereira-Sandoval et al, 2019a).…”

Section: Introductionunclassified

“…Diferentes autores han calibrado distintos índices espectrales adaptados a diferentes satélites para la estimación de la transparencia y/o la turbidez por teledetección (Khorram et al, 1991;Koponen et al, 2002;Gholizadeh et al, 2016;Matthews, 2011;Page et al, 2019). En un trabajo previo (Pereira-Sandoval et al, 2019a) hemos demostrado que, a partir de datos de campo de SD y radiometría directa obtenidos en ESAQS, los mejores índices para la estimación de SD a partir de imágenes S2 en los embalses de la zona valenciana, son R 490 /R 560 , R 490 /R 705 y R 560 /R 705 (donde Ri es la reflectividad en la banda i en nm). Estos índices fueron seleccionados después de comprobar un gran número de combinaciones simulando las bandas de S2 a partir de la radiometría de campo.…”

Section: Introductionunclassified

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Turbidez y profundidad de disco de Secchi con Sentinel-2 en embalses con diferente estado trófico en la Comunidad Valenciana

et al. 2019

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Transparency or turbidity is one of the main indicators in studies of water quality using remote sensing. Transparency can be measured in situ through the Secchi disc depth (SD), and turbidity using a turbidimeter. In recent decades, different relationships between bands from different remote sensing sensors have been used for the estimation of these variables. In this paper, several indices and spectral bands have been calibrated in order to estimate transparency from Sentinel-2 (S2) images from field data, obtained throughout 2017 and 2018 in Júcar basin reservoirs with a great variety of trophic states. Three atmospheric correction methods developed for waters have been applied to the S2 level L1C images taken at the same day as the field data: Polymer, C2RCC and C2X. From the spectra obtained from S2 and the SD field data, it has been found that the smallest error is obtained with the images atmospherically corrected with Polymer and a potential adjustment of the reflectivities’ ratio of the blue and green bands (R490/R560), which allow the estimation of SD with a relative error of 13%. Also the C2X method presents good adjustment with the same bands ratio, although with a greater error, while the correction C2RCC shows the worst correlation. The relationship between SD (in m) and turbidity (in NTU) has also been obtained, which provides an operational method for estimating turbidity with S2. The relationship for the different reservoirs between SD and chlorophyll-a concentration, suspended solids and dissolved organic matter, is also shown.

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Retrospective analysis of Chlorophyll-a and its correlation with climate and hydrological variations in Mindu Dam, Morogoro, Tanzania

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Chikoore

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et al. 2019

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The measurement of Chlorophyll-a in aquatic systems has usually correlated to harmful algae in water bodies. Harmful algal blooms (HABs) are as a result of massive proliferation of blue-green algae (Cyanobacteria). Harmful algal blooms (HABs) pose threats to both the environment as well as human health, and despite this well-known fact, their monitoring and management are still challenging. Climate change, extreme weather events, and hydrological changes are the main drivers and predicted to benefits HABs dynamics in most parts of the world. In Tanzania, studies of HABs proliferation and their possible correlation with variability in climate and hydrology still lag behind despite high demand for developing predicting tools and prevention of HABs proliferation. The present study reports on the retrospective analysis of HABs variation in Mindu Dam located in Morogoro, Tanzania using remote sensing techniques. In the present study comparison between in situ measurement and ocean color (OC2) Chlorophyll-a with the surface reflectance's (band and band combinations) of Landsat 7 and Landsat 8 Operational Land Imager (OLI), was performed. Another approach involved searching for patterns and trends, and teleconnection between Chlorophyll-a index (best band ration) and the climate and hydrological variations in the catchment. The findings demonstrated that minimum and maximum temperatures, solar radiation, Chlorophyll-a concentration registered significant increasing trends. Wind speed and directions, water levels for Mindu Dam showed a significant decreasing trend. On the other hand, rainfall showed no trend. The patterns suggest that there are link and causality between the HABs variations and meteorological parameters such as temperatures, solar radiations, and water levels. The study, therefore, contributes to the application of recent advances in remote sensing and retrospectively analysis of bloom dynamics and search for their link with climate and hydrological changes.

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Calibration and Validation of Algorithms for the Estimation of Chlorophyll-A in Inland Waters with Sentinel-2

Cited by 14 publications

References 3 publications

Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data

Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data

Turbidez y profundidad de disco de Secchi con Sentinel-2 en embalses con diferente estado trófico en la Comunidad Valenciana

Retrospective analysis of Chlorophyll-a and its correlation with climate and hydrological variations in Mindu Dam, Morogoro, Tanzania

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