AQUA-USERS: AQUAculture USEr driven operational Remote Sensing information services

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Technical note: Algal Pigment Index 2 in the Atlantic off the southwest Iberian Peninsula: standard and regional algorithms

Publication . Goela, Priscila; Cristina, Sónia; Kajiyama, Tamito; Icely, John; Moore, Gerald; Fragoso, Bruno; Newton, Alice

In this study, Algal Pigment Index 2 (API2) is investigated in Sagres, an area located in the Atlantic off the southwestern Iberian Peninsula. Standard results provided by the MEdium Resolution Image Spectrometer (MERIS) ocean colour sensor were compared with alternative data products, determined through a regional inversion scheme, using both MERIS and in situ remote sensing reflectances (R-rs) as input data. The reference quantity for performance assessment is in situ total chlorophyll a (TChl a) concentration estimated through a phytoplankton absorption coefficient (i.e. equivalent to API2). Additional comparison of data products has also been addressed for TChl a concentration determined by high-performance liquid chromatography. The MERIS matchup analysis revealed a systematic underestimation of TChl a, which was confirmed with an independent comparison of product map analysis. The study demonstrates the importance of regional algorithms for the study area that could complement upcoming standard results of the current Sentinel-3/OLCI space mission.

2016-12Journal article

Open Access

Using remote sensing as a support to the implementation of the European Marine Strategy Framework Directive in SW Portugal

Publication . Cristina, Sónia; Icely, John; Goela, Priscila; Angel DelValls, Tomás; Newton, Alice

The exclusive economic zones (EEZ) of coastal countries are coming under increasing pressure from various economic sectors such as fishing, aquaculture, shipping and energy production. In Europe, there is a policy to expand the maritime economic sector without damaging the environment by ensuring that these activities comply with legally binding Directives, such as the Marine Strategy Framework Directive (MSFD). However, monitoring an extensive maritime area is a logistical and economic challenge. Remote sensing is considered one of the most cost effective, methods for providing the spatial and temporal environmental data that will be necessary for the effective implementation of the MSFD. However, there is still a concern about the uncertainties associated with remote sensed products. This study has tested how a specific satellite product can contribute to the monitoring of a MSFD Descriptor for "good environmental status" (GES). The results show that the quality of the remote sensing product Algal Pigment Index 1 (API 1) from the MEdium Resolution Imaging Spectrometer (MERIS) sensor of the European Space Agency for ocean colour products can be effectively validated with in situ data from three stations off the SW Iberian Peninsula. The validation results show good agreement between the MERIS API 1 and the in situ data for the two more offshore stations, with a higher coefficient of determination (R-2) of 0.79, and with lower uncertainties for the average relative percentage difference (RPD) of 24.6% and 27.9% and a root mean square error (RMSE) of 0.40 and 0.38 for Stations B and C, respectively. Near to the coast, Station A has the lowest R-2 of 0.63 and the highest uncertainties with an RPD of 112.9% and a RMSE of 1.00. It is also the station most affected by adjacency effects from the land: when the Improved Contrast between Ocean and Land processor (ICOL) is applied the R-2 increases to 0.77 and there is a 30% reduction in the uncertainties estimated by RPD. The MERIS API 1 product decreases from inshore to offshore, with higher values occurring mainly between early spring and the end of the summer, and with lower values during winter. By using the satellite images for API 1, it is possible to detect and track the development of algal blooms in coastal and marine waters, demonstrating the usefulness of remote sensing for supporting the implementation of the MSFD with respect to Descriptor 5: Eutrophication. It is probable that remote sensing will also prove to be useful for monitoring other Descriptors of the MSFD.

2015-10Journal article

Open Access

MERIS phytoplankton time series products from the SW Iberian Peninsula (Sagres) using seasonal-trend decomposition based on loess

Publication . Cristina, Sónia; Cordeiro, Clara; Lavender, Samantha; Goela, Priscila; Icely, John; Newton, Alice

The European Space Agency has acquired 10 years of data on the temporal and spatial distribution of phytoplankton biomass from the MEdium Resolution Imaging Spectrometer (MERIS) sensor for ocean color. The phytoplankton biomass was estimated with the MERIS product Algal Pigment Index 1 (API 1). Seasonal-Trend decomposition of time series based on Loess (STL) identified the temporal variability of the dynamical features in the MERIS products for water leaving reflectance ((w)()) and API 1. The advantages of STL is that it can identify seasonal components changing over time, it is responsive to nonlinear trends, and it is robust in the presence of outliers. One of the novelties in this study is the development and the implementation of an automatic procedure, stl.fit(), that searches the best data modeling by varying the values of the smoothing parameters, and by selecting the model with the lowest error measure. This procedure was applied to 10 years of monthly time series from Sagres in the Southwestern Iberian Peninsula at three Stations, 2, 10 and 18 km from the shore. Decomposing the MERIS products into seasonal, trend and irregular components with stl.fit(), the (w)() indicated dominance of the seasonal and irregular components while API 1 was mainly dominated by the seasonal component, with an increasing effect from inshore to offshore. A comparison of the seasonal components between the (w)() and the API 1 product, showed that the variations decrease along this time period due to the changes in phytoplankton functional types. Furthermore, inter-annual seasonal variation for API 1 showed the influence of upwelling events and in which month of the year these occur at each of the three Sagres stations. The stl.fit() is a good tool for any remote sensing study of time series, particularly those addressing inter-annual variations. This procedure will be made available in R software.

2016-07Journal article

Open Access

Using CHEMTAX to evaluate seasonal and interannual dynamics of the phytoplankton community off the South-west coast of Portugal

Publication . Goela, Priscila; Danchenko, S.; Icely, John; Lubian, L. M.; Cristina, S.; Newton, A.

CHEMTAX was used to assess the relative contribution of the main phytoplankton classes to the total concentration of Chlorophyll a (Chl a) from the waters off SW coast of Portugal. Sampling campaigns were carried out during all seasons from 2008 to 2012, at three stations located 2, 10 and 18 km from the coast. Samples were taken from the surface, mid-Secchi and Secchi depth, for the determination of Chl a and other phytoplanktonic pigments by HPLC. Supporting data were also obtained including dissolved inorganic nutrients, salinity, transparency, temperature and upwelling indices. The CHEMTAX results were also related to microscopy counts and also spectral analysis of absorption of other samples from the same sampling campaigns. The pigment results showed that diatoms dominated from early spring to summer, coinciding with upwelling conditions, while cryptophytes, prymnesiophytes and prasinophytes dominated in autumn and winter, coinciding with seasonal stratification. Although the contribution of cyanobacteria to total Chl a was generally low, there were occasional sampling campaigns where it was exceptionally high, but these appeared not to be related to upwelling. Dinoflagellates and chrysophytes were minority groups although the pigment marker peridinin that was used to distinguish dinoflagellates was not adequate for distinguishing all the members of this group. CHEMTAX was particularly useful for discriminating between the smaller (0-20 mu m) classes of the microplankton that could not be easily identified by microscopy. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND

2014-12Journal article

Open Access

Time series analysis of data for sea surface temperature and upwelling components from the southwest coast of Portugal

Publication . Costa Goela, Priscila; Cordeiro, Clara; Danchenko, Sergei; Icely, John; Cristina, Sónia; Newton, Alice

This study relates sea surface temperature (SST) to the upwelling conditions off the southwest coast of Portugal using statistical analyses of publically available data. Optimum Interpolation (OI) of daily SST data were extracted from the United States (US) National Oceanic and Atmospheric Administration (NOAA) and data for wind speed and direction were from the US National Climatic Data Center. Time series were extracted at a daily frequency for a time horizon of 26 years. Upwelling indices were estimated using westerly (Q(x)) and southerly (Q(y)) Ekman transport components.In the first part of the study, time series were inspected for trend and seasonality over the whole period. The seasonally adjusted time series revealed an increasing slope for SST (0.15 degrees C per decade) and decreasing slopes for Q(x) (84.01 m(3) s(-1) km(-1) per decade) and Q(y) (-25.20 m(3) s(-1) km(-1) per decade), over the time horizon. Structural breaks analysis applied to the time series showed that a statistically significant incremental increase in SST was more pronounced during the last decade.Cross -correlation between upwelling indices and SST revealed a time delay of 5 and 2 days between Q(x) and SST, and between Qv and SST, respectively. A spectral analysis combined with the previous analysis enabled the identification of four oceanographic seasons. Those seasons were later recognised over a restricted time period of 4 years, between 2008 and 2012, when there was an extensive sampling programme for the validation of ocean colour remote sensing imagery. The seasons were defined as: summer, with intense and regular events of upwelling; autumn, indicating relaxation of upwelling conditions; and spring and winter, showing high inter annual variability in terms of number and intensity of upwelling events. (C) 2016 The Authors. Published by Elsevier B.V.

2016-07Journal article

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