This bibliographic review provides an overview of techniques used to detect marine litter using remote sensing. The review classified studies in terms of platform (satellite, aircrafts, drones), ...sensors (passive or active), spectral (visible, infrared, microwaves), spatial resolution (<1 to >30 m), type and size (macroplastics, microplastics), or classification methodology (sighting, photointerpretation, supervised). Most studies applied satellite information to address marine litter using multi- and hyper- spectral optical sensors. The correspondence analysis on analyzed variables exhibited that aircrafts with high spatial resolution (<3 m) with optical sensors (λ = 400 to 2500 nm) seem to be the most optimum combination to target marine litter, while satellites carrying Synthetic Aperture Radar (SAR) sensors (λ = 3.1 to 5.6 cm) may detect sea-slicks associated to surfactants that might contain high concentration of microplastics. Gaps indicate that future goals in marine litter detection should be addressed with platforms including optical and SAR sensors.
•Combinations of platform, sensors, spectral resolution are addressing marine litter.•Optical sensors onboard aircrafts target marine litter at precise spatial resolution.•Sea-slicks might be inferred by SAR sensors.•Marine litter detection requires optical and SAR sensors for future advances.
During summer, when oligotrophic conditions prevail offshore in the Mediterranean Sea, enhanced phytoplankton stripes are often observed in nearshore waters. In this study, we examine the cross-shore ...hydrographic variability and the associated microbial plankton communities in this zone. Detailed cross-shore underway sampling at 47 coastal sites spread along the Balearic and Catalan coasts revealed the widespread existence of narrow bands of warm and decreased salinity water beholding high phytoplankton biomass (up to 50-fold vs. offshore chlorophyll). Most intense physical and biological anomalies along these transects were generally constrained to the first hundred meters from the shoreline (i.e. a transition zone starting at ̴ 400 m). We use Principal Component Analysis (PCA) and k-means cluster analysis to categorized T, S and Chl in three main types of cross-shore trends. Prevalence of exponential-shaped Chl trends was observed particularly in areas with shoreward directed winds (B1-type). The other two trends (B2 and B3) presented variations off the coast produced by alongshore structures like river plumes, city outfalls and other features. Exponential-shaped cross-shore chlorophyll distribution (B1-type) accumulated 90% of the total transect Chl variation in the first 367±190m from the shoreline, whereas this distance was variable in the other profile types. Repeated daily sampling at one site with this transect typology revealed that wind forcing variations produced fast response on cross-shore T and S properties. Chl was less sensitive to changes at this time-scale. Phytoplankton communities exhibited site-dependent responses to the nearshore environment. Pico- and nanoplankton assemblages, typically dominating coastal assemblages during summer in the Mediterranean Sea, showed lower cross-shore variation. Conversely, larger response to nearshore conditions was observed in microplankton populations. These larger cells, represented by dinoflagellates, cryptophytes and diatoms, were able to actively exploit the nearshore conditions constituting an independent and distinct assemblage from that one prevailing offshore. Our results suggest that despite the importance of local-scale processes in determining biotic structure, some common patterns emerge providing clues on the main drivers of this nearshore niche.
The capability of L-band radiometry to monitor surface soil moisture (SM) at global scale has been analyzed in numerous studies, mostly in the framework of the ESA SMOS and NASA SMAP missions. To ...retrieve SM from L-band radiometric observations, two significant effects have to be accounted for, namely soil roughness and vegetation optical depth. In this study, soil roughness effects on retrieved SM values were evaluated using brightness temperatures acquired by the L-band ELBARA-II radiometer, over a vineyard field at the Valencia Anchor Station (VAS) site during the year 2013. Different combinations of the values of the model parameters used to account for soil roughness effects (HR, QR, NRH and NRV) in the L-MEB model were evaluated. The L-MEB model (L-band Microwave Emission of the Biosphere) is the forward radiative transfer model used in the SMOS soil moisture retrieval algorithm. In this model, HR parameterizes the intensity of roughness effects, QR accounts for polarization effects, and NRH and NRV parameterize the variations of the soil reflectivity as a function of the observation angle, θ, respectively for both H (Horizontal) and V (Vertical) polarizations. These evaluations were made by comparing in-situ measurements of SM (used here as a reference) against SM retrievals derived from tower-based ELBARA-II brightness temperatures mentioned above. The general retrieval approach consists of the inversion of L-MEB. Two specific configurations were tested: the classical 2-Parameter (2-P) retrieval configuration where SM and τNAD (vegetation optical depth at nadir) are retrieved, and a 3-Parameter (3-P) configuration, accounting for the additional effects of the vineyard vegetation structure.
Using the 2-P configuration, it was found that setting NRp (p=H or V) equals to −1 provided the best SM estimations in terms of correlation and unbiased Root Mean Square Error (ubRMSE). The assumption NRV=NRH=−1 simplifies the L-MEB retrieval, since the two parameters τNAD and HR can then be grouped and retrieved as a single parameter (method here defined as the Simplified Retrieval Method (SRP)). The main advantage of the SRP method is that it is not necessary to calibrate HR before performing the SM retrievals. Using the 3-P configuration, the results improved, with respect to SM retrievals, in terms of correlation and ubRMSE, as the structural characteristics of the vineyards were better accounted for. However, this method still requires the calibration of HR, a disadvantage for operational applications. Finally, it was found that the use of in-situ roughness measurements to calibrate the roughness model parameters did not provide significant improvements in the SM retrievals as compared to the SRP method.
•Roughness parameterizations at L-band were evaluated using in situ radiometric data.•2-P and 3-P retrievals, accounting for changes in vegetation structure, were tested.•Lower performances in SM retrievals were obtained for increasing values of HR.•Best SM retrievals were generally obtained using NRV=NRH=−1.•The use of in situ roughness measurements did not improve SM retrievals.
We estimated pelagic primary production (PP) in the
coastal (<200 m depth) Mediterranean Sea from satellite-borne data,
its contribution to basin-scale carbon fixation, its variability, and
long-term ...trends during the period 2002–2016. Annual coastal PP was
estimated at 0.041 Gt C, which approximately represents 12 % of total
carbon fixation in the Mediterranean Sea. About 51 % of this production
occurs in the eastern basin, whereas the western and Adriatic shelves
contribute with ∼25 % each of total coastal production.
Strong regional variability is revealed in coastal PP, from high-production
areas (>300 g C m−2) associated with major river
discharges to less productive provinces (<50 g C m−2) located
in the southeastern Mediterranean. PP variability in the Mediterranean Sea
is dominated by interannual variations, but a notable basin-scale decline (17 %) has been observed since 2012 concurring with a period of increasing sea
surface temperatures in the Mediterranean Sea and positive North Atlantic
Oscillation and Mediterranean Oscillation climate indices. Long-term trends
in PP reveal slight declines in most coastal areas (−0.05 to −0.1 g C m−2 per decade) except in the Adriatic where PP increases at +0.1 g C m−2 per decade. Regionalization of coastal waters based on PP seasonal
patterns reveals the importance of river effluents in determining PP in
coastal waters that can regionally increase up to 5-fold. Our study
provides insight into the contribution of coastal waters to basin-scale carbon
balances in the Mediterranean Sea while highlighting the importance of the
different temporal and spatial scales of variability.
The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the ...Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those observed by SMOS at the same dates and time. They were also used for the L-MEB model inversion to retrieve soil moisture (SM), which later on have been compared to those provided by SMOS as level 3 data. A good correlation between both TB datasets was found, improving year by year, mainly due to the decrease of precipitations in the analyzed period and the mitigation of radio frequency interferences at L-band. The larger homogeneity of the radiometer footprint as compared to SMOS explains the higher variability of its TB. Periods of more intense precipitation (spring and autumn) also presented higher SM, which corroborates the consistency of SM retrieved from ELBARA-II’s observations. However, the results show that SMOS level 3 data underestimate SM as compared to ELBARA-II’s, probably due to the influence of the small soil fraction which is not cultivated in vineyards. SMOS estimations in descending orbit (6 pm) had better quality (higher correlation, lower RMSE and bias) than the ones in ascending orbit (6 am, when there is a higher soil moisture).
La misión de SMOS (Soil Moisture and Ocean Salinity) se lanzó el 2 de Noviembre de 2009 con el objetivo de proporcionar datos de humedad del suelo y salinidad del mar. La principal actividad de la conocida como Valencia Anchor Station (VAS) es asistir en la validación a largo plazo de productos de suelo de SMOS. El presente estudio se centra en una validación de datos de nivel 3 de SMOS en la VAS con medidas in situ tomadas en el periodo 2010-2012. El radiómetro Elbara-II está situado dentro de los confines de la VAS, observando un campo de viñedos que se considera representativo de una gran proporción de un área de 50×50 km, suficiente para cubrir un footprint de SMOS. Las temperaturas de brillo (TB) adquiridas por ELBARA-II se compararon con las observadas por SMOS en las mismas fechas y horas. También se utilizó la inversión del modelo L-MEB con el fin de obtener humedades de suelo (SM) que, posteriormente, se compararon con datos de nivel 3 de SMOS. Se ha encontrado una buena correlación entre ambas series de TB, con mejoras año tras año, achacable fundamentalmente a la disminución de precipitaciones en el periodo objeto de estudio y a la mitigación de las interferencias por radiofrecuencia en banda L. La mayor homogeneidad del footprint del radiómetro ELBARA-II frente al de SMOS explica la mayor variabilidad de sus TB. Los periodos de precipitación más intensa (primavera y otoño) también son de mayor SM, lo que corrobora la consistencia de los resultados de SM simulados a través de las observaciones del radiómetro. Sin embargo, se debe resaltar una subestimación por parte de SMOS de los valores de SM respecto a los obtenidos por ELBARA-II, presumiblemente debido a la influencia que la pequeña fracción de suelo no destinado al cultivo de la vid tiene sobre SMOS. Las estimaciones por parte de SMOS en órbita descendente (6 p.m.) resultaron de mayor calidad (mayor correlación y menores RMSE y bias) que en órbita ascendente (6 a.m., momento de mayor humedad de suelo).
In this paper, roughness parameterizations providing best retrievals of soil moisture (SM) at L-band were evaluated. Different parameterizations were tested to find the best correlation R, bias and ...ubRMSE when comparing retrieved SM and in situ SM measurements carried out at the VAS (Valencia Anchor Station) over a vineyard field. Roughness measurements were always performed after the agricultural practices in the vineyard. These in situ data was used as input of the L-MEB (L-band Microwave Emission of the Biosphere) model, which permits the retrieval of SM and TAU (vegetation optical depth). In addition, a simplified method consisting on the retrieval of a parameter which combines the effects of roughness and TAU was tested. Significantly higher correlation (R=0.86) for SM was found using this method, while the absolute bias (-0.062) and RMSE (0.069) were slightly higher than for other roughness parameterizations.
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