Performance and Uncertainty of Satellite-Derived Bathymetry Empirical Approaches in an Energetic Coastal Environment

International audienceObjectives of this study are to evaluate the performance of different satellite-derived bathymetry (SDB) empirical models developed for multispectral satellite mission applications and to propose an uncertainty model based on inferential statistics. The study site is the Arcachon Bay inlet (France). A dataset composed of 450,837 echosounder data points and 89 Sentinel-2 A/B and Landsat-8 images acquired from 2013 to 2020, is generated to test and validate SDB and uncertainty models for various contrasting optical conditions. Results show that water column optical properties are characterized by a high spatio-temporal variability controlled by hydrodynamics and seasonal conditions. The best performance and highest robustness are found for the cluster-based approach using a green band log-linear regression model. A total of 80 satellite images can be exploited to calibrate SDB models, providing average values of root mean square error and maximum bathymetry of 0.53 m and 7.3 m, respectively. The uncertainty model, developed to extrapolate information beyond the calibration dataset, is based on a multi-scene approach. The sensitivity of the model to the optical variability not explained by the calibration dataset is demonstrated but represents a risk of error of less than 5%. Finally, the uncertainty model applied to a diachronic analysis definitively demonstrates the interest in SDB maps for a better understanding of morphodynamic evolutions of large-scale and complex coastal system

Geomorphological control of sandy beaches by a mixed-energy tidal inlet

Coastal areas adjacent to tidal inlets are highly valuable areas for marine ecosystems where a wide range of social and economic activities can be found. These areas can be differentiated from open coast due to their specific morphological behaviour caused by a complex nearshore bathymetry and interactions between wave and tidal forcing. The understanding of these interactions is usually limited by the lack of a systemic approach and the scarce availability of comprehensive datasets covering subtidal, intertidal and supratidal areas at large spatial and temporal scales. Here, the complementary use of different bathymetric and topographic datasets and the development of innovative methods using satellite imagery, offers the opportunity to develop a comprehensive understanding of the timescales and the key processes involved in the dynamics of tidal inlets and its control on the downdrift coast. The use of satellite-derived bathymetric maps, computed over the last two decades, showed two sequences of 8 and 9 years where large sandy shoals migrated along the tidal inlet and welded onto the downdrift coast. Although the study period covers one of the most energetic winter over the last decades, the most significant sediment volume changes (±300 m3/m) observed along the three kilometres of beach located south to the inlet were mostly attributed to the migration and welding of these sandy shoals, whereas the offshore wave forcing was of secondary importance. It was also demonstrated that these migrating and welding events had an impact on the pattern of the nearshore bathymetry and sandbars down to 10 km south to the inlet. Primary welding events near to the inlet are associated to the formation of kilometre-long and alongshore uniform nearshore sandbars that subsequently migrate further down the coast causing secondary welding events. The ability to understand and define the spatial and temporal boundaries at which beach behaviour is controlled by a local tidal inlet gives the opportunity to develop sediment compartment approach in order to make accurate predictions of future beach behaviour

Effect of inherent optical properties variability on the chlorophyll retrieval from ocean color remote sensing: an in situ approach

The impact of the inherent optical properties (IOP) variability on the chlorophyll, Chl, retrieval from ocean color remote sensing algorithms is analyzed from an in situ data set covering a large dynamic range. The effect of the variability of the specific phytoplankton absorption coefficient, a(phy)/Chl, specific particulate backscattering coefficient, b(bp)/Chl, and colored detrital matter absorption to non-water absorption ratio, a(cdm)/a(nw), on the performance of standard operational algorithms is examined. This study confirms that empirical algorithms are highly dependent on the specifics IOP values (especially b(bp)/Chl and a(cdm)/a(nw)): Chl is over-estimated in waters with specific IOP values higher than averaged values, and vice versa. These results clearly indicate the necessity to account for the influence of the specific IOP variability in Chl retrieval algorithms

Potential of High-Resolution Pléiades Imagery to Monitor Salt Marsh Evolution After Spartina Invasion

International audienceAn early assessment of biological invasions is important for initiating conservation strategies. Instrumental progress in high spatial resolution (HSR) multispectral satellite sensors greatly facilitates ecosystems' monitoring capability at an increasingly smaller scale. However, species detection is still challenging in environments characterized by a high variability of vegetation mixing along with other elements, such as water, sediment, and biofilm. In this study, we explore the potential of Pléiades HSR multispectral images to detect and monitor changes in the salt marshes of the Bay of Arcachon (SW France), after the invasion of Spartina anglica. Due to the small size of Spartina patches, the spatial and temporal monitoring of Spartina species focuses on the analysis of five multispectral images at a spatial resolution of 2 m, acquired at the study site between 2013 and 2017. To distinguish between the different types of vegetation, various techniques for land use classification were evaluated. A description and interpretation of the results are based on a set of ground truth data, including field reflectance, a drone flight, historical aerial photographs, GNSS and photographic surveys. A preliminary qualitative analysis of NDVI maps showed that a multi-temporal approach, taking into account a delayed development of species, could be successfully used to discriminate Spartina species (sp.). Then, supervised and unsupervised classifications, used for the identification of Spartina sp., were evaluated. The performance of the species identification was highly dependent on the degree of environmental noise present in the image, which is season-dependent. The accurate identification of the native Spartina was higher than 75%, a result strongly affected by intra-patch variability and, specifically, by the presence of areas with a low vegetation density. Further, for the invasive Spartina anglica, when using a supervised classifier, rather than an unsupervised one, the accuracy of the classification increases from 10% to 90%. However, both algorithms highly overestimate the areas assigned to this species. Finally, the results highlight that the identification of the invasive species is highly dependent both on the seasonal presence of itinerant biological features and the size of vegetation patches. Further, we believe that the results could be strongly improved by a coupled approach, which combines spectral and spatial information, i.e., pattern-recognition techniques

Time Series of Bio-Optical Properties in a Subtropical Gyre: Implications for the Evaluation of Interannual Trends of Biogeochemical Properties

With a validated Quasi‐Analytical Algorithm, an 11 year (1998–2008) monthly time series of the primary optical properties of waters in the center of the South Pacific gyre was developed from Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Also derived are chlorophyll a (Chl a) concentrations with the operational empirical algorithms for SeaWiFS and MODIS. The optical properties include the absorption coefficient (at 443 nm) of phytoplankton (aph) and that of the combination of detritus and gelbstoff (adg). From these time series, we further derived their annual background (summer low) and seasonal intensity (the difference between winter high and summer low). These time series show that (1) the optical properties have different seasonal and interannual variations, indicating different dynamics of these properties in the subtropical gyre; (2) there is a decreasing trend (r2 = 0.24) of the background aph in the 1998–2008 period and an increasing trend of the aph seasonal intensity (r2 = 0.11) for this period, and both trends are not statistically significant; (3) the aph time series agrees with the Chl a time series at the seasonal scale, but differs with respect to interannual variations; and (4) different interannual trends could be inferred with different time frames. These results emphasize that it is difficult to draw unequivocal conclusions about long‐term trends of biogeochemical properties in the oceans with the current relatively short bio‐optical records. To clarify and predict such trends, it is critical to get a full account of the forces that are responsible for the seasonal and interannual variations of these properties

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal ((w)) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i) an assessment of existing atmospheric correction (AC) algorithms developed for turbid coastal waters; and (ii) a switching method that automatically selects the most sensitive SPM vs. (w) relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer) to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR) spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE) with a method based on multi-temporal analyses of atmospheric constituents (MACCS). For the selected scenes, the ACOLITE-MACCS difference was lower than 7%. Despite some inaccuracies in (w) retrieval, we demonstrate that the SPM concentration can be reliably estimated using OLI, MODIS and VIIRS, regardless of their differences in spatial and spectral resolutions. Match-ups between the OLI-derived SPM concentration and autonomous field measurements from the Loire and Gironde estuaries' monitoring networks provided satisfactory results. The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors (namely Sentinel2/MSI and Sentinel3/OLCI) to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions

Time Series of Bio-Optical Properties in a Subtropical Gyre: Implications for the Evaluation of Interannual Trends of Biogeochemical Properties

With a validated Quasi‐Analytical Algorithm, an 11 year (1998–2008) monthly time series of the primary optical properties of waters in the center of the South Pacific gyre was developed from Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Also derived are chlorophyll a (Chl a) concentrations with the operational empirical algorithms for SeaWiFS and MODIS. The optical properties include the absorption coefficient (at 443 nm) of phytoplankton (aph) and that of the combination of detritus and gelbstoff (adg). From these time series, we further derived their annual background (summer low) and seasonal intensity (the difference between winter high and summer low). These time series show that (1) the optical properties have different seasonal and interannual variations, indicating different dynamics of these properties in the subtropical gyre; (2) there is a decreasing trend (r2 = 0.24) of the background aph in the 1998–2008 period and an increasing trend of the aph seasonal intensity (r2 = 0.11) for this period, and both trends are not statistically significant; (3) the aph time series agrees with the Chl a time series at the seasonal scale, but differs with respect to interannual variations; and (4) different interannual trends could be inferred with different time frames. These results emphasize that it is difficult to draw unequivocal conclusions about long‐term trends of biogeochemical properties in the oceans with the current relatively short bio‐optical records. To clarify and predict such trends, it is critical to get a full account of the forces that are responsible for the seasonal and interannual variations of these properties

Time Series of Bio-Optical Properties in a Subtropical Gyre: Implications for the Evaluation of Interannual Trends of Biogeochemical Properties

With a validated Quasi‐Analytical Algorithm, an 11 year (1998–2008) monthly time series of the primary optical properties of waters in the center of the South Pacific gyre was developed from Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Also derived are chlorophyll a (Chl a) concentrations with the operational empirical algorithms for SeaWiFS and MODIS. The optical properties include the absorption coefficient (at 443 nm) of phytoplankton (aph) and that of the combination of detritus and gelbstoff (adg). From these time series, we further derived their annual background (summer low) and seasonal intensity (the difference between winter high and summer low). These time series show that (1) the optical properties have different seasonal and interannual variations, indicating different dynamics of these properties in the subtropical gyre; (2) there is a decreasing trend (r2 = 0.24) of the background aph in the 1998–2008 period and an increasing trend of the aph seasonal intensity (r2 = 0.11) for this period, and both trends are not statistically significant; (3) the aph time series agrees with the Chl a time series at the seasonal scale, but differs with respect to interannual variations; and (4) different interannual trends could be inferred with different time frames. These results emphasize that it is difficult to draw unequivocal conclusions about long‐term trends of biogeochemical properties in the oceans with the current relatively short bio‐optical records. To clarify and predict such trends, it is critical to get a full account of the forces that are responsible for the seasonal and interannual variations of these properties

Toward Sentinel-2 High Resolution Remote Sensing of Suspended Particulate Matter in Very Turbid Waters: SPOT4 (Take5) Experiment in the Loire and Gironde Estuaries

At the end of the SPOT4 mission, a four-month experiment was conducted in 2013 to acquire high spatial (20 m) and high temporal (5 days) resolution satellite data. In addition to the SPOT4 (Take5) dataset, we used several Landsat5, 7, 8 images to document the variations in suspended particulate matter (SPM) concentration in the turbid Gironde and Loire estuaries (France). Satellite-derived SPM concentration was validated using automated in situ turbidity measurements from two monitoring networks. The combination of a multi-temporal atmospheric correction method with a near-infrared to visible reflectance band ratio made it possible to quantify SPM surface concentration in moderately to extremely turbid waters (38-4320 g center dot m(-3)), at an accuracy sufficient to detect the maximum turbidity zone (MTZ) in both estuaries. Such a multi-sensor approach can be applied to high spatial resolution satellite archives and to the new ESA Sentinel-2 mission. It offers a promising framework to study the response of estuarine ecosystems to global changes at unprecedented spatio-temporal resolution