ALBERT

Description: Ocean color satellite sensors are powerful tools to study and monitor the dynamics of suspended particulate matter (SPM) discharged by rivers in coastal waters. In this study, we test the capabilities of Landsat-8/Operational Land Imager (OLI), AQUA&TERRA/Moderate Resolution Imaging Spectroradiometer (MODIS) and MSG-3/Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors in terms of spectral, spatial and temporal resolutions to (i) estimate the seawater reflectance signal and then SPM concentrations and (ii) monitor the dynamics of SPM in the Rhône River plume characterized by moderately turbid surface waters in a micro-tidal sea. Consistent remote-sensing reflectance (Rrs) values are retrieved in the red spectral bands of these four satellite sensors (median relative difference less than ~16% in turbid waters). By applying a regional algorithm developed from in situ data, these Rrs are used to estimate SPM concentrations in the Rhône river plume. The spatial resolution of OLI provides a detailed mapping of the SPM concentration from the downstream part of the river itself to the plume offshore limits with well defined small-scale turbidity features. Despite the low temporal resolution of OLI, this should allow to better understand the transport of terrestrial particles from rivers to the coastal ocean. These details are partly lost using MODIS coarser resolutions data but SPM concentration estimations are consistent, with an accuracy of about 1 to 3 g·m−3 in the river mouth and plume for spatial resolutions from 250 m to 1 km. The MODIS temporal resolution (2 images per day) allows to capture the daily to monthly dynamics of the river plume. However, despite its micro-tidal environment, the Rhône River plume shows significant short-term (hourly) variations, mainly controlled by wind and regional circulation, that MODIS temporal resolution failed to capture. On the contrary, the high temporal resolution of SEVIRI makes it a powerful tool to study this hourly river plume dynamics. However, its coarse resolution prevents the monitoring of SPM concentration variations in the river mouth where SPM concentration variability can reach 20 g·m−3 inside the SEVIRI pixel. Its spatial resolution is nevertheless sufficient to reproduce the plume shape and retrieve SPM concentrations in a valid range, taking into account an underestimation of about 15%–20% based on comparisons with other sensors and in situ data. Finally, the capabilities, advantages and limits of these satellite sensors are discussed in the light of the spatial and temporal resolution improvements provided by the new and future generation of ocean color sensors onboard the Sentinel-2, Sentinel-3 and Meteosat Third Generation (MTG) satellite platforms.

Description: Remote Sensing, Vol. 10, Pages 1140: Detecting and Quantifying a Massive Invasion of Floating Aquatic Plants in the Río de la Plata Turbid Waters Using High Spatial Resolution Ocean Color Imagery Remote Sensing doi: 10.3390/rs10071140 Authors: Ana I. Dogliotti Juan I. Gossn Quinten Vanhellemont Kevin G. Ruddick The massive development of floating plants in floodplain lakes and wetlands in the upper Middle Paraná river in the La Plata basin is environmentally and socioeconomically important. Every year aquatic plant detachments drift downstream arriving in small amounts to the Río de la Plata, but huge temporary invasions have been observed every 10 or 15 years associated to massive floods. From late December 2015, heavy rains driven by a strong El Niño increased river levels, provoking a large temporary invasion of aquatic plants from January to May 2016. This event caused significant disruption of human activities via clogging of drinking water intakes in the estuary, blocking of ports and marinas and introducing dangerous animals from faraway wetlands into the city. In this study, we developed a scheme to map floating vegetation in turbid waters using high-resolution imagery, like Sentinel-2/SMI (MultiSpectral Imager), Landsat-8/OLI (Operational Land Imager), and Aqua/MODIS (MODerate resolution Imager Spectroradiometer)-250 m. A combination of the Floating Algal Index (that make use of the strong signal in the NIR part of the spectrum), plus conditions set on the RED band (to avoid misclassifying highly turbid waters) and on the CIE La*b* color space coordinates (to confirm the visually “green” pixels as floating vegetation) were used. A time-series of multisensor high resolution imagery was analyzed to study the temporal variability, covered area and distribution of the unusual floating macroalgae invasion that started in January 2016 in the Río de la Plata estuary.

Description: Remote Sensing, Vol. 10, Pages 352: Atmospheric Correction Inter-Comparison Exercise Remote Sensing doi: 10.3390/rs10020352 Authors: Georgia Doxani Eric Vermote Jean-Claude Roger Ferran Gascon Stefan Adriaensen David Frantz Olivier Hagolle André Hollstein Grit Kirches Fuqin Li Jérôme Louis Antoine Mangin Nima Pahlevan Bringfried Pflug Quinten Vanhellemont The Atmospheric Correction Inter-comparison eXercise (ACIX) is an international initiative with the aim to analyse the Surface Reflectance (SR) products of various state-of-the-art atmospheric correction (AC) processors. The Aerosol Optical Thickness (AOT) and Water Vapour (WV) are also examined in ACIX as additional outputs of AC processing. In this paper, the general ACIX framework is discussed; special mention is made of the motivation to initiate the experiment, the inter-comparison protocol, and the principal results. ACIX is free and open and every developer was welcome to participate. Eventually, 12 participants applied their approaches to various Landsat-8 and Sentinel-2 image datasets acquired over sites around the world. The current results diverge depending on the sensors, products, and sites, indicating their strengths and weaknesses. Indeed, this first implementation of processor inter-comparison was proven to be a good lesson for the developers to learn the advantages and limitations of their approaches. Various algorithm improvements are expected, if not already implemented, and the enhanced performances are yet to be assessed in future ACIX experiments.

Description: 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 (ρw) 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. ρw 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 ρw 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.