Spatio-temporal interpolation of Sea Surface Temperature using high resolution remote sensing data

International audienceIn this work, we present a statistical model to generate relevant reanalysis of geophysical parameters. In particular, we use a stochastic equation to control the temporal and spatial variability of the signal and we take into account the possible error of the observations. We resolve the system iteratively using an ensemble Kalman filter and smoother. We apply the methodology to remote sensing data of Sea Surface Temperature (SST). We use high resolution SST maps provided by an infrared sensor, sensible to the presence of cloud. Comparing the results with the reference SST reanalysis, we demonstrate the capability of our approach to interpolate missing data and keep into account the spatial and temporal consistency of the SST signal

GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection

Representing maritime traffic patterns and detecting anomalies from them are key to vessel monitoring and maritime situational awareness. We propose a novel approach-referred to as GeoTrackNet-for maritime anomaly detection from AIS data streams. Our model exploits state-of-the-art neural network schemes to learn a probabilistic representation of AIS tracks, then uses a contrario detection to detect abnormal events. The neural network helps us capture complex and heterogeneous patterns in vessels' behaviors, while the a contrario detection takes into account the fact that the learned distribution may be location-dependent. Experiments on a real AIS dataset comprising more than 4.2 million AIS messages demonstrate the relevance of the proposed method

AIS-based Evaluation of Target Detectors and SAR Sensors Characteristics for Maritime Surveillance

International audienceThis paper studies the performances of different ship detectors based on adaptive threshold algorithms. The detec- tion algorithms are based on various clutter distributions and assessed automatically with a systematic methodology. Evaluation using large datasets of medium resolution SAR images and AIS (Automatic Identification System) data as ground truths allows to evaluate the efficiency of each detector. Depending on the datasets used for testing, the detection algorithms offer different advantages and disadvantages. The systematic method used in discriminating real detected targets and false alarms in order to determine the detection rate, allows us to perform an appropriate and consistent comparison of the detectors. The impact of SAR sensors characteristics (incidence angle, polarization, frequency and spatial resolution) is fully assessed, the vessels' length being also considered. Experiments are conducted on Radarsat-2 and CosmoSkymed ScanSAR datasets and AIS data acquired by coastal stations

Simulation on large scale of acoustic signals for array processing

International audienceDue to operational constraints for underwater data acquisition, simulating realistic sonar data, like images, swath bathymetry profiles or interferometric signals, is crucial for tuning detection and classification algorithms according to sensors settings, sea-bottom nature and topography. Moreover, the robustness of any performance estimation or prediction can be greatly enhanced, as soon as such a simulation tool provides a modular and flexible underwater world representation (multiple sensors, environments and acquisition conditions). For signal and array processing, it is essential not only to generate the signal energy backscattered by a resolution cell, but also to produce a phase information that conveys its theoretical statistical properties. To this end, this paper proposes a Brownian motion-based approach to generate complex Gaussian signals from the contribution of a set of extended single scatterers inside a resolution cell. The resulting process preserves the conservation of energy when integrating on surfaces, as well as the decorrelation between different areas of the sea bottom, and the right interference between two sensors for interferometric applications

Interpolated swell fields from SAR measurements

International audienceSynthetic Aperture Radar (SAR) sensors on-board satellites are very well suited for observing sea surface geophysical parameters such as ocean swell. But on a very large scale, SAR data are too sparse for deriving some global information. From the original work of Collard et al. (2009), and following some generic assumption on the physics of the swell propagation in deep water, it was shown that using a back-propagating scheme, it was possible to retrieve the source of the swell system and then generate a propagating field. In this paper, we are proposing a simpler and original approach, by assimilating the SAR data into a given swell field and then using a Kalman Filter/Smoother technique for updating the main parameters of the swell (wavelength, direction, and significant wave height) within the complete field. This method shows very encouraging results which will be confronted with in situ measurements when available

Projet MOPS : Système dédié à l'utilisation des signaux GNSS pour l'océanographie et la surveillance de la surface de la mer

International audienceCe papier présente la réalisation d'un système avancé de réception de signaux GNSS qui enregistre simultanément le signal direct issu d'un satellite et le signal réfléchi par la surface maritime. La réception des signaux est réalisée à l'aide de deux antennes localisées à une dizaine de mètres au dessus de la surface maritime. Cette plateforme expérimentale est constituée de plusieurs éléments : un module électronique radiofréquence RF en bande L1 (1575.42 GHz), deux convertisseurs de fréquence intermédiaire FI (70 MHz), deux modules d'acquisition et de numérisation de signaux analogiques (8 GS/s sur 10 bits et 420 MS/s sur 12 bits). Le système ainsi réalisé doit permettre d'observer les fluctuations rapides et lentes de la surface de mer à petite et grande échelle avec de bonnes précisions. La constitution de cette plateforme s'inscrit dans le cadre du projet MOPS [1] porté par l'ENSTA-Bretagne, Télécom Bretagne et l'IFREMER. Ce projet est soutenu par le GIS Europôle Mer

Spatio-temporal segmentation of mesoscale ocean surface dynamics using satellite data

International audienceMulti-satellite measurements of altimeter-derived Sea Surface Height (SSH) and Sea Surface Temperature (SST) provide a wealth of information about ocean circulation, especially mesoscale ocean dynamics which may involve strong spatio-temporal relationships between SSH and SST fields. Within an observation-driven framework, we investigate the extent to which mesoscale ocean dynamics may be decomposed into a superimposition of dynamical modes, characterized by different local regressions between SSH and SST fields. Formally, we develop a novel latent class regression model to identify dynamical modes from joint SSH and SST observation series. Applied to the highly dynamical Agulhas region off South Africa, we demonstrate and discuss the geophysical relevance of the proposed mixture model to achieve a spatio-temporal segmentation of the upper ocean dynamics

Technologies numériques et environnement

International audienceThis paper discusses the relationship between digital technologies and environment. The aim is to better understand to which extent these technologies can help us to reduce our negative ecological impacts, what are their own ecological impacts and how they can be overcome. To do so, we suggest a taxonomy of the relationship between digital technologies and environment, give examples about how these technologies can help to preserve this environment, and discuss the limits of green digital technologies to save the planet

Technologies numériques et environnement

International audienceThis paper discusses the relationship between digital technologies and environment. The aim is to better understand to which extent these technologies can help us to reduce our negative ecological impacts, what are their own ecological impacts and how they can be overcome. To do so, we suggest a taxonomy of the relationship between digital technologies and environment, give examples about how these technologies can help to preserve this environment, and discuss the limits of green digital technologies to save the planet