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The Bay of Bonny, located along the Cameroon coastline, is home to diverse ecosystems. It is under significant pressure from large human activity, but remains very little studied, like much of the Gulf of Guinea. In order to understand its long-term shoreline variations and the role the wave regime plays in the evolution of the coastline, a study was conducted on the basis of optical image archives from Landsat 5 ∕ 7 ∕ 8 and Sentinel-2A/2B satellite missions acquired between October 1986 and May 2020, coupled with daily ERA-Interim wave re-analysis data covering the period from January 1986 to August 2019. Overall, the results show that the evolution of the coast is highly variable in space and time, as indicated by different levels of erosion (30.55 %), and accretion (27.7 %) on the decadal-scale, with the most significant variations occurring in estuarine areas. Nevertheless, 41.75% of the Cameroon shoreline remains stable during the study period. Three main periods (1986–1994; 1995–2005; 2006–2020) during which the coast underwent significant changes a different location were identified, reaching a retreat rate of up to −10 m/year in the northern section during the first period 1986–1994. The annual trend of significant wave heights anomaly along the coast (−5.6 to −4.1 mm/year) with wave height maxima estimated at 1.46 ± 0.65 m, where observed during the summer months (July–August). Monthly shoreline changes are inversely correlated with wave climate in some segments. Eigenvalue orthogonal decomposition analyses (Mode 1, Empirical Orthogonal Function) show that 76.3% of the observed variability would be due to the relatively strong local influence of erosion and accretion. This local influence can be related to wave regime at shorter timescale (monthly to seasonal) and the sediment variability from the source inland to the coast at longer timescale (seasonal to decadal). These observations explain a complex pattern of shoreline changes with an almost continuous retreat shoreline during the period 1986–2013 and a reversal in trend towards accretion during the period 2013–2020. EOF mode 2 explains 23.7% of variability, which can be potentially associated with the synergetic relationship between tidal currents and wave-induced longshore current, tidal currents and possibly pockets of human activity. This is attributed to an overall decrease in the supply of sediment via the coastal transport system that prevails in the Gulf of Guinea.

International audience; Les défis actuels de l’administration forestière ivoirienne sont la reconstitution du couvert forestier du pays à l’horizon 2040 avec un taux de reforestation annuel de 20%. Cette étude propose une méthode de mise en place d’un système de suivi des affectations des terres pour une agriculture intégrée au développement forestier et une gestion durable des ressources forestières du Sud-Ouest de la Côte d’Ivoire à partir de l’exploitation d’images satellitaires d’archives (optique et radar). Les prétraitements et les traitements réalisés sur des images LANDSAT ont permis d’abord d’évaluer la dynamique de l’occupation de sol à l’échelle du Sud-Ouest de la Côte d’Ivoire entre les années 1986, 2001 et 2015, et d’identifier les zones forestières les plus exposées (forêt classée de la Haute Dodo et de Cavally) aux activités agricoles. Ensuite, dans la forêt de la Haute Dodo, l’exploitation conjointe de la résolution spatiale et spectrale des images SENTINEL-2 et SPOT-6 a conduit à l’élaboration d’une cartographie des différentes exploitations agricoles (cacao, hévéa, palmier à huile, café...) à l’origine de la baisse importante des surfaces forestières. Enfin, dans la forêt de Cavally, la bonne résolution temporelle des données radar SENTINEL-1 a permis de faire un suivi saisonnier et annuel des formations forestières. Cette étude montre que les données satellitaires multicapteurs et multirésolutions peuvent être intégrées pour assurer un suivi des forêts tant sur le plan régional que local. Ces outils d’aide à la décision constituent des éléments pertinents auprès des parties prenantes pour la mise en œuvre d’une politique d’inversion des tendances à la dégradation des terres et des ressources naturelles en Côte d’Ivoire.

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article publié en français (p. 2-13), avec un résumé étendu en anglais (p. 14-15), et 3 planches couleur hors-texte (p. 53-54); International audience; Radar, owing to its geometry acquisition (directional and side viewing) and longer wavelengths, provides unique information on the Earth’s surface. It is complementary to optical remote sensors. The response of a scene to the wave emitted by a radar sensor is dependent primarily on a large number of factors including moisture, roughness, amount of vegetation, geometric structure of the scene, and, secondarily, on parameters of the system itself (wavelength, angle of incidence, polarization). Many studies have focused on the physical understandingof polarimetry, including backscatter, when characterizing a target (Huynen, 1970). The purpose of this work is to assess the potentialof radar data for the characterization of a complex lacustrine area and to evaluate the complementarity between radar and optical data for the identification of land use/land cover types. The study area is the lake system of Ichkeul-Bizerte, one of the important components of Tunisian coastal landscapes. It is located in northern Tunisia between latitudes N 37° 19’ and N 37° 5’. The area belongs to a collapse zonesurrounded by small hills and consequently the catchment is receiving various kinds of materials, inducing complex physical, chemical and biological processes in the water system. In the present study, multifrequency remote sensing data are used. A preprocessing phase wasperformed on the radar data, including geometric corrections and speckle reduction. Several speckle reduction filters were tested on radar bands (Median, Lee Kuan and Frost). Two evaluation criteria were used : a visual test and a statistical criterion. Color composite images have been produced, combining HH, HV and VV channels (plate 1). Intensity variations of the radar signal can be observed, which can be explained by wind-induced roughness differences of lake surfaces (Bizerte lake and Ichkeul lake). Mean backscatter is maximum in HV channel, for built-up and forest classes. Statistical and visual results of filtered images allowed us to retain the Enhanced Frost filter with a 3 x 3 pixels window. In addition to reducing speckle, this filter keeps the contours and details of information contained in radar channels. Using a 9 x 9 filter improves the separability between built-up and forest classes. Afterwards, radar images (ASAR and Palsar) and optical images (Landsat) have been re-sampled to the same pixel size of 15 m. The identification of the different scene components is based on their textural and spectral behavior. Textural parameters were calculated using the approach based on the co-occurrence matrix developed by Haralick et al. (1973). Least correlated parameters have been choosen. Thus, eight texture parameters were selected: standard deviation, mean, uniformity, dissimilarity, entropy, correlation, second angular momentum and contrast. These texture parameters are calculated for each of the radar bands CVV, LHV et LHH, unfiltered to preserve textural information. The optical data texture analysis was done using a mathematical morphology method that relies on processing techniques insensitive to radiometric variations (Kombé, 1999). Landsat ETM1 channel served as input image for morphological treatments. This approach included three phases : extraction of small structures, determination of an urban mask and reconstruction of urban patches. The evaluation of the potential of the various radar and optical data (spectral and textural) for identification and classification of land cover classes is made by means of multivariate statistical analysis. This analysis is used to the selection of variables and to study the optimal combinations of parameters to better discriminate cover classes. The linear combination method used is the Principal Component Analysis (PCA) which consists of a mathematical processing based on the analysis of the covariance of the image or the correlation matrix of several sets of data (Bonn and Rochon, 1992). Data integration was made in four steps, starting from the unfiltered data and going to processed data using different operator types. When a new parameter is added, it is checked whether this latter increases the total discriminant power obtained,based on the MPCC (Mathematical Programming with Complementary Constraints) and Kappa parameters. The results of performance classifications made after the four stages of application of the statistical analysis are presented at table 2. This gives us an overall classification accuracy of 75% from step I; this means that, on the basis of microwave multipolarisation information only, we are able to map only the main land cover classes. A filtered channel has improved the discrimination of different classes. The land cover classes are better identified with welldrawn boundaries and a high rate of elimination of isolated pixels. The average of correctly classified pixels (MPCC) is 86.7%. The textural channels improved separation between different classes of soil occupation. The percentage of correctly classified pixels reached 94.2%. The adding of the ETM1 derived channel obtained following the morphological processing in the linear combination has allowed the discrimination of urban structures on the classified image and increased the percentage of correctly classified pixels, reaching 96.2%. The final document generated by these treatments consists of a land use/land cover map. Altogether, eight classes are determined (plate 2). The evaluation of the results of the different steps is done based on MPCC parameters and on the Kappa index. The comparison of the land cover map andavailable cartographic document shows that the map derived from remote sensing data shows better cartographic fineness: it highlights localheterogeneity in the various classes.; Le but de ce travail est de présenter une méthodologie d’analyse et d’interprétation d’images satellitaires multisources radar RSO (ASAR et PALSAR) et optiques (Landsat ETM) visant à intervenir dans le domaine de la cartographie des classes d’occupation de sol dans les environs d’un système côtier méditerranéen qui est le système lacustre de Bizerte-Ichkeul. Les potentiels des données satellitaires ASAR, PALSAR et Landsat-7 sont comparées pour cartographier les principales classes d’occupation de sol du domaine d’étude. Les données radar polarimétriques de différents types (en bandes C et L ; en polarisations parallèles et croisées) brutes et filtrées, de même que des indices de texture (moyenne, écart-type, second moment angulaire, entropie, etc.) sont extraits de ces données. Des attributs géométriques extraitsdes données numériques par application des opérateurs de la morphologie mathématique (ouverture, fermeture, chapeau haut de forme) sont intégrés aux données précédentes. Après application de l’analyse statistique multivariée, seuls les paramètres les plus significatifs sontretenus et utilisés en quatre étapes dans un modèle de combinaison linéaire pour la mise en évidence des principales composantes du paysage côtier.

http://spie.org/Documents/ConferencesExhibitions/ERS-ESD13-Abstracts-lr.pdf

International audience; Mapping is a fundamental tool in the ecosystems studies. It is usually done by field records, but this method consumes a lot of time and resources. Remote sensing is a complementary tool but still need ground truth certification due to the scale factor. We present in this article a concept, the Extended Ground Truth, that try to keep the advantages of both techniques and offers the use of imaging tools while providing a ground truth. Then, we will develop this concept on one example concerning ecosystem analysis.

Canadian Journal of Remote Sensing, 2013, in press; International audience; This paper gives an illustration of the contribution of spatio-temporal multi-resolution of spaceborne radar data for the monitoring of land surfaces. More precisely, it illustrates the potential of C band spaceborne radar data, by using in synergy scatterometer and SAR (Synthetic Aperture Radar) sensors, for the spatio-temporal monitoring of evaporitic processes over a vast playa, the Chott el Djerid, located in central Tunisia. Scatterometer data from the ASCAT (Advanced Scatterometer) instrument are characterized by a high temporal frequency of acquisition, about 3 days over the Chott, with a spatial resolution of 25 km. It is well suited for an interpretation of radar temporal signatures in relationship with seasonal variations of surface states. SAR images obtained from both ASAR (Advanced SAR) and RADARSAT-2 sensors are less frequent (about 20 days) but provide a higher spatial resolution, allowing the discrimination of spatial patterns related to evaporitic processes. ASAR Wide Swath mode, associated to 150m of spatial resolution, allows for the monitoring of the whole Chott area, while RADARSAT-2, realizing full polarimetric acquisitions with a spatial resolution of 8 m over, allows for the discrimination of finer spatial patterns over a sub-area within the Chott. Both scatterometer and SAR data show an overall good agreement in radiometry. Polarimetry, available for the RADARSAT-2 data, allows to highlight striking spatial patterns in relation with the various sedimentation processes within the saline deposit over the chott.

International audience; A new approach has been proposed for radar and optical image fusion. Candidate images for fusion are polarimetric radar images and very high resolution stereoscopic optical images. The fused product is expected to produce more reliable large scale land cover classifications. In the first part of this paper, observation-based state-of-the-art methods for optical and radar image fusion are discussed. The idea of unmixing physical radar scattering mechanisms with the optical images has been proposed as a suitable means to improve the resolution of the polarimetric radar images. The second part focuses on a general description of the target algorithm. The suggested physical approach simulating synthetic scattering matrices with stereoscopic optical images is developed. Finally, future work to develop this unmixing algorithm is discussed.