International audienceWetlands provide a vital resource to ecosystem services and associated rural livelihoods but their extent, geomorphological heterogeneity and flat topography make the representation of their hydrological functioning complex. A semi automated method exploiting 526 MODIS (Moderate Resolution Imaging Spectroradiometer) 8-day 500 m resolution images was developed to study the spatial and temporal dynamics of the annual flood across the Niger Inner Delta over the period 2000–2011. A composite band ratio index exploiting the Modified Normalised Difference Water Index (MNDWI) and Normalised Difference Moisture Index (NDMI) with fixed thresholds provided the most accurate detection of flooded areas out of six commonly used band ratio indices. K-means classified Landsat images were used to calibrate the thresholds. Estimated flooded surface areas were evaluated against additional classified Landsat images, previous studies and field stage data for a range of hydrological units: river stretches, lakes, floodplains and irrigated areas. This method illustrated how large amounts of MODIS images may be exploited to monitor flood dynamics with adequate spatial and temporal resolution and good accuracy, except during the flood rise due to cloud presence. Previous correlations between flow levels and flooded areas were refined to account for the hysteresis as the flood recedes and for the varying amplitude of the flood. Peak flooded areas varied between 10 300 km2 and 20 000 km2, resulting in evaporation losses ranging between 12 km3 and 21 km3. Direct precipitation assessed over flooded areas refined the wetland’s water balance and infiltration estimates. The knowledge gained on the timing, duration and extent of the flood across the wetland and in lakes, floodplains and irrigated plots may assist farmers in agricultural water management. Furthermore insights provided on the wetland’s flood dynamics may be used to develop and calibrate a hydraulic model of the flood in the Niger Inner Delta

International audienceThe increasing availability of Very High Spatial Resolution images enables accurate digital maps production as an aid for management in the agricultural domain. In this study we develop a comprehensive and automatic tool for vineyard detection, delineation and characterizationusing aerial images and without any parcel plan availability. In France, vineyard training methods in rows or grids generate periodic patterns which make frequency analysis a suitable approach. The proposed method computes a Fast Fourier Transform on an aerial image, providing the delineation of vineyards and the accurate evaluation of row orientation and interrow width. These characteristics are then used to extract individual vine rows, with the aim of detecting missing vine plants and characterizing cultural practices. Using the red channel of an aerial image, 90\% of the parcels have been detected; 92\% have been correctly classified according to their rate of missing vine plants and 81\% according to their cultural practice (weed control method). The automatic process developed can be easily integrated into the final user's Geographical Information System and produces useful information for vineyard managemen

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SUMMARYPorAS, a new approximate-state Riemann solver, is proposed for hyperbolic systems of conservation laws with source terms and porosity. The use of porosity enables a simple representation of urban floodplains by taking into account the global reduction in the exchange sections and storage. The introduction of the porosity coefficient induces modified expressions for the fluxes and source terms in the continuity and momentum equations. The solution is considered to be made of rarefaction waves and is determined using the Riemann invariants. To allow a direct computation of the flux through the computational cells interfaces, the Riemann invariants are expressed as functions of the flux vector. The application of the PorAS solver to the shallow water equations is presented and several computational examples are given for a comparison with the HLLC solver.

A two-dimensional shallow water model with depth-dependent porosity is presented. The purpose is the coarse grid simulation of shallow ows over complex topographies and geometries. Two ux closures are examined: the Integral Porosity (IP) and Dual Integral Porosity (DIP) closures. Energy losses are described using a subgrid scale model that accounts for bottom and wall friction, transient momentum dissipation and energy losses induced by obstacle submersion. A complete wave propagation property analysis is provided for the IP and DIP closures, yielding more accurate numerical stability constraints than published previously. Five computational examples are presented, including transients in compound and meandering channels, urban dambreak problems with building submersion and runo over variable microtopography. The ability of the model to deal with subgrid-scale features is conrmed. The DIP ux is shown to be superior to the IP closure. The transient dissipation term is essential in reproducing the eect of obstacles and microtopography. Distinguishing between the building wall-and building roof-induced friction is seen to be essential. The model is validated successfully against a scale model experimental dataset for the submersion of a coastal urban area by a tsunami wave.

Transition metal oxide / phenylphosphonate hybrids with M/P ratios ranging from 1 to 5, (M= Ti, Zr) and metal phosphonates (M/P = 0.5) have been prepared by a sol-gel process involving in a first step the non-hydrolytic condensation between metal alkoxide and phosphonic acid leading to M-O-P bonds, followed by the hydrolysis-condensation of the remaining M-OR groups. The composition, texture and structure of the materials were investigated using EDX, TGA, XRD, IR and 31P NMR.

International audienceVine-plot mapping and monitoring are crucial issues in land management, particularly for areas where vineyards are dominant like in some French regions. In this context, the availability of an automatic tool for vineyard detection and characterization would be very useful. The objective of the study is to compare two different approaches to meet this need. The first one uses directional variations of the contrast feature computed from Haralick's cooccurrence matrices and the second one is based on a local Fourier Transform. For each pixel, a 'vine index' is computed on a sliding window. To foster large-scale applications, test and validation were carried out on standard very high spatial resolution remote-sensing data. 70.8% and 86% of the 271 plots of the study area were correctly classified using the cooccurrence and the frequency method respectively. Moreover, the latter enabled an accurate determination (less than 3% error) of interrow width and row orientation