Edwige Vannier
Centre national de la recherche scientifique
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Featured researches published by Edwige Vannier.
Progress in Electromagnetics Research-pier | 2012
Richard Dusséaux; Edwige Vannier; O. Taconet; Gérard Granet
We propose a 3D-approach of the soil surface height variations, either for the roughness characterization by the mean of the bidimensional correlation function, or as input of a backscattering model. We consider plots of 50cm by 50cm and two states of roughness of seedbed surfaces: an initial state just after tillage and a second state corresponding to the soil roughness evolution under a rainfall event. We show from stereovision data that the studied surfaces can be modelled as isotropic Gaussian processes. We study the change of roughness parameters between the two states. To discuss the relevance of their difierences, we flnd from Monte-Carlo simulations the bias and variance of estimator for each roughness parameters. We study the roughness and moisture combined in∞uences upon the direct backscattering coe-cients by means of an exact method based on Maxwells equations written in a nonorthogonal coordinate system and by averaging the scattering amplitudes over several realizations. We discuss results taking into account the numerical errors and the precision of radar. We show that the ability of the radar to discriminate the difierent states of seedbed surfaces is clearly linked to its precision.
Computers & Geosciences | 2009
Edwige Vannier; Valérie Ciarletti; Frédéric Darboux
One of the aims of the tillage operation is to produce a specific range of clod sizes, suitable for plant emergence. Due to its cloddy structure, a tilled soil surface has its own roughness, which is connected also with soil water content and erosion phenomena. The comprehension and modeling of surface runoff and erosion require that the micro-topography of the soil surface is well estimated. Therefore, the present paper focuses on the soil surface analysis and characterization. An original method consisting in detecting the individual clods or large aggregates on a 3D digital elevation model (DEM) of the soil surface is introduced. A multiresolution decomposition of the surface is performed by wavelet transform. Then a supervised local maxima extraction is performed on the different sub surfaces and a last process makes the validation of the extractions and the merging of the different scales. The method of detection was evaluated with the help of a soil scientist on a controlled surface made in the laboratory as well as on real seedbed and ploughed surfaces, made by tillage operations in an agricultural field. The identifications of the clods are in good agreement, with an overall sensitivity of 84% and a specificity of 94%. The false positive or false negative detections may have several causes. Some very nearby clods may have been smoothed together in the approximation process. Other clods may be embedded into another peace of the surface relief such as another bigger clod or a part of the furrow. At last, the low levels of decomposition are dependent on the resolution and the measurement noise of the DEM. Therefore, some borders of clods may be difficult to determine. The wavelet-based detection method seems to be suitable for soil surfaces described by 2 or 3 levels of approximation such as seedbeds.
Computers & Geosciences | 2013
O. Taconet; Richard Dusséaux; Edwige Vannier; Olivier Chimi-Chiadjeu
In this paper the selected approach to analyze seedbed roughness is to study soil surface structural elements, such as aggregates and clods lying on the soil substrate. Recently their identification has been made possible on millimetric resolution digital elevation models (DEMs) by new developed segmentation algorithms relying on contour-based procedure. Here we consider two DEMs of 30cm and 40cm by 90cm recorded on a freshly tilled seedbed of moderate roughness and build up a dataset of several hundreds of clods and large aggregates (sizes greater than 7mm). We show that these irregular shaped objects can be represented by simple approached forms: an ellipse for the base and a half-cosine function for the height. Values of areal (and volume) overlap rates indicate that half of clods bases are matched with very good rates greater than 0.74 up to 0.89 (respectively 0.70 up to 0.87). The set of detected objects enables to derive the statistical distributions characterizing the ellipse variables (orientation angle, major and minor axis lengths) and the half-cosine amplitude. Because of interdependence of lengths of major and minor axes, we introduce the horizontal compression factor which measures the ellipse flattening. We show plausible independence of the major axis length with the horizontal compression factor and we find that the major axis length minus its minimum is well fitted by the Gamma distribution and the normalized horizontal compression factor by the Beta distribution. We propose to infer the value of the minor axis length from the values of the two preceding variables knowing their statistical occurrences. Same reasoning is handled for inference of the half-cosine amplitude from the major axis length and the normalized vertical compression factor, which is also well fitted by the Beta distribution.
Computers & Geosciences | 2013
Olivier Chimi-Chiadjeu; Edwige Vannier; Richard Dusséaux; S. Le Hégarat-Mascle; O. Taconet
A seedbed has a cloddy structure that is highly connected to its random roughness. Identifying and characterizing the clods is thus a preliminary step in surface roughness measurement and modelling. The aim of this paper is to propose an algorithm, based on the simulated annealing optimization, to refine the clod delineation estimated on a seedbed surface Digital Elevation Model (DEM). In our case, the DEM image was recorded on a real seedbed immediately after tillage, and we assume an initialization for the clods boundaries. The proposed method is based on a cost function to minimize, introducing four main characteristics of the clod boundary, respectively related to the mean of the DEM gradient norms on the boundary (f1), the standard deviation of the DEM gradient norms on the boundary (f2), the standard deviation of the DEM values on the boundary (f3) and L2-norm of the DEM values on the boundary (f4). In our case, the relative weights of previous criteria have been learned using a target reference that is a manual delineation of individual clods completed by a soil scientist on a sub-part of the DEM image. The cost function minimization is then achieved using the simulated annealing technics. The result performance is measured in term of the overlap rate. Further study shows the key feature of the f4 criterion. Then, the influence of the weighting coefficients was studied using (f1,f2,f4) based new cost function. We finally conclude on the possibility of improving the clod boundaries of a large surface using the cost function parameters learned on a training sub-surface.
international congress on image and signal processing | 2012
Olivier Chimi-Chiadjeu; Edwige Vannier; Richard Dusséaux; O. Taconet; Sylvie Le Hégarat-Mascle
This study deals with the segmentation of altitude or elevation images, i.e. images of the distance (z-coordinate) between the surface or objects and the camera plane. Specifically to our soil science application, these images are acquired on agricultural surfaces in order to evaluate their roughness. The cloddy structure being a key factor to characterize soil roughness, the elevation image analysis aims at detecting and identifying the clods as accurately as possible. Now, rather than defining a new segmentation algorithm, we propose to transform the input data so as to take into account the different criteria characterizing the clod objects, namely the relative altitude and a function of the gradient norm. The proposed approach was validated on three agricultural surfaces (two synthetic and one real) and the results compared to those of an algorithm previously developed specifically for the clod identification problem.
Archive | 2014
Edwige Vannier; O. Taconet; Richard Dusséaux; OlivierChimi-Chiadjeu
Because the soil surface occurs at the boundary between the atmosphere and the pedosphere, it plays an important role for geomorphologic processes. Roughness of soil surface is a key parameter to understand soil properties and physical processes related to substrate movement, water infiltration or runoff, and soil erosion. It has been noted by many authors that most of the soil surface and water interaction processes have characteristic lengths in millimeter scales. Soil irregularities at small scale, such as aggregates, clods and interrill depressions, influence water outflow and infiltration rate. They undergo rapid changes caused by farming imple‐ ments, followed by a slow evolution due to rainfall events. Another objective of soil surface roughness study is investigating the effects of different tillage implements on soil physical properties (friability, compaction, fragmentation and water content) to obtain an optimal crop emergence. Seedbed preparation focuses on the creation of fine aggregates and the size distribution of aggregates and clods produced by tillage operations is frequently measured. Active microwave remote sensing allows potential monitoring of soil surface roughness or moisture retrieving at field scale using space-based Synthetic Aperture Radars (SAR) with high spatial resolution (metric or decametric). The scattering of microwaves depends on several surface characteristics as well as on imagery configuration. The SAR signal is very sensitive to soil surface irregularities and structures (clod arrangement, furrows) and moisture content in the first few centimeters of soil (depending on the radar wavelength). In order to link the remote sensing observations to scattering physical models as well as for modelling purpose, key features of the soil microtopography should be characterized. However, this characteri‐ zation is not fully understood and some dispersion of roughness parameters can be observed in the same field according to the methodology used. It seems also, that when describing surface roughness as a whole, some information related to structured elements of the micro‐ topography is lost.
Journal of Ecology and Toxicology | 2017
Edwige Vannier; O. Taconet; Richard Dusséaux; Frédéric Darboux
D the increased acreage of high-density irrigated orchards, traditional rainfed olive groves maintain huge social importance. While in irrigated orchards cover cropping is generalized, in the rainfed groves the ground continues to be tilled or maintained barely by using herbicides. Cover cropping is important as is an effective mean of reducing soil erosion. However, the covers consume water which can severely reduce olive yields. Over the last 18 years, experimental work has been done in searching for a solution for these orchards. This work summarizes the results obtained in several field trials, which included several soil management treatments, such as conventional tillage, bare soil by using residual or post-emergence herbicides, natural vegetation mowed or grazed, legumes of erect habit grown as green manures and self-reseeding annual pasture legumes. The results indicate that withdrawing tillage and allowing the development of the root system significantly increases olive yield. Cover crops of natural vegetation control soil erosion and improve several soil fertility parameters but significantly reduce olive yield through excessive competition for water. Green manures are difficult to manage since they require be sowing and incorporating into the soil by tillage. If the green manures are managed as mulching it causes significant nitrogen losses to the atmosphere. In these orchards, the theoretical model that aggregate the best results is the growing of very early-maturing self-reseeding annual legumes. These plants provide enough protection of the soil, fix nitrogen in rates able to maintain the trees at nutrition levels higher than the application of 60 kg N ha-1 year-1 and ensures high olive yields due to the little competition for water. These covers proved to be the only way to make profitable organic farming, an interesting alternative for these low input agricultural systems.Soil surface roughness plays an important role in determining how the soil will interact with its environment. Analysis of soil roughness at small scale matters both for preparation of soil in order to allow for plant emergence, and for decisions to favor soil conservation. Indeed, soil roughness may be shaped by tillage operations and then changes with time, under rainfall impact. Soil surface roughness is usually estimated by various indices, computed on measured profiles or images of elevations. Another approach is focusing on soil cloddiness, either by sieving or by image segmentation. The objective of this study is to monitor the evolution of clods under rainfall with Digital Elevation Model (DEM) recording and image processing. We prepared two trays of artificial soil surfaces in the laboratory with silt loam soil topped by pre-sieved clods. They were designed to look like a seedbed. Soil surface evolution was achieved by subjecting the trays to controlled artificial rainfalls, and DEM were recorded at each stage. We performed automatic clod segmentation and measurement of the volume of individual clods. Under rainfall impact, we could see smoothing and leveling of clods until disappearance of the smaller ones. We focused on the larger clods greater than 12 mm in diameter that remained till the last rainfall. They showed swelling (volume increase) followed by erosion (volume decrease), these two phenomena being size dependent. Clod volume decrease was modeled by an exponential function. Now, the slope and the amplitude parameters decreased according to a power law, as a function of mean volume of clods. Monitoring of clod volume with cumulated precipitation with the help of DEM measurements is able to differentiate the dynamics of clod depending on their size. This technique improves the usual roughness description and allows for a better understanding of the processes.Statement of the Problem: The fruits of Capsicum chinense plants grown in the Yucatan Peninsula have its appellation of origin based on their unique characteristics, which are suggested to be due to the particularities of the soils in they are cultivated. Leptosols are the most common soils in the world (12%). This is also the case in Mexico (24%) and in the state of Yucatan (80%) The high spatial heterogeneity of Leptosol areas complicates agricultural development and transfer of agricultural technology, among other things. The aim of this study was to characterize three types of soil from Yucatan Mexico (K’aankab lu’um, Red, Box lu’um, black and stony ch’ich’ lu’um, brown) and to analyze its effect on the growth habanero chili plants.Statement of the Problem: The physical characterization of soil horizons based on color is a key diagnostic method in the description of soil profiles, and has been integrated in to diagnostic keys such as the world reference base for soil resources. The Munsell color system has been the primary qualitative or semi-quantitative mean to describe soil color. The purpose of this study is to explore the feasibility of using flatbed scanners and digital cameras to derive colorimetrically accurate images and data of soil samples, and to replace semi-quantitative Munsell chart comparison, or more expensive spectrophotometers.
international geoscience and remote sensing symposium | 2007
Karim Aït Braham; Richard Dusséaux; Edwige Vannier; O. Taconet; G. Granet
We propose a statistical model to describe the seedbed surfaces and we study the roughness and moisture influence upon the backscattering coefficient and the scattering patterns by means of Monte-Carlo predictions. For each realization, the scattering amplitudes are obtained by the C method.
Soil & Tillage Research | 2010
O. Taconet; Edwige Vannier; S. Le Hégarat-Mascle
Catena | 2014
Olivier Chimi-Chiadjeu; Sylvie Le Hégarat-Mascle; Edwige Vannier; O. Taconet; Richard Dusséaux