Search results for "roughness"

showing 10 items of 216 documents

How and why does willow biochar increase a clay soil water retention capacity?

2018

Addition of biochar into a soil changes its water retention properties by modifying soil textural and structural properties. In addition, internal micrometer-scale porosity that is able to directly store readily plant available water affects soil water retention properties. This study shows how precise knowledge of the internal micrometer-scale pore size distribution of biochar can deepen the understanding of the biochar-water interactions in soils. The micrometer-scale porosity of willow biochar was quantitatively and qualitatively characterized using X-ray tomography, 3D image analysis and Helium ion microscopy. The effect of biochar application on clay soil water retention was studied by…

Water retention curveSoil science010501 environmental sciencesmikroskopia01 natural sciencessavihuokoisuussoil water retentiontomografiaBiocharSurface roughnessmedicine3D image analysisbiochar3D-mallinnusPorosityta216Waste Management and DisposalWater contentta2180105 earth and related environmental sciences219 Environmental biotechnologybiohiilimaaperäta114Renewable Energy Sustainability and the EnvironmentChemistryForestry04 agricultural and veterinary sciences15. Life on land6. Clean waterWater retentionmikrorakenteetSoil structureplant available waterSoil water040103 agronomy & agriculturehelium ion microscopy0401 agriculture forestry and fisheriesmedicine.symptomvesipitoisuusAgronomy and Crop ScienceX-ray tomographyBiomass and Bioenergy
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Impact of very low crop residues cover on wind erosion in the Sahel

2011

International audience; In the Sahel, with average annual precipitation in the order of 500 mm yr− 1, wind erosion occurs mainly on cultivated millet fields whose surfaces are only partially covered by crop residues. The impact of these residues on wind erosion was not clearly established. The objective of this study is thus to quantify the actual amount of crop residues in traditional Sahelian fields and to determine their impacts on wind erosion by reference to a bare surface throughout the seasonal cycle over several years. At the beginning of the year during dry season, Sahelian farmers use to "clean" their fields, i.e. cut and lay flat on the soil surface any millet stalks still standi…

Wet seasonCrop residuecrop residuescover010504 meteorology & atmospheric sciencesAGROCLIMATOLOGIE[SDE.MCG]Environmental Sciences/Global ChangesCrop residues coverSoil surface01 natural sciencesEROSION EOLIENNEcrop residue coverDry season[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentClearingPrecipitationNigerwind erosion[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment0105 earth and related environmental sciencesEarth-Surface Processesmillet field2. Zero hungerHydrologyRESIDU VEGETAL04 agricultural and veterinary sciences15. Life on landAerodynamic roughness length[ SDE.MCG ] Environmental Sciences/Global ChangesMillet fieldAgronomyWind erosion040103 agronomy & agricultureErosion0401 agriculture forestry and fisheriesEnvironmental scienceAeolian processesAerodynamic roughness
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Roughness evaluation of vine leaf by image processing

2013

International audience; The study of leaf surface roughness is very important in the domain of precision spraying. It is one of the parameters that allow to reduce costs and losses of phytosanitary prod- ucts and to improve the spray accuracy. Moreover, the leaf roughness is related to adhesion mechanisms of liquid on a surface. It can be used to define leaf nature surface (hy- drophilic/hydrophobic). The main goal of this study is thus to estimate and to follow the evolution of leaf roughness using image processing and computer vision. The develop- ment and application of computer vision for measurement of surface leaf roughness using artificial neural networks will be described. The syste…

[ MATH ] Mathematics [math]0106 biological sciences0209 industrial biotechnologyScanning electron microscope[SDV]Life Sciences [q-bio]Computer Vision[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[MATH] Mathematics [math]02 engineering and technologySurface finishLeaf roughness01 natural sciences[PHYS] Physics [physics][SPI]Engineering Sciences [physics]020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ SPI ] Engineering Sciences [physics]Surface roughnessComputer vision[MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS[PHYS]Physics [physics][ PHYS ] Physics [physics]Artificial neural network[STAT]Statistics [stat]Multilayer perceptron[SDE]Environmental SciencesBiological system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMaterials science[ STAT ] Statistics [stat][INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics]IASTEDFast Fourier transformNeural NetworkImage processingImage processing[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyTexturelanguage technologies[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPrecision agriculturebusiness.industry[STAT] Statistics [stat]Precision agricultureArtificial intelligencebusiness010606 plant biology & botany
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Digital Correlation Method Based on Microgeometrical Texture Patterns for Strain Fields Measurements

2005

International audience; Digital correlation method is widely used in experimental mechanics to obtain the deformation field. Currently this method is applied with digital images of the initial and deformed surface sprayed with black or white painting. Speckle patterns are then captured and the correlation can be made with high 0.01 pixel accuracy in 2D-cases. In three-dimensions, the stereo-correlation can be used with a lower accuracy. The work presented in this paper, is a first approach based on the use of a 3D laser scanner in the objective of three-dimensional strain field measurement. The digital speckle patterns are not given by gray level but from the micro-geometrical surface textu…

[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]strain field measurement[PHYS.MECA.GEME] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph][ PHYS.MECA.GEME ] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph][PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]digital laser scanner[SPI.MECA.GEME] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]roughness pattern[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]
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Study and Comparison of Surface Roughness Measurements

2014

Journées du Groupe de Travail en Modélisation Géométrique (GTMG'14), Lyon; This survey paper focus on recent researches whose goal is to optimize treatments on 3D meshes, thanks to a study of their surface features, and more precisely their roughness and saliency. Applications like watermarking or lossy compression can benefit from a precise roughness detection, to better hide the watermarks or quantize coarsely these areas, without altering visually the shape. Despite investigations on scale dependence leading to multi-scale approaches, an accurate roughness or pattern characterization is still lacking, but challenging for those treatments. We think there is still room for investigations t…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]watermarking.quality assessmentsaliencywatermarking[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]simplificationvisual perceptionsmoothing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingfeature-preservingcompression[ PHYS.PHYS.PHYS-DATA-AN ] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]multi-scale analysisvisual masking3D mesh[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an][PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an][ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]roughness[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Morphological and chemical dynamics upon electrochemical cyclic sodiation of electrochromic tungsten oxide coatings extracted by in situ ellipsometry.

2020

The sodiation–desodiation process of sputtered amorphous electrochromic tungsten oxide coatings in an aqueous-based medium was simultaneously monitored over 99 cycles by cyclic voltammetry and in situ spectroscopic ellipsometry. This allowed extracting the evolution of optical and geometrical parameters upon cycling. The resulting electrochemical coloring-bleaching process was dynamically fitted in the 1.8–2.8 eV optical range with a four-phase model including a constrained spline parametrization of the dielectric function. This allows real time access to thickness, surface roughness, and dielectric function of N a x W O 3 . The temporal evolution of the latter in the fully colored state wa…

[PHYS]Physics [physics]Materials sciencebusiness.industryScanning electron microscopeAnalytical chemistryCharge density01 natural sciencesAtomic and Molecular Physics and OpticsAmorphous solid010309 opticsOpticsEllipsometryElectrochromism0103 physical sciencesContent (measure theory)Surface roughnessElectrical and Electronic EngineeringCyclic voltammetrybusinessEngineering (miscellaneous)Applied optics
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Measuring vine leaf roughness by image processing

2013

International audience; In precision spraying, spray application efficiency depends on the pesticide application method, the phytosanitary product as well as the leaf surface properties. For environmental and economic reasons, the global trend is to reduce the pesticide application rate of the few approved active substances. Under these constraints, one of the challenges is to improve the efficiency of pesticide application. Different parameters can influence on pesticide application as nozzle types, liquid viscosity and leaf surface. Specific models have been developed showing that the predominant factor for the leaf is the leaf roughness, because it is related on adhesion mechanisms of li…

[SDV] Life Sciences [q-bio][SDE] Environmental SciencesGeneralized Fourier Descriptor[SDV]Life Sciences [q-bio][SDE]Environmental SciencesNeural Network[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyleaf surface roughnessnonlinear reduction dimensionality methodstexture
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Leaf surface roughness characterization by image processing

2013

International audience

[SDV] Life Sciences [q-bio][SDE] Environmental Sciencesleaf roughnessprecision agriculturecharacterization of the leaf surface[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyComputingMilieux_MISCELLANEOUSaccurate sprayingtexture analysisspectral analysis
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3 D digitization of specular metallic surfaces by means of infrared imaging

2012

For the past twenty years, the need for three-dimensional digitization of manufactured objects has increased significantly and consequently, many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non cooperative surfaces, such as transparent or specular ones. Since the working principle of conventional scanners is based on the acquisition of the diffuse part of the reflection, transparency and specular reflections may cause outliers. To address highly reflective metallic surfaces, we propose the extension of a non conventional technique that was originally dedicated to glass objects, called “Scanning from Heati…

[SPI.OTHER]Engineering Sciences [physics]/OtherSpecular surfacesRugosité[ SPI.OTHER ] Engineering Sciences [physics]/Other[SPI.OTHER] Engineering Sciences [physics]/OtherTransferts thermiques[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Surfaces spéculaires[ PHYS.COND.CM-GEN ] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Roughness3D digitization[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH][PHYS.COND.CM-GEN] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other][PHYS.COND.CM-GEN]Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Heat transfer[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Numérisation 3DInfraredInfrarouge
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Coupling two radar backscattering models to assess soil roughness and surface water content at farm scale

2013

Remote sensing techniques are useful for agro-hydrological monitoring at the farm scale because the availability of spatially and temporally distributed data improves agricultural models for irrigation and crop yield optimization under water scarcity conditions. This research focuses on the surface water content retrieval using active microwave data. Two semi-empirical models were chosen as these showed the best performances in simulating cross and co-polarized backscatter. Thus, these models were coupled to obtain reliable assessments of both soil water content and soil roughness. The use of the coupled model enables one to avoid using roughness measured in situ. Remote sensing images and …

backscattering soil water content surface roughness vegetation indicesBackscatterSettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiasoil water contentRadar backscatteringSurface finishlaw.inventionData setlawvegetation indicesSoil waterSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEnvironmental scienceRadarUnderwaterSettore ICAR/08 - Scienza Delle CostruzioniScale (map)Surface waterWater Science and TechnologyRemote sensingHydrological Sciences Journal
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