Academic literature on the topic 'Variogramme'
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Journal articles on the topic "Variogramme"
Ambara, Joseph, Kadiri Serge Bobo, Juvenal Donfack Demesse, and Antoine David Mvondo-Ze. "Caractérisation de la compétition et de la croissance de Pericopsis elata (Harms) Van Meeuven dans les plantations de la Réserve Forestière de Deng-Deng (Est, Cameroun)." International Journal of Biological and Chemical Sciences 15, no. 2 (June 22, 2021): 559–77. http://dx.doi.org/10.4314/ijbcs.v15i2.15.
Full textChampion, Hervé. "Variogramme et évolution des structures spatiales : la population de l'aire métropolitaine marseillaise." Méditerranée 79, no. 1 (1994): 75–78. http://dx.doi.org/10.3406/medit.1994.1855.
Full textCarbonara, Pierluigi, Teresa Silecchia, Maria Spedicato, Alessandra Acrivulis, and Giuseppe Lembo. "A GEOSTATISTICAL APPROACH TO THE ASSESSMENT OF THE SPATIAL DISTRIBUTION OF PARAPENAEUS LONGIROSTRIS (LUCAS, 1846) IN THE CENTRAL-SOUTHERN TYRRHENIAN SEA." Crustaceana 72, no. 9 (1999): 1093–108. http://dx.doi.org/10.1163/156854099504040.
Full textRakotonirina, M. D. L., and Jean-Paul Ngbolua. "Modélisation géologique et estimation d’un gisement de Fer de Bekisopa, Madagascar." Revue Congolaise des Sciences & Technologies 2, no. 4 (February 10, 2022): 498–504. http://dx.doi.org/10.59228/rcst.023.v2.i4.56.
Full textMaus, Stefan, K. P. Sengpiel, B. Röttger, B. Siemon, and E. A. W. Tordiffe. "Variogram analysis of helicopter magnetic data to identify paleochannels of the Omaruru River, Namibia." GEOPHYSICS 64, no. 3 (May 1999): 785–94. http://dx.doi.org/10.1190/1.1444588.
Full textBénina, Touaïbia, Inegliz Souhila, and Ould Amara Arezki. "Couplage d’une analyse en composantes principales et d’une approche géostatistique pour l’élaboration de cartes pluviométriques du Centre de l’Algérie du Nord." Revue des sciences de l'eau 19, no. 3 (September 13, 2006): 213–19. http://dx.doi.org/10.7202/013539ar.
Full textMaus, Stefan. "Variogram analysis of magnetic and gravity data." GEOPHYSICS 64, no. 3 (May 1999): 776–84. http://dx.doi.org/10.1190/1.1444587.
Full textSkøien, J. O., and G. Blöschl. "Catchments as space-time filters – a joint spatio-temporal geostatistical analysis of runoff and precipitation." Hydrology and Earth System Sciences Discussions 3, no. 3 (June 12, 2006): 941–85. http://dx.doi.org/10.5194/hessd-3-941-2006.
Full textSkøien, J. O., and G. Blöschl. "Catchments as space-time filters – a joint spatio-temporal geostatistical analysis of runoff and precipitation." Hydrology and Earth System Sciences 10, no. 5 (September 26, 2006): 645–62. http://dx.doi.org/10.5194/hess-10-645-2006.
Full textDíaz, Arturo Buelga, César Castañón Fernández, Gonzalo Ares, Daniel Arias Prieto, and Isidro Diego Álvarez. "RecMin Variograms: Visualisation and Three-Dimensional Calculation of Variograms in Block Modelling Applications in Geology and Mining." International Journal of Environmental Research and Public Health 19, no. 19 (September 29, 2022): 12454. http://dx.doi.org/10.3390/ijerph191912454.
Full textDissertations / Theses on the topic "Variogramme"
Leroy, Olivier. "Régénération naturelle des systèmes agroforestiers : le cas des dehesas de la Sierra de Grazalema, Andalousie, Espagne." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCC139/document.
Full textThe regeneration of Holm oak (Quercus ilex) populations remains problematic in most dehesa agroforestry systems, allegedly due to the absence of a shrub layer protecting seedlings from grazing and heat. This thesis explores the latter claim using the regressive method. Our study focuses on the Sierra de Grazalema Natural Park, a site located at the periphery of dehesa regions in Andalusia, Spain and not previously analyzed in this manner. Regeneration was interpreted as a naturalized technique that evolves over time and within disciplinary fields. Our study features an analysis of historical documents, from 1765 to the present day, as well as fieldwork including 71 transects measuring shrub and tree layers on five public lands and three private lands. The tree layer was examined using a distribution into diameter classes and variograms analyzed seeding patterns on several scales. The reverse J-shaped diameter distribution indicates successful regeneration, but with a strong heterogeneity both among transects and due to land status. A significant number of young trees were found: 4516.65 seedlings / ha, 986 thickets / ha and 543 saplings / ha. Variograms indicate regeneration patterns present at several scales; at about ten meters, at 45 to 90 meters, at 100 to 200 meters and near one kilometer. These results, very different from previous studies, complement historical trajectories, and indicate that there is not one form of regeneration but several, related to both historical eras and environments. Patterns of regeneration include cases without a matorral shrublands and woodlands stage, cases belonging to a regressive or progressive series, and finally, cases of regeneration sensu stricto
Genton, Marc G. Genton Marc Georges. "Robustesse dans l'estimation et l'ajustement du variogramme en géostatistique /." [S.l.] : [s.n.], 1996. http://library.epfl.ch/theses/?nr=1595.
Full textLamour, Julien. "Analyse de données spatialisées issues de la production pour améliorer le diagnostic agronomique en bananeraie - Prise en compte de l’asynchronisme de la culture." Thesis, Montpellier, SupAgro, 2019. http://www.theses.fr/2019NSAM0017.
Full textExported bananas are produced on industrial plantations covering large areas and relying most of the times on clones of the Cavendish cultivars. This crop is input and labour intensive and is subject to environmental and societal constraints that impose an improvement in agricultural practices. Precision Agriculture (PA) is a methodological approach that has emerged on arable crops to optimize their yield, quality and reduce their environmental impact. This approach uses geo-referenced producer’s data and studies their spatial variability to increase the farming performance by adjusting the management by area. Its objective is to highlight the variable growth conditions and identify those that are manageable in order to optimize production processes according to the specific potential of the sites on the farm. Unlike arable crops, bananas exhibit unique characteristics that must be taken into account when studying production and yields. In particular, banana plants are asynchronous, their development cycle is not seasonal and is not synchronized by the cropping system. As a result, the fields are made up of banana plants at different phenological stages. Thus, unlike arable crops which are synchronous, the observations that can be made on a banana plantation at a given time depend not only on growing conditions but also on the variable phenological stages of the plants. The objective of this doctoral thesis was to propose new methods for using data produced in banana plantations in order to facilitate agronomic diagnosis in a PA approach. The data used are mainly those recorded to manage the harvests. These are observations classically recorded in banana plantations. We also studied remote sensing data and proposed analytical methods to study spatial variability by reducing the bias due to the asynchronism of banana plants.The first thesis work consisted in proposing methods to characterize the asynchronism of the fields. For this purpose, we defined several indicators: the average duration of the banana plant development cycle; the heterogeneity of growing conditions; and finally the average phenological stage of a field and the within field variability of the stages. These methods were applied to flowering data from an industrial plantation in Cameroon. An effect of the environment and producers' practices on asynchronism was highlighted. A second part of the thesis work consisted in proposing a model that identifies variability related to the environment and producers' choices using production data. The purpose of this method was to generate maps that could be interpreted agronomically, without the asynchronism bias. The model we proposed was applied to a particular property: the time between flowering and commercial maturity. It is assumed that this method is general enough to be applied to other agronomic properties such as the weight of bunches at harvest.Finally, the last subject we studied was the relevancy of remote sensing in banana plantations despite the diversity of phenological stages. We assessed the importance of different sources of variability on the chlorophyll content of banana leaves measured from a pedestrian sensor and constructed an index to predict this content by drone. Maps of within field variability of chlorophyll content have been produced by this method, but agronomic interpretation must be done with caution because the phenological stages are not known and their effects cannot be corrected. The conditions for interpreting these maps are discussed
Geraets, David. "Modélisation géostatistique de champs de vitesse géophysique en exploration petrolière." Paris, ENMP, 2002. http://www.theses.fr/2002ENMP1103.
Full textOussou-Koffi, Marie. "Contrôle de la qualité du traitement des données sismiques du bassin sédimentaire de la Côte d'Ivoire : apport de la géostatistique : tentative de retraitement." Paris 6, 2009. http://www.theses.fr/2009PA066604.
Full textDoukouré, Moussa. "Variabilité des flux turbulents de surface au sein du bassin versant d'Ara au Bénin." Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENU014/document.
Full textWest Africa atmosphere circulation is characterized by south-westerly wind (monsoon regime) during the wet season and north-easterly wind (harmattan regime) during the dry season. This alternation of wind regime is due to surface pressure variability linked to surface heterogeneities. Surface heterogeneities generate surface flux variability, secondary circulation and make complex analysis when trying to document surface-atmosphere feedbacks. LES modelling usually used for boundary-layer studies due to its potential to take into account 3D turbulence over complex topography, is used here to overcome these difficulties. Our site of interest is located in north of Benin characterized by Soudanian climate and heterogeneous surface properties. Climate analysis are first performed with radiosoundings, UHF radar, and EC station data in order to extract composite profile representing dry and wet season.. These composite profiles are then used to force atmosphere part of the Méso-NH LES model. To characterize turbulent fluxes length scales relative to dry and wet season, standard surface forcing data with Méso-NH like GTOPO30 orography (1km ) and ECOCLIMAP vegetation (1km) are respectively replaced by SRTM (90m) and SPOT/HRV vegetation data (20m) resampled to 90m. Along with statistical tools like 2D variography and Lagrangian, we notice that during dry season on heterogeneous vegetation, sensible heat flux H is more driven by wind and orography while we not able to discuss the latent heat flux E case. During wet season with the same surface forcing, it appears that H is driven by wind while E is more dependent to vegetation variability. Our study concludes in all case that H and E are not characterized by the same length scale
Machecler, Ingrid. "Application des réseaux de neurones à l'analyse d'images de réservoirs d'hydrocarbures." Paris, Institut de physique du globe, 2005. http://www.theses.fr/2005GLOB0003.
Full textMethods of image analysis, applied to data survey, such as seismic or wellbore logs, are crucial in structural and stratigrafic analysis of formations suspected of containing hydrocarbon reservoirs. This thesis investigates two methods to perform zonation or contour detection in electrical wellbore image (FMI). The first method, based on a model of pre-attentive human vision, yields image segmentation or contour enhencement, depending on the input (preprocessed synthetic or real image). The second one uses artficial neural networks to infer, from FMI data, the parameters of the variogram quantifying the spatial variability in the formation. The networks are trained using stochastic simulations of deposits of given geostatistical properties. This method is tested on real images having isotropic horizontal spatial variability as well as on synthetic FMI data showing anisotropic horizontal spatial variability
Lefranc, Marie. "Variations et variabilité spatio-temporelle des argilites callovo-oxfordiennes de Meuse/Haute-Marne : Valorisation géostatistique des données diagraphiques." Phd thesis, Paris, ENMP, 2007. http://www.theses.fr/2007ENMP0001.
Full textAndra has conducted studies in its Meuse/Haute-Marne Underground Research Laboratory located at a depth of about 490 m in the Callovo-Oxfordian argillite. The purpose of the present work is to obtain as much information as possible from high-resolution log data and to optimize their analysis to specify and characterize space-time variations of the argillites from the Meuse/Haute-Marne site and subsequently predict the evolution of argillite properties on a 250 km2 zone around the underground laboratory. The spatial variations can be studied on various scales. First, well-to-well correlations are established between seven wells at different scales. Relative variations of the thickness are observed locally. Second, FMI® (Fullbore Formation MicroImager, Schlumberger) data are studied in detail to extract as much information as possible. For example, the analysis of FMI® images reveals a clear carbonate – clay interbedding which displays cycles. Third, geostatistical tools are used to study these cycles. The variographic analysis of conventional log data shows one-metre cycles. With FMI® data, smaller periods can be detected. Variogram modelling and factorial kriging analysis suggest that three spatial periods exist. They vary vertically and laterally in the boreholes but cycle ratios are stable and similar to orbital-cycle ratios (Milankovitch cycles). The three periods correspond to eccentricity, obliquity and precession. Since the duration of these orbital cycles is known, depth intervals can be converted into time intervals (duration) and thus give real sedimentation rates and an estimation of the duration of the ammonites zones and hiatuses
Mangapi, Augustin Assonga. "Krigeage et cokrigeage, méthodes d’interpolation spatiale pour les systèmes d’information géographique." Mémoire, Université de Sherbrooke, 1994. http://hdl.handle.net/11143/7880.
Full textLefranc, Marie. "Variations et variabilité spatio-temporelle des argilites callovo-oxfordiennes de Meuse/Haute-Marne : valorisation géostatistique des données diagraphiques." Phd thesis, École Nationale Supérieure des Mines de Paris, 2007. http://pastel.archives-ouvertes.fr/pastel-00585401.
Full textLe passage à un repère géochronologique a d'abord permis d'estimer des durées et en particulier la durée d'unités biostratigraphiques dans des étages (Callovien et Oxfordien) où les durées absolues ne sont quasiment pas connues. Enfin, l'étude des variations du taux moyen de sédimentation dans un repère géochronologique a montré les évolutions verticales et latérales du taux de sédimentation à l'échelle du site de Meuse/Haute-Marne et le synchronisme de la plupart des niveaux condensés. Elle a infirmé certaines hypothèses concernant la présence de hiatus et en a validé d'autres, et dans ce cas a abouti à l'estimation de la durée de ces hiatus.
Books on the topic "Variogramme"
Dauphine, Andre. Variogrammes et structures spatiales. Montpellier: GIP RECLUS, 1988.
Find full textOliver, Margaret A., and Richard Webster. Basic Steps in Geostatistics: The Variogram and Kriging. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15865-5.
Full textKrajewski, Stephen. Understanding contouring: A practical guide to spatial estimation using a computer and basics of using variograms. Boulder, Colo: Gibbs Associates, 2001.
Find full textKrajewski, Stephen. A variogram primer: Basics of using variograms (Special publication / Industrial Ergonomics). Gibbs Associates, 1993.
Find full textOliver, Margaret A., and Richard Webster. Basic Steps in Geostatistics: The Variogram and Kriging. Springer London, Limited, 2015.
Find full textBook chapters on the topic "Variogramme"
Akin, Hikmet, and Heinrich Siemes. "Variogramme." In Praktische Geostatistik, 26–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73542-4_2.
Full textMarques da Silva, José Rafael, and Manuela Correia. "Basics of geostatistical analyses with GIS." In Manuali – Scienze Tecnologiche, 27. Florence: Firenze University Press, 2020. http://dx.doi.org/10.36253/978-88-5518-044-3.27.
Full textDutter, Rudolf. "Das Variogramm." In Geostatistik, 61–87. Wiesbaden: Vieweg+Teubner Verlag, 1985. http://dx.doi.org/10.1007/978-3-322-99493-6_4.
Full textMonestiez, P., R. Habib, and J. M. Audergon. "Estimation de la Covariance et du Variogramme Pour une Fonction Aleatoire a Support Arborescent : Application a L’etude des Arbres Fruitiers." In Geostatistics, 39–56. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-6844-9_3.
Full textShekhar, Shashi, and Hui Xiong. "Variogram." In Encyclopedia of GIS, 1217. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1436.
Full textSadeghi, Behnam. "Variogram." In Encyclopedia of Mathematical Geosciences, 1–6. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_344-1.
Full textSadeghi, Behnam. "Variogram." In Encyclopedia of Mathematical Geosciences, 1609–13. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_344.
Full textArmstrong, Margaret. "Experimental Variograms." In Basic Linear Geostatistics, 47–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58727-6_4.
Full textArmstrong, Margaret. "The Variogram." In Basic Linear Geostatistics, 25–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58727-6_3.
Full textShekhar, Shashi, and Hui Xiong. "Variogram Modeling." In Encyclopedia of GIS, 1217. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1437.
Full textConference papers on the topic "Variogramme"
Kato, Kazuyuki, Tadashi Maeda, and Hiroyasu Takase. "Evaluation of Uncertainty Associated With Spatially Variable Properties." In ASME 2003 9th International Conference on Radioactive Waste Management and Environmental Remediation. ASMEDC, 2003. http://dx.doi.org/10.1115/icem2003-4561.
Full textC. Hoeber, H., S. Butt, C. Lacombe, S. Campbell, and D. N. Whitcombe. "Understanding 4D Repeatability Variograms." In 68th EAGE Conference and Exhibition incorporating SPE EUROPEC 2006. European Association of Geoscientists & Engineers, 2006. http://dx.doi.org/10.3997/2214-4609.201402399.
Full textMacDonald, John A., Fernando P. Miranda, and James R. Carr. "Textural image classification using variograms." In Orlando '90, 16-20 April, edited by Paul Janota. SPIE, 1990. http://dx.doi.org/10.1117/12.21411.
Full textCekli, H. E., and H. Gunes. "Spatial Resolution Enhancement and Reconstruction of Mixed Convection Data Using Kriging Method." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14019.
Full textLi, Shaohua, and Wentao Lu. "Automatic Fit of the Variogram." In 2010 Third International Conference on Information and Computing Science (ICIC). IEEE, 2010. http://dx.doi.org/10.1109/icic.2010.303.
Full textEzeora, Obiora Sam, Jana Heckenbergerova, and Petr Musilek. "Analysis of environmental measurements using variograms." In 2015 16th International Scientific Conference on Electric Power Engineering (EPE). IEEE, 2015. http://dx.doi.org/10.1109/epe.2015.7161201.
Full textHajiannezhad, Akram, and Saeed Mozaffari. "Font recognition using Variogram fractal dimension." In 2012 20th Iranian Conference on Electrical Engineering (ICEE). IEEE, 2012. http://dx.doi.org/10.1109/iraniancee.2012.6292432.
Full textXu, Aiping, Qi Wang, Li Hu, and Hong Shu. "Computing spatiotemporal variogram and covariance model." In 2011 Seventh International Conference on Natural Computation (ICNC). IEEE, 2011. http://dx.doi.org/10.1109/icnc.2011.6022553.
Full textMadu, Osita Robinson, Jerry Orrelo Athoja, Amarachi Queen Kalu, and Obi Mike Onyekonwu. "Integrated Approach to Geostatistics For Optimal Reservoir Properties Distribution – Case Study of X-Reservoir in Niger Delta Basin." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/207116-ms.
Full textDevi, M. Uma, Arun Agarwal, and C. Raghavendra Rao. "Gaussian Variogram Model for Printing Technology Identification." In 2009 Third Asia International Conference on Modelling & Simulation. IEEE, 2009. http://dx.doi.org/10.1109/ams.2009.20.
Full textReports on the topic "Variogramme"
Murillo Castellano, David, and José Luis Romero Béjar. INTRODUCTION TO SPATIAL AND SPATIOTEMPORAL RANDOM FIELDS. Fundación Avanza, May 2023. http://dx.doi.org/10.60096/fundacionavanza/1632022.
Full textOliver, Margaret A. Application of Geostatistical Methods and Wavelets to the Analysis of Hyperspectral Imagery and the Testing of a Moving Variogram. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada393009.
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