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1
Ghassemi, Ali. "Nonparametric geostatistical estimation of soil physical properties." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63904.
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Fanshawe, Thomas Robert. "Geostatistical models for exposure estimation in environmental epidemiology." Thesis, Lancaster University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543958.
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Tawo, Ekure Etta. "The incorporation of subjective and descriptive information in geostatistical estimation." Thesis, University of Leeds, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.291038.
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Spadavecchia, Luke. "Estimation of landscape carbon budgets : combining geostatistical and data assimilation approaches." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/14462.
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Quantification of carbon (C) budgets at the landscape or catchment scale is generally achieved using process-based models as scaling tools. Such models require some metric of the exchange surface capability (e.g. Leaf Area Index, LAI) and a set of rate parameters for C processing. The net C exchange is then determined by driving the model with meteorological observations. Regional fields of parameters and drivers may be derived by upscaling site level measurements, constrained using Earth Observation data such as vegetation indices and digital elevation models (DEMs). I explore issues of error and uncertainty when upscaling C model parameters and drivers, and the effect of these uncertainties on the final analysis of the carbon budget. Two study areas focus the research: a region of tundra in Arctic Sweden and a ponderosa pine stand in Oregon. I use geostatistical techniques to develop fields of LAI and meteorology, complete with error statistics, whilst the distributions of rate parameters for a C model are derived via the Ensemble Kalman filter (EnKF). I report that the use of DEM data can provide LAI fields with an r2 ~50% greater than those derived from EO data alone. In particular I find strong relationships between LAI, elevation and topographic exposure. I explore the use of spatio-temporal geostatistics to improve meteorological fields, but report a better interpolation skill when temporal autocorrelations are ignored. Variation in parameters has a much larger effect on the uncertainty of the carbon budge (~50%) than driver uncertainty (~10%). The combined uncertainty in parameterisation and meteorology may result in a 53% uncertainty in total C uptake.
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Adisoma, Gatut Suryoprapto. "The application of the jackknife in geostatistical resource estimation: Robust estimator and its measure of uncertainty." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186547.
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The application of the jackknife in geostatistical resource estimation (in conjunction with kriging) is shown to yield two significant contributions. The first one is a robust new estimator, called jackknife kriging, which retains ordinary kriging's simplicity and global unbiasedness while at the same time reduces its local bias and oversmoothing tendency. The second contribution is the ability, through the jackknife standard deviation, to set a confidence limit for a reserve estimate of a general shape. Jackknifing the ordinary kriging estimate maximizes sample utilization, as well as information of sample spatial correlation. The jackknife kriging estimator handles the high grade smearing problem typical in ordinary kriging by assigning more weight to the closest sample(s). The result is a reduction in the local bias without sacrificing global unbiasedness. When data distribution is skewed, log transformation of the data prior to jackknifing is shown to improve the estimate by making the data behave better under jackknifing. The technique of block kriging short-cut, combined with jackknifing, are shown as an easy-to-use solution to the problem of grade estimation of a general three-dimensional digitized shape and the uncertainty associated with the estimate. The results are a single jackknife kriging estimate for the shape and its corresponding jackknife variance. This approach solves the problem of combining independent block estimation variances, and provides a simple way to set confidence levels for global estimates. Unlike the ordinary kriging variance, which is a measure of data configuration and is independent of data values, the jackknife kriging variance reflects the variability of the values being inferred, both on an individual block level and on the global level. Case studies involving two exhaustive (symmetric and highly skewed) data sets indicates the superiority of the jackknife kriging estimator over the original (ordinary kriging) estimator. Some instability of the log-transformed jackknife estimate is noted in the highly skewed situation, where the data do not generally behave well under standard jackknifing. A promising solution for future investigations seems to lie in the use of weighted jackknife formulation, which should better handle a wider spectrum of data distribution.
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Owaniyi, Kunle Meshach. "Geostatistical Interpolation and Analyses of Washington State AADT Data from 2009 – 2016." Thesis, North Dakota State University, 2019. https://hdl.handle.net/10365/31649.
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Annual Average Daily Traffic (AADT) data in the transportation industry today is an important tool used in various fields such as highway planning, pavement design, traffic safety, transport operations, and policy-making/analyses. Systematic literature review was used to identify the current methods of estimating AADT and ranked. Ordinary linear kriging occurred most. Also, factors that influence the accuracy of AADT estimation methods as identified include geographical location and road type amongst others. In addition, further analysis was carried out to determine the most apposite kriging algorithm for AADT data. Three linear (universal, ordinary, and simple), three nonlinear (disjunctive, probability, and indicator) and bayesian (empirical bayesian) kriging methods were compared. Spherical and exponential models were employed as the experimental variograms to aid the spatial interpolation and cross-validation. Statistical measures of correctness (mean prediction and root-mean-square errors) were used to compare the kriging algorithms. Empirical bayesian with exponential model yielded the best result.
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Zha, Yuanyuan, Tian-Chyi J. Yeh, Walter A. Illman, Hironori Onoe, Chin Man W. Mok, Jet-Chau Wen, Shao-Yang Huang, and Wenke Wang. "Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach." AMER GEOPHYSICAL UNION, 2017. http://hdl.handle.net/10150/624351.
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Hydraulic tomography (HT) has become a mature aquifer test technology over the last two decades. It collects nonredundant information of aquifer heterogeneity by sequentially stressing the aquifer at different wells and collecting aquifer responses at other wells during each stress. The collected information is then interpreted by inverse models. Among these models, the geostatistical approaches, built upon the Bayesian framework, first conceptualize hydraulic properties to be estimated as random fields, which are characterized by means and covariance functions. They then use the spatial statistics as prior information with the aquifer response data to estimate the spatial distribution of the hydraulic properties at a site. Since the spatial statistics describe the generic spatial structures of the geologic media at the site rather than site-specific ones (e. g., known spatial distributions of facies, faults, or paleochannels), the estimates are often not optimal. To improve the estimates, we introduce a general statistical framework, which allows the inclusion of site-specific spatial patterns of geologic features. Subsequently, we test this approach with synthetic numerical experiments. Results show that this approach, using conditional mean and covariance that reflect site-specific large-scale geologic features, indeed improves the HT estimates. Afterward, this approach is applied to HT surveys at a kilometerscale- fractured granite field site with a distinct fault zone. We find that by including fault information from outcrops and boreholes for HT analysis, the estimated hydraulic properties are improved. The improved estimates subsequently lead to better prediction of flow during a different pumping test at the site.
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Onnen, Nathaniel J. "Estimation of Bivariate Spatial Data." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1616243660473062.
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Mohamed, Hamad O. "Land suitability evaluation, improving accuracy of assessments with a new paradigm based on geostatistical estimation and fuzzy set theory." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0015/MQ57975.pdf.
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Sengupta, Aritra. "Empirical Hierarchical Modeling and Predictive Inference for Big, Spatial, Discrete, and Continuous Data." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1350660056.
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YATES, SCOTT RAYMOND. "GEOSTATISTICAL METHODS FOR ESTIMATING SOIL PROPERTIES (KRIGING, COKRIGING, DISJUNCTIVE)." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/187990.
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Geostatistical methods were investigated in order to find efficient and accurate means for estimating a regionalized random variable in space based on limited sampling. The random variables investigated were (1) the bare soil temperature (BST) and crop canopy temperature (CCT) which were collected from a field located at the University of Arizona's Maricopa Agricultural Center, (2) the bare soil temperature and gravimetric moisture content (GMC) collected from a field located at the Campus Agricultural Center and (3) the electrical conductivity (EC) data collected by Al-Sanabani (1982). The BST was found to exhibit strong spatial auto-correlation (typically greater than 0.65 at 0⁺ lagged distance). The CCT generally showed a weaker spatial correlation (values varied from 0.15 to 0.84) which may be due to the length of time required to obtain an "instantaneous" sample as well as wet soil conditions. The GMC was found to be strongly spatially dependent and at least 71 samples were necessary in order to obtain reasonably well behaved covariance functions. Two linear estimators, the ordinary kriging and cokriging estimators, were investigated and compared in terms of the average kriging variance and the sum of squares error between the actual and estimated values. The estimate was obtained using the jackknifing technique. The results indicate that a significant improvement in the average kriging variance and the sum of squares could be expected by using cokriging for GMC and including 119 BST values in the analysis. A nonlinear estimator in one variable, the disjunctive kriging estimator, was also investigated and was found to offer improvements over the ordinary kriging estimator in terms of the average kriging variance and the sum of squares error. It was found that additional information at the estimation site is a more important consideration than whether the estimator is linear or nonlinear. Disjunctive kriging produces an estimator of the conditional probability that the value at an unsampled location is greater than an arbitrary cutoff level. This latter feature of disjunctive kriging is explored and has implications in aiding management decisions.
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Müller, Werner, and Dale L. Zimmerman. "Optimal Design for Variogram Estimation." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1997. http://epub.wu.ac.at/756/1/document.pdf.
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The variogram plays a central role in the analysis of geostatistical data. A valid variogram model is selected and the parameters of that model are estimated before kriging (spatial prediction) is performed. These inference procedures are generally based upon examination of the empirical variogram, which consists of average squared differences of data taken at sites lagged the same distance apart in the same direction. The ability of the analyst to estimate variogram parameters efficiently is affected significantly by the sampling design, i.e., the spatial configuration of sites where measurements are taken. In this paper, we propose design criteria that, in contrast to some previously proposed criteria oriented towards kriging with a known variogram, emphasize the accurate estimation of the variogram. These criteria are modifications of design criteria that are popular in the context of (nonlinear) regression models. The two main distinguishing features of the present context are that the addition of a single site to the design produces as many new lags as there are existing sites and hence also produces that many new squared differences from which the variograrn is estimated. Secondly, those squared differences are generally correlated, which inhibits the use of many standard design methods that rest upon the assumption of uncorrelated errors. Several approaches to design construction which account for these features are described and illustrated with two examples. We compare their efficiency to simple random sampling and regular and space-filling designs and find considerable improvements. (author's abstract)Series: Forschungsberichte / Institut für Statistik
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Arzuman, Sadun. "Comparison Of Geostatistics And Artificial Neural Networks In Reservoir Property Estimation." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611192/index.pdf.
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In this dissertation, 3D surface seismic data was integrated with the well logs
to be able to define the properties in every location for the reservoir under
investigation. To accomplish this task, geostatistical and artificial neural networks
(ANN) techniques were employed.
First, missing log sets in the study area were estimated using common
empirical relationships and ANN. Empirical estimations showed linear dependent
results that cannot be generalized. On the other hand, ANNs predicted missing logs
with an very high accuracy. Sonic logs were predicted using resistivity logs with 90%
correlation coefficient. Second, acoustic impedance property was predicted in the
study area. AI estimation first performed using sonic log with GRNN and 88% CC
was obtained. AI estimation was repeated using sonic and resistivity logs and the
result were improved to 94% CC.
In the final part of the study, SGS technique was used with collocated
cokriging techniques to estimate NPHI property. Results were varying due to nature
of the algorithm. Then, GRNN and RNN algorithms were applied to predict NPHI
property. Using optimized GRNN network parameters, NPHI was estimated with
high accuracy.
Results of the study were showed that ANN provides a powerful solution for
reservoir parameter prediction in the study area with its flexibility to find out nonlinear
relationships from the existing available data.
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Chipeta, Michael Give. "Geostatistical design and analysis for estimating local variations in malaria disease burden." Thesis, Lancaster University, 2016. http://eprints.lancs.ac.uk/84366/.
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Geostatistical design and analysis methods are increasingly used in disease mapping, particularly in resource-limited settings where uniformly precise mapping may be unrealistically costly and the priority is often to identify critical areas where interventions can have the most health impact. In this thesis, which is based on four papers, we address the problem of geostatistical sampling design. In the first paper, we consider the problem of sampling design for efficient spatial prediction taking account of uncertain covariance structure, in the context of nonadaptive designs. We propose two classes of designs, namely: simple inhibitory and inhibitory plus close pairs. We evaluate the performance of these designs using an average prediction variance criterion and show how the findings are applied to the design of a rolling Malaria Indicator Survey (rMIS) in an ongoing large-scale, five-year malaria transmission reduction project in Malawi. In the second paper, we address the problem of efficient spatial prediction in the context of adaptive geostatistical designs (AGD). We propose two classes of designs based on singleton and batch sampling. We show how our findings inform an AGD of rMIS, in the perimeter of Majete Wildlife Reserve (MWR) in Chikwawa, southern Malawi. The third paper is a commentary on a paper by Ferreira and Gamerman (2015), which addressed the effect of preferential sampling of the locations at which to measure a spatial process. In the fourth paper, we present the first epidemiological field application of AGD sampling in a malaria prevalence survey. We give an in-depth description of the project, the study area and practical implementation of our adaptive sampling strategy. We present prevalence maps for children 6–59 months in MWR perimeter, showing high malaria transmission areas, often called “hotspots”, that could be targeted with interventions.
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Nogueira, Neto Joao Antunes 1952. "APPLICATION OF GEOSTATISTICS TO AN OPERATING IRON ORE MINE." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276417.
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The competition in the world market for iron ore has increased lately. Therefore, an improved method of estimating the ore quality in small working areas has become an attractive cost-cutting strategy in short-term mine plans. Estimated grades of different working areas of a mine form the basis of any short-term mine plan. The generally sparse exploration data obtained during the development phase is not enough to accurately estimate the grades of small working areas. Therefore, additional sample information is often required in any operating mine. The findings of this case study show that better utilization of all available exploration information at this mine would improve estimation of small working areas even without additional face samples. Through the use of kriging variance, this study also determined the optimum face sampling grid, whose spacing turned out to be approximately 100 meters as compared to 50 meters in use today. (Abstract shortened with permission of author.)
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Rojas, Ricardo Vicente 1951. "ORE-WASTE SELECTION UTILIZING GEOSTATISTICS (ARIZONA)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/291255.
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Kapageridis, Ioannis K. "Application of artificial neural network systems to ore grade estimation from exploration data." Thesis, University of Nottingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301663.
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Cavalcante, Fraga Luis Henrique. "Caractérisation des sols pollués via des méthodes géophysiques : couplage entre le diagnostic conventionnel et les méthodes géophysiques pour estimer la distribution spatiale des polluants à l’aide du formalisme géostatistique." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS645.
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La caractérisation spatiale de sources de pollution est un enjeu majeur pour la réhabilitation de sites pollués. Les analyses géochimiques d’échantillons sont coûteuses et onéreuses en temps et ne permet qu’une vision ponctuelle des sites. Ces travaux ont évalué la méthode de cartographie électromagnétique (EMI) pour imager les propriétés physiques indirectes du sous-sol afin de (1) définir des protocoles de mesures géophysiques adaptés (2) d’exploiter les mesures spatialisées (géophysiques et géochimiques) pour l'estimation des volumes de sols pollués aux hydrocarbures grâce au formalisme géostatistique. Les résultats sur le site de Poitiers, localisé en contexte péri-urbain, ont mis en évidence la sensibilité de la méthode EMI pour déterminer la géométrie d'une couche de remblais. La stratégie finale appliquée sur le site de Rouen, fortement pollué aux hydrocarbures et situé en milieu urbain, a été modifiée avec une cartographie EMI exhaustive, des panneaux électriques, une prospection au géoradar et des mesures sur échantillons. L’analyse statistique multivariable a indiqué une corrélation globale entre les teneurs en hydrocarbures et les conductivités électriques apparentes mesurées par la méthode EMI. L’hétérogénéité des remblais, les aménagements et un aquifère discontinu ont fortement perturbé les mesures EMI. Malgré la diminution de la variance de l’erreur d’estimation lorsque les données géophysiques ont été intégrées dans les modèles géostatistiques, les corrélations linéaires restent encore faibles et limitées par la représentativité des sites. Un protocole de mesures géophysiques a été conçu et a montré son potentiel pour la caractérisation de sites polluésThe spatial characterization of pollution sources is a key step for estimating the costs of the rehabilitation of contaminated sites. Geochemical sampling is costly and time-consuming and only allows punctual information about contamination levels. This PhD work evaluated the electromagnetic mapping method (EMI) for imaging the physical properties of the subsoil to (1) define geophysical measurement protocols and (2) exploit spatialized geophysical and geochemical data for a better estimation of hydrocarbon-polluted soil volumes through geostatistical formalism. The results at the Poitiers’ site, located in a peri-urban context with an unknown backfill coverage, highlighted the sensitivity of the EMI method for determining the geometry of the backfill layer. The new geophysical measurement strategy applied at the Rouen’s site, which is heavily polluted with hydrocarbons and located in an urban environment, has been modified with exhaustive EMI mapping, electrical resistivity and polarization tomography, ground penetrating radar and physical measurements at sample scale. The multivariate statistical analysis indicated an overall correlation between the hydrocarbon levels and the apparent electrical conductivities measured by the EMI method. Nevertheless, the heterogeneity of the urban fill, surface facilities and a discontinuous aquifer have severely disrupted EMI measurements. Despite the decrease in the variance of estimation error when geophysical data have been integrated into geostatistical models, linear correlations are still weak. A novel geophysical measurement protocol has been designed and demonstrated its potential for assessing contaminated sites
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Barahona-Palomo, Marco. "Estimation of aquifers hydraulic parameters by three different tecniques: geostatistics, correlation and modeling." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144941.
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Characterization of aquifers hydraulic parameters is a difficult task that requires field information. Most of the time the hydrogeologist relies on a group of values coming from different test to interpret the hydrogeological setting and possibly, generate a model. However, getting the best from this information can be challenging.
In this thesis, three cases are explored. First, hydraulic conductivities associated with measurement scale of the order of 10−1 m and collected during an extensive field campaign near Tübingen, Germany, are analyzed. Estimates are provided at coinciding locations in the system using: the empirical Kozeny-Carman formulation, providing conductivity values, based on particle size distribution, and borehole impeller-type flowmeter tests, which infer conductivity from measurements of vertical flows within a borehole. Correlation between the two sets of estimates is virtually absent. However, statistics of the natural logarithm of both sets at the site are similar in terms of mean values and differ in terms of variogram ranges and sample variances. This is consistent with the fact that the two types of estimates can be associated with different (albeit comparable) measurement (support) scales. It also matches published results on interpretations of variability of geostatistical descriptors of hydraulic parameters on multiple observation scales. The analysis strengthens the idea that hydraulic conductivity values and associated key geostatistical descriptors inferred from different methodologies and at similar observation scales (of the order of tens of cm) are not readily comparable and should not be embedded blindly into a flow (and eventually transport) prediction model.
Second, a data-adapted kernel regression method, originally developed for image processing and reconstruction is modified and used for the delineation of facies. This non-parametric methodology uses both the spatial and the sample value distribution, to produce for each data point a locally adaptive steering kernel function, self-adjusting the kernel to the direction of highest local spatial correlation. The method is shown to
outperform the nearest-neighbor classification (NNC) in a number of synthetic aquifers whenever the available number of data is small and randomly distributed. Still, in the limiting case, when the domain is profusely sampled, both the steering kernel method and the NNC method converge to the true solution. Simulations are finally used to explore which parameters of the locally adaptive kernel function yield optimal reconstruction results in typical field settings. It is shown that, in practice, a rule of thumb can be used to get suboptimal results, which are best when key prior information
such as facies proportions is used.
Third, the effect of water temperature fluctuation on the hydraulic conductivity profile of coarse sediments beneath an artificial recharge facility is model and compared with field data. Due to the high permeability, water travels at a high rate, and therefore also water with different temperature is also present on the sediment under the pond at different moments, this translates into different hydraulic conductivity values within the same layer, even though all the other parameters are the same for this layer. Differences of almost 79% in hydraulic conductivity were observed for the model temperatures (2 °C – 25 °C). This variation of hydraulic conductivity in the sediment below the infiltration pond when water with varying temperature enters the sediment, causes the infiltration velocity to change with time and produces the observed fluctuation on the field measurements.La caracterización de los parámetros hidráulicos de los acuíferos es una tarea difícil que requiere información de campo. La mayoría de las veces el hidrogeólogo se basa en un grupo de valores procedentes de diferentes pruebas para interpretar la configuración hidrogeológica y posiblemente , generar un modelo . Sin embargo, obtener lo mejor de esta información puede ser un reto. En esta tesis se analizan tres casos. Primero, se analizan las conductividades hidráulicas asociadas a una escala de medición del orden de 10 m− 1 y obtenidas durante una extensa campaña de campo cerca de Tübingen, Alemania. Las estimaciones se obtuvieron en puntos coincidentes en el sitio, mediante: la formulación empírica de Kozeny - Carman, proporcionando valores de conductividad, con base en la distribución de tamaño de partículas y las pruebas del medidor de caudal de tipo impulsor en el pozo, el cual infiere las medidas de conductividad a partir de los flujos verticales dentro de un pozo. La correlación entre los dos conjuntos de estimaciones es prácticamente ausente. Sin embargo, las estadísticas del logaritmo natural de ambos conjuntos en el lugar son similares en términos de valores medios y difieren en términos de rangos del variograma y varianzas de muestra. Esto es consecuente con el hecho de que los dos tipos de estimaciones pueden estar asociados con escalas de apoyo de medición diferentes (aunque comparables). También coincide con los resultados publicados sobre la interpretación de la variabilidad de los descriptores geoestadísticos de parámetros hidráulicos en múltiples escalas de observación . El análisis refuerza la idea de que los valores de conductividad hidráulica y descriptores geoestadísticos clave asociados al inferirse de diferentes metodologías y en las escalas de observación similares (en el caso del orden de decenas de cm) no son fácilmente comparables y debe ser utilizados con cuidado en la modelación de flujo (y eventualmente, el transporte) del agua subterránea. En segundo lugar, un método de regresión kernel adaptado a datos, originalmente desarrollado para el procesamiento y la reconstrucción de imágenes se modificó y se utiliza para la delimitación de las facies. Esta metodología no paramétrica utiliza tanto la distribución espacial como el valor de la muestra, para producir en cada punto de datos una función kernel de dirección localmente adaptativo, con ajuste automático del kernel a la dirección de mayor correlación espacial local. Se demuestra que este método supera el NNC (por su acrónimo en inglés nearest-neighbor classification) en varios casos de acuíferos sintéticos donde el número de datos disponibles es pequeño y la distribución es aleatoria. Sin embargo, en el caso límite, cuando hay un gran número de muestras, tanto en el método kernel adaptado a la dirección local como el método de NNC convergen a la solución verdadera. Las simulaciones son finalmente utilizadas para explorar cuáles parámetros de la función kernel localmente adaptado dan resultados óptimos en la reconstrucción de resultados en escenarios típicos de campo. Se demuestra que, en la práctica, una regla general puede ser utilizada para obtener resultados casi óptimos, los cuales mejoran cuando se utiliza información clave como la proporción de facies. En tercer lugar, se modela el efecto de la fluctuación de la temperatura del agua sobre la conductividad hidráulica de sedimentos gruesos debajo de una instalación de recarga artificial y se compara con datos de campo. Debido a la alta permeabilidad, el agua se desplaza a alta velocidad alta, y por lo tanto, agua con temperatura diferente también está presente en el sedimento bajo el estanque en diferentes momentos, esto se traduce en diferentes valores de conductividad hidráulica dentro de la misma capa, a pesar de que todos los demás parámetros son los mismos para esta capa. Se observaron diferencias de casi 79 % en la conductividad hidráulica en el modelo, para las temperaturas utilizadas (2 º C - 25 º C ). Esta variación de la conductividad hidráulica en el sedimento por debajo de la balsa de infiltración cuando el agua de temperatura variable entra en el sedimento, causa un cambio en la velocidad de infiltración con el tiempo y produce las fluctuacciones observadas en las mediciones de campo.
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Teixeira, Daniel De Bortoli [UNESP]. "Incertezas na estimativa da variabilidade espacial da emissão de CO2 do solo e propriedades edáficas em área de cana crua." Universidade Estadual Paulista (UNESP), 2011. http://hdl.handle.net/11449/88232.
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A emissão de CO2 do solo (FCO2) apresenta alta variabilidade espacial, sendo devida a grande dependência espacial existente nas propriedades do solo que a influenciam. Neste estudo objetivou-se (i) caracterizar e relacionar a variabilidade e a distribuição espacial da FCO2, temperatura do solo, porosidade livre de água (PLA), teor de matéria orgânica do solo (MO) e densidade do solo (Ds), (ii) avaliar a acurácia dos resultados fornecidos pelo método da krigagem ordinária (KO) e simulação sequencial Gaussiana (SSG), e (iii) avaliar a incerteza na predição da variabilidade espacial das FCO2 e demais propriedades utilizando a SSG. O estudo foi conduzido em uma malha amostral regular de 60 x 60 m2 com 141 pontos, com espaçamento mínimo variando de 0,50 a 10 m, instalada em área de cana-de-açúcar. Nestes pontos foram avaliados a FCO2, temperatura do solo, PLA, determinadas com base na média de 07 dias de avaliação, MO e Ds. Todas as variáveis apresentaram estrutura de dependência espacial, sendo ajustados modelos Gaussianos, esféricos e exponenciais. A configuração da malha amostral e possivelmente a presença de espessa camada de resíduos da cultura sobre o solo influenciaram a estrutura de variabilidade espacial da FCO2, temperatura e MO. FCO2 apresentou correlações positivas com a MO (r = 0,25, p < 0,05) e PLA (r = 0,27, p < 0,01) e negativa com a Ds (r = - 0,41, p < 0,01). No entanto, quando os valores digitais estimados espacialmente (N=8.833) são considerados, a PLA passa a ser a principal variável responsável pelas características espaciais da FCO2, apresentando correlação de 0,26 (p < 0,01). As simulações individuais propiciaram, para todas as variáveis analisadas, melhor reprodução das funções de distribuição acumuladas (fdac), e dos variogramas em comparação...
The soil CO2 emission (FCO2) has high spatial variability, which caused due to the strong spatial dependence in soil properties that influence it. This study aimed to (i) to characterize the variability and spatial distribution of FCO2, soil temperature, air-filled pore space (AFPS), soil organic matter (OM) and soil bulk density (BD) and related properties, (ii) evaluate the accuracy of the results provided by the method of ordinary kriging (OK) and sequential Gaussian simulation (SGS), and (iii) evaluate the uncertainty in predicting the spatial variability of FCO2 and other properties using the SSG. The study was conducted on an regular sampling grid with 141 points, with spacing ranging from 0.50 to 10 m, installed in a sugarcane area. In this place were evaluated FCO2, soil temperature, AFPS, were based on the average of 07 days of evaluation, OM and BD. All variables showed spatial dependence structure, and models adjusted Gaussian, spherical and exponential. The configuration of the sampling grid and the presence of intense layer of crop residues in the soil influenced the structure of spatial variability of FCO2, temperature, and OM. The FCO2 showed positive correlations with OM (r = 0.25, p <0.05) and AFPS (r = 0.27, p <0.01) and negatively with Ds (r = - 0.41, p <0.01). However, when the estimated spatially values are considered, the AFPS becomes the main variable responsible for the spatial characteristics of FCO2, showing correlation of 0.26 (p <0.01). The individual simulations led to all variables, better reproduction of the cumulative distribution functions (cdf), and variograms compared to OK and E-type estimate. The analysis results show strong similarities between the E-type estimates to those generated by the procedure of OK. The major uncertainties in predicting FCO2 were associated with areas with the highest... (Complete abstract click electronic access below)
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Rodriguez-Vilca, Juliet, Jose Paucar-Vilcañaupa, Humberto Pehovaz-Alvarez, Carlos Raymundo, Nestor Mamani-Macedo, and Javier M. Moguerza. "Method for the Interpretation of RMR Variability Using Gaussian Simulation to Reduce the Uncertainty in Estimations of Geomechanical Models of Underground Mines." Springer, 2020. http://hdl.handle.net/10757/656171.
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.The application of conventional techniques, such as kriging, to model rock mass is limited because rock mass spatial variability and heterogeneity are not considered in such techniques. In this context, as an alternative solution, the application of the Gaussian simulation technique to simulate rock mass spatial heterogeneity based on the rock mass rating (RMR) classification is proposed. This research proposes a methodology that includes a variographic analysis of the RMR in different directions to determine its anisotropic behavior. In the case study of an underground deposit in Peru, the geomechanical record data compiled in the field were used. A total of 10 simulations were conducted, with approximately 6 million values for each simulation. These were calculated, verified, and an absolute mean error of only 3.82% was estimated. It is acceptable when compared with the value of 22.15% obtained with kriging.
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Zelelew, Mulugeta. "Improving Runoff Estimation at Ungauged Catchments." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for vann- og miljøteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19675.
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Water infrastructures have been implemented to support the vital activities of human society. The infrastructure developments at the same time have interrupted the natural catchment response characteristics, challenging society to implement effective water resources planning and management strategies. The Telemark area in southern Norway has seen a large number of water infrastructure developments, particularly hydropower, over more than a century. Recent developments in decision support tools for flood control and reservoir operation has raised the need to compute inflows from local catchments, most of which are regulated or have no observed data. This has contributed for the motivation of this PhD thesis work, with an aim of improving runoff estimation at ungauged catchments, and the research results are presented in four manuscript scientific papers. The inverse distance weighting, inverse distance squared weighting, ordinary kriging, universal kriging and kriging with external drift were applied to analyse precipitation variability and estimate daily precipitation in the study area. The geostatistical based univariate and multivariate map-correlation concepts were applied to analyse and physically understand regional hydrological response patterns. The Sobol variance based sensitivity analysis (VBSA) method was used to investigate the HBV hydrological model parameterization significances on the model response variations and evaluate the model’s reliability as a prediction tool. The HBV hydrological model space transferability into ungauged catchments was also studied. The analyses results showed that the inverse distance weighting variants are the preferred spatial data interpolation methods in areas where relatively dense precipitation station network can be found. In mountainous areas and in areas where the precipitation station network is relatively sparse, the kriging variants are the preferred methods. The regional hydrological response correlation analyses suggested that geographic proximity alone cannot explain the entire hydrological response correlations in the study area. Besides, when the multivariate map-correlation analysis was applied, two distinct regional hydrological response patterns - the radial and elliptical-types were identified. The presence of these hydrological response patterns influenced the location of the best-correlated reference streamgauges to the ungauged catchments. As a result, the nearest streamgauge was found the best-correlated in areas where the radial-type hydrological response pattern is the dominant. In area where the elliptical-type hydrological response pattern is the dominant, the nearest reference streamgauge was not necessarily the best-correlated. The VBSA verified that varying up to a minimum of four to six influential HBV model parameters can sufficiently simulate the catchments' responses characteristics when emphasis is given to fit the high flows. Varying up to a minimum of six influential model parameters is necessary to sufficiently simulate the catchments’ responses and maintain the model performance when emphasis is given to fit the low flows. However, varying more than nine out of the fifteen HBV model parameters will not make any significant change on the model performance. The hydrological model space transfer study indicated that estimation of representative runoff at ungauged catchments cannot be guaranteed by transferring model parameter sets from a single donor catchment. On the other hand, applying the ensemble based model space transferring approach and utilizing model parameter sets from multiple donor catchments improved the model performance at the ungauged catchments. The result also suggested that high model performance can be achieved by integrating model parameter sets from two to six donor catchments. Objectively minimizing the HBV model parametric dimensionality and only sampling the sensitive model parameters, maintained the model performance and limited the model prediction uncertainty.
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Zhang, Xi. "SPATIAL ESTIMATION OF HYDRAULIC PROPERTIES IN STRUCTURED SOILS AT THE FIELD SCALE." UKnowledge, 2019. https://uknowledge.uky.edu/pss_etds/117.
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Improving agricultural water management is important for conserving water during dry seasons, using limited water resources in the most efficient way, and minimizing environmental risks (e.g., leaching, surface runoff). The understanding of water movement in different zones of agricultural production fields is crucial to developing an effective irrigation strategy. This work centered on optimizing field water management by characterizing the spatial patterns of soil hydraulic properties. Soil hydraulic conductivity was measured across different zones in a farmer’s field, and its spatial variability was investigated by using geostatistical techniques. Since direct measurement of hydraulic conductivity is time-consuming and arduous, pedo-transfer functions (PTFs) have been developed to estimate hydraulic conductivity indirectly through more easily measurable soil properties. Due to ignoring soil structural information and spatial covariance between soil variables, PTFs often perform unsatisfactorily when field-scale estimations of hydraulic conductivity are needed. The performance of PTFs in estimating hydraulic conductivity in the field was therefore critically evaluated. Due to the presence of structural macro-pores, saturated hydraulic conductivity (Ks) showed high spatial heterogeneity, and this variability was not captured by texture-dominated PTF estimates. However, the general spatial pattern of near-saturated hydraulic conductivity can still be reasonably generated by PTF estimates. Therefore, the hydraulic conductivity maps based on PTF estimates should be evaluated carefully and handled with caution. Recognizing the significant contribution of macro-pores to saturated water flow, PTFs were further improved by including soil macro-porosity and were proven to perform much better in estimating Ks compared with established PTFs tested in this study. Additionally, the spatial relationship between hydraulic conductivity and its potential influencing factors were further quantified by the state-space approach. State-space models outperformed current PTFs and effectively described the spatial characteristics of hydraulic conductivity in the studied field. These findings provided a basis for modeling water/solute transport in the vadose zone, and sitespecific water management.
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Seck, Ibrahim. "Estimation et prévision immédiate des précipitations sur un bassin urbain." Thesis, Université Clermont Auvergne (2017-2020), 2020. http://www.theses.fr/2020CLFAC055.
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Dans le contexte de changement climatique, les évènements météorologiques extrêmes sont appelés à augmenter en termes de fréquence et d’intensité. Conséquemment, le développement de systèmes d’alerte des crues soudaines est primordial pour les agglomérations urbaines. Cette thèse se penche sur deux volets de tels systèmes, à savoir l’amélioration des estimations quantitatives et la prévision immédiate des précipitations (moins de 6 heures) sur le bassin urbain « Clermont Ferrand-Riom », un bassin classé comme étant un territoire à risque important d’inondation. Deux instruments sont utilisés : le pluviomètre (réseau pluviométrique de la métropole Clermont Auvergne, et réseau pluviométrique de Météo France), et le radar météorologique (« petit » radar en bande X du Laboratoire de Météorologie Physique, et le réseau de radar ARAMIS de Météo-France). Sur le premier volet, on a examiné la performance des méthodes géostatistiques pour l’amélioration des estimations quantitatives des précipitations à haute résolution spatiotemporelle (5 minutes et 100 m), particulièrement deux méthodes multivariables (le krigeage avec dérive externe et la fusion conditionnée) pour la fusion des données radar en bande X avec les données pluviométriques locaux, et ce par type de précipitations (stratiforme, convectif ou mixte). Pour ce faire, une analyse variographique a été réalisée pour la détermination des variogrammes climatologiques caractéristiques de chaque type de précipitations. Il est en est ressorti que les estimations quantitatives des précipitations issues des données pluviométriques peuvent être améliorées de façon significative en utilisant les données radar comme variable secondaire avec les méthodes géostatistiques d’interpolation spatiale, en particulier pour la restitution de la variabilité des champs de précipitations. Deux méthodes de fusion de données radar ont également été examinées pour l’amélioration des estimations quantitatives de précipitations sur le bassin clermontois avec le radar en bande X et le produit PANTHERE (mosaïque de lames d’eau sur tout le territoire français avec une résolution de 5 minutes et 1 km avec le réseau de radars ARAMIS, essentiellement en bande C et S). La première vise à corriger les effets de l’atténuation entachant les champs en bande X en utilisant les mesures de réflectivités en bande C et S du produit PANTHERE, moins affectés par l’atténuation. La deuxième consiste à l’application de la méthode de correction quantile-quantile sur les champs de précipitations du radar en bande X pour tirer profit de la précision des mesures du produit PANTHERE. Notre évaluation de la performance de ces deux méthodes montre leur efficacité en termes de minimisation des biais des mesures du radar en bande X par rapport aux mesures pluviométriques.Dans le second volet, nous nous sommes intéressés à la capacité de notre radar en bande X à fournir des prévisions immédiates des précipitations malgré sa portée de 20 km seulement, nous avons donc appliqué une méthode « orientée objet » sur deux évènements pluvieux à partir d’images de cet instrument. Cette méthode se base sur l’identification des cellules précipitantes, la reconstitution de leurs trajectoires au fil du temps, et enfin l’extrapolation de leurs caractéristiques (comme la surface, la vitesse, la direction, le taux de précipitations moyen…) pour avoir des prévisions. Les vérifications des prévisions immédiates réalisées grâce au deux études de cas considérés montrent que les prévisions sont globalement correctes pour les échéances inférieures à 30 minutes, elles commencent à se détériorer au-delà. Les recherches menées dans le cadre de cette thèse montrent tout le potentiel que possèdent les « petits » radars pour l’estimation et la prévision immédiate des précipitations, en particulier pour les bassins urbainsGood quality rainfall estimations and nowcasts are an essential prerequisite for the development of reliable flash flood warning systems, especially for urban catchments, where the socioeconomic consequences of hazardous precipitation events are high. The risks posed by such extreme events are further heightened because of climate change. In this context, this thesis aims to investigate the potential of using a small weather radar in combination with the local rain gauge and national radar networks to improve the quantitative precipitation estimation (QPE) of rainfall, and to deliver reliable nowcasts. This research was carried out in the flood prone urban catchment of Clermont Ferrand-Riom.To improve QPEs with a high spatiotemporal resolution (5 minutes and a 100 m), the performance of geostatistical interpolation techniques has been investigated using rain gauge data as a primary variable and X-band radar data as a secondary variable for the kriging with an external drift and conditional merging techniques. Radar data was used for the inference of climatological variograms for each precipitation type (stratiform, convective or mixed) for all geostatistical interpolation techniques including ordinary kriging. The long-term evaluation of these techniques shows the benefit of using the geostatistical approach to merge rain gauge and radar data, especially to capture the spatial variability of rainfall. Additionally, two methods were examined to combine the X-band LAWR (Local Area Weather Radar) data with the PATNTHERE product (Rainfall sums with a resolution of 5 minutes and 1 km, provided by the national weather service Météo-France). The first method uses the PANTHERE product (using mainly a C-band radar over the area of interest) to correct X-band data from attenuation effects, and the second one consists of applying a quantile-quantile correction to the X-band data using the PANTHERE product to take advantage of its overall better measurement accuracy, both methods have shown satisfactory results in terms of reducing bias of X-band radar data in comparison with rain gauge data.In the second section of this research, a feature-based forecasting method has been applied to two rainfall events in order to investigate the ability of the X-band LAWR of providing reliable nowcasts. The method includes several steps aimed at identifying, tracking, and then interpolating the features of rainfall cells such as area, speed, and average precipitation intensity. The application of this method on two case studies shows that it provided satisfactory results for forecast lead times up to 30 minutes but efficiency degrades for further time frames.In conclusion, the research carried out in this thesis indicates that local X-band LAWR have great potential for rain estimates and forecast and should be considered in the development of flash flood warning systems, especially for urban catchments
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Teixeira, Daniel De Bortoli. "Incertezas na estimativa da variabilidade espacial da emissão de CO2 do solo e propriedades edáficas em área de cana crua /." Jaboticabal : [s.n.], 2011. http://hdl.handle.net/11449/88232.
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Orientador: Newton La Scala JúniorCoorientador: Alan Rodrigo Panosso
Coorientador: Gener Tadeu Pereira
Banca: Carlos Eduardo Pellegrino Cerri
Banca: Glauco de Souza Rolim
Resumo: A emissão de CO2 do solo (FCO2) apresenta alta variabilidade espacial, sendo devida a grande dependência espacial existente nas propriedades do solo que a influenciam. Neste estudo objetivou-se (i) caracterizar e relacionar a variabilidade e a distribuição espacial da FCO2, temperatura do solo, porosidade livre de água (PLA), teor de matéria orgânica do solo (MO) e densidade do solo (Ds), (ii) avaliar a acurácia dos resultados fornecidos pelo método da krigagem ordinária (KO) e simulação sequencial Gaussiana (SSG), e (iii) avaliar a incerteza na predição da variabilidade espacial das FCO2 e demais propriedades utilizando a SSG. O estudo foi conduzido em uma malha amostral regular de 60 x 60 m2 com 141 pontos, com espaçamento mínimo variando de 0,50 a 10 m, instalada em área de cana-de-açúcar. Nestes pontos foram avaliados a FCO2, temperatura do solo, PLA, determinadas com base na média de 07 dias de avaliação, MO e Ds. Todas as variáveis apresentaram estrutura de dependência espacial, sendo ajustados modelos Gaussianos, esféricos e exponenciais. A configuração da malha amostral e possivelmente a presença de espessa camada de resíduos da cultura sobre o solo influenciaram a estrutura de variabilidade espacial da FCO2, temperatura e MO. FCO2 apresentou correlações positivas com a MO (r = 0,25, p < 0,05) e PLA (r = 0,27, p < 0,01) e negativa com a Ds (r = - 0,41, p < 0,01). No entanto, quando os valores digitais estimados espacialmente (N=8.833) são considerados, a PLA passa a ser a principal variável responsável pelas características espaciais da FCO2, apresentando correlação de 0,26 (p < 0,01). As simulações individuais propiciaram, para todas as variáveis analisadas, melhor reprodução das funções de distribuição acumuladas (fdac), e dos variogramas em comparação... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: The soil CO2 emission (FCO2) has high spatial variability, which caused due to the strong spatial dependence in soil properties that influence it. This study aimed to (i) to characterize the variability and spatial distribution of FCO2, soil temperature, air-filled pore space (AFPS), soil organic matter (OM) and soil bulk density (BD) and related properties, (ii) evaluate the accuracy of the results provided by the method of ordinary kriging (OK) and sequential Gaussian simulation (SGS), and (iii) evaluate the uncertainty in predicting the spatial variability of FCO2 and other properties using the SSG. The study was conducted on an regular sampling grid with 141 points, with spacing ranging from 0.50 to 10 m, installed in a sugarcane area. In this place were evaluated FCO2, soil temperature, AFPS, were based on the average of 07 days of evaluation, OM and BD. All variables showed spatial dependence structure, and models adjusted Gaussian, spherical and exponential. The configuration of the sampling grid and the presence of intense layer of crop residues in the soil influenced the structure of spatial variability of FCO2, temperature, and OM. The FCO2 showed positive correlations with OM (r = 0.25, p <0.05) and AFPS (r = 0.27, p <0.01) and negatively with Ds (r = - 0.41, p <0.01). However, when the estimated spatially values are considered, the AFPS becomes the main variable responsible for the spatial characteristics of FCO2, showing correlation of 0.26 (p <0.01). The individual simulations led to all variables, better reproduction of the cumulative distribution functions (cdf), and variograms compared to OK and E-type estimate. The analysis results show strong similarities between the E-type estimates to those generated by the procedure of OK. The major uncertainties in predicting FCO2 were associated with areas with the highest... (Complete abstract click electronic access below)
Mestre
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Xu, Shan. "Caractérisation de l’environnement karstique de la grotte de Lascaux par couplage de méthodes géophysique, statistique et géostatistique." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0244/document.
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La grotte de Lascaux (inscrite au patrimoine mondial de l’UNESCO et l’une des plus connues au monde) nécessite, dans le cadre de sa conservation et suite aux aléas subis depuis sa découverte, une attention particulière tant pour elle-même que pour son environnement. L’utilisation d’une méthode géophysique, la Tomographie de Résistivité électrique (TRE) qui est une méthode non intrusive par excellence, est donc proposée pour la reconnaissance du milieu karstique l’environnant.Un suivi temporel par TRE a été mise en oeuvre pour caractériser l’amont hydraulique de la grotte et surveiller la variation temporelle de la résistivité des terrains. A l’aide d’analyses statistiques, et en couplant les données microclimatiques aux résultats d’un suivi temporel de vingt-deux mois, nous avons montré la capacité de ce type de mesures à caractériser l’environnement épikarstique de la grotte, particulièrement les zones d’alimentation et celles permettant l’infiltration des eaux pluviales. Une modélisation du débit d’un écoulement situé à l’entrée de la grotte est proposée à partir des données de résistivité dans la zone d’alimentation identifiée au cours du suivi. Ce modèle a la capacité de prédire les arrêts et les reprises des écoulements dans la grotte, éventuellement des évènements journaliers.A partir des données de résistivité issues d’une prospection 3D du site, des modélisations géostatistiques par krigeage ordinaire et par indicatrice ont été effectuées permettant des représentations spatiales en fonction de la résistivité des terrains. Ces modèles se sont révélés extrêmement instructifs par l’imagerie de l’environnement karstique de la grotte de Lascauxqui en a résulté. Les limites des formations détritiques et des calcaires sont identifiées à l’est et l’ouest du site. A l’intérieur des calcaires, on retrouve, bien sûr, les anomalies conductrices déjà identifiées au cours du suivi temporel mais aussi leur extension spatiale. Ainsi, on a pu mettre en évidence la continuité spatiale de certaines anomalies.Le suivi temporel par TRE a permis la compréhension de la structure et du fonctionnement de l’alimentation de l’épikarst. Les modèles géostatistiques 3D ont montré leur efficacité pour la caractérisation de l’environnement de la grotte. Les résultats aideraient à proposer des conseils pour la protection du milieu environnant la grotte et ainsi pour la préservation de cette dernièreThe Lascaux cave, one of the most important prehistoric caves in the world, located in Dordogne (24, France) needs particular attention both for itself and for the environment interms of conservation and vulnerability since its discovery. Geophysical methods in particular Electrical Resistivity Tomography (ERT) enable us, in a non-invasive way, to monitor the karsticenvironment.A Time-Lapse monitoring by ERT was carried out next to the cave. Together with analysis of the local effective rainfall (ground water recharge) and the flow in the cave, the monitoringhelped us to identify an area where upstream underground water is probably stored e.g. arecharge zone. There is a large electrical contrast between the surrounding limestone and theprobable recharge zone. Then, a multivariate analysis through the resistivity values allowed usto characterize the model blocks, showing a specific behavior over time, especially the blockswith the lowest electrical resistivity. A prediction model of the flow in relation with the recharge zone succeeded to predict the beginning and the end of flow, even the daily event withextremely high value of flow.In order to visualize the environment in 3D condition, a geostatistical modelling was then applied to the resistivity values. The geostatistical models can emphasize the limit betweenthe limestone promontory and the clayey/sandy formations to the east/west part of the site. In the limestone promontory, the models also showed the possible connection between theanomalous conductive areas that may have a special consequence in this karstic environment.The Time-Lapse monitoring by ERT allows us to understand the karstic structures andrecharge phenomena. The 3D geostatistical modeling showed efficiency for the characterization of the cave environment. Those results can help to provide advices for the cave preservation
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Zonete, Maria Carolina Cunha. "Avaliação do uso de técnicas de interpolação para estimativa de volume em florestas clonais de Eucalyptus sp." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/11/11150/tde-05082009-082221/.
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O conhecimento do estoque florestal é uma importante ferramenta para que o planejamento de curto, médio e longo prazo possam ser realizados. Em cada talhão o estoque é obtido através do inventário florestal. O trabalho realizado teve como objetivo aplicar conceitos de geoestatística que se beneficiem da dependência espacial de certas variáveis para estimar o volume em pontos não amostrados. Para a realização deste estudo, foram utilizados métodos de interpolação, procedimento pelo qual se estimam valores de uma variável em área interior aos pontos de amostragem disponíveis, permitindo representar o comportamento de variáveis amostradas pontualmente e extrapolar valores da variável fora dos limites da área amostrada. Foram instaladas 34 parcelas para estimativa do inventário florestal e 36 parcelas de controle para comparar as diferenças entre o valor estimado e o valor efetivamente medido das variáveis: volume, área basal e altura média de um povoamento de clones de eucalipto em aproximadamente 205 ha, localizados em Mogi-Guaçu-SP. Além destas parcelas, foram mensuradas 24 parcelas em uma área vizinha aos talhões em estudo para compor cenários que pudessem melhorar a estimativa em regiões de borda. Com o auxílio do software Geomedia Professional®, três métodos de interpolação foram testados: Krigagem universal, Inverso da distância ponderada (IDW) e Spline. Para cada um dos métodos foram realizadas simulações com a inclusão de novas parcelas visando avaliar o comportamento da estimativa com o aumento da intensidade amostral. Nesse procedimento, foram criados 6 diferentes cenários com crescente números de parcelas: Am com 34 parcelas; G com 58 parcelas; G+5 com 63 parcelas; G+10 com 68 parcelas; G+15 com 73 parcelas e G+20.com 78 parcelas. A comparação entre o valor estimado e valor medido foi feita através dos erros em porcentagem para cada parcela. Todos os modelos testados apresentaram uma tendência, em média, a subestimar os valores. O erro mínimo encontrado para volume foi de -3,17% estimado pelo modelo Spline. Para altura média e área Basal os menores desvios foram de -1,7% e 0,82% igualmente estimados pelo modelo Spline. Na estimativa realizada através do modelo Krigagem, o melhor resultado foi de - 7,95%, -2,25% e -5,75% de desvio para área basal, altura e volume, respectivamente. Já o modelo IDW resultou num desvio de -7,48%, -1,29%, 7,53% para as mesmas variáveis. A análise dos resultados mostra que a estimativa por meio de interpolação utilizando modelos implícitos em software geoestatísticos produz alguns desvios significativos e o uso de modelos geoestatísticos ajustados ao conjunto de dados pode produzir estimativas melhores.The Knowledge about the forest stock is an important tool to support the short, medium and long term planning. In each stand the stock is obtained through the forest inventory. This work aimed to apply geostatistics concepts that get benefits from the spatial dependence of certain variables to estimate the volume at non sampled points. For this study, it were used interpolation methods ,which procedure is used to estimate the variables values in the internal area of the sampled points, allowing to represent the locally sampled variables behavior and extrapolate the variables value to the outside sampled area. It were sampled 34 plots to estimates the forest inventory and 36 control plots were sampled to compare the differences between the estimated and actually measured value for the variables: volume, basal area and average height of a cloned Eucalyptus group of stands in approximately 205 ha, located in Mogi-Guaçu-SP. Futher these plots, it were measure more 24 plots in an adjacent area which were used to compose a scenarios study that could support the improvements in borders regions estimations. Using the Geomedia Professional ® software, three interpolation methods were tested: Kriging, Inverse Distance Weighting (IDW) and Spline. For each method it was performed simulations considering the inclusion of new plots to evaluate the estimate behavior by increasing the sample size. In this procedure, we created 6 different scenarios with increasing numbers of plots: Am with 34 plots, G with 58 plots, G +5 with 63 plots, G +10 with 68 plots, G +15 with 73 plots and G +20 with 78 plots. The comparison between the estimated and measured value was made through the errors in percentage for each plot. All the tested models had a tendency, on average, to underestimate the values. The minimum error found for volume was -3.17% estimated by the Spline model. For height and basal area the minor deviations were -1.7% and 0.82% estimated by the Spline model also. In the estimations made by the Kriging model, the best result was -7.95%, -2.25% and -5.75% deviation for basal area, height and volume, respectively. IDW model resulted in a deviation of -7.48%, -1.29%, -7.53% for the same variables. The result analysis shows that the estimations made by the interpolation models using implicit geostatistical software models produces some significant deviations and the use of adjusted geostatistical models to the data set may produce better estimates.
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Prado, Naimara Vieira do. "Abordagens para análise de dados composicionais." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-17082017-155240/.
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Dados composicionais são vetores, chamados de composições, cujos componentes são todos positivos, satisfazem a soma igual a 1 e possuem um espaço amostral próprio chamado Simplex. A restrição da soma induz a correlação entre os componentes. Isso exige que os métodos estatísticos para análise desses conjuntos de dados considerem esse fato. A teoria para dados composicionais foi desenvolvida inicialmente por Aitchison na década de 80. Desde então, várias técnicas e métodos têm sido desenvolvidos para a modelagem dos dados composicionais. Este trabalho apresenta as principais abordagens para a análise estatística de dados composicionais independentes. Sendo, regressão Dirichlet (distribuição natural aos dados composicionais) ou o uso de transformações em razões logarítmicas que saem do espaço simplex para o espaço real. Também descreve os métodos para os casos em que a suposição de independência não pode ser atendida. Por exemplo, dados composionais com dependência espacial. Para esses casos, há na literatura métodos baseados nas teorias desenvolvidas para análise geoestatística de dados univariados; ou, no uso de transformações em razões logarítmicas com a inclusão da dependência espacial. Além de revisitar os métodos já difundidos, propõe-se o uso do método de Equações de Estimação Generalizadas (EEG) como alternativa para a análise de dados composicionais independentes e com dependência espacial. A principal vantagem é que as equações de estimação necessitam apenas da especificação de funções que descrevam a média e a estrutura de covariância. Assim, não é necessário atribuir uma distribuição de probabilidade aos dados ou fazer o uso de transformações. A aplicação do método EEG para dados composicionais independentes apresentou resultados tão eficientes quanto a regressão Dirichlet ou transformação em razões logarítmicas. Para os dados composicionais com dependência espacial, o método baseado em verossimilhança foi o que apresentou valores preditos mais próximos aos valores reais. O método EEG foi mais eficaz do que a abordagem geoestatística dos componentes individuais, porém, comparado com os demais métodos, foi o que apresentou maior valor residual.C ompositional data are vectors, called compositions, whose components are all positive, it satisfies the sum equal one and has a Simplex space. The sum constraint induces the correlation between the components and this requires that the statistical methods for the analysis of datasets consider this fact. The theory for compositional data was developed mainly by Aitchison in the 1980s, and since then, several techniques and methods have been developed for compositional data modelling. This work presents the main approaches for the statistical analysis of independent compositional data, such as Dirichlet regression (natural distribution to compositional data) or the use of transformations log-ratios that aim to leave the simplex space for to Euclidean space. Also describes the methods for cases where the assumption of independence cannot be satisfied, for example, spatial dependence compositional data. For these cases, there are in the literature methods of analysis based on the theories developed for univariate geostatistics analysis or use of logratios transformations with the inclusion of the spatial dependence generated by the distance between the points. In addition, to revisiting the already diffused methods, this work propose the use of the Generalized Estimation Equation (GEE) method as an alternative for the analysis of independent compositional data and with spatial dependence. The GEE only requires the specification of functions that describe the mean and correlation matrix (covariance structure, therefore, it is not necessary to assign a probability distribution to the data or transformations. The application of the GEE method for independent compositional data presented results as efficient as Dirichlet regression or log-ratios transformation. Compositional data with spatial dependence, log-ratios transformations presented predicted values close to the real values. GEE method was more effective than the traditional geostatistical approach, however, compared with the other methods, It was the one that presented the high residual values.
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Dalbianco, Leandro. "Variabilidade espacial e estimativa da condutividade hidráulica e caracterização física-hídrica de uma microbacia hidrográfica rural." Universidade Federal de Santa Maria, 2009. http://repositorio.ufsm.br/handle/1/5494.
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Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorThe soil management systems involve changes in soil physico-hydrical properties. The objective of this study was (i) characterize the soil physico-hydrical properties in the layer 0-5 cm for different soil management systems in the Cândido Brum watershed, (ii) build a map with the spatial variability of soil saturated hydraulic conductivity (Ks), (iii) estimate the Ks from other soil physico-hydrical properties and (iv) test the reliability of others pedotransfer functions for Ks found in the literature. The study was conducted in the watershed Cândido Brum, Brazil, which predominate the soil management systems native pasture, native forest, conventional tillage, minimum tillage and no-tillage. Orthogonal contrasts were performed between groups of soil management systems, which compared the effect of soil cultivation, the type of vegetation and bovine trampling, conservation practice and permanent soil cover. Determinations of soil bulk density, porosity, size particles, organic carbon, degree of flocculation, aggregate stability, Ks, air permeability, retention and availability of water and shear stress of the soil were made. Besides being used for the comparison of management systems, the water-physical properties used as input variables for the development of pedotransfer functions for Ks, which used the stepwise method in the selection of variables, and to test the reliability of pedotransfer functions found in the literature. The map of spatial variability of Ks was constructed from data interpolation using kriging. The soils of the watershed under crops had degraded structure, with low organic matter and low aggregates stability. Soil with native pasture had reduced the macroporosity, the Ks and air permeability in relation to other soil management systems. Conservation practices were effective in increasing the retention and vailability of soil water in relation to conventional tillage. The variables that represent the structure of the soil were more accurate in estimating the Ks that the size particle variables. The pedotransfer functions found in the literature, usually developed for soils of temperate climate, were not reliable in the estimation of Ks of soils watershed. The range of spatial dependence of the values of Ks was 141 m. The map of spatial variability allowed the visualization of areas that need management practices and conservation of soil and water.
Os sistemas de manejo do solo implicam em mudanças nas suas propriedades físico-hídricas. O objetivo do estudo foi (i) caracterizar as propriedades físico-hídricas do solo na camada 0-5 cm para diferentes sistemas de manejo da microbacia hidrográfica Cândido Brum, (ii) construir um mapa com a variabilidade espacial da condutividade hidráulica do solo saturado (Ks), (iii) estimar a Ks a partir de outras propriedades físicohídricas do solo e (iv) testar a confiabilidade de funções de pedotransferência para a Ks encontradas na literatura. O estudo foi conduzido na microbacia Cândido Brum, em Arvorezinha-RS, em que predominam os sistemas de manejo campo nativo, mata nativa, preparo convencional, plantio direto e preparo mínimo. Foram realizados contrastes ortogonais entre grupos de sistemas de manejo do solo, em que se comparou o efeito do cultivo, do tipo de vegetação natural e pisoteio animal, das práticas conservacionistas e da cobertura permanente do solo. Foram realizadas determinações de densidade do solo, porosidade, granulometria, carbono orgânico, grau de floculação, estabilidade de agregados, Ks, permeabilidade ao ar, retenção e disponibilidade de água e tensão de cisalhamento do solo. As propriedades físico-hídricas serviram também como variáveis de entrada para a elaboração de funções de pedotransferência para a Ks e para testes de confiabilidade de funções de pedotransferência encontradas na literatura. O mapa de variabilidade espacial da Ks foi construído a partir da interpolação dos dados com o método da krigagem. Os solos cultivados da microbacia apresentaram estrutura degradada, com pouca matéria orgânica e baixa estabilidade de agregados. O uso com campo nativo reduziu a macroporosidade, a Ks e a permeabilidade ao ar em relação aos outros sistemas de manejo do solo. As práticas conservacionistas foram eficientes em aumentar a retenção e a disponibilidade de água no solo em relação ao preparo convencional. As variáveis que representam a estrutura do solo foram mais precisas em estimar a Ks que as variáveis granulométricas. As funções de pedotransferência encontradas na literatura, geralmente elaboradas para solos de clima temperado, não foram confiáveis na estimativa da Ks da microbacia. O alcance da dependência espacial dos valores de Ks foi de 141 m. O mapa de variabilidade espacial possibilitou a visualização de áreas que necessitam de práticas de manejo e conservação do solo e da água.
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Gonçalves, Aline Kuramoto. "Sensoriamento remoto para estimativa dos parâmetros físicos e químicos para fertilidade do solo da Fazenda Experimental Lageado, Botucatu/SP /." Botucatu, 2019. http://hdl.handle.net/11449/191486.
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Orientador: Zacarias Xavier BarrosResumo: O uso de ferramentas computacionais e da tecnologia desenvolvida por ferramentas do sensoriamento remoto para o mapeamento e estimação da fertilidade do solo são importantes para o desenvolvimento de áreas com práticas agrícolas. O emprego da técnica por meio da análise espacial pode proporcionar melhorias no manejo do solo. O objetivo deste trabalho foi estimar a fertilidade dos solos da Fazenda Experimental Lageado que pertence a Faculdade de Ciências Agronômicas- UNESP, localizada na cidade de Botucatu/São Paulo através dos atributos do solo e as bandas espectrais do vermelho, verde e azul do Vant (Veículo Aéreo Não Tripulado) e do satélite LandSat- 8. Neste contexto, o atributo do solo é essencial para entendermos a sua fertilidade. Foi utilizado um conjunto de amostras de solos com 52 amostras para correlacionar com as respostas espectrais dos solos nos comprimentos de onda do visível, para a geração do modelo. Os dados foram separados em três áreas e apresentaram coeficientes de correlação variam entre -0,58 a 0,56 para imagens de Vant entretanto para as imagens de satélites foram correlações fracas. Para o Vant os preditores mais correlacionados ph e matéria orgânica. Os resultados obtidos pela análise de regressão r² foram considerados baixos, sendo não indicado não espacialização e a geração do modelo de fertilidade.
Abstract: The use of computational tools and the technology developed by remote sensing tools for mapping and estimating soil fertility are important for the development of areas with agricultural practices. The use of the technique through spatial analysis can provide improvements in soil management. The objective of this work was to estimate the fertility of the soils of the Experimental Lageado Farm which belongs to the Faculty of Agronomic Sciences - UNESP, located in the city of Botucatu / São Paulo through the soil attributes and the spectral bands of the red, green and blue of the drone and the LandSat- 8 satellite. In this context, the soil attribute is essential to understand its fertility. A set of soil samples with 52 samples was used to correlate with the spectral responses of the soils in the visible wavelengths, for the generation of the model. The data were separated into three areas and showed correlation coefficients ranging from -0.58 to 0.56 for drone images however for satellite images they were weak correlations. For Vant, the most correlated predictors are ph and organic matter. The results obtained by the r² regression analysis were considered low, with no spatialization and the generation of the fertility model being indicated.
Doutor
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Pereira, Paulo Elias Carneiro. "Estimativa de recursos minerais e otimização de cava aplicados a um estudo de caso de uma mina de calcário." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/7140.
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A mining enterprise is composed of a set of successive and interdependent phases between them, which may or may not culminate in the exploitation of the mineral assets. The project begins with a Mineral Exploration phase, whose objective is to discover and subsequently evaluate the deposit for the feasibility of its extraction. This process involves setting the shape, dimensions and grades, resulting in a model that will be used to determine the recoverable reserves, that is, the economically usable part of the mineral resource, which will base the decision on the implementation or not of the enterprise, based mainly on technicaleconomic criteria. The elaboration of the physical form of the geological bodies that control the mineralization (geological model) and the estimation of the geological variables that characterize the quality of the different materials can be done by two approaches: by traditional or by geostatistical methods. The latter approach is currently being preferred, as it is a more accurate alternative and therefore, more reliable over traditional methods. The work uses indicator kriging (IK) and ordinary kriging (OK), both geostatistical tools, for the determination of the geological model and estimation of the geological variables (grades), respectively, of a limestone deposit located at Indiara city, Goiás State. Finally, from the obtained model the optimal limits of the extraction were established, based on the algorithm of Lerchs-Grossmann, that maximize the net present value of the enterprise. The results showed a significant deviation between themodel calculated by IK and the reality (samples), which can have as consequence the present spatial configuration of the sample data. The estimated geological variables also showed important deviations (overestimation and/or underestimation), particularly MgO oxide. The areas of occurrence of such deviations were coincident for all variables, which makes evident the existence of problems with the current sampling grid (spacing between samples and presence of very different sample supports), in such a way that it is recommended to collect additional samples, particularly with standardized supports. The optimal pit delimited a total reserve of 109,436,160.43 tons, with a total strip ratio of 0.13, which makes the venture, at first, attractive. This configuration, however, tends to be modified according to the collection of new geological evidence.
Um empreendimento mineiro é composto por um conjunto de fases sucessivas e interdependentes entre si, as quais podem culminar ou não na explotação do bem mineral. O projeto se inicia com uma fase de Exploração Mineral, cujo objetivo é descobrir e subsequentemente avaliar o depósito quanto à viabilidade de sua extração. Tal processo envolve estabelecer a forma, as dimensões e os teores, resultando em um modelo que será utilizado para a determinação das reservas lavráveis, ou seja, a parte economicamente aproveitável do recurso mineral, a qual fundamentará a decisão sobre a implantação ou não do empreendimento a partir de critérios principalmente técnico-econômicos. A elaboração do formato físico dos corpos geológicos que controlam a mineralização (modelo geológico) e a estimativa das variáveis geológicas que caracterizam a qualidade dos diferentes materiais podem ser feitas a partir de duas abordagens: por métodos tradicionais ou por geoestatísticos. Os últimos têm sido utilizados recentemente como uma proposta mais precisa em relação aosmétodos tradicionais. O trabalho utiliza a krigagem indicadora (KI) e a krigagem ordinária (KO), ambas ferramentas geoestatísticas, para a determinação do modelo geológico e estimativa das variáveis geológicas (teores), respectivamente, em um depósito de calcário situado no município de Indiara, estado de Goiás. Por fim, a partir do modelo obtido estabeleceu-se os limites ótimos da extração baseados no algoritmo de Lerchs-Grossmann, que maximizamo valor presente líquido do empreendimento. Os resultados mostraram um desvio significativo entre o modelo calculado pela KI e realidade (amostras), o que pode ter como consequência significativa a atual configuração espacial da amostragem. As variáveis geológicas estimadas também demonstraram desvios (sobrestimativa e subestimativa) importantes, particularmente o óxido MgO. As áreas de ocorrência de tais desvios foram coincidentes para todas as variáveis, o que torna evidente a existência de problemas com a atual malha de amostragem (espaçamento entre amostras e presença suportes amostrais muito diferentes), de tal forma que se recomenda a coleta de amostras adicionais, e de suportes padronizados. A cava ótima delimitou uma reserva total de 109.436.160,43 toneladas, com uma relação estéril-minério (REM) total de 0,13, o que torna o empreendimento, a princípio, atrativo. Tal configuração, entretanto, tende a ser alterada conforme a coleta de novas evidências geológicas.
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Carvalho, Samuel de Pádua Chaves e. "Estimativa volumétrica por modelo misto e tecnologia laser aerotransportado em plantios clonais de Eucalyptus sp." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/11/11150/tde-06092013-100239/.
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O trabalho se estruturou em torno de dois estudos. O primeiro avaliou o ajuste de um modelo não linear de efeito misto para descrever o afilamento do tronco de árvores clonais de eucalipto. O modelo utilizado para descrever as variações da altura em função do raio foi o logístico de quatro parâmetros que, por integração permitiu a estimação do volume das árvores. A incorporação de funções de variância no processo de ajuste resultou em redução significativa no valor do Critério de informação de Akaike, mas os resíduos não apresentaram melhorias notáveis. Com a finalidade de compatibilizar precisão e parcimônia, o modelo que considera as variações do afilamento como uma função da altura total e do raio à altura do peito mostrou-se como o mais indicado para a estimativa do volume de árvores por funções de afilamento. O segundo estudo analisou uma nova proposta para inventários florestais em plantios clonais de eucalipto que integra modelagem geoestatística, medições de circunferência das árvores em campo e a tecnologia LiDAR aeroembarcada. As estatísticas propostas mostraram que o modelo geoestatístico com função para média foi estatisticamente superior ao modelo com média constante, com erros reduzidos em até 40%. A altura das árvores que compuseram o grid de predição para aplicação do modelo geoestatístico foi obtida pelo processamento da nuvem de pontos dos dados LiDAR. Obtidos os pares de diâmetro e altura, aplicou-se o modelo de afilamento selecionado no primeiro artigo em que se observaram diferenças médias na predição do volume próximas a 0,7%, e 0,18% para contagem de árvores, ambas com tendências de subestimativas. Diante dos resultados obtidos, o método é considerado como promissor e trabalhos futuros visam gerar um banco de parcelas permanentes que propiciem estudos de crescimento e produção florestal.This study investigates the use of mixed-effect model and the use of LiDAR based model to estimate volume from eucalyptus forest plantation. At the first part, this study evaluates nonlinear mixed-effects to model stem taper of monoclonal Eucalyptus trees. The relation between radius and height variation was described by the four-parameter logistic model that integration returns stem volume. Embedding variance functions to the estimation process decreased significantly the Akaike\'s Information Criterion but did not improve the residual analysis. The best model to estimate stem volume from taper equations explained the stem taper as a function of the commercial height and the radius at breast height. The second part investigated the volume estimation fusing geostatistic derived from field information and airborne laser scanning data. The model based on geostatistic assumptions was statistically superior to the traditional one, with errors 40% lower. Thus, the geostatistical model was applied over tree heights extracted from the laser cloud. To each combination of diameter and height, the taper equation form the first part of this study was used. The volume and the number of trees were underestimated in 0.7% and 0.18%, respectively. The results look promising, and more permanent plots are necessary to allow studies about growth and yield of forest.
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Silva, Bruno Claytton Oliveira da. "Estudo te?rico-bioclim?tico da potencialidade de desenvolvimento do Aedes aegypti no estado do Rio Grande do Norte." Universidade Federal do Rio Grande do Norte, 2009. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18190.
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Previous issue date: 2009-02-03Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior
In the current climate of global public health there is the emergence of urban dengue, a disease regarded as acute infectious fever. The disease annually, has affected millions of people worldwide, mostly in the range of the intertropical globe. The disease's main vector in urban areas, the Aedes aegypti mosquito. Recent studies indicate that the distribution of the insect vector of dengue in the geographical area is directly tied to the behavior of environmental restrictions that area, especially among those, the air temperature and relative humidity. From that context, the work aims to estimate and spatializing, monthly, for each municipality in the state of Rio Grande do Norte, the potential of biophysical conditions conducive to the development of Aedes aegypti. Yet, made use of the following methodology: collection of epidemiological data and climatological, Normal climatological, descriptive statistics (measures of central tendency and scatter), uniform distribution, estimation geostatistics and sufer program, version 8.0. The results flagged for a behavior very heterogeneous, both in space and in time, in the case of the potential of biophysical conditions conducive to the development of Aedes aegypti in the state of Rio Grande do Norte. Still, he noted that there is a tendency for lifting the potential of development for the entire state, from the month of January, ending in the month of April mainly in central and western portions of the state. By contrast, there is the permanence of increased potential for development in the eastern portion of the state. The latter record maximum potential in the month of July, resulting probability of greater than 70% have been favorable conditions for the development of Aedes aegypti in that area. In the period between the months of August to December, it is small potential for development of Aedes aegypti in all parts of the state
Na atual conjuntura da sa?de p?blica mundial destaca-se a emerg?ncia da dengue urbana, doen?a infecciosa febril aguda que tem como principal vetor no meio urbano o Aedes aegypti. A doen?a, anualmente, tem acometido milh?es de pessoas em todo o mundo, principalmente na faixa intertropical do globo. A partir desse contexto, o trabalho objetiva estimar e espacializar mensalmente, sob a ?tima bioclim?tica, a potencialidade, para cada munic?pio do Rio Grande do Norte (RN), da condi??o biof?sica Favor?vel ao Desenvolvimento do Aedes aegypti. Para tanto, fez uso: coleta de dados epidemiol?gicos e climatol?gicos, Normal Climatol?gica, estat?stica descritiva (medidas de tend?ncia central e dispers?o), distribui??o uniforme, estima??o geoestat?stica e o programa sufer, vers?o 8.0. Os resultados sinalizaram para um comportamento bastante heterog?neo, tanto no espa?o como no tempo, em se tratando da potencialidade da condi??o biof?sica Favor?vel ao desenvolvimento do Aedes aegypti no estado RN. Ainda, observou-se que h? uma tend?ncia de eleva??o da potencialidade de desenvolvimento, para todo o estado, a partir do m?s de janeiro, cessando-se no m?s de abril principalmente nas por??es central e oeste do estado. Em contrapartida, para o mesmo per?odo, verifica-se a perman?ncia de aumento da potencialidade de desenvolvimento na por??o leste do estado. Esta ?ltima registrar? potencial m?ximo no m?s de julho, resultando em probabilidade maior que 70% de ter-se condi??es favor?veis ao desenvolvimento do Aedes aegypti naquela ?rea. No per?odo compreendido entre os meses de agosto a dezembro, constatou-se diminuto potencial de desenvolvimento do Aedes aegypti em todas as por??es do estado
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Zahaby, Mohamed El. "Contribution à la définition d'une norme des sites pollués : élaboration d'une méthodologie pour l'évaluation de la contamination d'un sol par éléments tracés." Vandoeuvre-les-Nancy, INPL, 1998. http://www.theses.fr/1998INPL045N.
Full textAbstract:
Des études récentes ont montré l'accumulation continue des éléments tracés dans les sols, provoquant des atteintes pour l'environnement et présentant même des dangers pour la santé humaine. De ce fait, apparait aujourd'hui la nécessite d'avoir une nouvelle politique qui peut mettre en place dans un cadre réglementaire et juridique les moyens de protection des milieux naturels. Ce travail de thèse a été effectué dans le but d'établir, au moyen de méthodes statistiques et géostatistiques, un outil de diagnostic et d'évaluation de la qualité du sol et d'apprécier les risques correspondants, afin de contribuer à la détermination de valeurs guides pour les sols français. Dans un premier temps, après avoir rappelé les différents aspects normatifs en Europe et aux USA, ainsi que l'état actuel en France, nous nous attachons à présenter, de façon exhaustive, la répartition des éléments traces dans les différents types de roches et de sols. Vient ensuite une présentation de leur répartition dans les sols au niveau national, dont nous montrons que l'analyse statistique peut permettre d'interpréter au mieux la dynamique et les sources naturelles ou dues à des activités humaines des éléments traces induits dans un sol. Nous mettons notamment l'accent sur la comparaison des teneurs en éléments traces dans les sols français avec les valeurs communément adoptées comme normes ou valeurs guides par les différents pays. Dans un second temps, quatre niveaux de la distribution d'un élément trace dans un sol ont été défini : la concentration de base, le fond géochimique, la contamination et la pollution. Basé sur cette constatation, une méthode a été développée par la suite, avec, pour objectif de différencier le fond géochimique. Un jeu de données de 12 feuilles, 14000 échantillons dans les régions des Vosges et d'Alsace a été fourni par le BRGM afin de mettre au point et de valider les résultats. Enfin, la distribution spatiale des éléments tracés a été modélisée par des méthodes géostatistiques. Une estimation par la méthode de krigeage de probabilité a eu pour objectif la délimitation de la zone de pollution et l'établissement de cartes de risques face à un usage précis du sol.
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Watanabe, Jorge. "Métodos geoestatísticos de co-estimativas: estudo do efeito da correlação entre variáveis na precisão dos resultados." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/44/44137/tde-14082008-165227/.
Full textAbstract:
Esta dissertação de mestrado apresenta os resultados de uma investigação sobre os métodos de co-estimativa comumente utilizados em geoestatística. Estes métodos são: cokrigagem ordinária; cokrigagem colocalizada e krigagem com deriva externa. Além disso, a krigagem ordinária foi considerada apenas a título de ilustração como esse método trabalha quando a variável primária estiver pobremente amostrada. Como sabemos, os métodos de co-estimativa dependem de uma variável secundária amostrada sobre o domínio a ser estimado. Adicionalmente, esta variável deveria apresentar correlação linear com a variável principal ou variável primária. Geralmente, a variável primária é pobremente amostrada enquanto a variável secundária é conhecida sobre todo o domínio a ser estimado. Por exemplo, em exploração petrolífera, a variável primária é a porosidade medida em amostras de rocha retiradas de testemunhos e a variável secundária é a amplitude sísmica derivada de processamento de dados de reflexão sísmica. É importante mencionar que a variável primária e a variável secundária devem apresentar algum grau de correlação. Contudo, nós não sabemos como eles funcionam dependendo do grau de correlação. Esta é a questão. Assim, testamos os métodos de co-estimativa para vários conjuntos de dados apresentando diferentes graus de correlação. Na verdade, esses conjuntos de dados foram gerados em computador baseado em algoritmos de transformação de dados. Cinco valores de correlação foram considerados neste estudo: 0,993, 0,870, 0,752, 0,588 e 0,461. A cokrigagem colocalizada foi o melhor método entre todos testados. Este método tem um filtro interno que é aplicado no cálculo do peso da variável secundária, que por sua vez depende do coeficiente de correlação. De fato, quanto maior o coeficiente de correlação, maior é o peso da variável secundária. Então isso significa que este método funciona mesmo quando o coeficiente de correlação entre a variável primária e a variável secundária é baixo. Este é o resultado mais impressionante desta pesquisa.This master dissertation presents the results of a survey into co-estimation methods commonly used in geostatistics. These methods are ordinary cokriging, collocated cokriging and kriging with an external drift. Besides that ordinary kriging was considered just to illustrate how it does work when the primary variable is poorly sampled. As we know co-estimation methods depend on a secondary variable sampled over the estimation domain. Moreover, this secondary variable should present linear correlation with the main variable or primary variable. Usually the primary variable is poorly sampled whereas the secondary variable is known over the estimation domain. For instance in oil exploration the primary variable is porosity as measured on rock samples gathered from drill holes and the secondary variable is seismic amplitude derived from processing seismic reflection data. It is important to mention that primary and secondary variables must present some degree of correlation. However, we do not know how they work depending on the correlation coefficient. That is the question. Thus, we have tested co-estimation methods for several data sets presenting different degrees of correlation. Actually, these data sets were generated in computer based on some data transform algorithms. Five correlation values have been considered in this study: 0.993; 0.870; 0.752; 0.588 and 0.461. Collocated simple cokriging was the best method among all tested. This method has an internal filter applied to compute the weight for the secondary variable, which in its turn depends on the correlation coefficient. In fact, the greater the correlation coefficient the greater the weight of secondary variable is. Then it means this method works even when the correlation coefficient between primary and secondary variables is low. This is the most impressive result that came out from this research.
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Galle, Sylvie. "Analyse des champs spatiaux par utilisation de la télédétection : estimation de la durée quotidienne d'insolation en France à l'aide d'images du satellite Météosat et de mesures sol." Phd thesis, Grenoble INPG, 1987. http://tel.archives-ouvertes.fr/tel-00694114.
Full textAbstract:
L'insolation est étudiée, à l'échelle synoptique (la France) à l'aide d'un ensemble de mesures de la durée quotidienne d'insolation réalisées au sol et par télédétection satellitaire. L'objectif poursuivi est d'analyser une série de données suffi* samment longue pour caractériser de manière statistique le comportement climatologique de l'insolation dans l'espace. Les données sont fournies par 88 héliographes du réseau synoptique français ainsi que par le programme " Cactus " de la Météorologie Nationale, qui utilise les images visibles du satellite Météosat. L'étude porte sur une année de données. La similarité de la structure spatiale des mesures du sol et du satellite est montrée par analyse objective, et par analyse en composantes principales de processus. La fine perception de la variabilité spatiale du satellite est alors utilisée pour optimiser un réseau de mesures au sol. Les performances du programme Cactus sont comparées avec celles de méthodes d'interpolation classiques (basées sur 23 héliographes), pour l'estimation du rapport d'insolation. Elles se sont révélées plus performantes en terme de cofluctuation. Il apparaît cependant une tendance du satellite à exagérer les valeurs extrêmes. L'étalonnage des mesures satellitaires par des mesures sol a pour but de conjuguer les qualités de précision des hélio* graphes, et la définition spatiale du satellite. Une approche géostatistique est proposée. L'effet recherché est observé à partir d'une certaine densité du réseau d'étalonnage
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Wagner, Laurent. "MINESTIS, the route to resource estimates." Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2015. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-181676.
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Minestis software allows geological domain modeling and resource estimation through an efficient and simplified geostatistics-based workflow. It has been designed for all those, geologists, mining engineers or auditors, for whom quick production of quality models is at the heart of their concerns.
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McFadzean-Ferguson, Simon. "Spatial estimation: the geostatistical point of view." Thesis, 1995. http://hdl.handle.net/2429/3817.
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Geostatistics involves the statistical estimation of erratic surfaces, similar to those found
in geology, using sample data. It has been my experience that there are few texts in geostatistics
written for people who are new to the subject, and who have not been immersed
in it since its inception in the 1960's. To prevent other people becoming confused by the
changing notation, and unspoken assumptions, I provide an overview of this subject, with
the aim of providing a clearer understanding of the concepts involved, the assumptions
made, and the motivation behind each type of estimator. I then concentrate on the more
general form of estimation assuming a nonhomogeneous trend, called Universal Kriging.
I explain in detail how this estimator can be found in an accurate and computationally
efficient way. Using the information gained from robustness studies of this estimator, I
then attempt to apply it to real surfaces, for different methods of covariance estimation
and trend orders.
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Yang, Hong-Ding, and 楊洪鼎. "Parameter Estimation and Spatial Prediction for Geostatistical Regression Models." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/60680837733858629830.
Full textAbstract:
博士國立彰化師範大學
數學系
104
Using a model-based method to analyze geostatistical data is essential in many environmental studies. In this thesis, we consider a geostatistical regression model to analyze environmental data sets and predict spatial variables of interest, where the Matérn covariogram is used to describe the spatial dependence of observations and the likelihood-based methods are applied to estimate model parameters. It is known that parameters in the Matérn covariogram cannot be estimated well even when increasing amounts of data are collected densely in a fixed domain. Although a best linear unbiased predictor has been proposed when model parameters are known, a predictor with estimated parameters is nonlinear and may be not the best in practice. Therefore, from a prediction point of view, we propose an adjusted procedure for the likelihood-based estimators to modify the parameter estimates toward the true parameter values and simultaneously improve the corresponding prediction performance. The adjusted parameter estimators based on minimizing a corrected Stein's unbiased risk estimator tend to have less bias than the conventional likelihood-based estimators, and the resulting spatial predictor is more accurate and more stable. The validities of the proposed methodology for parameter estimation and spatial prediction in geostatistical regression models are justified both theoretically and numerically. For illustration, a groundwater data set in Bangladesh is analyzed.
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Huang, Chung-Bin, and 黃忠斌. "Simultaneous Selection for Sampling and Parameter Estimation Methods in Geostatistical Models." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/48442067829905018628.
Full textAbstract:
碩士國立彰化師範大學
統計資訊研究所
101
Predicting spatial variables of interest based on noisy data is an important problem in spatial statistics. There are many sampling methods and estimation methods of model parameters that can be used for the problem of spatial prediction. In general, different methods have different performances in practice. How to choose an appropriate combination among these methods is an essential issue. In this thesis, we focus on predicting spatial variables of interest based on geostatististical models and discuss the performances of different combinations of sampling methods and estimation methods. We propose a stabilized spatial prediction methods based on a data perturbation technique and the concept of generalized degrees of freedom is used to assess the complexity of a spatial prediction methods. We develop an unbiased estimator of mean squared prediction errors for a predicted surface to assess its performance and then an appropriate combination of sampling methods and estimation methods is obtained by minimizing this unbiased estimator over candidate sets. Statistical inferences and effectiveness of the proposed methods are illustrated theoretically and numerically.
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Hong, Sahyun. "Multivariate Analysis of Diverse Data for Improved Geostatistical Reservoir Modeling." Phd thesis, 2010. http://hdl.handle.net/10048/1390.
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Improved numerical reservoir models are constructed when all available diverse data sources are accounted for to the maximum extent possible. Integrating various diverse data is not a simple problem because data show different precision and relevance to the primary variables being modeled, nonlinear relations and different qualities. Previous approaches rely on a strong Gaussian assumption or the combination of the source-specific probabilities that are individually calibrated from each data source.
This dissertation develops different approaches to integrate diverse earth science data. First approach is based on combining probability. Each of diverse data is calibrated to generate individual conditional probabilities, and they are combined by a combination model. Some existing models are reviewed and a combination model is proposed with a new weighting scheme. Weakness of the probability combination schemes (PCS) is addressed. Alternative to the PCS, this dissertation develops a multivariate analysis technique. The method models the multivariate distributions without a parametric distribution assumption and without ad-hoc probability combination procedures. The method accounts for nonlinear features and different types of the data. Once the multivariate distribution is modeled, the marginal distribution constraints are evaluated. A sequential iteration algorithm is proposed for the evaluation. The algorithm compares the extracted marginal distributions from the modeled multivariate distribution with the known marginal distributions and corrects the multivariate distribution. Ultimately, the corrected distribution satisfies all axioms of probability distribution functions as well as the complex features among the given data.
The methodology is applied to several applications including: (1) integration of continuous data for a categorical attribute modeling, (2) integration of continuous and a discrete geologic map for categorical attribute modeling, (3) integration of continuous data for a continuous attribute modeling. Results are evaluated based on the defined criteria such as the fairness of the estimated probability or probability distribution and reasonable reproduction of input statistics.Mining Engineering
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Burrows, Sean Nicolas Grant. "Geostatistical estimation of leaf area index and net primary production of five North American biomes." 2002. http://www.library.wisc.edu/databases/connect/dissertations.html.
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Hevesi, Joseph A. "Precipitation estimation in mountainous terrain using multivariate geostatistics." Thesis, 1990. http://hdl.handle.net/1957/37937.
Full textAbstract:
Estimates of average annual precipitation (AAP) are-needed for hydrologic modeling at
Yucca Mtn., Nevada, site of a proposed, high-level nuclear waste repository. Historical
precipitation data and station elevation were obtained for stations in southern Nevada and
southeastern California. Elevations for 1,531 additional locations were obtained from
topographic maps. The sample direct-variogram for the transformed variable TAAP =
ln(AAP) * 1000 was fit with an isotropic, spherical model with a small nugget and a range
of 190,000 ft. The sample direct-variogram for elevation was fit with an isotropic model
with four nested structures (nugget, Gaussian, spherical, and linear) with ranges between 0
and 270,000 ft. There was a significant (p = 0.05, r = 0.75) linear correlation between
TAAP and station elevation. The sample cross-variogram for TAAP and elevation was fit
with two nested structures (Gaussian, spherical) with ranges from 55,000 to 355,000 ft.
Alternate model structures and parameters were compared using cross-validation.
Isohyetal maps for average annual precipitation (AAP) were prepared from
estimates obtained by kriging and cokriging using the selected models. Isohyets based on
the kriging estimates were very smooth, increasing gradually from the southwest to the
northeast. Isohyets based on the cokriging estimates and the spatial correlation between
AAP and elevation were more irregular and displayed known orographic effects. Indirect
confirmation of the cokriging estimates were obtained by comparing isohyets prepared with
the cokriging estimates to the boundaries of more densely vegetated and/or forested zones.
Estimates for AAP at the repository site were 145 and 165 mm for kriging and cokriging,
respectively. Cokriging reduced estimation variances at the repository site by 55% relative
to kriging. The effectiveness of an existing network of stations for measuring AAP is
evaluated and recommendations are made for optimal locations for additional stations.Graduation date: 1991
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Boisvert, Jeff. "Geostatistics with locally varying anisotropy." Phd thesis, 2010. http://hdl.handle.net/10048/1107.
Full textAbstract:
Many geological deposits contain nonlinear anisotropic features such as veins, channels, folds or local changes in orientation; numerical property modeling must account for these features to be reliable and predictive. This work incorporates locally varying anisotropy into inverse distance estimation, kriging and sequential Gaussian simulation. The methodology is applicable to a range of fields including (1) mining-mineral grade modeling (2) petroleum-porosity, permeability, saturation and facies modeling (3) environmental-contaminate concentration modeling. An exhaustive vector field defines the direction and magnitude of anisotropy and must be specified prior to modeling. Techniques explored for obtaining this field include: manual; moment of inertia of local covariance maps; direct estimation and; automatic feature interpolation.
The methodology for integrating locally varying anisotropy into numerical modeling is based on modifying the distance/covariance between locations in space. Normally, the straight line path determines distance but in the presence of nonlinear features the appropriate path between locations traces along the features. These paths are calculated with the Dijkstra algorithm and may be nonlinear in the presence of locally varying anisotropy. Nonlinear paths do not ensure positive definiteness of the required system of equations when used with kriging or sequential Gaussian simulation. Classical multidimensional scaling is applied to ensure positive definiteness but is found to be computationally infeasible for large models, thus, landmark points are used for efficiency with acceptable losses in precision. The methodology is demonstrated on two data sets (1) net thickness of the McMurray formation in northern Alberta and (2) gold grade in a porphyry copper deposit. Integrating LVA into numerical modeling increases local accuracy and improves leave-one-out cross validation analysis results in both case studies.Mining Engineering
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Nengovhela, Avhurengwi Colbert. "The application of geostatistics in coal estimation and classification." Thesis, 2018. https://hdl.handle.net/10539/24878.
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A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Engineering (Mining), January 2018This study set out to assess a multiplicity of related questions regarding the applicability of geostatistical principles, practices and techniques to the estimation, classification and reporting of Coal Resources. Two cases, i.e. Case A and B were selected for the study. Both areas are in the Witbank Coalfield. A few exercises were undertaken to investigate whether a technique such as Ordinary Kriging (OK) could be better suited. The second part of the problem statement is to evaluate whether the current drill hole spacing recommended by the SANS 10320:2004 standard is appropriate for the considered cases. In terms of drill spacing, the South African National Standard (SANS 10320:2004) provides that for a Measured, Indicated and Inferred classification, samples should be spaced at 200 m (minimum of 8 samples), 282 m (minimum of 4 samples) and 564 m (minimum of 1 sample) respectively. By quantifying the precision associated with estimating the two cases at different drill grids, it was shown that for both Cases A and B, a Measured Resource can be classified by using drill holes that are spaced approximately 1000 m apart. It was established that precision results associated with the global estimation variance are only applicable to the area in which the study was undertaken i.e. the findings are not globally applicable although rough approximations can be deduced. For short-term mine planning purposes, further drilling may and is usually required. The guidelines provided in the SANS standard for separation distances are evidently too stringent for both Cases A and B. Therefore, a drill spacing of 500 m, 1000 m and 4000 m should be considered as being more appropriate than the current overly tight spacing. With regard to the use of OK, the findings of this study clearly show that the current Growth Algorithm (GA) technique commonly used by South Africa coal estimators is more appropriate than other alternatives as it outperforms both OK and Inverse Distance Weighting (IDW) whether on a global or local scale. The current estimation method used for these cases is therefore appropriate. The current drill grids are too small for global estimation and reporting and thus there is possible overspending if the required estimation precision is between 5 and 10 %. At the current drill spacing, precision is around 2 % within ‘Measured’ areas, which is more than what is required to produce predictable long-term plans.
XL2018
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Hsu, Chun-Ming, and 許峻銘. "Estimation on Groundwater Safty Yield of Taipei Basin by using Geostatistics Method." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/33123155276848398114.
Full textAbstract:
碩士國立成功大學
資源工程學系碩博士班
94
In discussing groundwater problems, it is important to evaluate groundwater flow precisely. Such evaluation can be accomplished by executing the situ-experiment, but due to the financial limitation of the study, the situ-data available in this research can be limited. However, geostatistics method, requiring few situ-data to generate a statistic result, can overcome the problem of lacking such data in this study. In addition to 130 borehole data obtained in Taipei Basin and 5 conductivity data, this research applied Sequential Gaussian Simulation Method (SGS) to construct the conductivity random spacing field in Taipei Basin. The continuity of the random spacing field is related to the river mud sediment direction. MODFLOW was utilized on the random spacing field, to construct the groundwater model in Taipei Basin and to simulate the groundwater flow behavior. Subsequently, Hill Method and Harding Method were exploited to estimate the groundwater safety yield and safety water level. The result of the study indicates that the areas in Taipei Basin suitable for pumping groundwater are Beitou District, Shilin District, Sindian City and Wugu countryside, while those unsuitable are Zhongshan District, Songshan District, Neihu District. At the aspects of groundwater safety yield and discharging volume, Sindian City has a larger amount of discharging volume, which can provide more safety yield than other areas in the basin. Within the four years from 1999 to 2002, the annual average safety yield in Taipei Basin is about 88.50 million tons per year.
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Adjorlolo, Clement. "Estimating woody vegetation cover in an African Savanna using remote sensing and geostatistics." Thesis, 2008. http://hdl.handle.net/10413/420.
Full textAbstract:
A major challenge in savanna rangeland studies is estimating woody vegetation cover and densities over large areas where field based census alone is impractical. It is therefore crucial that the management and conservation oriented research in savannas identify data sources that provides quick, timely and economical means to obtain information on vegetation cover. Satellite remote sensing can provide such information. Remote sensing investigations, however, require establishing statistical relationships between field and remotely sensed data. Usually regression is the empirical method applied to field and remotely sensed data for the spatial estimation of woody vegetation variables. Geostatistical techniques, which take spatial autocorrelation of variables into consideration, have rarely been used for this purpose. We investigated the possibility of improving woody biomass predictions in tropical savannas using cokriging. Cokriging was used to evaluate the cross-correlated information between SPOT (Satellites Pour l’Observation de la Terre or Earth-observing Satellites)-derived vegetation variables and field sampled woody vegetation percentage canopy cover and density. The main focus was to estimate woody density and map the distribution of woody cover in an African savanna environment. In order to select the best SPOT-derived vegetation variable that best correlate with field sampled woody variables, several spectral vegetation and texture indices were evaluated. Next, variogram models were developed: one for woody canopy cover and density, one for the best SPOT-derived vegetation variable, and a crossvariogram between woody variables and best SPOT-derived data. These variograms were then used in cokriging to estimate woody density and map its spatial distribution. Results obtained indicate that through cokriging, the estimation accuracy can be improved compared to ordinary kriging and stepwise linear regression. Cokriging therefore provided a method to combine field and remotely sensed data to accurately estimate woody cover variables.Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.
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Huang, China-Ching, and 黃家慶. "A Study of Estimation Rainfall Spatial Analysis Distribution by Combing Frequency and Geostatistics Approach - Sueh-Pa National Park as an Example." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/4nuz5j.
Full textAbstract:
碩士國立中興大學
水土保持學系所
98
In these recent years, because of global warming influence, the climate became more anomalous and hydrology events became more extreme, it caused rainfall distribution in Taiwan area to be more unbalanced, and brought about an extremely severe disaster. In search of the most suitable ways for rainfall spatial distribution in Shei-Pa National Park, this research will take Shei-Pa National Park as the boundary, and use Spline , IDW(Inverse Distance Weighted), Kriging method to estimate the distribution of rainfall space, also compare the merits and demerits of these three methods, and find out the most suitable analysis method that used in this area and Hydrological observation station where is located at severe shortage area. This study will divide the rainfall into long time annual rainfall and short time daily cloudburst, and will be discussed separately, (1) for annual rainfall side, collect in the study area of annual rainfall in year 2000, and estimate its annual rainfall space distribution by using those three methods above, and also use geographical information system and traditional Thiessen Polygons method to calculate the average of annual rainfall volume, for comparing its results. (2) For cloudburst side, collect in the study area of the highest accumulated rainfall volume for 24, 48, 72 delayed rainfall volume, and also use the most extreme value of Gumbel type I distribution method and Log-Pearson Type III distribution method to analyze among 5, 10, 20, 50, 100 rainfall frequency for each year, and also take this rainfall volume as property value, and use those three methods above to estimate the distribution of cloudburst space. (3) Finally, using RMS to analyze annual rainfall and cloudburst space distribution result, and also find out the most suitable method that used in the distribution of rainfall space, and analyze DAD(Depth Area Duration) of this area and also K, n value of Hortan formula. The conclusions of this study are : (1). IDW(Inverse Distance Weighted) and Kriging method are better used in analyzing of annual rainfall space distribution, but the average of annual rainfall volume that analyzed by three methods are almost same, but it is more accurate than the results of analysis by Thiessen Polygons method. (2). Kriging method is better used in analyzing of cloudburst space distribution, its average relative error is only 7%, while by using those two other methods it will be 14%. (3). Although IDW(Inverse Distance Weighted) method is better than Spline method in annual rainfall space distribution, but the results of cloudburst space distribution are the worst, conform to Gotway and other people theory, only the stability of IDW(Inverse Distance Weighted) method is bad, and can be easily influenced by the factors. (4). The annual rainfall space distribution uses 11 sample size, while cloudburst space distribution used 14 sample size, the both sample sizes are different, and cloudburst space distribution relative error is the lowest(only 10%), we can know that if sample sizes are more, the results will be more accurate. (5). Kriging method result is the best after using RMS analysis method. There are two suggestions : (1). The average relative error is only 13.3% by using Kriging analysis method, while by using RMS analysis method, its residual is 76. Therefore, this study suggests using Kriging analysis method in annual and daily rainfall space distribution analysis. (2). When cloudburst is analyzed by using Kriging method, it can cause the boundary of estimate will be wider, thus cloudburst frequency analysis should use Log-Pearson Type III distribution method.
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Maakamedi, Maja Ruddy. "Geozone definition of the UG2 reef for improved mineral resource estimation based on statistics and geostatistics at Amandelbult Platinum Mine, Thabazimbi." Thesis, 2020. https://hdl.handle.net/10539/31136.
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A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering, 2020The economic viability of any mine is underpinned by its Mineral Resource estimation. Crucial to this is the utilisation of all relevant and available data, to ensure that the resource evaluation process is comprehensive and carried out to the highest standard possible. There is always the case, where, in the initial development stages of a mine project limited data is available however, as the project progresses information regarding the orebody usually also increases. The increase in information opens an opportunity to assess whether the existing estimation method remains suitable and also allows for the modification of the current estimation method to better suit the behaviour of the orebody based on the additional new information. Standard procedure when carrying outa Mineral Resource estimate is to split the orebody into zones that show statistical and geostatistical homogeneity i.e. similar characteristics for example grade and or reef thickness. Of course, when data is limited this privilege might not be possible. The reason being that geostatistics rely of an assumption of second order stationarity which means that the mean and co-variance is consistent irrespective of the location within the orebody, an assumption that cannot be validated with limited data. In recent years the Amandelbult UG2 reef database increased in terms of both surface borehole intersections and underground channel sampling. Splitting the UG2 orebody into homogeneous zones for resource estimation using statistics as well geostatistics is outlined in this research report. Statically the orebody thickness, density and platinum grade show variation across the area of interest, this allowed for subdivision of the orebody into several homogeneous geozones. Both the descriptive statistics and graphical data summaries confirmed local variation in these three variables. The geostatistical analysis involved the creation of two sets of variograms, one for each identified geozone and a global variogram ignoring the individual identified geozones within the project area. Ordinary kriging was used to estimate the UG2 orebody thickness, density and platinum grade using these variograms. A comparison was conducted to check if the quality of the estimates improved by comparing the true values and estimated values and the correlation coefficient of the two indicated that the estimates were improved when using individual variograms rather than a global variogram. Additionally, comparisons of the errors from the true values and estimated values indicate that the Mean Absolute Error and Root Mean Error are reduced when using separate variograms rather than using a global variogram when solving the kriging solutions. In conclusion this research study has shown that by delineating the orebody into homogeneous zones for thickness, density and platinum grade and applying ordinary kriging using the relevant individual geozone variograms resulted in improved block estimates for Amandelbult UG2 reef
CK2021
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Haskard, Kathryn Anne. "An anisotropic Matern spatial covariance model: REML estimation and properties." 2007. http://hdl.handle.net/2440/47972.
Full textAbstract:
This thesis concerns the development, estimation and investigation of a general anisotropic spatial correlation function, within model-based geostatistics, expressed as a Gaussian linear mixed model, and estimated using residual maximum likelihood (REML). The Matern correlation function is attractive because of its parameter which controls smoothness of the spatial process, and which can be estimated from the data. This function is combined with geometric anisotropy, with an extension permitting different distance metrics, forming a flexible spatial covariance model which incorporates as special cases many infinite- range spatial covariance functions in common use. Derivatives of the residual log-likelihood with respect to the four correlation-model parameters are derived, and the REML algorithm coded in Splus for testing and refinement as a precursor to its implementation into the software ASReml, with additional generality of linear mixed models. Suggestions are given regarding initial values for the estimation. A residual likelihood ratio test for anisotropy is also developed and investigated. Application to three soil-based examples reveals that anisotropy does occur in practice, and that this technique is able to fit covariance models previously unavailable or inaccessible. Simulations of isotropic and anisotropic data with and without a nugget effect reveal the following principal points. Inclusion of some closely-spaced locations greatly improves estimation, particularly of the Matern smoothness parameter, and of the nugget variance when present. The presence of geometric anisotropy does not adversely affect parameter estimation. Presence of a nugget effect introduces greater uncertainty into the parameter estimates, most dramatically for the smoothness parameter, and also increases the chance of non-convergence and decreases the power of the test for anisotropy. Estimation is more difficult with very “unsmooth" processes (Matern smoothness parameter 0.1 or 0.25) | non- convergence is more likely and estimates are less precise and/or more biased. However it is still often possible to fit the full model including both anisotropy and nugget effect using REML with as few as 100 observations. Additional simulations involving model misspecification reveal that ignoring anisotropy when it is present can substantially increase the mean squared error of prediction, but overfitting by attempting to model anisotropy when it is absent is less damaging. Further, plug-in estimates of prediction error variance are reasonable estimates of the actual mean squared error of prediction, regardless of the model fitted, weakening the argument requiring Bayesian approaches to properly allow for uncertainty in the parameter estimates when estimating prediction error variance. The most valuable outcome of this research is the implementation of an anisotropic Matern correlation function in ASReml, including the full generality of Gaussian linear mixed models which permits additional fixed and random effects, making publicly available the facility to fit, via REML estimation, a much wider range of variance models than has previously been readily accessible. This greatly increases the probability and ease with which a well-fitting covariance model can be found for a spatial data set, thus contributing to improved geostatistical spatial analysis.http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1297562
Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2007