Relevant bibliographies by topics / Geostatistic methods

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Geostatistic methods'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Geostatistic methods"

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Daniel Maramis, Stefan, Rika Ernawati, and Waterman Sulistyana Bargawa. "Distribution Analysis of Heavy Metal Contaminants in Soil With Geostatistic Methods; Paper Review." Eduvest - Journal Of Universal Studies 1, no. 7 (July 20, 2021): 620–28. http://dx.doi.org/10.36418/edv.v1i7.111.

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Heavy metal contaminants in the soil will have a direct effect on human life. The spatial distribution of naturally occurring heavy metals is highly heterogeneous and significantly increased concentrations may be present in the soil at certain locations. Heavy metals in areas of high concentration can be distributed to other areas by surface runoff, groundwater flow, weathering and atmospheric cycles (eg wind, sea salt spray, volcanic eruptions, deposition by rivers). More and more people are now using a combination of geographic information science (GIS) with geostatistical statistical analysis techniques to examine the spatial distribution of heavy metals in soils on a regional scale. The most widely used geostatistical methods are the Inverse Distance Weighted, Kriging, and Spatial Autocorrelation methods as well as other methods. This review paper will explain clearly the source of the presence of heavy metals in soil, geostatistical methods that are often used, as well as case studies on the use of geostatistics for the distribution of heavy metals. The use of geostatistical models allows us to accurately assess the relationship between the spatial distribution of heavy metals and other parameters in a map.
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Nagy, Ildikó, and János Tamás. "Optimization of Density of Sugar Beet (Beta vulgaris L.) Production Quotas by Pointwise Geostatistic Methods." Acta Agraria Debreceniensis, no. 18 (March 4, 2005): 46–50. http://dx.doi.org/10.34101/actaagrar/18/3246.

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The regional distribution of the Hungarian sugar beet production quotas was developed by the conventional concurrency relationships. In our research we analyzed 320 sectors of 9 factories with geostatistic methods in a GIS environment. The applied researches of spatial mean, spatial deviation, deviational ellipse have been introduced by us in this speciality. We used two different methods in our optimization inquiries, where the spatial segment of the standard deviational ellipse was based on a more robust preliminary data processing solution, and this is why it is a less parametricable method. The inquiry of the spatial buffer zones in production sectors ensures an obvious optimization possibility. We considered the supply route distances in both cases as a modeling boundary condition. Our results show that we introduced an effective decision making method to the occurent replanning of the production sectors with the pointwise density inquiries and the geometric analogy that was fitted to it.
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Cesaroni, Donatella, Pasquale Matarazzo, Giuliana Allegrucci, and Valerio Sbordoni. "Comparing patterns of geographic variation in cave crickets by combining geostatistic methods and Mantel tests." Journal of Biogeography 24, no. 4 (July 1997): 419–31. http://dx.doi.org/10.1111/j.1365-2699.1997.00104.x.

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Denis, Alain, and Francis Cremoux. "Traitement et analyse des paramètres de pilotage d'un tunnelier." Canadian Geotechnical Journal 39, no. 2 (April 1, 2002): 451–62. http://dx.doi.org/10.1139/t01-093.

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Tunnel boring parameters are used to control the good-functioning of the tunnel boring machine along the bored tunnel route and rarely to obtain more information about the nature or the mechanical behavior of the bored soil. Actually, they can bring very informative data, firstly, to improve the geological section to have the exact tunnel length in each soil formation and, secondly, to quantify the variability of the boring process along the tunnel route. Previously, a mechanical parameter is obtained from the combination of three tunnel boring parameters, which are thrust, penetration rate, and rotary speed. From statistical and geostatistical methods, the drillability signal, which can be seen as a time series, is divided into a set of stationary subdomains. The resulting series is then a stationary one, by zones, whose analysis can bring more information about the tunnel length for each soil formation and on the variability of the boring process. This last piece of information might then be utilized by contractors to explain some low advance rate totally unexpected before boring.Key words: tunnel boring machine, boring parameters, drillability, homogeneous zone, variability, statistic, geostatistic.
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Sadeghi, S. H., A. Allbuali, and R. Ghazavi. "Investigation of Temporal and Spatial Trends of Water Quality Parameters Change Using Geostatistic Methods in Kashan Plain." Journal of Water and Soil Science 20, no. 76 (August 1, 2016): 73–83. http://dx.doi.org/10.18869/acadpub.jstnar.20.76.73.

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Pomortseva, Olena, Sergiy Kobzan, Oleksii Voronkov, and Andrey Yevdokimov. "Geospatial modeling of the infrastructure facility optimal location." E3S Web of Conferences 280 (2021): 11013. http://dx.doi.org/10.1051/e3sconf/202128011013.

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The purpose of the research is to reveal current trends in modeling the location of new catering establishments in the study area. The relevance of research in the article is determined by the development of the tourism industry. This applies to catering establishments operating in the lower price category. Such catering establishments include fast food restaurants. The article proposes to use geographic information systems for spatial analysis using software. The researchers used ArcGis software, which allows you to visualize the results of the analysis. Visualization of the results will allow to make the necessary decision on the location of catering establishments. The research was conducted on the example of the Industrialny District of Kharkiv. Analysis of geostatic models can be used to process statistical data in any locality by using a geostatistical method to convert data from a discrete view to a permanent representation. With the help of geostatistics methods, data from a discrete form are transformed into a continuous form. Researchers present mathematical formulas for determining the index of concentration of the actual population in a given area or the projected index. These indicators can be determined on the basis of data obtained during the research. Indicators are presented using elements of the ArcGis software package in discrete form and permanent form. In the research the model of optimization of placement of public catering establishments was developed. It is proposed to place twelve new catering establishments in the studied area of the city with the exact indication of their location. The scientific conclusion of the study will further improve the service to the local population and the promotion of the city of Kharkiv as a object of tourism. The principle of developing a digital map and geodatabase is effective to address issues related to tourism infrastructure, so the developed model can be used in other cities. Further research in this direction may be related to improving geostatistic analysis of data and taking into account more factors..
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Sales, Maria Clécia Gomes, Elilson Gomes de Brito Filho, Milton César Costa Campos, José Maurício da Cunha, Guilherme Abadia Silva, Elyenayra Nogueira Pinheiro, Douglas Marcelo Pinheiro da Silva, Flávio Pereira de Oliveira, and Fernando Gomes de Souza. "Behavior of Soil Chemical Attributes in Field-Forest Succession in Southern Amazonas." Journal of Agricultural Studies 8, no. 3 (June 4, 2020): 807. http://dx.doi.org/10.5296/jas.v8i3.16846.

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The use of geostatistical methods in the identification of the size and structure of the spatial variability of soil chemical attributes has been a very important tool in the evaluation and behavior of soil attributes. This research aimed to evaluate the spatial variability of chemical attributes in natural field and forest areas, in the Humaitá region (AM). In these areas, meshes with dimensions of 70 m x 70 m were established at regular intervals of 10 minutes in the 0.0-0.2 m layers, totaling 64 samples per layer. It was determined: soil pH, phosphorus (P), potassium (K+), calcium (Ca2+), magnesium (Mg2+), aluminum (Al3+) and potential acidity (H++Al3+). Base saturation (V%) and sum of bases (SB) were calculated. The data were evaluated by descriptive statistics and spatial dependence analysis, based on the best models and semivariograms adjustment. The chemical attributes are spatially dependent, they present random distribution of ideal sample spacing, considering that the variables that showed dependence were adjusted to the exponential and spherical model. Geostatistic was presented as an appropriate tool, providing information that allows the understanding of the spatial distribution. The degree of dependence was strong and moderate. The highest reaches were recorded in the natural field area.
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Volfová, Adéla, and Martin Šmejkal. "Geostatistical Methods in R." Geoinformatics FCE CTU 8 (October 14, 2012): 29–54. http://dx.doi.org/10.14311/gi.8.3.

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Geostatistics is a scientific field which provides methods for processing spatial data. In our project, geostatistics is used as a tool for describing spatial continuity and making predictions of some natural phenomena. An open source statistical project called R is used for all calculations. Listeners will be provided with a brief introduction to R and its geostatistical packages and basic principles of kriging and cokriging methods. Heavy mathematical background is omitted due to its complexity. In the second part of the presentation, several examples are shown of how to make a prediction in the whole area of interest where observations were made in just a few points. Results of these methods are compared.
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Syaeful, Heri, and Suharji Suharji. "Geostatistics Application On Uranium Resources Classification: Case Study of Rabau Hulu Sector, Kalan, West Kalimantan." EKSPLORIUM 39, no. 2 (January 31, 2019): 131. http://dx.doi.org/10.17146/eksplorium.2018.39.2.4960.

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ABSTRACT In resources estimation, geostatistics methods have been widely used with the benefit of additional attribute tools to classify resources category. However, inverse distance weighting (IDW) is the only method used previously for estimating the uranium resources in Indonesia. The IDW method provides no additional attribute that could be used to classify the resources category. The objective of research is to find the best practice on geostatistics application in uranium resource estimation adjusted with geological information and determination of acceptable geostatistics estimation attribute for resources categorization. Geostatistics analysis in Rabau Hulu Sector was started with correlation of the orebody between boreholes. The orebodies in Rabau Hulu Sectors are separated individual domain which further considered has the hard domain. The orebody-15 was selected for further geostatistics analysis due to its wide distribution and penetrated most by borehole. Stages in geostatistics analysis cover downhole composites, basic statistics analysis, outliers determination, variogram analysis, and calculation on the anisotropy ellipsoid. Geostatistics analysis shows the availability of the application for two resources estimation attributes, which are kriging efficiency and kriging variance. Based on technical judgment of the orebody continuity versus the borehole intensity, the kriging efficiency is considered compatible with geological information and could be used as parameter for determination of the resources category. ABSTRAK Pada estimasi sumber daya, metode geostatistik telah banyak digunakan dengan kelebihan adanya alat atribut tambahan untuk mengklasifikasikan kategori sumber daya. Namun demikian, pembobotan inverse distance (IDW) adalah satu-satunya metode yang sebelumnya digunakan untuk mengestimasi sumber daya uranium di Indonesia. Metode IDW tidak memberikan tambahan atribut yang dapat digunakan dalam mengklasifikasikan kategori sumber daya. Tujuan dari penelitian adalah mendapatkan praktek terbaik untuk aplikasi geostatistik pada estimasi sumber daya disesuaikan dengan informasi geologi dan penentuan atribut geostatistik yang dapat digunakan untuk kategorisasi sumber daya. Analisis geostatistik di Sektor Rabau Hulu diawali dengan korelasi tubuh bijih antara lubang bor. Tubuh-tubuh bijih di Sektor Rabau Hulu merupakan domain individual yang selanjutnya dipertimbangkan memiliki domain tegas. Tubuh bijih-15 dipilih untuk digunakan pada analisis geostatistik selanjutnya karena distribusinya yang luas dan paling banyak dipenetrasi bor. Tahapan dalam analisis geostatistik mencakup komposit downhole, analisis statistik dasar, determinasi outliers, analisis variogram, dan perhitungan ellipsoid anisotropi. Analisis geostatistik menghasilkan kemungkinan aplikasi dua atribut estimasi sumber daya, yaitu kriging efisiensi dan kriging varians. Berdasarkan penilaian teknis kemenerusan tubuh bijih terhadap intensitas lubang bor, kriging efisiensi dipertimbangkan sesuai dengan informasi geologi dan dapat digunakan sebagai parameter untuk penentuan kategori sumber daya.
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Penížek, V., and L. Borůvka. "Processing of conventional soil survey data using geostatistical methods." Plant, Soil and Environment 50, No. 8 (December 10, 2011): 352–57. http://dx.doi.org/10.17221/4043-pse.

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The aim of this study is to find a suitable treatment of conventional soil survey data for geostatistical exploitation. Different aims and methods of a conventional soil survey and the geostatistics can cause some problems. The spatial variability of clay content and pH for an area of 543 km<sup>2</sup> was described by variograms. First the original untreated data were used. Then the original data were treated to overcome the problems that arise from different aims of conventional soil survey and geostatistical approaches. Variograms calculated from the original data, both for clay content and pH, showed a big portion of nugget variability caused by a few extreme values. Simple exclusion of data representing some specific soil units (local extremes, non-zonal soils) did not bring almost any improvement. Exclusion of outlying values from the first three lag classes that were the most influenced due to a relatively big portion of these extreme values provided much better results. The nugget decreased from pure nugget to 50% of the sill variability for clay content and from 81 to 23% for pH.
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Dissertations / Theses on the topic "Geostatistic methods"

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Reyes, Gómez Sandra Tatiana. "Avaliação da distribuição espacial de poluentes de origem industrial na bacia hidrográfica Taquari-Antas." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/150545.

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Os recursos hídricos representam para a sociedade e o meio ambiente um papel de suma importância. Em termos de sociedade relacionamos os múltiplos usos que se fazem destes, sem esquecer que o principal uso é para o consumo e abastecimento das necessidades primárias. Já em termos de meio ambiente sabemos que são os pilares para o suporte e desenvolvimento da biodiversidade e produção de biomassa na terra. A destinação dos resíduos industriais é uma preocupação na atualidade, e mesmo das indústrias sendo obrigadas a tratar seus resíduos antes de despejá-los nos corpos hídricos, não o estão executando com eficiência. Uma das razões que levam a esta situação é a falta de conhecimento dos efeitos que seus resíduos podem ocasionar, deixando-os em um segundo plano, e o orçamento elevado que se requer para investir em uma estação de tratamento de efluentes, considerando não somente a construção, mas também a demanda que exige a sua manutenção. Cada vez mais a integração dos métodos geoestatísticos, Sensoriamento Remoto e SIG, está sendo utilizado para estudos de contaminação ambiental. Suas vantagens e grande variedade de ferramentas permitem um primeiro acesso qualificado a todas essas questões e informações que são onerosas e às vezes desconhecidas. Indo ao encontro da busca de soluções para esta problemática e, através da técnica de análise de componentes principais, se estabeleceu uma ferramenta adequada para diagnóstico da distribuição espacial de concentração de potencial poluidor dos efluentes industriais, tendo como área de estudo a bacia hidrográfica Taquari-Antas. Um total de 393 indústrias foram classificadas em 24 setores. O potencial poluidor de Metais da água (MA), Tóxicos da água (TA), Demanda Bioquímica de Oxigênio (DBO) e Sólidos em Suspensão Totais (SST) para o meio aquático foi estimado através da metodologia The Industrial Pollution Projection System (IPPS). Foram gerados valores para as concentrações dos poluentes para cada mês do ano, utilizando uma série histórica de 26 anos das vazões na bacia. Os padrões temporais para as concentrações mensais foram verificados por meio de testes estatísticos dos modelos ANOVA e testes TukeyHSD, para cada tipo de poluente. A principal tendência temporal encontrada para os quatro tipos de poluentes são a transição do outono para o inverno, onde há uma grande queda dos valores de concentração devido ao aumento da vazão dos rios (época de cheia). Da primavera para o outono os valores vão crescendo novamente até se tornarem os maiores. Na sequência foram gerados mapas de contorno para o potencial poluidor estimado e concentrações mensais além de mapas de classificação das áreas da bacia segundo a legislação do CONAMA.
The water resources represent an important roll for society and the environment. In terms of society we relate the multiple uses that are made of them, without forgetting that their main use is for consumption and supply of primary needs. On the environmental side we know that they are the pillar for the support and development of biodiversity and production of biomass on earth. The destination of the industrial residues are a concern today, despite the industries being obliged to treat their waste before disposing them into any body of water, it’s not being done efficiently. Some of the reasons that lead to this situation are the lack of knowledge of the effects that may result from their residues, pushing them aside. Another reason is the elevated budget required to invest in an industrial wastewater treatment station (ETI), considering not only construction but also the demand that requires its maintenance. Increasingly, the integration of geostatistic methods, Remote Sensing and GIS are being used for environmental contamination studies. Its advantages and wide variety of tools allow an initial quality access to all these matters and information that are costly and sometimes unknown. Seeking solutions of this issue and, through the principal component analysis technique, it has established a suitable tool for the diagnosis of spatial concentration distribution of industrial effluents emissions, having as the subject of study the Taquari-Antas watershed. A total of 393 industries were classified into 24 sectors. Water metals pollution potential (MA), Water Toxics (TA), Biochemical Oxygen Demand (BOD) and Total Suspended Solids (TSS) to water were estimated by The Industrial Pollution Projection System (IPPS) methodology. Values were generated for concentrations of pollutants for each month of the year, using a historical series of 26 years of stream flow in the watershed. The temporal patterns for monthly concentrations were verified by means of statistical tests of ANOVA models and TukeyHSD tests for each type of pollutant. The main temporal trends found for the four types of pollutants are the autumn transition to winter, where there is a decrease of concentration values due to increased river flows (flood season). From spring to autumn the values will grow again till becoming the highest. Following the temporal trends were generated contour maps for estimated pollution potential and monthly concentrations as well as areas of classification maps of the watershed according to CONAMA legislation.
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Giorgi, Emanuele. "Geostatistical methods for disease prevalence mapping." Thesis, Lancaster University, 2015. http://eprints.lancs.ac.uk/75770/.

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Geostatistical methods are increasingly used in low-resource settings where disease registries are either non-existent or geographically incomplete. In this thesis, which is comprised of four papers, we address some of the common issues that arise from analysing disease prevalence data. In the first paper we consider the problem of combining data from multiple spatially referenced surveys so as to account for two main sources of variation: temporal variation, when surveys are repeated over time; data-quality variation, e.g. between randomised and non-randomised surveys. We then propose a multivariate binomial geostatistical model for the combined analysis of data from multiple surveys. We also show an application to malaria prevalence data from three surveys conducted in two consecutive years in Chikwawa District, Malawi, one of which used a more economical convenience sampling strategy. In the second paper, we analyse river-blindness prevalence data from a survey conducted in 20 African countries enrolled in the African Programme of Onchocerciasis Control (APOC). The main challenge of this analysis is computational, as a binomial geostatistical model has to be fitted to more than 14,000 village locations and predictions carried out on about 10 millions locations across Africa. To make the computation feasible and efficient, we then develop a low rank approximation based on a convolution-kernel representation which avoids matrix inversion. The third paper is a tutorial on the use of a new R package, namely “PrevMap”, which provides functions for both likelihood-based and Bayesian analysis of spatially referenced prevalence data. In the fourth paper, we present some extensions of the standard geostatistical model for spatio-temporal analysis of prevalence data and modelling of spatially structured zero-inflation. We then describe three applications that have arisen through our collaborations with researchers and public health programmers in African countries.
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Johansson, Björn. "Statistical Methods for Mineral Models of Drill Cores." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279848.

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In modern mining industry, new resource efficient and climate resilient methods have been gaining traction. Commissioned efforts to improve the efficiency of European mining is further helping us to such goals. Orexplore AB's X-ray technology for analyzing drill cores is currently involved in two such project. Orexplore AB wishes to incorporate geostatistics (spatial statistics) into their analyzing process in order to further extend the information gained from the mineral data. The geostatistical method implemented here is ordinary kriging which is an interpolation method that, given measured data, predicts intermediate values governed by prior covariance models. Ordinary kriging facilitates prediction of mineral concentrations on a continuous grid in 1-D up to 3-D. Intermediate values are predicted on a Gaussian process regression line, governed by prior covariances. The covariance is modeled by fitting a model to a calculated experimental variogram. Mineral concentrations are available along the lateral surface of the drill core. Ordinary kriging is implemented to sequentially predict mineral concentrations on shorter sections of the drill core, one mineral at a time. Interpolation of mineral concentrations is performed on the data considered in 1-D and 3-D. The validation is performed by calculating the corresponding density at each section that concentrations are predicted on and compare each such value to measured densities. The performance of the model is evaluated by subjective visual evaluation of the fit of the interpolation line, its smoothness, together with the variance. Moreover, the fit is tested through cross-validation using different metrics that evaluates the variance and prediction errors of different models. The results concluded that this method accurately reproduces the measured concentrations while performing well according to the above mentioned metrics, but does not outperform the measured concentrations when evaluated against the measured densities. However, the method was successful in providing information of the minerals in the drill core by producing mineral concentrations on a continuous grid. The method also produced mineral concentrations in 3-D that reproduced the measured densities well. It can be concluded that ordinary kriging implemented according to the methodology described in this report efficiently produces mineral concentrations that can be used to obtain information of the distribution of concentrations in the interior of the drill core.
I den moderna gruvindustrin har nya resurseffektiva och klimatbeständiga metoder ökat i efterfråga. Beställda projekt för att förbättra effektiviteten gällande den europeiska gruvdriften bidrar till denna effekt ytterligare. Orexplore AB:s röntgenteknologi för analys av borrkärnor är för närvarande involverad i två sådana projekt. Orexplore AB vill integrera geostatistik (spatial statistik) i sin analysprocess för att ytterligare vidga informationen från mineraldatan. Den geostatistiska metoden som implementeras här är ordinary kriging, som är en interpolationsmetod som, givet uppmätta data, skattar mellanliggande värden betingade av kovariansmodeller. Ordinary kriging tillåter skattning av mineralkoncentrationer på ett kontinuerligt nät i 1-D upp till 3-D. Mellanliggande värden skattas enligt en Gaussisk process-regressionslinje. Kovariansen modelleras genom att passa en modell till ett beräknat experimentellt variogram. Mineralkoncentrationer är tillgängliga längs borrkärnans mantelyta. Ordinary kriging implementeras för att sekventiellt skatta mineralkoncentrationer på kortare delar av borrkärnan, ett mineral i taget. Interpolering av mineralkoncentrationer utförs på datan betraktad i 1-D och 3-D. Valideringen utförs genom att utifrån de skattade koncentrationerna beräkna den motsvarande densiteten vid varje sektion som koncentrationer skattas på och jämföra varje sådant värde med uppmätta densiteter. Undersökning av modellen utförs genom subjektiv visuell utvärdering av interpolationslinjens passning av datan, dess mjukhet, tillsammans med variansen. Dessutom testas passformen genom korsvalidering med olika mätvärden som utvärderar varians- och skattningsfel för olika modeller. Slutsatsen från resultaten är att denna metod reproducerar de uppmätta koncentrationerna väl samtidigt som den presterar bra enligt de mätvärden som utvärderas, men överträffar ej de uppmätta koncentrationerna vid utvärdering mot de uppmätta densiteterna. Metoden var emellertid framgångsrik med att tillhandahålla information om mineralerna i borrkärnan genom att producera mineralkoncentrationer på ett kontinuerligt rutnät. Metoden producerade också mineralkoncentrationer i 3-D som reproducerade de uppmätta densiteterna väl. Slutsatsen dras att ordinary kriging, implementerad enligt den metod som beskrivs i denna rapport, effektivt skattar mineralkoncentrationer som kan användas för att få information om fördelningen av koncentrationer i det inre av borrkärnan.
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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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Aló, Lívia Lanzi. "Uso de componentes de imagens de satélites na modelagem espacial do volume em povoamento de Eucalyptus sp." Universidade Federal de São Carlos, 2016. https://repositorio.ufscar.br/handle/ufscar/8934.

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Forest inventory is an important tool used to estimate forest wood production. However, some methodologies used in forest inventory are based in Classical Statistics, which disregards any spatial continuity that may exist between sample unities. Some geostatistic interpolators such as ordinary kriging (OK) and external drift kriging (EDK) allow us to assess this spatial structure. Furthermore, besides spatial variability, interpolators as EDK use one or more auxiliary variables. Satellite images have different components that interrelate with dendrometric variables and that can be used as auxiliary variables in order to increase the degree of precision of estimates. The aim of this study was to assess EDK performance on the volume estimation of Eucalyptus sp. stands using satellite image components as secondary variables and to compare it with OK performance. With this purpose, a forest inventory of 210 circular plots of 500 m² was carried out in order to estimate the volume (m³ ha-1 ) in each plot. Images obtained of studied area had blue, green, red and near infrared band. From these bands, it were extracted: gray level in each band, the ratio between bands, vegetation index (NDVI, SAVI e ARVI), texture measures and index generated from textures related to plot area. Covariance model adjustement throughout Stepwise method and selection by AIC (Akaike Information Criterion) method were made to EDK geostatistic. EDK and OK semivariograms were adjusted by different theoretical models through Ordinary Least Squares (OLS) method and the choice of the best model was given by the lowest value of residual standard error. From statistic analysis of images and correlation matrix, it was observed a correlation of variables with volume and also autocorrelation between these variables. The best covariance model selected was composed by band 2, measure of COR texture of band 2, MULCOR texture index of band 1 and by age. In the two semivariograms, the best model adjusted was the exponential one. Analysing the results, volume estimates generated by EDK produced better results than OK estimates and had the lowest value of residual standard error and the best area under curve (AUC) in receiver operating characteristic (ROC) curve analysis.
O inventário florestal é uma importante ferramenta utilizada para estimar a produção dos povoamentos florestais. Contudo, algumas metodologias utilizadas no inventário são embasadas na Estatística Clássica, que desconsidera qualquer continuidade espacial que possa existir entre as unidades amostrais. Alguns interpoladores geoestatísticos, tais como a krigagem ordinária (KO) e a krigagem de deriva externa (KDE), permitem avaliar essa estrutura espacial. Além disso, interpoladores como a KDE utilizam, além da variável espacial, uma ou mais variáveis auxiliares. As imagens de satélites possuem diferentes componentes que se correlacionam com as variáveis dendrométricas podendo ser usados como variáveis auxiliares, visando o aumento do grau de precisão das estimativas. O objetivo deste estudo foi avaliar o desempenho da KDE na estimativa do volume de povoamentos florestais de Eucalyptus sp., utilizando os componentes de imagens de satélites como variáveis auxiliares e compará-la com o desempenho da KO. Com esse propósito, processouse um inventário florestal de 210 parcelas circulares de 500 m², a fim de estimar o volume (m³ ha-1 ) por parcela. As imagens obtidas da área do estudo continham as bandas azul, verde, vermelho e infravermelho próximo. A partir destas, foram extraídos o nível de cinza (NC) de cada banda, da razão simples entre as bandas, índices de vegetação (NDVI, SAVI e ARVI), medidas de textura e índices gerados a partir das texturas referentes à área da parcela. Para a geoestatística KDE, foi feito o ajuste do modelo de covariância através do método Stepwise e a seleção pelo método AIC (Critério de Informação de Akaike). Os semivariogramas da KDE e da KO foram ajustados por diferentes modelos teóricos por meio do método dos Mínimos Quadrados Ordinários (MQO) e a escolha do melhor modelo se deu pelo menor valor do erro padrão residual. Nas análises das estatísticas das imagens e da matriz de correlação geradas, foi possível observar a correlação das variáveis com o volume e também a autocorrelação existente entre as variáveis. O melhor modelo de covariância selecionado foi composto por banda 2, medida de textura COR (correlação) da banda 2, índice de textura MULCOR (correlação multiplicado pela banda) da banda 1 e pela idade. Nos dois semivariogramas, o modelo que melhor se ajustou foi o exponencial. Nas análises dos resultados, as estimativas de volume geradas pela KDE produziram melhores resultados que as estimativas da KO, obtendo o menor valor de erro padrão residual e a melhor área sob a curva (AUC) na análise da curva ROC (Receiver Operating Characteristic).
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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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Long, Andrew Edmund. "Cokriging, kernels, and the SVD: Toward better geostatistical analysis." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186892.

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Three forms of multivariate analysis, one very classical and the other two relatively new and little-known, are showcased and enhanced: the first is the Singular Value Decomposition (SVD), which is at the heart of many statistical, and now geostatistical, techniques; the second is the method of Variogram Analysis, which is one way of investigating spatial correlation in one or several variables; and the third is the process of interpolation known as cokriging, a method for optimizing the estimation of multivariate data based on the information provided through variogram analysis. The SVD is described in detail, and it is shown that the SVD can be generalized from its familiar matrix (two-dimensional) case to three, and possibly n, dimensions. This generalization we call the "Tensor SVD" (or TSVD), and we demonstrate useful applications in the field of geostatistics (and indicate ways in which it will be useful in other areas). Applications of the SVD to the tools of geostatistics are described: in particular, applications dependent on the TSVD, including variogram modelling in coregionalization. Variogram analysis in general is explored, and we propose broader use of an old tool (which we call the "corhogram ", based on the variogram) which proves useful in helping one choose variables for multivariate interpolation. The reasoning behind kriging and cokriging is discussed, and a better algorithm for solving the cokriging equations is developed, which results in simultaneous kriging estimates for comparison with those obtained from cokriging. Links from kriging systems to kernel systems are made; discovering kerneIs equivalent to kriging systems will be useful in the case where data are plentiful. Finally, some results of the application of geostatistical techniques to a data set concerning nitrate pollution in the West Salt River Valley of Arizona are described.
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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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MOURA, PEDRO NUNO DE SOUZA. "LSHSIM: A LOCALITY SENSITIVE HASHING BASED METHOD FOR MULTIPLE-POINT GEOSTATISTICS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32005@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
A modelagem de reservatórios consiste em uma tarefa de muita relevância na medida em que permite a representação de uma dada região geológica de interesse. Dada a incerteza envolvida no processo, deseja-se gerar uma grande quantidade de cenários possíveis para se determinar aquele que melhor representa essa região. Há, então, uma forte demanda de se gerar rapidamente cada simulação. Desde a sua origem, diversas metodologias foram propostas para esse propósito e, nas últimas duas décadas, Multiple-Point Geostatistics (MPS) passou a ser a dominante. Essa metodologia é fortemente baseada no conceito de imagem de treinamento (TI) e no uso de suas características, que são denominadas de padrões. No presente trabalho, é proposto um novo método de MPS que combina a aplicação de dois conceitos-chave: a técnica denominada Locality Sensitive Hashing (LSH), que permite a aceleração da busca por padrões similares a um dado objetivo; e a técnica de compressão Run-Length Encoding (RLE), utilizada para acelerar o cálculo da similaridade de Hamming. Foram realizados experimentos com imagens de treinamento tanto categóricas quanto contínuas que evidenciaram que o LSHSIM é computacionalmente eciente e produz realizações de boa qualidade, enquanto gera um espaço de incerteza de tamanho razoável. Em particular, para dados categóricos, os resultados sugerem que o LSHSIM é mais rápido do que o MS-CCSIM, que corresponde a um dos métodos componentes do estado-da-arte.
Reservoir modeling is a very important task that permits the representation of a geological region of interest. Given the uncertainty involved in the process, one wants to generate a considerable number of possible scenarios so as to find those which best represent this region. Then, there is a strong demand for quickly generating each simulation. Since its inception, many methodologies have been proposed for this purpose and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this work, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. We have performed experiments with both categorical and continuous images which showed that LSHSIM is computationally efficient and produce good quality realizations, while achieving a reasonable space of uncertainty. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.
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Mandallaz, Daniel. "Geostatistical methods for double sampling schemes : application to combined forest inventories /." Zürich : Chair of Forest Inventory and Planning, Swiss Federal Institute of Technology (ETH), 1993. http://e-collection.ethbib.ethz.ch/show?type=habil&nr=19.

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Books on the topic "Geostatistic methods"

1

Journel, A. G. Mining geostatistics. Caldwell, N.J: Blackburn Press, 2003.

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Yates, S. R. Geostatistics for waste management: User's manual for the GEOPACK (version 1.0) geostatistical software system. Ada, OK: U.S. Environmental Protection Agency, Robert S. Kerr Environmental Research Laboratory, 1990.

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Pierre, Delfiner, ed. Geostatistics: Modeling spatial uncertainty. New York: Wiley, 1999.

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Yates, S. R. Geostatistics for waste management: A user's manual for the GEOPACK (version 1.0) geostatistical software system. Ada, Okla: Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 1990.

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Mohan, Srivastava R., ed. Applied geostatistics. New York: Oxford University Press, 1989.

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M, Armstrong. Basic linear geostatistics. Berlin: Springer, 1998.

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Petroleum geostatistics. Richardson, TX: Society of Petroleum Engineers, 2005.

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Modern spatiotemporal geostatistics. Mineola, N.Y: Dover Publications, 2012.

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Zorilescu, Dan. Introducere în geostatistica informațională. București: Editura Academiei Republicii Socialiste România, 1986.

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1974-, Leuangthong Oy, and Deutsch Clayton V, eds. Geostatistics Banff 2004. Dordrecht: Springer, 2005.

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Book chapters on the topic "Geostatistic methods"

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Wackernagel, Hans, Pierre Petitgas, and Yves Touffait. "Overview of Methods for Coregionalization Analysis." In Geostatistics, 409–20. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-6844-9_31.

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Boulanger, F. "Geostatistique ET Processus Autoregressifs : Une Nouvelle Methode de Modelisation." In Geostatistics, 259–71. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-6844-9_19.

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Maliva, Robert G. "Geostatistical Methods and Applications." In Springer Hydrogeology, 595–617. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32137-0_20.

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Ma, Y. Z. "Geostatistical Estimation Methods: Kriging." In Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling, 373–401. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17860-4_16.

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Maurya, S. P., N. P. Singh, and K. H. Singh. "Geostatistical Inversion." In Seismic Inversion Methods: A Practical Approach, 177–216. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45662-7_7.

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Filzmoser, Peter, and Clemens Reimann. "Robust Multivariate Methods in Geostatistics." In Studies in Classification, Data Analysis, and Knowledge Organization, 429–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-55991-4_46.

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Abrahamsen, Petter. "Combining Methods for Subsurface Prediction." In Geostatistics Banff 2004, 601–10. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/978-1-4020-3610-1_61.

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Arroyo, Daisy, Xavier Emery, and María Peláez. "Sequential Simulation with Iterative Methods." In Geostatistics Oslo 2012, 3–14. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4153-9_1.

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Pyrcz, Michael J., Peter Janele, Doug Weaver, and Sebastien Strebelle. "Geostatistical Methods for Unconventional Reservoir Uncertainty Assessments." In Geostatistics Valencia 2016, 671–83. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46819-8_45.

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Akin, Hikmet, and Heinrich Siemes. "Überblick der Fortgeschrittenen Methoden der Geostatistik." In Praktische Geostatistik, 189–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73542-4_6.

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Conference papers on the topic "Geostatistic methods"

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Faucheux, Claire, and Nicolas Jeanne´e. "Industrial Experience Feedback of a Geostatistical Estimation of Contaminated Soil Volumes." In ASME 2011 14th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2011. http://dx.doi.org/10.1115/icem2011-59181.

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Geostatistics meets a growing interest for the remediation forecast of potentially contaminated sites, by providing adapted methods to perform both chemical and radiological pollution mapping, to estimate contaminated volumes, potentially integrating auxiliary information, and to set up adaptive sampling strategies. As part of demonstration studies carried out for GeoSiPol (Geostatistics for Polluted Sites), geostatistics has been applied for the detailed diagnosis of a former oil depot in France. The ability within the geostatistical framework to generate pessimistic / probable / optimistic scenarios for the contaminated volumes allows a quantification of the risks associated to the remediation process: e.g. the financial risk to excavate clean soils, the sanitary risk to leave contaminated soils in place. After a first mapping, an iterative approach leads to collect additional samples in areas previously identified as highly uncertain. Estimated volumes are then updated and compared to the volumes actually excavated. This benchmarking therefore provides a practical feedback on the performance of the geostatistical methodology.
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Zaytsev*, V. N., P. Biver, H. Wackernagel, and D. Allard. "Geostatistical Simulations on Irregular Reservoir Models Using Methods of Nonlinear Geostatistics." In Petroleum Geostatistics 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201413618.

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Desnoyers, Yvon, and Didier Dubot. "Geostatistical Methodology for Waste Optimization of Contaminated Premises." In ASME 2011 14th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2011. http://dx.doi.org/10.1115/icem2011-59344.

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The presented methodological study illustrates a geostatistical approach suitable for radiological evaluation in nuclear premises. The waste characterization is mainly focused on floor concrete surfaces. By modeling the spatial continuity of activities, geostatistics provide sound methods to estimate and map radiological activities, together with their uncertainty. The multivariate approach allows the integration of numerous surface radiation measurements in order to improve the estimation of activity levels from concrete samples. This way, a sequential and iterative investigation strategy proves to be relevant to fulfill the different evaluation objectives. Waste characterization is performed on risk maps rather than on direct interpolation maps (due to bias of the selection on kriging results). The use of several estimation supports (punctual, 1 m2, room) allows a relevant radiological waste categorization thanks to cost-benefit analysis according to the risk of exceeding a given activity threshold. Global results, mainly total activity, are similarly quantified to precociously lead the waste management for the dismantling and decommissioning project.
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de Figueiredo, L. Passos, D. Grana, M. Roisenberg, and B. Rodrigues. "Markov Chain Monte Carlo Methods for High-dimensional Mixture Distributions." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902273.

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Chen*, Y. "Keynote - Geologically Consistent History Matching Using the Ensemble based Methods." In Petroleum Geostatistics 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201413627.

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Gazizov, R., A. Bezrukov, and B. Feoktistov. "Stochastic Realizations of Gaussian Random Fields: Analysis and Comparison of Modeling Methods." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902181.

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Raanes, P. N., G. Evensen, and A. S. Stordal. "Revising the Method of Ensemble Randomized Maximum Likelihood." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902205.

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Juda, P., J. Straubhaar, and P. Renard. "Simplified Direct Sampling Method for Geostatistical Multiple-point Simulations." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902227.

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Renard, P., C. Jäggli, Y. Dagasan, and J. Straubhaar. "The Posterior Population Expansion Ensemble Method to Invert Categorical Fields." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902270.

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Yarus*, J., C. Rodriguez, J. Dahl, C. Davila, and J. Spaid. "Interactive Earth Modeling in Unconventional Reservoirs - Principles, Methods, and a Case Study from the Mississippian, Barnett Shale." In Petroleum Geostatistics 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201413600.

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Reports on the topic "Geostatistic methods"

1

SVITELMAN, Valentina, and Oleg DINARIEV. The method of spherical harmonics in rock microstructural geostatistics. Cogeo@oeaw-giscience, September 2011. http://dx.doi.org/10.5242/iamg.2011.0048.

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NOVAK ZELENIKA, Kristina, Josipa VELIĆ, Tomislav MALVIĆ, and Marko CVETKOVIĆ. Geological Variables Fitting in Normal Distribution and Application in Indicator Geostatistical Methods. Cogeo@oeaw-giscience, September 2011. http://dx.doi.org/10.5242/iamg.2011.0230.

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Oliver, Margaret A. Application of Geostatistical Methods and Wavelets to the Analysis of Hyperspectral Imagery and the Testing of a Moving Variogram. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada393009.

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