Kriging is proposed as a tool for Wi-Fi signal strength estimation for complex indoor environments. This proposal is based on two studies suggesting that kriging might be suitable for this application. Both of these studies have shortcomings in supporting this proposal, but their results encourage a more in depth investigation into this. Even though kriging is a geostatistical method developed for geographical interpolation, it has been used successfully in a wide range of other applications as well. This further suggests that kriging might be a versatile method to overcome some of the difficul- ties of existing signal strength estimation methods. Two main types of signal strength estimation are deterministic methods and empirical methods. Deterministic methods are generally very complex and requires input parameters that are difficult to obtain. Empirical methods are known to have low accuracy which makes them unreliable for practical use. Three main investigations are presented in order to evaluate the use of kriging for this application. A sampling plan is proposed as part of a generic application protocol for the practical use of kriging for Wi-Fi signal strength. It is concluded that kriging can be conffidently used as an estimation technique for Wi-Fi signal strength in complex indoor environments. Kriging is recommended for practical applications, especially where in- sufficient information is available about a building or where time consuming site surveys are not feasible. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Kriging is proposed as a tool for Wi-Fi signal strength estimation for complex indoor environments. This proposal is based on two studies suggesting that kriging might be suitable for this application. Both of these studies have shortcomings in supporting this proposal, but their results encourage a more in depth investigation into this. Even though kriging is a geostatistical method developed for geographical interpolation, it has been used successfully in a wide range of other applications as well. This further suggests that kriging might be a versatile method to overcome some of the difficul- ties of existing signal strength estimation methods. Two main types of signal strength estimation are deterministic methods and empirical methods. Deterministic methods are generally very complex and requires input parameters that are difficult to obtain. Empirical methods are known to have low accuracy which makes them unreliable for practical use. Three main investigations are presented in order to evaluate the use of kriging for this application. A sampling plan is proposed as part of a generic application protocol for the practical use of kriging for Wi-Fi signal strength. It is concluded that kriging can be conffidently used as an estimation technique for Wi-Fi signal strength in complex indoor environments. Kriging is recommended for practical applications, especially where in- sufficient information is available about a building or where time consuming site surveys are not feasible. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

This is a thesis about the spatial distribution of willow warbler, nightingale, blackbird, robin and grey flycatcher in Svealand and Götaland, that is the southern third of Sweden. It explores the possibilities of using statistics to describe the distribution and variation of birds in a given region.The data was collected by observation of birds on sites called standard routes, with 25 kilometres between them. The standard routes are the points in a grid net placed upon the map of Sweden. The purpose of standard routes is to represent the birds in Sweden both geographic and biotopological.The thesis compare the results from kriging, variogram and four alternative poisson regressions. In the end I come up with the information provided by kriging and variogram and which poisson regression that bests estimates the population sizes of the birds at a given site with information about year, mean temperature from January to May and what kind of environment or habitat the site consist of.

As imagens de alta resolução espacial impulsionaram os estudos de Sensoriamento Remoto em ambientes urbanos, já que elas permitem uma melhor distinção dos elementos que compõem esse ambiente tão heterogêneo. Técnicas de Geoestatística são cada vez mais utilizadas em estudos de Sensoriamento Remoto e o variograma é uma importante ferramenta de análise geoestatística, pois permitem entender o comportamento espacial de uma variável regionalizada, neste caso, os níveis de cinza de uma imagem de satélite. O presente trabalho pretende avaliar a proposta metodológica que consiste em identificar padrões residenciais urbanos de três classes de uso e ocupação do solo por meio da análise dos valores apresentados pelos parâmetros, alcance, patamar e efeito pepita de um variograma. A hipótese é que os valores correspondentes a esses parâmetros representem o comportamento espectral padrão de cada classe e, portando, indicam que há um padrão na organização espacial de cada uma das classes. Para a presente pesquisa foram utilizadas imagem IKONOS 2002, e a classificação de uso e ocupação do solo da sub-bacia do córrego Bananal na bacia do Rio Cabuçu de Baixo em São Paulo SP. Amostras das imagens de cada classe foram extraídas e os valores de nível de cinza em cada pixel foram utilizados para calcular os variogramas. Após análise dos resultados obtidos, apenas o parâmetro alcance foi levado em consideração, pois é através desse parâmetro que se observa o grau de homogeneidade de cada amostra. Os valores de alcance obtidos nos cálculos dos variogramas identificaram com melhor precisão a classe Conjuntos Residenciais que é uma classe com padrões e características singulares, já a identificação das classes Ocupação Densa Regular e Ocupação Densa Irregular não obteve uma precisão boa, sendo que essas classes são similares em diversos aspectos. / The images of high spatial resolution studies of leveraged Remote Sensing in urban environments, as they enable better distinction of the elements that make up this very heterogeneous environment. Geostatistical techniques are increasingly used in studies of Remote Sensing, the variogram is an important tool geostatiscal analysis, because it allows to understand the spatial behavior of a regionalized variable, in this case, the gray levels of a satellite image. This study aims to assess the methodological proposal is to identify urban residential patterns of three classes of use and occupation of land by the analysis of the figures presented by the parameters, scope, and level of a nugget effect variogram. The hypothesis is that the values corresponding to these parameters represent the standard of each class spectral behavior and bearing indicate that there is a pattern in the spatial organization of each class. IKONOS 2002 image were used for this research, and the classification of the use and occupation of the stream Banana plantation sub-basin in the Rio Cabuçu Low Bowl in Sao Paulo - SP. Samples of stock were taken from each class and the values of gray level in each pixel are used to calculate the variogram. After analyzing the results, only the parameter range was taken into account , because it is through this parameter is observed the degree of homogeneity of each sample. The range of values obtained in the calculation of variograms identified with better accuracy class \"Multiple Dwelling Unit\" which is a class with unique patterns and characteristics, since the identification of classes \"Regulated Dense Occupation\" and \"Irregular Dense Occupation\" did not get a good precision since the classes are similar in several respects.

Dolphinfish (Coryphaena hippurus) is a pelagic species that is ecologically and commercially important in the western Atlantic region. This species has been linked to dominant oceanographic features such as sea surface temperature (SST) frontal regions. This work first explored the linkages between the catch rates of dolphinfish and the oceanography (satellite-derived SST, distance to front calculations, bottom depth and hook depth) using Principal Components Analysis (PCA). It was demonstrated that higher catch rates are found in relation to warmer SST and nearer to frontal regions. This environmental information was then included in standardizations of catch-per-unit-effort (CPUE) indices. It was found that including the satellite-derived SST and distance to front increases the confidence in the index. The second part of this work focused on addressing spatial variability in the catch rate data for a subsection of the sampling area: the Gulf of Mexico region. This study used geostatistical techniques to model and predict spatial abundances of two pelagic species with different habitat utilization patterns: dolphinfish (Coryphaena hippurus) and swordfish (Xiphias gladius). We partitioned catch rates into two components, the probability of encounter, and the abundance, given a positive encounter. We obtained separate variograms and kriged predictions for each component and combined them to give a single density estimate with corresponding variance. By using this two stage approach we were able to detect patterns of spatial autocorrelation that had distinct differences between the two species, likely due to differences in vertical habitat utilization. The patchy distribution of many living resources necessitates a two-stage variogram modeling and prediction process where the probability of encounter and the positive observations are modeled and predicted separately. Such a "geostatistical delta-lognormal" approach to modeling spatial autocorrelation has distinct advantages in allowing the probability of encounter and the abundance, given an encounter to possess separate patterns of autocorrelation and in modeling of severely non-normally distributed data that is plagued by zeros.

This dissertation includes two parts. Part 1 develops a geostatistical method to calibrate Texas NexRad rainfall estimates using rain gauge measurements. Part 2 explores the asymptotic joint distribution of sample space-time covariance estimators. The following two paragraphs briefly summarize these two parts, respectively. Rainfall is one of the most important hydrologic model inputs and is considered a random process in time and space. Rain gauges generally provide good quality data; however, they are usually too sparse to capture the spatial variability. Radar estimates provide a better spatial representation of rainfall patterns, but they are subject to substantial biases. Our calibration of radar estimates, using gauge data, takes season, rainfall type and rainfall amount into account, and is accomplished via a combination of threshold estimation, bias reduction, regression techniques and geostatistical procedures. We explore a varying-coefficient model to adapt to the temporal variability of rainfall. The methods are illustrated using Texas rainfall data in 2003, which includes WAR-88D radar-reflectivity data and the corresponding rain gauge measurements. Simulation experiments are carried out to evaluate the accuracy of our methodology. The superiority of the proposed method lies in estimating total rainfall as well as point rainfall amount. We study the asymptotic joint distribution of sample space-time covariance esti-mators of stationary random fields. We do this without any marginal or joint distri-butional assumptions other than mild moment and mixing conditions. We consider several situations depending on whether the observations are regularly or irregularly spaced, and whether one part or the whole domain of interest is fixed or increasing. A simulation experiment illustrates the asymptotic joint normality and the asymp- totic covariance matrix of sample space-time covariance estimators as derived. An extension of this part develops a nonparametric test for full symmetry, separability, Taylor's hypothesis and isotropy of space-time covariances.

No description available.

Geotechnical engineering design has relied upon deterministic methods of analysis whereby values for analysis parameters and conditions are selected subjectively based on judgment with the intent of providing acceptable margins of safety. The objective of this research was to improve the use of probabilistic slope stability analysis in practice so that the design of slopes can be made on a consistent and probabilistic basis. The current research involved the development of a methodology for the measurement and modeling of the anisotropic autocorrelation distance of cohesive soils, which was demonstrated at Dyke 17 West of the McArthur Falls Generating Station. In-situ testing using the piezocone and laboratory testing was conducted to characterize the spatial variability of the effective-shear strength envelope. Vertical (down-hole) and horizontal (cross-hole) geostatistical analysis was conducted to assess the anisotropy of the semivariogram. The investigation identified that heterogeneous inclusions had significant impacts on the results, but that simplistic (visual) identification and filtering procedures were adequate. The effective-stress shear strength envelope was statistically characterized as a random field, which was simulated as a first-order Markov process using customized add-in functions in a limit-equilibrium slope stability analysis. The analysis accounts for the spatial variability of shear strength and is capable of simulating both isotropic and anisotropic autocorrelation functions. The study showed that the critical slip surface geometry and the probability of failure can be significantly different when the anisotropy of spatial correlation is accounted for. The study also showed that neglecting spatial correlation may over-estimate the probability of failure, however this finding was noted to be likely case-specific. The primary conclusion of the study was that appropriate representation of spatial correlation is essential to calculating the probability of failure. Finally, convergence of the probabilistic simulation was evaluated using bootstrapping of the simulated factor of safety distribution to assess the standard error in the mean factor of safety, standard deviation of factor of safety and the probability of failure. A convergence criterion based on the percentage standard error in the probability of failure was proposed and used to define the number of Monte-Carlo iterations required.

Made available in DSpace on 2014-07-29T16:24:19Z (GMT). No. of bitstreams: 1 Distribuicao espacial do percevejo do colmo.pdf: 2200998 bytes, checksum: 96ba2e406bd13f5eab8e639d97bddb15 (MD5) Previous issue date: 2012-11-09 / The injury imposed by Tibraca limbativentris Stål in plants of rice can negatively affect the production and reduce grain yield. Knowing the spatial arrangement of this species allows fast and accurate sampling and identifies focuses of infestation determining the ideal moment of decision-making for the control. The aim of this study was to investigate the spatial and probabilistic distribution of adults and nymphs of T. limbativentris in irrigated rice. Fifteen fields with plants of 50-80 days after emergency were sampled on approximately regular grids in 2008, 2010, and 2011. Poisson and Negative binomial distributions were tested and Pearson chi-squared test was used to determine a probability distribution with the best fit. Polynomial regressions of the number of individuals versus geographical coordinates were used to try detecting trends related with macroscale. Later, semivariograms were used to interpret the spatial dependence and distribution of insects. The semivariance of the samples obtained with nymphs showed patterns grouped in 13% of fields sampled. Similar pattern was also obtained by semivariograms of adults in 26% of fields sampled. However, there were no spatial dependence in the most of the sampled fields with adults (74%) and nymphs (87%). In conclusion, adults and nymphs of T. limbativentris are randomly distributed in irrigated rice fields, though rarely clustered pattern can occur. The probability distribution that best fits the data sampling is the Negative binomial. Adults and nymphs do not inhabit the same local in the rice field. Population levels above the value of economic damage may occur, but individuals are not present in about 2/3 of the units sampled. Polynomial regression models tested are not appropriate to fit the trends related to macro-scale in irrigated rice fields. / A injúria imposta por Tibraca limbativentris Stål às plantas de arroz pode inviabilizar a produção e reduzir o rendimento de grãos. Conhecer o arranjo espacial desta espécie permite que amostragens rápidas e precisas identifiquem focos de infestação e se determine o momento ideal de tomada de decisão para o controle. O objetivo desse trabalho foi verificar a distribuição espacial e probabilística de adultos e ninfas de T. limbativentris em arroz irrigado. Quinze campos com plantas de 50-80 dias de emergência foram amostrados em grades aproximadamente regulares durante as safras 2008, 2010 e 2011. A distribuição Poisson e Binomial negativa foram ajustadas e o teste de qui-quadrado de Pearson foi utilizado para verificar a distribuição probabilística de melhor ajuste. Regressões polinomiais do número de indivíduos em função das coordenadas geográficas foram utilizadas na tentativa de detectar tendências de macroescala. Posteriormente, semivariogramas foram utilizados para interpretar a dependência espacial e distribuição dos insetos. As semivariâncias obtidas das amostragens com ninfas indicaram padrão agregado em 13% dos campos amostrados. Padrão semelhante também foi obtido pelos semivariogramas de adultos em 26% dos campos amostrados. No entanto, houve ausência de dependência espacial na maior parte dos campos amostrados com adultos (74%) e ninfas (87%). Compreende-se então que adultos e ninfas de T. limbativentris se distribuem aleatoriamente pelos campos de arroz irrigado, embora, raramente, ocorram padrões agregados. A distribuição de probabilidade que melhor se ajusta aos dados de amostragem é a Binomial negativa. Os adultos e ninfas não ocupam os mesmos locais da lavoura. Níveis populacionais acima do valor de dano econômico podem ocorrer, mas os indivíduos não estão presentes em cerca de 2/3 das unidades amostradas. Os modelos de regressões polinomiais testados não são indicados para ajustar as tendências de macroescala em campos de arroz irrigado.

As imagens de alta resolução espacial impulsionaram os estudos de Sensoriamento Remoto em ambientes urbanos, já que elas permitem uma melhor distinção dos elementos que compõem esse ambiente tão heterogêneo. Técnicas de Geoestatística são cada vez mais utilizadas em estudos de Sensoriamento Remoto e o variograma é uma importante ferramenta de análise geoestatística, pois permitem entender o comportamento espacial de uma variável regionalizada, neste caso, os níveis de cinza de uma imagem de satélite. O presente trabalho pretende avaliar a proposta metodológica que consiste em identificar padrões residenciais urbanos de três classes de uso e ocupação do solo por meio da análise dos valores apresentados pelos parâmetros, alcance, patamar e efeito pepita de um variograma. A hipótese é que os valores correspondentes a esses parâmetros representem o comportamento espectral padrão de cada classe e, portando, indicam que há um padrão na organização espacial de cada uma das classes. Para a presente pesquisa foram utilizadas imagem IKONOS 2002, e a classificação de uso e ocupação do solo da sub-bacia do córrego Bananal na bacia do Rio Cabuçu de Baixo em São Paulo SP. Amostras das imagens de cada classe foram extraídas e os valores de nível de cinza em cada pixel foram utilizados para calcular os variogramas. Após análise dos resultados obtidos, apenas o parâmetro alcance foi levado em consideração, pois é através desse parâmetro que se observa o grau de homogeneidade de cada amostra. Os valores de alcance obtidos nos cálculos dos variogramas identificaram com melhor precisão a classe Conjuntos Residenciais que é uma classe com padrões e características singulares, já a identificação das classes Ocupação Densa Regular e Ocupação Densa Irregular não obteve uma precisão boa, sendo que essas classes são similares em diversos aspectos. / The images of high spatial resolution studies of leveraged Remote Sensing in urban environments, as they enable better distinction of the elements that make up this very heterogeneous environment. Geostatistical techniques are increasingly used in studies of Remote Sensing, the variogram is an important tool geostatiscal analysis, because it allows to understand the spatial behavior of a regionalized variable, in this case, the gray levels of a satellite image. This study aims to assess the methodological proposal is to identify urban residential patterns of three classes of use and occupation of land by the analysis of the figures presented by the parameters, scope, and level of a nugget effect variogram. The hypothesis is that the values corresponding to these parameters represent the standard of each class spectral behavior and bearing indicate that there is a pattern in the spatial organization of each class. IKONOS 2002 image were used for this research, and the classification of the use and occupation of the stream Banana plantation sub-basin in the Rio Cabuçu Low Bowl in Sao Paulo - SP. Samples of stock were taken from each class and the values of gray level in each pixel are used to calculate the variogram. After analyzing the results, only the parameter range was taken into account , because it is through this parameter is observed the degree of homogeneity of each sample. The range of values obtained in the calculation of variograms identified with better accuracy class \"Multiple Dwelling Unit\" which is a class with unique patterns and characteristics, since the identification of classes \"Regulated Dense Occupation\" and \"Irregular Dense Occupation\" did not get a good precision since the classes are similar in several respects.