In the early 1950s the study on how to determine true ore-grade distributions in the mining sector, sparked the development of a series of statistical tools that specifically allows for spatial and subsequently spatial-temporal dependence. These statistics are commonly referred to as geostatistics, and has since been incorporated in several fields of study characterized by this dependence. Basic descriptive statistics and mapping tools for geostatistics are defined and illustrated by means of a simulated dataset. The moments are modelled according to predefined conditions and model structures to describe the spatial and spatial-temporal variance in the data. These variograms and covariance structures are subsequently utilized in the least square procedure, namely kriging. At present, kriging is most commonly used in geostatistics for the interpolation and simulation of spatial or spatial-temporal data. The univariate and multivariate spatial and spatial-temporal kriging techniques are tested on the simulated dataset, to demonstrate how interpolation weights are determined according to the lag distances and underlying variance structure. The strength, weaknesses and inherent complexities of the methodologies are highlighted. / Dissertation (MSc)--University of Pretoria, 2010. / Statistics / unrestricted

More frequent and harsh storms coupled with sea level rise are affecting Canada’s sensitive coastlines. This research studies Isle Madame in Cape Breton, Nova Scotia which has been designated by Natural Resource Canada as a sea level rise vulnerable coastal community in Canada. The research models the spatial and temporal impacts of sea level rise from storm surge by focusing on identifying vulnerable areas in the community via geographical information systems (GIS) using ArcGIS, as well as modeling dynamic coastal damage via system dynamics using STELLA. The research evaluates the impacts in terms of the environmental, social, cultural, economic pillars that profile the coastal community for a series of modelled Storm Scenarios. This research synthesizes information from a variety of sources including the coastal ecology and natural resources, as well as human society and socioeconomic indicators included in the four mentioned pillars. The objective of the research is to determine vulnerable areas on Isle Madame susceptible to storm damage, and consequently, to improve local community knowledge and preparedness to more frequent harsh storms. This research therefore presents a dynamic model for the evaluation of storm impacts in Isle Madame designed with the goal to help the community ultimately to plan and implement a strategy to adapt to pending environmental change.

Attended objects are perceived differently than unattended objects. Spatial attention is consistently associated with an enhancement in spatial resolution. However, the relation between spatial attention and temporal resolution is not as straightforward. Some studies have shown that attention enhances temporal resolution, and others have shown that attention degrades temporal resolution. The motivation of the present work was to investigate the source of this discrepancy. In particular, the research herein examines the hypothesis that attention degrades temporal resolution when the target stimuli are easily integrated (i.e., according to the Gestalt principles of grouping), and that attention enhances temporal resolution when the targets are easy to perceptually segregate. Temporal resolution was assessed by the mean just noticeable difference (the minimum temporal interval in milliseconds required by observers to perform the task at 75% accuracy) in a visual temporal order judgment (TOJ) task. Trials involved the presentation of two targets, at randomly varying stimulus onset asynchronies, and observers reported which one they perceived first. The primary research questions concerned the effect of perceptual grouping on temporal resolution, and the influence of attention on that relation. Grouping processes were manipulated using a variety of Gestalt principles and attention was investigated under conditions of automatically-and voluntarily-driven orienting. Three main findings emerged: temporal resolution is worse for grouped than ungrouped targets; attention modulates the effect of grouping on temporal resolution on a continuum - strong grouping effects produce large impairments on temporal resolution, and weaker grouping effects produce smaller impairments; and automatic and voluntary spatial orienting affect the relation between grouping and temporal resolution differently - automatic orienting augments the relation, while voluntary orienting does not. I conclude that the discrepant findings in the previous research are due to object-based factors pertaining to the target stimuli and propose an object-based theory of temporal perception. / Thesis / Doctor of Philosophy (PhD)

No description available.

Stochastic reaction-diffusion simulations has become an efficient approach for modelling spatial aspects of intracellular biochemical reaction networks. By accounting for intrinsic noise due to low copy number of chemical species, stochastic reaction-diffusion simulations have the ability to more accurately predict and model biological systems. As with many simulations software, exploration of the parameters associated with the model can be needed to yield new knowledge about the underlying system. The exploration can be conducted by executing parameter sweeps for a model. However, with little or no prior knowledge about the modelled system, the effort for practitioners to explore the parameter space can get overwhelming. To account for this problem we perform a feasibility study on an explorative behavioural analysis of stochastic reaction-diffusion simulations by applying spatial-temporal data mining to large parameter sweeps. By reducing individual simulation outputs into a feature space involving simple time series and distribution analytics, we were able to find similar behaving simulations after performing an agglomerative hierarchical clustering.

Lake trout (Salvelinus namaycush) have a broad distribution across Canada’s north, yet most studies that describe reproductive habitat and behaviour have been conducted in the southern extent of their range. Northern regions are experiencing unprecedented changes from climate and industrial development, and thus there is a pressing need to understand the reproductive habitat and behaviour of this species. I examined a dozen sites around Alexie Lake, Northwest Territories, to test if physical habitat and wind exposure were important determinants of spawning site use and embryonic survival. Spawning was found to occur in ~2 m water depth, on 3–15 cm diameter clean substrate on the leading edge of shoals that ended in a rock crib rising abruptly in nearshore regions around the lake. Wind direction was predominantly from the west, although it was highly variable within and among spawning seasons. I found evidence of lake trout spawning at each site examined, which was not limited to shoals facing a predominant wind direction. High variation in embryonic survival (2–83%) from incubation trays was observed among spawning sites, demonstrating a large gradient in habitat quality exists within a given lake. However, modelled wind exposure did not predict embryonic survival, nor did physical characteristics - including shoal depth and slope, as well as cobble size and shape - that may influence interstitial water flow on spawning shoals. Using an acoustic telemetry monitoring system and novel spatial temporal clustering analysis, I was able to quantify lake trout spawning movements and behaviours over the course of an entire spawning season. Lake trout formed clusters on spawning shoals around the entire nearshore region, as well as around several islands, confirming that suitable spawning habitat is abundant in Alexie Lake. Males arrived on spawning shoals earlier than females and remained longer for a maximum of 25 consecutive days; females occupied spawning shoals for a maximum of 8 consecutive days over the course of the spawning season. Males formed over four times as many spawning clusters and visited twice as many sites than females. Spawning clusters were predominantly formed at night but were also observed during daylight hours, especially during the peak spawning season (September 9–19). I found males had higher activity rates, and spent longer periods on spawning shoals, than females, in spite of similar daily travel distances between sexes. Overall, my findings challenge the conventional role of wind as a predominant predictor of lake trout spawning site quality. I propose that the unpredictable nature of wind and abundance of suitable habitat may favour lake-wide spawning by lake trout as a bet-hedging strategy in northern lakes with limited fetch. / May 2016

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / In this paper, we propose applying the spatio-temporal signal processing and OFDM techniques to a multiple-antenna system in order to achieve high data rate and high performance transmission capability. In order to perform real time processing for this system, we also propose a complexity reduced QR beamforming algorithm. The performance of the proposed system has been investigated for a two-ray frequency-selective fading model by extensive computer simulations. These results show that significant benefits can be realized in terms of lower bit error rate and higher data transmission rate.

As sensor data becomes more and more available, there is an increasing interest in assimilating real time sensor data into spatial temporal simulations to achieve more accurate simulation or prediction results. Particle Filters (PFs), also known as Sequential Monte Carlo methods, hold great promise in this area as they use Bayesian inference and stochastic sampling techniques to recursively estimate the states of dynamic systems from some given observations. However, PFs face major challenges to work effectively for complex spatial temporal simulations due to the high dimensional state space of the simulation models, which typically cover large areas and have a large number of spatially dependent state variables. As the state space dimension increases, the number of particles must increase exponentially in order to converge to the true system state. The purpose of this dissertation work is to develop localized particle filtering to support PFs-based data assimilation for large-scale spatial temporal simulations. We develop a spatially dependent particle-filtering framework that breaks the system state and observation data into sub-regions and then carries out localized particle filtering based on these spatial regions. The developed framework exploits the spatial locality property of system state and observation data, and employs the divide-and-conquer principle to reduce state dimension and data complexity. Within this framework, we propose a two-level automated spatial partitioning method to provide optimized and balanced spatial partitions with less boundary sensors. We also consider different types of data to effectively support data assimilation for spatial temporal simulations. These data include both hard data, which are measurements from physical devices, and soft data, which are information from messages, reports, and social network. The developed framework and methods are applied to large-scale wildfire spread simulations and achieved improved results. Furthermore, we compare the proposed framework to existing particle filtering based data assimilation frameworks and evaluate the performance for each of them.

Introdução: Estima-se que 2,5 bilhões de pessoas vivam em áreas de risco de dengue, em mais de 100 países endêmicos. Mais de 50 milhões de infecções ocorrem anualmente com 500.000 casos de dengue hemorrágica e 22.000 mortes, principalmente entre crianças. A cidade de Araraquara apesar de apresentar boas condições sociais e econômicas, tem apresentado graves epidemias de dengue na última década. Objetivo: Este estudo examinou os fatores socioambientais urbanos associados à incidência de dengue em Araraquara, que é uma cidade de médio porte localizada no interior do estado de São Paulo, na região sudeste do Brasil nos anos de 1998 a 2008. Métodos: Foi realizado um estudo ecológico longitudinal, no qual foram avaliados dados de incidência de Dengue notificados no Sistema de Informação de Agravos de Notificação (SINAN) em todas as semanas epidemiológicas dos anos de 1998 a 2008, no município de Araraquara. As variáveis socioambientais urbanas investigadas foram extraídas do censo demográfico, de imagens de satélite e de planos de informações georreferenciados do ambiente construído. As variáveis meteorológicas investigadas foram obtidas a partir de uma estação automática com mediçoes diárias para todo o período analisado. Para investigar o padrão espaço temporal da distribuição da incidência de dengue no município, foram utilizadas as técnicas de análise exploratória de dados espaciais. Para investigar o efeito independente de variáveis socioambientais urbanas sobre a ocorrência de casos de dengue nos setores censitários de Araraquara, ao longo do período de 1998 a 2008, foram utilizados modelos de análise multivariada para dados longitudinais, por meio de equações de estimação generalizadas (GEE, Generalized Estimating Equations). Resultados: foram identificados padrões sazonais da incidência de dengue. Foram observados efeitos significativos de variáveis sociombientais urbanas, incluindo as variáveis meteorológicas, epidemiológicas e do ambiente construído, como fatores de risco à ocorrência de dengue e estes fatores variam no tempo e no espaço. Conclusão: os resultados mostraram a complexidade dos fatores associados à incidência de dengue no município de Araraquara, que envolve fatores socioambientais urbanos, em diferentes escalas espaciais e temporais. A consideração dos fatores no planejamento de políticas públicas pode ser importante para o enfrentamento desse grave problema de saúde urbana. / Introduction: It is estimated that 2.5 billion people live in areas at risk of dengue fever in more than 100 endemic countries. Over 50 million infections occur annually with 500,000 cases of DHF and 22,000 deaths, mostly among children. The city of Araraquara, despite having good social and economic conditions, had severe dengue epidemics in the last decade. Objective: This study examined the urban socio-environmental factors associated with the incidence of dengue in Araraquara, which is a medium-sized city located in the state of São Paulo, in southeastern Brazil in the years 1998 to 2008. Methods: We conducted a longitudinal ecological study, which evaluated data on the incidence of dengue reported in the Information System for Notifiable Diseases (SINAN) in all epidemiological weeks of the years 1998 to 2008, for the city of Araraquara. The urban social and environmental variables investigated were taken from the census, satellite images and geo-referenced data layers of the built environment. The meteorological variables investigated were obtained from an automatic station with daily measurements for the whole period. To investigate the pattern of spatial and temporal distribution of the incidence of dengue in the city, we used the techniques of exploratory spatial data analysis. To investigate the independent effect of urban social and environmental variables on the occurrence of dengue cases in the census tracts of Araraquara, over the period 1998 to 2008, we used multivariate analysis models for longitudinal data, and generalized estimating equations (GEE). Results: We identified seasonal patterns of dengue incidence. Significant effects were observed for urban social and environmental variables, including meteorological variables, epidemiological and built environment as risk factors to the occurrence of dengue and these factors vary in time and space. Conclusion: The results showed the complexity of factors associated with the incidence of dengue in the city of Araraquara, which involves urban socio-environmental factors at different spatial and temporal scales. The consideration of these factors in the planning of public policies can be important to deal with this serious problem of urban health.

Introdução: Estima-se que 2,5 bilhões de pessoas vivam em áreas de risco de dengue, em mais de 100 países endêmicos. Mais de 50 milhões de infecções ocorrem anualmente com 500.000 casos de dengue hemorrágica e 22.000 mortes, principalmente entre crianças. A cidade de Araraquara apesar de apresentar boas condições sociais e econômicas, tem apresentado graves epidemias de dengue na última década. Objetivo: Este estudo examinou os fatores socioambientais urbanos associados à incidência de dengue em Araraquara, que é uma cidade de médio porte localizada no interior do estado de São Paulo, na região sudeste do Brasil nos anos de 1998 a 2008. Métodos: Foi realizado um estudo ecológico longitudinal, no qual foram avaliados dados de incidência de Dengue notificados no Sistema de Informação de Agravos de Notificação (SINAN) em todas as semanas epidemiológicas dos anos de 1998 a 2008, no município de Araraquara. As variáveis socioambientais urbanas investigadas foram extraídas do censo demográfico, de imagens de satélite e de planos de informações georreferenciados do ambiente construído. As variáveis meteorológicas investigadas foram obtidas a partir de uma estação automática com mediçoes diárias para todo o período analisado. Para investigar o padrão espaço temporal da distribuição da incidência de dengue no município, foram utilizadas as técnicas de análise exploratória de dados espaciais. Para investigar o efeito independente de variáveis socioambientais urbanas sobre a ocorrência de casos de dengue nos setores censitários de Araraquara, ao longo do período de 1998 a 2008, foram utilizados modelos de análise multivariada para dados longitudinais, por meio de equações de estimação generalizadas (GEE, Generalized Estimating Equations). Resultados: foram identificados padrões sazonais da incidência de dengue. Foram observados efeitos significativos de variáveis sociombientais urbanas, incluindo as variáveis meteorológicas, epidemiológicas e do ambiente construído, como fatores de risco à ocorrência de dengue e estes fatores variam no tempo e no espaço. Conclusão: os resultados mostraram a complexidade dos fatores associados à incidência de dengue no município de Araraquara, que envolve fatores socioambientais urbanos, em diferentes escalas espaciais e temporais. A consideração dos fatores no planejamento de políticas públicas pode ser importante para o enfrentamento desse grave problema de saúde urbana. / Introduction: It is estimated that 2.5 billion people live in areas at risk of dengue fever in more than 100 endemic countries. Over 50 million infections occur annually with 500,000 cases of DHF and 22,000 deaths, mostly among children. The city of Araraquara, despite having good social and economic conditions, had severe dengue epidemics in the last decade. Objective: This study examined the urban socio-environmental factors associated with the incidence of dengue in Araraquara, which is a medium-sized city located in the state of São Paulo, in southeastern Brazil in the years 1998 to 2008. Methods: We conducted a longitudinal ecological study, which evaluated data on the incidence of dengue reported in the Information System for Notifiable Diseases (SINAN) in all epidemiological weeks of the years 1998 to 2008, for the city of Araraquara. The urban social and environmental variables investigated were taken from the census, satellite images and geo-referenced data layers of the built environment. The meteorological variables investigated were obtained from an automatic station with daily measurements for the whole period. To investigate the pattern of spatial and temporal distribution of the incidence of dengue in the city, we used the techniques of exploratory spatial data analysis. To investigate the independent effect of urban social and environmental variables on the occurrence of dengue cases in the census tracts of Araraquara, over the period 1998 to 2008, we used multivariate analysis models for longitudinal data, and generalized estimating equations (GEE). Results: We identified seasonal patterns of dengue incidence. Significant effects were observed for urban social and environmental variables, including meteorological variables, epidemiological and built environment as risk factors to the occurrence of dengue and these factors vary in time and space. Conclusion: The results showed the complexity of factors associated with the incidence of dengue in the city of Araraquara, which involves urban socio-environmental factors at different spatial and temporal scales. The consideration of these factors in the planning of public policies can be important to deal with this serious problem of urban health.