WorldWideScience

Sample records for spatio-temporal disease patterns

  1. Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

    Science.gov (United States)

    Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

    2011-01-01

    Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,pQueensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

  2. Spatio-temporal transmission patterns of black-band disease in a coral community.

    Directory of Open Access Journals (Sweden)

    Assaf Zvuloni

    Full Text Available BACKGROUND: Transmission mechanisms of black-band disease (BBD in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease. METHODOLOGY/PRINCIPAL FINDINGS: 3,175 susceptible and infected corals were mapped over an area of 10x10 m in Eilat (northern Gulf of Aqaba, Red Sea and the distribution of the disease was examined monthly throughout almost two full disease cycles (June 2006-December 2007. Spatial and spatio-temporal analyses were applied to infer the transmission pattern of the disease and to calculate key epidemiological parameters such as (basic reproduction number. We show that the prevalence of the disease is strongly associated with high water temperature. When water temperatures rise and disease prevalence increases, infected corals exhibit aggregated distributions on small spatial scales of up to 1.9 m. Additionally, newly-infected corals clearly appear in proximity to existing infected corals and in a few cases in direct contact with them. We also present and test a model of water-borne infection, indicating that the likelihood of a susceptible coral becoming infected is defined by its spatial location and by the relative spatial distribution of nearby infected corals found in the site. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence that local transmission, but not necessarily by direct contact, is likely to be an important factor in the spread of the disease over the tested spatial scale. In the absence of potential disease vectors with limited mobility (e.g., snails, fireworms in the studied site, water-borne infection is likely to be a significant transmission mechanism of BBD. Our suggested model of water-borne transmission supports this hypothesis. The spatio-temporal analysis also points

  3. Spatio-temporal patterns of coral recruitment at Vamizi Island ...

    African Journals Online (AJOL)

    Spatio-temporal patterns of coral recruitment at Vamizi Island, Quirimbas Archipelago, Mozambique. ... Spatial and temporal patterns of recruitment of reef corals were assessed for the first time in Mozambique ... AJOL African Journals Online.

  4. Spatio-temporal databases complex motion pattern queries

    CERN Document Server

    Vieira, Marcos R

    2013-01-01

    This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobi

  5. Spatio-temporal patterns in simple models of marine systems

    Science.gov (United States)

    Feudel, U.; Baurmann, M.; Gross, T.

    2009-04-01

    Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

  6. Patterns of urban violent injury: a spatio-temporal analysis.

    Directory of Open Access Journals (Sweden)

    Michael Cusimano

    2010-01-01

    Full Text Available Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre.Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18-64 in Toronto, Canada, during 2002 and 2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a "nightlife" district. The locational pattern of patient residences remained unchanged during those times.Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. However, later at night, the injury location of highest density shifts to a "nightlife" district, whereas the residence locations of those most at risk of injury do not change.

  7. Nonparametric evaluation of dynamic disease risk: a spatio-temporal kernel approach.

    Directory of Open Access Journals (Sweden)

    Zhijie Zhang

    Full Text Available Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the "average" spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled "spatio-temporal kernel density estimation (stKDE" that employs hybrid kernel (i.e., weight functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also "borrows" information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based kernel density estimation (trKDE which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.

  8. Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes

    Science.gov (United States)

    Metzen, Daniel; Sheridan, Gary; Nyman, Petter; Lane, Patrick

    2016-04-01

    Vegetation co-evolves with soils and topography under a given long-term climatic forcing. Previous studies demonstrated a strong eco-hydrologic feedback between topography, vegetation and energy and water fluxes. Slope orientation (aspect and gradient) alter the magnitude of incoming solar radiation resulting in larger evaporative losses and less water availability on equator-facing slopes. Furthermore, non-local water inputs from upslope areas potentially contribute to available water at downslope positions. The combined effect of slope orientation and drainage position creates complex spatial patterns in biological productivity and pedogenesis, which in turn alter the local hydrology. In complex upland landscapes, topographic alteration of incoming radiation can cause substantial aridity index (ratio of potential evapotranspiration to precipitation) variations over small spatial extents. Most of the upland forests in south-east Australia are located in an aridity index (AI) range of 1-2, around the energy limited to water limited boundary, where forested systems are expected to be most sensitive to AI changes. In this research we aim to improve the fundamental understanding of spatio-temporal evolution of evapotranspiration (ET) patterns in complex terrain, accounting for local topographic effects on system properties (e.g. soil depth, sapwood area, leaf area) and variation in energy and water exchange processes due to slope orientation and drainage position. Six measurement plots were set-up in a mixed species eucalypt forest on a polar and equatorial-facing hillslope (AI ˜1.3 vs. 1.8) at varying drainage position (ridge, mid-slope, gully), while minimizing variations in other factors, e.g. geology and weather patterns. Sap flow, soil water content, incoming solar radiation and throughfall were continuously monitored at field sites spanning a wide range of soil depth (0.5 - >3m), maximum tree heights (17 - 51m) and LAI (1.2 - 4.6). Site-specific response curves

  9. An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk

    OpenAIRE

    Rushworth, Alastair; Lee, Duncan; Sarran, Christophe

    2014-01-01

    Statistical models used to estimate the spatio-temporal pattern in disease\\ud risk from areal unit data represent the risk surface for each time period with known\\ud covariates and a set of spatially smooth random effects. The latter act as a proxy\\ud for unmeasured spatial confounding, whose spatial structure is often characterised by\\ud a spatially smooth evolution between some pairs of adjacent areal units while other\\ud pairs exhibit large step changes. This spatial heterogeneity is not c...

  10. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    Directory of Open Access Journals (Sweden)

    Yanxia Wang

    2014-05-01

    Full Text Available Ischemic heart disease (IHD is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents and the standardized rate (the observed cases standardized by the expected cases of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015 to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction

  11. Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis

    Science.gov (United States)

    Watanabe, Kazuhiko; Wakita, Jun-ichi; Itoh, Hiroto; Shimada, Hirotoshi; Kurosu, Sayuri; Ikeda, Takemasa; Yamazaki, Yoshihiro; Matsuyama, Tohey; Matsushita, Mitsugu

    2002-02-01

    Spatio-temporal patterns emerged inside a colony of bacterial species Proteus mirabilis on the surface of nutrient-rich semisolid agar medium have been investigated. We observed various patterns composed of the following basic types: propagating stripe, propagating stripe with fixed dislocation, expanding and shrinking target, and rotating spiral. The remarkable point is that the pattern changes immediately when we alter the position for observation, but it returns to the original if we restore the observing position within a few minutes. We further investigated mesoscopic and microscopic properties of the spatio-temporal patterns. It turned out that whenever the spatio-temporal patterns are observed in a colony, the areas are composed of two superimposed monolayers of elongated bacterial cells. In each area they are aligned almost parallel with each other like a two-dimensional nematic liquid crystal, and move collectively and independently of another layer. It has been found that the observed spatio-temporal patterns are explained as the moiré effect.

  12. Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

    Science.gov (United States)

    Khorram, Saeed; Ergil, Mustafa

    2018-03-01

    A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

  13. A model for optimizing file access patterns using spatio-temporal parallelism

    Energy Technology Data Exchange (ETDEWEB)

    Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-01-01

    For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.

  14. Pattern selection and spatio-temporal transition to chaos in Ginzburg-Landau equation

    Energy Technology Data Exchange (ETDEWEB)

    Nozaki, K; Bekki, N

    1983-07-01

    It is shown that a modulationally unstable pattern is selected and propagates into an initially unstable motionless state in the 1-D generalized Ginzburg-Landau equation. A further spatio-temporal transition occurs with a sharp interface from the selected unstable pattern to a stabilized pattern or a chaotic state. The distinct transition makes a coherent structure to coexist with a chaotic state. 12 refs., 4 figs.

  15. Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy.

    Science.gov (United States)

    Marchione, Elio; Johnson, Shane D

    2013-11-01

    To examine patterns in the timing and location of incidents of maritime piracy to see whether, like many urban crimes, attacks cluster in space and time. Data for all incidents of maritime piracy worldwide recorded by the National Geospatial Intelligence Agency are analyzed using time-series models and methods originally developed to detect disease contagion. At the macro level, analyses suggest that incidents of pirate attacks are concentrated in five subregions of the earth's oceans and that the time series for these different subregions differ. At the micro level, analyses suggest that for the last 16 years (or more), pirate attacks appear to cluster in space and time suggesting that patterns are not static but are also not random. Much like other types of crime, pirate attacks cluster in space, and following an attack at one location the risk of others at the same location or nearby is temporarily elevated. The identification of such regularities has implications for the understanding of maritime piracy and for predicting the future locations of attacks.

  16. Discovery of spatio-temporal patterns from location-based social networks

    Science.gov (United States)

    Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

    2016-03-01

    Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

  17. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    OpenAIRE

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-01-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire dis...

  18. Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand

    Directory of Open Access Journals (Sweden)

    Phaisarn Jeefoo

    2010-12-01

    Full Text Available In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007 was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group, data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall, spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

  19. Pattern formations in chaotic spatio-temporal systems

    Indian Academy of Sciences (India)

    5Beijing–Hong Kong–Singapore Joint Center of Nonlinear and Complex Systems, ... For theoretical studies most previous work has focused on pattern .... Lyapunov exponents from arbitrary initial conditions, and the plots look rather.

  20. SPATIO-TEMPORAL PATTERN MINING ON TRAJECTORY DATA USING ARM

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    S. Khoshahval

    2017-09-01

    Full Text Available Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user’s visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users’ behaviour in a system and can be utilized in various location-based applications.

  1. Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

    Science.gov (United States)

    Khoshahval, S.; Farnaghi, M.; Taleai, M.

    2017-09-01

    Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

  2. Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

    Science.gov (United States)

    Kitsunezaki, S.

    In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

  3. Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns

    Directory of Open Access Journals (Sweden)

    Yali Si

    2009-11-01

    Full Text Available The global spread of highly pathogenic avian influenza H5N1 in poultry, wild birds and humans, poses a significant pandemic threat and a serious public health risk. An efficient surveillance and disease control system relies on the understanding of the dispersion patterns and spreading mechanisms of the virus. A space-time cluster analysis of H5N1 outbreaks was used to identify spatio-temporal patterns at a global scale and over an extended period of time. Potential mechanisms explaining the spread of the H5N1 virus, and the role of wild birds, were analyzed. Between December 2003 and December 2006, three global epidemic phases of H5N1 influenza were identified. These H5N1 outbreaks showed a clear seasonal pattern, with a high density of outbreaks in winter and early spring (i.e., October to March. In phase I and II only the East Asia Australian flyway was affected. During phase III, the H5N1 viruses started to appear in four other flyways: the Central Asian flyway, the Black Sea Mediterranean flyway, the East Atlantic flyway and the East Africa West Asian flyway. Six disease cluster patterns along these flyways were found to be associated with the seasonal migration of wild birds. The spread of the H5N1 virus, as demonstrated by the space-time clusters, was associated with the patterns of migration of wild birds. Wild birds may therefore play an important role in the spread of H5N1 over long distances. Disease clusters were also detected at sites where wild birds are known to overwinter and at times when migratory birds were present. This leads to the suggestion that wild birds may also be involved in spreading the H5N1 virus over short distances.

  4. Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm.

    Science.gov (United States)

    Denis, Marie; Cochard, Benoît; Syahputra, Indra; de Franqueville, Hubert; Tisné, Sébastien

    2018-02-01

    In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propagation modes and transmission vectors. We investigate two alternative process models to study the unobserved mechanism driving the infection process. The models help gain insight into the spatio-temporal dynamic of the infection by identifying a genetic component in the disease spread and by highlighting a spatial component acting at the end of the experiment. In this challenging context, we propose models that provide assumptions on the unobserved mechanism driving the infection process while making short-term predictions using ready-to-use software. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Spatio-temporal flow maps for visualizing movement and contact patterns

    Directory of Open Access Journals (Sweden)

    Bing Ni

    2017-03-01

    Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

  6. Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

    International Nuclear Information System (INIS)

    Martins, Anabela; Figueira, Rui; Sousa, António Jorge; Sérgio, Cecília

    2012-01-01

    Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area. - Highlights: ► We estimated copper contamination in mosses by spatio-temporal kriging between 1992 and 2006. ► We determined local distribution functions to define variation intervals at each location. ► Significance of temporal changes is assessed using an indicator based on uncertainty interval. ► There is general decrease in copper contamination, but spatial patterns are not uniform. - The contamination of copper in mosses was estimated by spatio-temporal kriging, with determination of uncertainty classes in the temporal variation.

  7. Spatio-temporal dynamics of the white-eye square superlattice pattern in dielectric barrier discharge

    International Nuclear Information System (INIS)

    Wei, Lingyan; Dong, Lifang; Feng, Jianyu; Liu, Weibo; Fan, Weili; Pan, Yuyang

    2016-01-01

    We report on the first investigation of the white-eye square superlattice pattern (WESSP) in a dielectric barrier discharge system. The evolution of patterns with increasing voltage is given. A phase diagram of WESSP as functions of gas pressure p and argon concentration φ is presented. The spatio-temporal dynamics of the WESSP is studied by using an intensified charge-coupled device camera and photomultipliers. Results show that the WESSP consists of four different transient sublattices, whose discharge sequence is small spots—spots on the line—halos—central spots in each half voltage cycle. The discharge moment and position of each sublattice are dependent upon the field of the wall charges produced by all sublattices discharged previously. (paper)

  8. Estimating Activity Patterns Using Spatio-temporal Data of Cellphone Networks

    Directory of Open Access Journals (Sweden)

    Zahedi Seyedmostafa

    2016-01-01

    Full Text Available The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years, but these models have suffered insufficient data for calibration. This paper discusses ways to process the cellphone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. Movements of each subscriber is described by a sequence of stays and trips and each stay is labeled by an activity. The type of activities are estimated using features such as land use, duration of stay, frequency of visit, arrival time to that activity and its distance from home. Finally, the chains of trips are identified and different patterns that citizens follow to participate in activities are determined. The data comprises 144 million records of the location of 300,000 citizens of Shiraz at five-minute intervals.

  9. Spatio-temporal patterns of soil erosion and suspended sediment dynamics in the Mekong River Basin.

    Science.gov (United States)

    Suif, Zuliziana; Fleifle, Amr; Yoshimura, Chihiro; Saavedra, Oliver

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Spatio-temporal pattern formation in predator-prey systems with fitness taxis

    DEFF Research Database (Denmark)

    Heilmann, Irene T.; Thygesen, Uffe Høgsbro; Sørensen, Mads Peter

    2018-01-01

    We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction–advection–di......We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction...... of diffusive motion, is ecologically plausible, and provides an alternative mechanism for formation of patterns in spatially explicit ecosystem models, with emphasis on non-stationary spatio-temporal dynamics....

  11. Clonal mobility and its implications for spatio-temporal patterns of plant communities: what do we need to know next?

    Czech Academy of Sciences Publication Activity Database

    Zobel, M.; Moora, M.; Herben, Tomáš

    2010-01-01

    Roč. 119, č. 5 (2010), s. 802-806 ISSN 0030-1299 Institutional research plan: CEZ:AV0Z60050516 Keywords : clonal mobility * spatio-temporal patterns * plant communities Subject RIV: EF - Botanics Impact factor: 3.393, year: 2010

  12. Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

    Science.gov (United States)

    Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

    2017-10-24

    A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

  13. Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

    Science.gov (United States)

    Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

    2014-10-01

    Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

  14. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  15. SPAN: spike pattern association neuron for learning spatio-temporal sequences

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2012-01-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

  16. Zebrafish: an exciting model for investigating the spatio-temporal pattern of enteric nervous system development.

    LENUS (Irish Health Repository)

    Doodnath, Reshma

    2012-02-01

    AIM: Recently, the zebrafish (Danio rerio) has been shown to be an excellent model for human paediatric research. Advantages over other models include its small size, externally visually accessible development and ease of experimental manipulation. The enteric nervous system (ENS) consists of neurons and enteric glia. Glial cells permit cell bodies and processes of neurons to be arranged and maintained in a proper spatial arrangement, and are essential in the maintenance of basic physiological functions of neurons. Glial fibrillary acidic protein (GFAP) is expressed in astrocytes, but also expressed outside of the central nervous system. The aim of this study was to investigate the spatio-temporal pattern of GFAP expression in developing zebrafish ENS from 24 h post-fertilization (hpf), using transgenic fish that express green fluorescent protein (GFP). METHODS: Zebrafish embryos were collected from transgenic GFP Tg(GFAP:GFP)(mi2001) adult zebrafish from 24 to 120 hpf, fixed and processed for whole mount immunohistochemistry. Antibodies to Phox2b were used to identify enteric neurons. Specimens were mounted on slides and imaging was performed using a fluorescent laser confocal microscope. RESULTS: GFAP:GFP labelling outside the spinal cord was identified in embryos from 48 hpf. The patterning was intracellular and consisted of elongated profiles that appeared to migrate away from the spinal cord into the periphery. At 72 and 96 hpf, GFAP:GFP was expressed dorsally and ventrally to the intestinal tract. At 120 hpf, GFAP:GFP was expressed throughout the intestinal wall, and clusters of enteric neurons were identified using Phox2b immunofluorescence along the pathway of GFAP:GFP positive processes, indicative of a migratory pathway of ENS precursors from the spinal cord into the intestine. CONCLUSION: The pattern of migration of GFAP:GFP expressing cells outside the spinal cord suggests an organized, early developing migratory pathway to the ENS. This shows for the

  17. Understanding the Spatio-Temporal Pattern of Fire Disturbance in the Eastern Mongolia Using Modis Product

    Science.gov (United States)

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-04-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2) The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3) Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4) The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

  18. Large-Scale Spatio-Temporal Patterns of Mediterranean Cephalopod Diversity.

    Directory of Open Access Journals (Sweden)

    Stefanie Keller

    Full Text Available Species diversity is widely recognized as an important trait of ecosystems' functioning and resilience. Understanding the causes of diversity patterns and their interaction with the environmental conditions is essential in order to effectively assess and preserve existing diversity. While diversity patterns of most recurrent groups such as fish are commonly studied, other important taxa such as cephalopods have received less attention. In this work we present spatio-temporal trends of cephalopod diversity across the entire Mediterranean Sea during the last 19 years, analysing data from the annual bottom trawl survey MEDITS conducted by 5 different Mediterranean countries using standardized gears and sampling protocols. The influence of local and regional environmental variability in different Mediterranean regions is analysed applying generalized additive models, using species richness and the Shannon Wiener index as diversity descriptors. While the western basin showed a high diversity, our analyses do not support a steady eastward decrease of diversity as proposed in some previous studies. Instead, high Shannon diversity was also found in the Adriatic and Aegean Seas, and high species richness in the eastern Ionian Sea. Overall diversity did not show any consistent trend over the last two decades. Except in the Adriatic Sea, diversity showed a hump-shaped trend with depth in all regions, being highest between 200-400 m depth. Our results indicate that high Chlorophyll a concentrations and warmer temperatures seem to enhance species diversity, and the influence of these parameters is stronger for richness than for Shannon diversity.

  19. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    Directory of Open Access Journals (Sweden)

    Wurihan

    2018-04-01

    Full Text Available Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1 The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2 The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3 Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4 The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

  20. Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression

    Science.gov (United States)

    Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

    2017-04-01

    Cortical spreading depression (CSD) is an example of one of the most common abnormalities in biophysical brain functioning. Despite the fact that there are many mathematical models describing the cortical spreading depression (CSD), most of them do not take into consideration the role of redistribution of cerebral blood flow (CBF), that results in the formation of spatio-temporal patterns. The paper presents a mathematical model, which successfully explains the CBD role in the CSD process. Numerical study of this model has revealed the formation of stationary dissipative structures, visually analogous to Turing structures. However, the mechanism of their formation is not diffusion. We show these structures occur due to another type of spatial coupling, that is related to tissue perfusion rate. The proposed model predicts that at similar state of neurons the distribution of blood flow and oxygenation may by different. Currently, this effect is not taken into account when the Blood oxygen-level dependent (BOLD) contrast imaging used in functional magnetic resonance imaging (fMRI). Thus, the diagnosis on the BOLD signal can be ambiguous. We believe that our results can be used in the future for a more correct interpretation of the data obtained with fMRI, NIRS and other similar methods for research of the brain activity.

  1. Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

    Science.gov (United States)

    Matsubara, Takashi

    2017-01-01

    Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

  2. Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

    Science.gov (United States)

    Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

    2017-01-01

    Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

  3. Span: spike pattern association neuron for learning spatio-temporal spike patterns.

    Science.gov (United States)

    Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

    2012-08-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

  4. Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

    OpenAIRE

    Taiye Oluwafemi Adewuyi; Patrick Ali Eneji; Anthonia Silas Baduku; Emmanuel Ajayi Olofin

    2017-01-01

    This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote s...

  5. Spatio-temporal seasonal drought patterns in Europe from 1950 to 2015

    Science.gov (United States)

    Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen

    2016-04-01

    Drought is one of the natural disasters with severe impacts in Europe, not only in areas which frequently experience water scarcity such as the Mediterranean, but also in temperate or continental climates such as Central and Eastern Europe and even in cold regions such as Scandinavia and Iceland. In this study the spatio-temporal patterns of seasonal meteorological droughts in Europe between 1950 and 2015 are investigated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). Since the focus is on the analysis of seasonal drought trends, indicators were calculated for 3 monthly accumulation periods. The input variables of precipitation and temperature were derived from E-OBS grids (v11-v12) at a spatial resolution of 0.25°x0.25°. Seasonal trends of drought frequency and severity were analyzed for moderate (SPI or SPEI 2.0) events during the periods 1950-2015 and 1981-2015. For the moderate events, results of the SPI analysis (precipitation driven) demonstrate a significant tendency towards less frequent and severe droughts in Northern Europe and Russia, especially in winter and spring; oppositely, an increasing trend is visible in Southern Europe, mainly in spring and summer. According to the SPEI analysis (precipitation and temperature driven) Northern Europe shows wetting patterns, while Southern and Eastern Europe show a more remarkable drying tendency, especially in summer and autumn for drought frequency and in every season for drought severity. The evolution towards drier conditions is more relevant from 1981 onwards, both in terms of frequency and severity. This is especially true for Central Europe in spring, for the Mediterranean in summer, and for Eastern Europe in autumn. Extreme events follow similar patterns, but in autumn no spatially coherent trend can be found.

  6. Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

    Science.gov (United States)

    Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

    2016-06-01

    For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  7. ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

    Directory of Open Access Journals (Sweden)

    S. Busch

    2016-06-01

    Full Text Available For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  8. Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia.

    Science.gov (United States)

    Low, Gary K K; Papapreponis, Panayoti; Isa, Ridzuan M; Gan, Seng Chiew; Chee, Hui Yee; Te, Kian Keong; Hatta, Nadia M

    2018-05-07

    Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia's leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds.

  9. Spatio-temporal distribution patterns of the epibenthic community in the coastal waters of Suriname

    Science.gov (United States)

    Willems, Tomas; De Backer, Annelies; Wan Tong You, Kenneth; Vincx, Magda; Hostens, Kris

    2015-10-01

    This study aimed to characterize the spatio-temporal patterns of the epibenthic community in the coastal waters of Suriname. Data were collected on a (bi)monthly basis in 2012-2013 at 15 locations in the shallow (turbid-water zone (6-20 m depth), dominated by Atlantic seabob shrimp Xiphopenaeus kroyeri (Crustacea: Penaeoidea). Near the 30 m isobath, sediments were much coarser (median grain size on average 345±103 μm vs. 128±53 μm in the coastal assemblage) and water transparency was much higher (on average 7.6±3.5 m vs. 2.4±2.1 m in the coastal assemblage). In this zone, a diverse offshore assemblage was found, characterized by brittle stars (mainly Ophioderma brevispina and Ophiolepis elegans) and a variety of crabs, sea stars and hermit crabs. In between both zones, a transition assemblage was noted, with epibenthic species typically found in either the coastal or offshore assemblages, but mainly characterized by the absence of X. kroyeri. Although the epibenthic community was primarily structured in an on-offshore gradient related to depth, sediment grain size and sediment total organic carbon content, a longitudinal (west-east) gradient was apparent as well. The zones in the eastern part of the Suriname coastal shelf seemed to be more widely stretched along the on-offshore gradient. Although clear seasonal differences were noted in the environmental characteristics (e.g. dry vs. rainy season), this was not reflected in the epibenthic community structure. X. kroyeri reached very high densities (up to 1383 ind 1000 m-²) in the shallow coastal waters of Suriname. As X. kroyeri is increasingly exploited throughout its range, the current study provides the ecological context for its presence and abundance, which is crucial for an ecosystem approach and the sustainable management of this commercially important species and its habitat.

  10. Wildlife in the Matrix: Spatio-Temporal Patterns of Herbivore Occurrence in Karnataka, India

    Science.gov (United States)

    Karanth, Krithi K.

    2016-01-01

    Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500 km2 landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.

  11. Modeling and Statistical Analysis of the Spatio-Temporal Patterns of Seasonal Influenza in Israel

    Science.gov (United States)

    Katriel, Guy; Yaari, Rami; Roll, Uri; Stone, Lewi

    2012-01-01

    Background Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998–2009. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters. Findings Despite the biological complexity of the disease we found that a simple SIR-type model can be fitted successfully to the seasonal influenza data. This was true at both the national levels and at the scale of single cities.The effective reproductive number Re varies between the different years both nationally and among Israeli cities. However, we did not find differences in Re between different Israeli cities within a year. R e was positively correlated to the strength of the spatial synchronization in Israel. For those years in which the disease was more “infectious”, then outbreaks in different cities tended to occur with smaller time lags. Our spatial analysis demonstrates that both the timing and the strength of the outbreak within a year are highly synchronized between the Israeli cities. We extend the spatial analysis to demonstrate the existence of high synchrony between Israeli and French influenza outbreaks. Conclusions The data analysis combined with mathematical modeling provided a better understanding of the spatio-temporal and synchronization dynamics of influenza in Israel and between Israel and France. Altogether, we show that despite major differences in demography and weather conditions intra-annual influenza epidemics are tightly synchronized in both their timing and magnitude, while they may vary greatly between years. The predominance of

  12. An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972-2011) and Incidence (1995-2008) in Taiwan.

    Science.gov (United States)

    Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

    2016-05-01

    Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972-2011) and incidence (1995-2008) in Taiwan.Two sets of color maps were made based on "age-adjusted mortality by rate" and "age-adjusted mortality by rank." AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008.The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment.This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan.

  13. Analyzing Local Spatio-Temporal Patterns of Police Calls-for-Service Using Bayesian Integrated Nested Laplace Approximation

    Directory of Open Access Journals (Sweden)

    Hui Luan

    2016-09-01

    Full Text Available This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA. Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, and space-time interaction (i.e., unusual departures from overall spatial and temporal patterns were estimated. Temporally, calls-for-service were found to be lowest in the early morning (02:00–03:59 and highest in the evening (20:00–21:59, while high levels of calls-for-service were spatially located in central business areas and in areas characterized by major roadways, universities, and shopping centres. Space-time interaction was observed to be geographically dispersed during daytime hours but concentrated in central business areas during evening hours. Interpreted through the routine activity theory, results are discussed with respect to law enforcement resource demand and allocation, and the advantages of modeling spatio-temporal datasets with Bayesian INLA methods are highlighted.

  14. Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

    Science.gov (United States)

    Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

    2009-12-01

    The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

  15. Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

    2012-04-01

    Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

  16. Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

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    Pietro Quaglio

    2017-05-01

    Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

  17. A Comparison of Spatio-Temporal Disease Mapping Approaches Including an Application to Ischaemic Heart Disease in New South Wales, Australia

    Directory of Open Access Journals (Sweden)

    Craig Anderson

    2017-02-01

    Full Text Available The field of spatio-temporal modelling has witnessed a recent surge as a result of developments in computational power and increased data collection. These developments allow analysts to model the evolution of health outcomes in both space and time simultaneously. This paper models the trends in ischaemic heart disease (IHD in New South Wales, Australia over an eight-year period between 2006 and 2013. A number of spatio-temporal models are considered, and we propose a novel method for determining the goodness-of-fit for these models by outlining a spatio-temporal extension of the Moran’s I statistic. We identify an overall decrease in the rates of IHD, but note that the extent of this health improvement varies across the state. In particular, we identified a number of remote areas in the north and west of the state where the risk stayed constant or even increased slightly.

  18. A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters.

    Science.gov (United States)

    Adin, A; Lee, D; Goicoa, T; Ugarte, María Dolores

    2018-01-01

    Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.

  19. Bifurcation analysis and spatio-temporal patterns of nonlinear oscillations in a delayed neural network with unidirectional coupling

    International Nuclear Information System (INIS)

    Song Yongli; Tadé, Moses O; Zhang Tonghua

    2009-01-01

    In this paper, a delayed neural network with unidirectional coupling is considered which consists of two two-dimensional nonlinear differential equation systems with exponential decay where one system receives a delayed input from the other system. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the centre manifold theorem. We also investigate the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay-differential equations combined with representation theory of Lie groups. Then the global continuation of phase-locked periodic solutions is investigated. Numerical simulations are given to illustrate the results obtained

  20. Spatio Temporal Expression Pattern of an Insecticidal Gene (cry2A in Transgenic Cotton Lines

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    Allah BAKHSH

    2012-11-01

    Full Text Available The production of transgenic plants with stable, high-level transgene expression is important for the success of crop improvement programs based on genetic engineering. The present study was conducted to evaluate genomic integration and spatio temporal expression of an insecticidal gene (cry2A in pre-existing transgenic lines of cotton. Genomic integration of cry2A was evaluated using various molecular approaches. The expression levels of cry2A were determined at vegetative and reproductive stages of cotton at regular intervals. These lines showed a stable integration of insecticidal gene in advance lines of transgenic cotton whereas gene expression was found variable with at various growth stages as well as in different plant parts throughout the season. The leaves of transgenic cotton were found to have maximum expression of cry2A gene followed by squares, bolls, anthers and petals. The protein level in fruiting part was less as compared to other parts showing inconsistency in gene expression. It was concluded that for culturing of transgenic crops, strategies should be developed to ensure the foreign genes expression efficient, consistent and in a predictable manner.

  1. Spatio-temporal expression patterns of Wnt signaling pathway during the development of temporomandibular condylar cartilage.

    Science.gov (United States)

    Chen, Kan; Quan, Huixin; Chen, Gang; Xiao, Di

    2017-11-01

    There is a growing body of evidence supporting the involvement of the Wnt signaling pathway in various aspects of skeletal and joint development; however, it is unclear whether it is involved in the process of temporomandibular joint development. In order to clarify this issue, we examined the spatio-temporal distribution of mRNAs and proteins of the Wnt family during the formation of the mandibular condylar cartilage at the prenatal and postnatal stages. An in situ hybridization test revealed no mRNAs of β-catenin and Axin2 during early mesenchymal condensation; the ligands surveyed in this study (including Wnt-4, 5a, and 9a) were clearly detected at various ranges of expression, mainly in the condylar blastema and later distinct cartilaginous layers. Apart from β-catenin and Axin2, the Wnt family members surveyed in this study, including Lef-1, were found to be immunopositive during early chondrogenesis in the condylar cartilage at E14.5. After distinct chondrocyte layers were identified within the cartilage at E16.5, the expression of the Wnt signaling members was different and mainly restricted to proliferating cells and mineralized hypertrophic chondrocytes. In the adult mandibular condylar cartilage, the Wnt-4 mRNA, as well as the Wnt-4 and Wnt-9a proteins, was not observed. Our findings demonstrated that the Wnt signaling pathway was associated with the development of mandibular condylar cartilage. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Investigating fine-scale spatio-temporal predator-prey patterns in dynamic marine ecosystems: a functional data analysis approach

    NARCIS (Netherlands)

    Embling, C.B.; Illian, J.; Armstrong, E.; van der Kooij, J.; Sharples, J.; Camphuysen, K.C.J.; Scott, B.E.

    2012-01-01

    1. Spatial management of marine ecosystems requires detailed knowledge of spatio-temporal mechanisms linking physical and biological processes. Tidal currents, the main driver of ecosystem dynamics in temperate coastal ecosystems, influence predator foraging ecology by affecting prey distribution

  3. Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

    Science.gov (United States)

    Jung, Minju; Hwang, Jungsik; Tani, Jun

    2015-01-01

    It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

  4. Spatio-temporal patterns and factors controlling the hydrogeochemistry of the river Jhelum basin, Kashmir Himalaya.

    Science.gov (United States)

    Mir, Riyaz Ahmad; Jeelani, Gh; Dar, Farooq Ahmad

    2016-07-01

    River Jhelum is a major source of water for growing population and irrigation in the Kashmir Himalaya. The region is trending towards water scarcity as well as quality deterioration stage due to its highly unregulated development. The existence of few literature on various aspects of the basin prompts us to study the spatio-temporal variability of its physicochemical parameters and thereby to understand the regulating hydrogeochemical mechanisms based on 50 samples collected during high flow (June 2008) and low flow (January 2009) periods. The water chemistry exhibited significant spatial variability reflecting the mixing processes in the basin. The seasonal effect does change the concentration of ions significantly with modest variability in the order of ionic abundance. The Ca(2+) ion among cations and HCO3 (-) ion among anions dominate the ionic budget and correlates significantly with the diverse lithology of the basin. Three major water types, i.e., Ca-Mg-HCO3 (72 %), Ca-HCO3 (12 %), and Mg-Ca-HCO3 (16 %), suggest that the chemical composition of water is dominantly controlled by carbonate lithology, besides a significant contribution from silicates. However, at certain sites, the biological processes and anthropogenic activities play a major role. Relatively, the lower ionic concentration during high flow period (summer season) suggested the significant influence of higher discharge via dilution effect. The higher discharge due to higher rainfall and snow melting in response to rising temperature in this period leads to strong flushing of human and agricultural wastes into the river. The factor analysis also reflected the dominant control of varied lithology and anthropogenic sources on the water quality based on the four significant factors explaining collectively about 70-81 % of the total data variance. A two-member chloride mixing model used to estimate the discharge contribution of tributaries to the main river channel showed reliable results. It may

  5. Numerical investigations of triggering mechanisms of shallow landslides due to heterogeneous spatio-temporal hydrological patterns.

    Science.gov (United States)

    Schwarz, Massimiliano; Cohen, Denis

    2016-04-01

    Rainfall is one of the major triggering factor of shallow landslide around the world. The increase of soil moisture in the soil influences the stability of a slope through the increase of soil bulk density, the reduction of soil apparent cohesion (due to suction stress), and the increase in pore water pressure.The spatio-temporal transformations of such properties of soil are know to be heterogeneous and under constant change. For instance, there may be a condition where, in cracked clay-soil, water, during a rain event, produces a rapid increase of pore water pressure along preferential flow-paths (crack or roots), while soil moisture and suction within the soil matrix change minimally. An another site in a sandy soil, the situation might be very different where the increase of soil moisture and pore water pressure, and the decrease of soil suction take place more or less simultaneously across the entire soil profile. In both of these cases topography plays a major role in determining the accumulation of water along the slope through different subsurface flows intensities and directions. In many documented cases in the Alps, shallow landslides may also be triggered by the punctual exfiltration of water from bedrock or weathered geological strata. The hydro-geological characteristics of the catchment control this mechanism. These different situations aim to give an idea of the large spectrum of hydrological triggering conditions of shallow landslides. The heterogeneities of these hydrological conditions represent a difficult issue in modeling shallow landslide triggering mechanisms. In the simplest models, hydrology is assumed to influence changes in pore water pressure only, mostly using one dimensional vertical infiltration models. More advanced models consider changes in apparent cohesion due to changes in soil moisture or include more complex hydrological models to simulate water flow and distribution during a rainfall event. However, most models at the

  6. Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

    Science.gov (United States)

    Huang, X.; Tan, J.

    2014-11-01

    Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G ≡ (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

  7. Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

    Science.gov (United States)

    Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

    2014-01-01

    Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  8. Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

    Science.gov (United States)

    Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

    2018-01-01

    The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

  9. Stability switches, oscillatory multistability, and spatio-temporal patterns of nonlinear oscillations in recurrently delay coupled neural networks.

    Science.gov (United States)

    Song, Yongli; Makarov, Valeri A; Velarde, Manuel G

    2009-08-01

    A model of time-delay recurrently coupled spatially segregated neural assemblies is here proposed. We show that it operates like some of the hierarchical architectures of the brain. Each assembly is a neural network with no delay in the local couplings between the units. The delay appears in the long range feedforward and feedback inter-assemblies communications. Bifurcation analysis of a simple four-units system in the autonomous case shows the richness of the dynamical behaviors in a biophysically plausible parameter region. We find oscillatory multistability, hysteresis, and stability switches of the rest state provoked by the time delay. Then we investigate the spatio-temporal patterns of bifurcating periodic solutions by using the symmetric local Hopf bifurcation theory of delay differential equations and derive the equation describing the flow on the center manifold that enables us determining the direction of Hopf bifurcations and stability of the bifurcating periodic orbits. We also discuss computational properties of the system due to the delay when an external drive of the network mimicks external sensory input.

  10. Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China.

    Directory of Open Access Journals (Sweden)

    Guanghu Zhu

    2016-04-01

    Full Text Available Dengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human mobility. The purpose of this study is to detect dengue transmission patterns and identify the disease dispersion dynamics in Guangzhou, China.We conducted surveys in 12 districts of Guangzhou, and collected daily data of Breteau index (BI and reported cases between September and November 2014 from the public health authority reports. Based on the available data and the Ross-Macdonald theory, we propose a dengue transmission model that systematically integrates entomologic, demographic, and environmental information. In this model, we use (1 BI data and geographic variables to evaluate the spatial heterogeneities of Aedes mosquitoes, (2 a radiation model to simulate the daily mobility of humans, and (3 a Markov chain Monte Carlo (MCMC method to estimate the model parameters.By implementing our proposed model, we can (1 estimate the incidence rates of dengue, and trace the infection time and locations, (2 assess risk factors and evaluate the infection threat in a city, and (3 evaluate the primary diffusion process in different districts. From the results, we can see that dengue infections exhibited a spatial and temporal variation during 2014 in Guangzhou. We find that urbanization, vector activities, and human behavior play significant roles in shaping the dengue outbreak and the patterns of its spread. This study offers useful information on dengue dynamics, which can help policy makers improve control and prevention measures.

  11. The effect of neighbourhood definitions on spatio-temporal models of disease outbreaks: Separation distance versus range overlap.

    Science.gov (United States)

    Laffan, Shawn W; Wang, Zhaoyuan; Ward, Michael P

    2011-12-01

    The definition of the spatial relatedness between infectious and susceptible animal groups is a fundamental component of spatio-temporal modelling of disease outbreaks. A common neighbourhood definition for disease spread in wild and feral animal populations is the distance between the centroids of neighbouring group home ranges. This distance can be used to define neighbourhood interactions, and also to describe the probability of successful disease transmission. Key limitations of this approach are (1) that a susceptible neighbour of an infectious group with an overlapping home range - but whose centroid lies outside the home range of an infectious group - will not be considered for disease transmission, and (2) the degree of overlap between the home ranges is not taken into account for those groups with centroids inside the infectious home range. We assessed the impact of both distance-based and range overlap methods of disease transmission on model-predicted disease spread. Range overlap was calculated using home ranges modelled as circles. We used the Sirca geographic automata model, with the population data from a nine-county study area in Texas that we have previously described. For each method we applied 100 model repetitions, each of 100 time steps, to 30 index locations. The results show that the rate of disease spread for the range-overlap method is clearly less than the distance-based method, with median outbreaks modelled using the latter being 1.4-1.45 times larger. However, the two methods show similar overall trends in the area infected, and the range-overlap median (48 and 120 for cattle and pigs, respectively) falls within the 5th-95th percentile range of the distance-based method (0-96 and 0-252 for cattle and pigs, respectively). These differences can be attributed to the calculation of the interaction probabilities in the two methods, with overlap weights generally resulting in lower interaction probabilities. The definition of spatial

  12. Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period.

    Science.gov (United States)

    Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

    2016-03-01

    Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter-gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter-gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC-800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. © 2016 The Author(s).

  13. Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

    Directory of Open Access Journals (Sweden)

    Taiye Oluwafemi Adewuyi

    2017-12-01

    Full Text Available This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote sensing and Global Positioning Systems (GPS for spatial data. Questionnaires were administered for other attribute information required. The analysis carried out in a Geographic Information System (GIS environment especially for mapping and the establishment of spatial patterns.  The results indicated that the main types of crime committed were theft and house breaking (42.9%, followed by assault (12.4%, mischief (11.3%, forgery (10.5%, car snatching (9.05%, armed robbery (8.5%, trespass (5.2% and culpable homicide (0.2%. In terms of hot spots the districts recorded the following: Garki (27.62%, Maitama (25.7%, Utako (24.3%, Wuse (20.9% and Asokoro district (1.4% respectively with most of the crime committed during the day time. Many attributed the crimes to mainly high rate of unemployment and poverty (79.1%. Consequently to reduce the crime rate, the socio-economic situation of the city must be improved through properly constructed interventions scheme in areas known to quickly generate employment such as agriculture, small and medium scale enterprises, mining and tourism.

  14. Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

    Science.gov (United States)

    J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

    2012-01-01

    Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

  15. Training spiking neural networks to associate spatio-temporal input-output spike patterns

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2013-01-01

    In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

  16. Data Integration for Spatio-Temporal Patterns of Gene Expression of Zebrafish development: the GEMS database

    Directory of Open Access Journals (Sweden)

    Belmamoune Mounia

    2008-06-01

    Full Text Available The Gene Expression Management System (GEMS is a database system for patterns of gene expression. These patterns result from systematic whole-mount fluorescent in situ hybridization studies on zebrafish embryos. GEMS is an integrative platform that addresses one of the important challenges of developmental biology: how to integrate genetic data that underpin morphological changes during embryogenesis. Our motivation to build this system was by the need to be able to organize and compare multiple patterns of gene expression at tissue level. Integration with other developmental and biomolecular databases will further support our understanding of development. The GEMS operates in concert with a database containing a digital atlas of zebrafish embryo; this digital atlas of zebrafish development has been conceived prior to the expansion of the GEMS. The atlas contains 3D volume models of canonical stages of zebrafish development in which in each volume model element is annotated with an anatomical term. These terms are extracted from a formal anatomical ontology, i.e. the Developmental Anatomy Ontology of Zebrafish (DAOZ. In the GEMS, anatomical terms from this ontology together with terms from the Gene Ontology (GO are also used to annotate patterns of gene expression and in this manner providing mechanisms for integration and retrieval . The annotations are the glue for integration of patterns of gene expression in GEMS as well as in other biomolecular databases. At the one hand, zebrafish anatomy terminology allows gene expression data within GEMS to be integrated with phenotypical data in the 3D atlas of zebrafish development. At the other hand, GO terms extend GEMS expression patterns integration to a wide range of bioinformatics resources.

  17. Spatio-temporal patterns and predictions of phytoplankton assemblages in a subtropical river delta system

    DEFF Research Database (Denmark)

    Wang, Chao; Li, Xinhui; Wang, Xiangxiu

    2016-01-01

    Spatial and seasonal sampling within a subtropical river delta system, the Pearl River Delta (China), provided data to determine seasonal phytoplankton patterns and develop prediction models. The high nutrient levels and frequent water exchanges resulted in a phytoplankton community with greatest...

  18. Spatio-temporal growth pattern and patronage level of airline travel ...

    African Journals Online (AJOL)

    This study assesses the growth pattern of airline travel agencies over a period of forty years across locations in Nigeria as well as the patronage level of agency business. The need for the study arises because of the technological marketing of airline tickets through direct online ticket sales that aims at reducing cost by ...

  19. The spatio-temporal dynamic pattern of rural domestic solid waste discharge of China and its challenges.

    Science.gov (United States)

    Tian, Guangjin; Kong, Lingqiang; Liu, Xiaojuan; Yuan, Wenping

    2018-04-01

    At present, construction of rural domestic waste treatment facilities is seriously lagging, and in many cases, treatment facilities do not yet exist in some villages of China. Serious rural waste pollution has not only impacted the quality of surface water and groundwater but also the atmosphere and the living environment of farmers of China. There are relatively few studies of rural domestic waste pollution, especially with respect to the spatio-temporal dynamic pattern of rural domestic waste discharge. Using survey data and income per capita, we calculated rural domestic waste discharge per capita per day. From this, we calculated provincial rural domestic waste discharge. According to our study, rural domestic waste discharge was 1.42 × 10 8 t/year in 2000. This number increased to 2.3 × 10 8 t/year in 2006 and to 2.47 × 10 8 t/year in 2010. Rural domestic waste increased dramatically while the actual rural population and the proportion of the rural population declined. When examining the eight regions, the rural domestic waste discharge of northeastern China, Qinghai-Tibet, middle China, and southwestern China had increased dramatically, while that of northern China, southern China, and eastern China increased relatively slowly. The economies of northern China, southern China, and eastern China are more developed; their rural domestic waste discharge has been high since 2000 and has continued to increase slowly. In northeastern China, Qinghai-Tibet, middle China, and southwestern China, rural domestic waste discharge was low in 2000; however, in the ten-year period from 2000 to 2010, their rural domestic waste discharge increased dramatically.

  20. Climate change and human infectious diseases: A synthesis of research findings from global and spatio-temporal perspectives.

    Science.gov (United States)

    Liang, Lu; Gong, Peng

    2017-06-01

    The life cycles and transmission of most infectious agents are inextricably linked with climate. In spite of a growing level of interest and progress in determining climate change effects on infectious disease, the debate on the potential health outcomes remains polarizing, which is partly attributable to the varying effects of climate change, different types of pathogen-host systems, and spatio-temporal scales. We summarize the published evidence and show that over the past few decades, the reported negative or uncertain responses of infectious diseases to climate change has been growing. A feature of the research tendency is the focus on temperature and insect-borne diseases at the local and decadal scale. Geographically, regions experiencing higher temperature anomalies have been given more research attention; unfortunately, the Earth's most vulnerable regions to climate variability and extreme events have been less studied. From local to global scales, agreements on the response of infectious diseases to climate change tend to converge. So far, an abundance of findings have been based on statistical methods, with the number of mechanistic studies slowly growing. Research gaps and trends identified in this study should be addressed in the future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Beach-dune dynamics: Spatio-temporal patterns of aeolian sediment transport under complex offshore airflow

    Science.gov (United States)

    Lynch, K.; Jackson, D.; Delgado-Fernandez, I.; Cooper, J. A.; Baas, A. C.; Beyers, M.

    2010-12-01

    This study examines sand transport and wind speed across a beach at Magilligan Strand, Northern Ireland, under offshore wind conditions. Traditionally the offshore component of local wind regimes has been ignored when quantifying beach-dune sediment budgets, with the sheltering effect of the foredune assumed to prohibit grain entrainment on the adjoining beach. Recent investigations of secondary airflow patterns over coastal dunes have suggested this may not be the case, that the turbulent nature of the airflow in these zones enhances sediment transport potential. Beach sediment may be delivered to the dune toe by re-circulating eddies under offshore winds in coastal areas, which may explain much of the dynamics of aeolian dunes on coasts where the dominant wind direction is offshore. The present study investigated aeolian sediment transport patterns under an offshore wind event. Empirical data were collected using load cell traps, for aeolian sediment transport, co-located with 3-D ultrasonic anemometers. The instrument positioning on the sub-aerial beach was informed by prior analysis of the airflow patterns using computational fluid dynamics. The array covered a total beach area of 90 m alongshore by 65 m cross-shore from the dune crest. Results confirm that sediment transport occurred in the ‘sheltered’ area under offshore winds. Over short time and space scales the nature of the transport is highly complex; however, preferential zones for sand entrainment may be identified. Alongshore spatial heterogeneity of sediment transport seems to show a relationship to undulations in the dune crest, while temporal and spatial variations may also be related to the position of the airflow reattachment zone. These results highlight the important feedbacks between flow characteristics and transport in a complex three dimensional surface.

  2. Spatio-temporal patterns in the north-western Mediterranean from MERIS derived chlorophyll a concentration

    Directory of Open Access Journals (Sweden)

    Ana Gordoa

    2008-12-01

    Full Text Available We address the major surface signatures of chlorophyll a in the Catalan Sea within the context of the dynamics of the north-western Mediterranean basin. Monthly composites from MERIS measurements and CHL products for Case 1 waters were analysed from June 2002 to June 2005. Composite images of variability were used to identify surface dynamics. The results showed that coastal and open sea waters were separated by a belt of low variability, a permanent oligotrophic belt that is noticeable with respect to the bloom conditions of the surrounding areas. The width of this Catalan Oligotrophic Belt (COB located along the continental slope, varied between 17 and 30 km and became blurred in the southernmost area. The chlorophyll a temporal pattern over the shelf showed an almost steady increase from September to March. A similar behaviour but with lower concentrations was observed in oceanic waters. Both temporal patterns showed a disruption during January and/or February that coincided with the well known deep water formation event in the Gulf of Lions. In 2004, the convection was weaker and the offshore temporal trend was not disrupted; however, the opposite was observed in 2005. The spatial chlorophyll a distribution of oceanic waters presented a clear north-south decreasing trend, while the coastal distribution did not show any latitudinal patterns but rather peaks in the areas enriched by river runoff. The observed seasonality was similar to the one published from SeaWiFS data and slightly different from the seasonality shown by CZCS data. Nevertheless, we did not discard the possibility that some of the observed seasonal differences could be a true temporal shift in chlorophyll a production.

  3. Characterizing the Spatio-Temporal Pattern of Land Surface Temperature through Time Series Clustering: Based on the Latent Pattern and Morphology

    Directory of Open Access Journals (Sweden)

    Huimin Liu

    2018-04-01

    Full Text Available Land Surface Temperature (LST is a critical component to understand the impact of urbanization on the urban thermal environment. Previous studies were inclined to apply only one snapshot to analyze the pattern and dynamics of LST without considering the non-stationarity in the temporal domain, or focus on the diurnal, seasonal, and annual pattern analysis of LST which has limited support for the understanding of how LST varies with the advancing of urbanization. This paper presents a workflow to extract the spatio-temporal pattern of LST through time series clustering by focusing on the LST of Wuhan, China, from 2002 to 2017 with a 3-year time interval with 8-day MODerate-resolution Imaging Spectroradiometer (MODIS satellite image products. The Latent pattern of LST (LLST generated by non-parametric Multi-Task Gaussian Process Modeling (MTGP and the Multi-Scale Shape Index (MSSI which characterizes the morphology of LLST are coupled for pattern recognition. Specifically, spatio-temporal patterns are discovered after the extraction of spatial patterns conducted by the incorporation of k -means and the Back-Propagation neural networks (BP-Net. The spatial patterns of the 6 years form a basic understanding about the corresponding temporal variances. For spatio-temporal pattern recognition, LLSTs and MSSIs of the 6 years are regarded as geo-referenced time series. Multiple algorithms including traditional k -means with Euclidean Distance (ED, shape-based k -means with the constrained Dynamic Time Warping ( c DTW distance measure, and the Dynamic Time Warping Barycenter Averaging (DBA centroid computation method ( k - c DBA and k -shape are applied. Ten external indexes are employed to evaluate the performance of the three algorithms and reveal k - c DBA as the optimal time series clustering algorithm for our study. The study area is divided into 17 geographical time series clusters which respectively illustrate heterogeneous temporal dynamics of LST

  4. Spatio-temporal epidemiology of human West Nile virus disease in South Dakota.

    Science.gov (United States)

    Wimberly, Michael C; Giacomo, Paolla; Kightlinger, Lon; Hildreth, Michael B

    2013-10-29

    Despite a cold temperate climate and low human population density, the Northern Great Plains has become a persistent hot spot for human West Nile virus (WNV) disease in North America. Understanding the spatial and temporal patterns of WNV can provide insights into the epidemiological and ecological factors that influence disease emergence and persistence. We analyzed the 1,962 cases of human WNV disease that occurred in South Dakota from 2002-2012 to identify the geographic distribution, seasonal cycles, and interannual variability of disease risk. The geographic and seasonal patterns of WNV have changed since the invasion and initial epidemic in 2002-2003, with cases shifting toward the eastern portion of South Dakota and occurring earlier in the transmission season in more recent years. WNV cases were temporally autocorrelated at lags of up to six weeks and early season cumulative case numbers were correlated with seasonal totals, indicating the possibility of using these data for short-term early detection of outbreaks. Epidemiological data are likely to be most effective for early warning of WNV virus outbreaks if they are integrated with entomological surveillance and environmental monitoring to leverage the strengths and minimize the weaknesses of each information source.

  5. Spatio-temporal patterns of ptarmigan occupancy relative to shrub cover in the Arctic

    Science.gov (United States)

    Schmutz, Joel A.

    2014-01-01

    Rock and willow ptarmigan are abundant herbivores that require shrub habitats in arctic and alpine areas. Shrub expansion is likely to increase winter habitat availability for ptarmigan, which in turn influence shrub architecture and growth through browsing. Despite their ecological role in the Arctic, the distribution and movement patterns of ptarmigan are not well known, particularly in northern Alaska where shrub expansion is occurring. We used multi-season occupancy models to test whether ptarmigan occupancy varied within and among years, and the degree to which colonization and extinction probabilities were related to shrub cover and latitude. Aerial surveys were conducted from March to May in 2011 and April to May 2012 in a 21,230 km2 area in northeastern Alaska. In areas with at least 30 % shrub cover, the probability of colonization by ptarmigan was >0.90, indicating that moderate to extensive patches of shrubs (typically associated with riparian areas) had a high probability of becoming occupied by ptarmigan. Occupancy increased throughout the spring in both years, providing evidence that ptarmigan migrated from southern wintering areas to breeding areas north of the Brooks Range. Occupancy was higher in the moderate snow year than the high snow year, and this was likely due to higher shrub cover in the moderate snow year. Ptarmigan distribution and migration in the Arctic are linked to expanding shrub communities on a wide geographic scale, and these relationships may be shaping ptarmigan population dynamics, as well as rates and patterns of shrub expansion.

  6. Spatio-Temporal Patterns of the International Merger and Acquisition Network.

    Science.gov (United States)

    Dueñas, Marco; Mastrandrea, Rossana; Barigozzi, Matteo; Fagiolo, Giorgio

    2017-09-07

    This paper analyses the world web of mergers and acquisitions (M&As) using a complex network approach. We use data of M&As to build a temporal sequence of binary and weighted-directed networks for the period 1995-2010 and 224 countries (nodes) connected according to their M&As flows (links). We study different geographical and temporal aspects of the international M&A network (IMAN), building sequences of filtered sub-networks whose links belong to specific intervals of distance or time. Given that M&As and trade are complementary ways of reaching foreign markets, we perform our analysis using statistics employed for the study of the international trade network (ITN), highlighting the similarities and differences between the ITN and the IMAN. In contrast to the ITN, the IMAN is a low density network characterized by a persistent giant component with many external nodes and low reciprocity. Clustering patterns are very heterogeneous and dynamic. High-income economies are the main acquirers and are characterized by high connectivity, implying that most countries are targets of a few acquirers. Like in the ITN, geographical distance strongly impacts the structure of the IMAN: link-weights and node degrees have a non-linear relation with distance, and an assortative pattern is present at short distances.

  7. Quantum noise and spatio-temporal pattern formation in nonlinear optics

    DEFF Research Database (Denmark)

    Bache, Morten

    2002-01-01

    a nondegenerate parametric oscillation. We find that this model may completely stabilize the instabilities normally expected in SHG, but it may also give rise to entirely new phenomena, such as oscillating cavity solitons, intensity spirals and self-pulsing solutions. Especially the self-pulsing is important...... rise to spatially modulated structures, patterns. The two main parts of the thesis are the classical model and the quantum mechanical model, the latter being an extension of the former by including the inherent quantum fluctuations of light. From a theoretical point of view the classical dynamics...... are investigated with an experimental implementation in mind. Thus, we study the internally pumped optical parametric oscillator (IPOPO) as an experimentally more realistic model than the usual SHG model. In the IPOPO a competing process to SHG is taken into account, where the generated second harmonic drives...

  8. Spatio-Temporal Expression Patterns of Arabidopsis thaliana and Medicago truncatula Defensin-Like Genes

    Science.gov (United States)

    Nallu, Sumitha; Wang, Lin; Botanga, Christopher J.; Gomez, S. Karen; Costa, Liliana M.; Harrison, Maria J.; Samac, Deborah A.; Glazebrook, Jane; Katagiri, Fumiaki; Gutierrez-Marcos, Jose F.; VandenBosch, Kathryn A.

    2013-01-01

    Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species. PMID:23527067

  9. Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.

    Directory of Open Access Journals (Sweden)

    Marie Morfin

    Full Text Available This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea. To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.

  10. Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes.

    Directory of Open Access Journals (Sweden)

    Mesfin Tesfaye

    Full Text Available Plant genomes contain several hundred defensin-like (DEFL genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species.

  11. Landscape analysis of urban growth patterns in Seremban, Malaysia, using spatio-temporal data

    Science.gov (United States)

    Aburas, Maher M.; Abdullah, Sabrina H.; Ramli, Mohammad F.; As'shari, Zulfa H.

    2016-06-01

    Urban growth is one of the major issues that have played a significant role in destroying the ecosystem in recent years. Landscape analysis is an important technique widely used to evaluate urban growth patterns. In this study, four land-use maps from 1984, 1990, 2000, and 2010 have been used to analyze an urban landscape. The values of a built-up area were initially computed using a geographic information system environment based on the spatial gradient approach. Mathematical matrices were then used to determine the amount of change in urban patches in each direction. Results of the number of patches, landscape shape index, aggregation index, and total edges confirmed that the urban patches in Seremban, Malaysia, have become more dispersed from 2000 to 2010. The urban patches have also become more continuous, especially in the north-western part of Seremban as a result of the urban development in the Nilai District. These results indicate the necessity to create new policies in the city to protect the sustainability of the land use of Seremban.

  12. Spatio-temporal pattern of vestibular information processing after brief caloric stimulation

    International Nuclear Information System (INIS)

    Marcelli, Vincenzo; Esposito, Fabrizio; Aragri, Adriana; Furia, Teresa; Riccardi, Pasquale; Tosetti, Michela; Biagi, Laura; Marciano, Elio; Di Salle, Francesco

    2009-01-01

    Processing of vestibular information at the cortical and subcortical level is essential for head and body orientation in space and self-motion perception, but little is known about the neural dynamics of the brain regions of the vestibular system involved in this task. Neuroimaging studies using both galvanic and caloric stimulation have shown that several distinct cortical and subcortical structures can be activated during vestibular information processing. The insular cortex has been often targeted and presented as the central hub of the vestibular cortical system. Since very short pulses of cold water ear irrigation can generate a strong and prolonged vestibular response and a nystagmus, we explored the effects of this type of caloric stimulation for assessing the blood-oxygen-level-dependent (BOLD) dynamics of neural vestibular processing in a whole-brain event-related functional magnetic resonance imaging (fMRI) experiment. We evaluated the spatial layout and the temporal dynamics of the activated cortical and subcortical regions in time-locking with the instant of injection and were able to extract a robust pattern of neural activity involving the contra-lateral insular cortex, the thalamus, the brainstem and the cerebellum. No significant correlation with the temporal envelope of the nystagmus was found. The temporal analysis of the activation profiles highlighted a significantly longer duration of the evoked BOLD activity in the brainstem compared to the insular cortex suggesting a functional de-coupling between cortical and subcortical activity during the vestibular response.

  13. Efficient Spatio-Temporal Local Binary Patterns for Spontaneous Facial Micro-Expression Recognition

    Science.gov (United States)

    Wang, Yandan; See, John; Phan, Raphael C.-W.; Oh, Yee-Hui

    2015-01-01

    Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effort has gone into the creation of these datasets for research purposes. There are currently two publicly available spontaneous micro-expression datasets—SMIC and CASME II, both with baseline results released using the widely used dynamic texture descriptor LBP-TOP for feature extraction. Although LBP-TOP is popular and widely used, it is still not compact enough. In this paper, we draw further inspiration from the concept of LBP-TOP that considers three orthogonal planes by proposing two efficient approaches for feature extraction. The compact robust form described by the proposed LBP-Six Intersection Points (SIP) and a super-compact LBP-Three Mean Orthogonal Planes (MOP) not only preserves the essential patterns, but also reduces the redundancy that affects the discriminality of the encoded features. Through a comprehensive set of experiments, we demonstrate the strengths of our approaches in terms of recognition accuracy and efficiency. PMID:25993498

  14. Spatio-Temporal Distribution and Hotspots of Hand, Foot and Mouth Disease (HFMD in Northern Thailand

    Directory of Open Access Journals (Sweden)

    Ratchaphon Samphutthanon

    2013-12-01

    Full Text Available Hand, Foot and Mouth Disease (HFMD is an emerging viral disease, and at present, there are no antiviral drugs or vaccines available to control it. Outbreaks have persisted for the past 10 years, particularly in northern Thailand. This study aimed to elucidate the phenomenon of HFMD outbreaks from 2003 to 2012 using general statistics and spatial-temporal analysis employing a GIS-based method. The spatial analysis examined data at the village level to create a map representing the distribution pattern, mean center, standard deviation ellipse and hotspots for each outbreak. A temporal analysis was used to analyze the correlation between monthly case data and meteorological factors. The results indicate that the disease can occur at any time of the year, but appears to peak in the rainy and cold seasons. The distribution of outbreaks exhibited a clustered pattern. Most mean centers and standard deviation ellipses occurred in similar areas. The linear directional mean values of the outbreaks were oriented toward the south. When separated by season, it was found that there was a significant correlation with the direction of the southwest monsoon at the same time. An autocorrelation analysis revealed that hotspots tended to increase even when patient cases subsided. In particular, a new hotspot was found in the recent year in Mae Hong Son province.

  15. Spatio-temporal migration patterns of Pacific salmon smolts in rivers and coastal marine waters.

    Directory of Open Access Journals (Sweden)

    Michael C Melnychuk

    Full Text Available BACKGROUND: Migrations allow animals to find food resources, rearing habitats, or mates, but often impose considerable predation risk. Several behavioural strategies may reduce this risk, including faster travel speed and taking routes with shorter total distance. Descriptions of the natural range of variation in migration strategies among individuals and populations is necessary before the ecological consequences of such variation can be established. METHODOLOGY/PRINCIPAL FINDINGS: Movements of tagged juvenile coho, steelhead, sockeye, and Chinook salmon were quantified using a large-scale acoustic tracking array in southern British Columbia, Canada. Smolts from 13 watersheds (49 watershed/species/year combinations were tagged between 2004-2008 and combined into a mixed-effects model analysis of travel speed. During the downstream migration, steelhead were slower on average than other species, possibly related to freshwater residualization. During the migration through the Strait of Georgia, coho were slower than steelhead and sockeye, likely related to some degree of inshore summer residency. Hatchery-reared smolts were slower than wild smolts during the downstream migration, but after ocean entry, average speeds were similar. In small rivers, downstream travel speed increased with body length, but in the larger Fraser River and during the coastal migration, average speed was independent of body length. Smolts leaving rivers located towards the northern end of the Strait of Georgia ecosystem migrated strictly northwards after ocean entry, but those from rivers towards the southern end displayed split-route migration patterns within populations, with some moving southward. CONCLUSIONS/SIGNIFICANCE: Our results reveal a tremendous diversity of behavioural migration strategies used by juvenile salmon, across species, rearing histories, and habitats, as well as within individual populations. During the downstream migration, factors that had strong

  16. Spatio-temporal patterns of distribution of West Nile virus vectors in eastern Piedmont Region, Italy

    Directory of Open Access Journals (Sweden)

    Bisanzio Donal

    2011-12-01

    Full Text Available Abstract Background West Nile Virus (WNV transmission in Italy was first reported in 1998 as an equine outbreak near the swamps of Padule di Fucecchio, Tuscany. No other cases were identified during the following decade until 2008, when horse and human outbreaks were reported in Emilia Romagna, North Italy. Since then, WNV outbreaks have occurred annually, spreading from their initial northern foci throughout the country. Following the outbreak in 1998 the Italian public health authority defined a surveillance plan to detect WNV circulation in birds, horses and mosquitoes. By applying spatial statistical analysis (spatial point pattern analysis and models (Bayesian GLMM models to a longitudinal dataset on the abundance of the three putative WNV vectors [Ochlerotatus caspius (Pallas 1771, Culex pipiens (Linnaeus 1758 and Culex modestus (Ficalbi 1890] in eastern Piedmont, we quantified their abundance and distribution in space and time and generated prediction maps outlining the areas with the highest vector productivity and potential for WNV introduction and amplification. Results The highest abundance and significant spatial clusters of Oc. caspius and Cx. modestus were in proximity to rice fields, and for Cx. pipiens, in proximity to highly populated urban areas. The GLMM model showed the importance of weather conditions and environmental factors in predicting mosquito abundance. Distance from the preferential breeding sites and elevation were negatively associated with the number of collected mosquitoes. The Normalized Difference Vegetation Index (NDVI was positively correlated with mosquito abundance in rice fields (Oc. caspius and Cx. modestus. Based on the best models, we developed prediction maps for the year 2010 outlining the areas where high abundance of vectors could favour the introduction and amplification of WNV. Conclusions Our findings provide useful information for surveillance activities aiming to identify locations where the

  17. Coupled Spatio-Temporal Patterns of Solute Transport, Metabolism and Nutrient Uptake in Streams

    Science.gov (United States)

    Kurz, M. J.; Schmidt, C.

    2017-12-01

    Slower flow velocities and longer residence times within stream transient storage (TS) zones facilitate interaction between solutes and microbial communities, potentially increasing local rates of metabolic activity. Multiple factors, including channel morphology and substrate, variable hydrology, and seasonal changes in biological and physical parameters, result in changes in the solute transport dynamics and reactivity of TS zones over time and space. These changes would be expected to, in turn, influence rates of whole-stream ecosystem functions such as metabolism and nutrient uptake. However, the linkages between solute transport and ecosystem functioning within TS zones, and the contribution of TS zones to whole-stream functioning, are not always so straight forward. This may be due, in part, to methodological challenges. In this study we investigated the influence of stream channel hydro-morphology and substrate type on reach (103 m) and sub-reach (102 m) scale TS and ecosystem functioning. Patterns in solute transport, metabolism and nitrate uptake were tracked from April through October in two contrasting upland streams using several methods. The two streams, located in the Harz Mountains, Germany, are characterized by differing size (0.02 vs. 0.3 m3/s), dominant stream channel substrate (bedrock vs. alluvium) and sub-reach morphology (predominance of pools, riffles and glides). Solute transport parameters and respiration rates at the reach and sub-reach scale were estimated monthly from coupled pulse injections of the reactive tracer resazurin (Raz) and conservative tracers uranine and salt. Raz, a weakly fluorescent dye, irreversibly transforms to resorufin (Rru) under mildly reducing conditions, providing a proxy for aerobic respiration. Daily rates of primary productivity, respiration and nitrate retention at the reach scale were estimated using the diel cycles in dissolved oxygen and nitrate concentrations measured by in-situ sensors. Preliminary

  18. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

    Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....

  19. Satellite-Derived Photic Depth on the Great Barrier Reef: Spatio-Temporal Patterns of Water Clarity

    Directory of Open Access Journals (Sweden)

    Scarla Weeks

    2012-11-01

    Full Text Available Detecting changes to the transparency of the water column is critical for understanding the responses of marine organisms, such as corals, to light availability. Long-term patterns in water transparency determine geographical and depth distributions, while acute reductions cause short-term stress, potentially mortality and may increase the organisms’ vulnerability to other environmental stressors. Here, we investigated the optimal, operational algorithm for light attenuation through the water column across the scale of the Great Barrier Reef (GBR, Australia. We implemented and tested a quasi-analytical algorithm to determine the photic depth in GBR waters and matched regional Secchi depth (ZSD data to MODIS-Aqua (2002–2010 and SeaWiFS (1997–2010 satellite data. The results of the in situ ZSD/satellite data matchup showed a simple bias offset between the in situ and satellite retrievals. Using a Type II linear regression of log-transformed satellite and in situ data, we estimated ZSD and implemented the validated ZSD algorithm to generate a decadal satellite time series (2002–2012 for the GBR. Water clarity varied significantly in space and time. Seasonal effects were distinct, with lower values during the austral summer, most likely due to river runoff and increased vertical mixing, and a decline in water clarity between 2008–2012, reflecting a prevailing La Niña weather pattern. The decline in water clarity was most pronounced in the inshore area, where a significant decrease in mean inner shelf ZSD of 2.1 m (from 8.3 m to 6.2 m occurred over the decade. Empirical Orthogonal Function Analysis determined the dominance of Mode 1 (51.3%, with the greatest variation in water clarity along the mid-shelf, reflecting the strong influence of oceanic intrusions on the spatio-temporal patterns of water clarity. The newly developed photic depth product has many potential applications for the GBR from water quality monitoring to analyses of

  20. Second-order analysis of structured inhomogeneous spatio-temporal point processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....

  1. Spatio-temporal patterns of mass fluxes of micropollutants in Swiss rivers of catchments with different land use

    Science.gov (United States)

    Stamm, Christian; van der Voet, Jürgen; Singer, Heinz

    2010-05-01

    lakes, where it has a residence time of several weeks, while it flows through the river system within a few days. This example illustrates how compound properties, season and spatial location may interact and control the occurrence of micropollutants in a stream. The spatial nesting of study catchments made it possible to check the data for plausibility and consistency: we present data on cumulative mass balances downstream and test whether the load development along the river network corresponds to the spatial distribution of possible compound sources (e.g., acreage of arable fields, number of inhabitants etc.). Overall, the data show that monitoring of micropollutants may be achieved even without changing an existing monitoring programme. However, given the generally low concentrations in the composite samples of the NADUF programme compounds with lower use and/or lower stability may fall below the limit of reliable quantification or even detection. A proper interpretation of the data relies on additional (spatio-temporal) information like land use data or precipitation patterns.

  2. Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

    Science.gov (United States)

    Qin, Y.; Xiao, X.; Dong, J.

    2016-12-01

    Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

  3. Spatio-temporal modeling for residential burglary

    NARCIS (Netherlands)

    Mahfoud, M.; Bhulai, Sandjai; van der Mei, R.D.; Bhulai, Sandjai; Kardaras, Dimitris

    2017-01-01

    Spatio-temporal modeling is widely recognized as a promising means for predicting crime patterns. Despite their enormous potential, the available methods are still in their infancy. A lot of research focuses on crime hotspot detection and geographic crime clusters, while a systematic approach to

  4. Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

    Full Text Available Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER], and socio-economic conditions (US Census Bureau were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases.

  5. Schistosoma japonicum risk in Jiangsu province, People’s Republic of China: identification of a spatio-temporal risk pattern along the Yangtze River

    Directory of Open Access Journals (Sweden)

    Kun Yang

    2013-11-01

    Full Text Available The risk for Schistosoma japonicum infection in Jiangsu province, People’s Republic of China, was investigated by a mouse bioassay. Various investigations were conducted in the period 2009-2011 with the presentation here representing the summary of the results from 45-50 sites in the marshlands along the Yangtze River’s course through the province. Indices representing three aspects of the infection were collected to assess risk: (i the proportion of sentinel points where at least one mouse infection was recorded; (ii the proportion of infected mice at each of these sites; and (iii the average worm burdens. Directional distribution analysis and scan statistics were used to explore the spatio-temporal risk pattern. The spatial distribution was oriented along the Yangtze River and the directional distributions for the proportion of infected mice and mean worm burdens were similar for the positive sentinel sites. Four statistically significant clusters were detected in 2009, but only one in 2010 and 2011, respectively. Temporal windows for infection risk were seen in June and September. The study illustrates the utility of spatio-temporal analysis in assessing the risk for schistosomiasis. This approach should be useful with respect to surveillance and response that can be expected to be increasingly applied when moving from morbidity control to transmission control.

  6. Spatio-temporal pattern formation, fractals, and chaos in conceptual ecological models as applied to coupled plankton-fish dynamics

    International Nuclear Information System (INIS)

    Medvinskii, Aleksandr B; Tikhonova, Irina A; Tikhonov, D A; Ivanitskii, Genrikh R; Petrovskii, Sergei V; Li, B.-L.; Venturino, E; Malchow, H

    2002-01-01

    The current turn-of-the-century period witnesses the intensive use of the bioproducts of the World Ocean while at the same time calling for precautions to preserve its ecological stability. This requires that biophysical processes in aquatic systems be comprehensively explored and new methods for monitoring their dynamics be developed. While aquatic and terrestrial ecosystems have much in common in terms of their mathematical description, there are essential differences between them. For example, the mobility of oceanic plankton is mainly controlled by diffusion processes, whereas terrestrial organisms naturally enough obey totally different laws. This paper is focused on the processes underlying the dynamics of spatially inhomogeneous plankton communities. We demonstrate that conceptual reaction-diffusion mathematical models are an appropriate tool for investigating both complex spatio-temporal plankton dynamics and the fractal properties of planktivorous fish school walks. (reviews of topical problems)

  7. EFFECTS OF PHYSICAL REHABILITATION INTEGRATED WITH RHYTHMIC AUDITORY STIMULATION ON SPATIO-TEMPORAL AND KINEMATIC PARAMETERS OF GAIT IN PARKINSON’S DISEASE

    Directory of Open Access Journals (Sweden)

    Massimiliano Pau

    2016-08-01

    Full Text Available Movement rehabilitation by means of physical therapy represents an essential tool in the management of gait disturbances induced by Parkinson’s disease (PD. In this context, the use of Rhythmic Auditory Stimulation (RAS has been proven useful in improving several spatio-temporal parameters, but concerning its effect on gait patterns scarce information is available from a kinematic viewpoint. In this study we used three-dimensional gait analysis based on optoelectronic stereophotogrammetry to investigate the effects of 5 weeks of intensive rehabilitation, which included gait training integrated with RAS on 26 individuals affected by PD (age 70.4±11.1, Hoehn & Yahr 1-3. Gait kinematics was assessed before and at the end of the rehabilitation period and after a three-month follow-up, using concise measures (Gait Profile Score and Gait Variable Score, GPS and GVS, respectively, which are able to describe the deviation from a physiologic gait pattern. The results confirm the effectiveness of gait training assisted by RAS in increasing speed and stride length, in regularizing cadence and correctly reweighting swing/stance phase duration. Moreover, an overall improvement of gait quality was observed, as demonstrated by the significant reduction of the GPS value, which was created mainly through significant decreases in the GVS score associated with the hip flexion-extension movement. Future research should focus on investigating kinematic details to better understand the mechanisms underlying gait disturbances in people with PD and the effects of RAS, with the aim of finding new or improving current rehabilitative treatments.

  8. Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

    Science.gov (United States)

    Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

    Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river

  9. Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

    Science.gov (United States)

    Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam

    2011-03-01

    This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

  10. Silica in invasive wetland plant species of lagoons, Côte d'Ivoire: Spatio-temporal patterns

    Science.gov (United States)

    José-mathieu Koné, Yéfanlan; Schoelynck, Jonas

    2017-04-01

    Tropical wetlands are known to accumulate a large quantity of Biogenic Silica (BSi) produced by wetland plant species (Struyf et al., 2015), and approximately 70-80% of the total supply of Dissolved Si (DSi) to the coastal zone occurs in (sub) tropical river systems (Jennerjahn et al. 2006). However, the data at these latitudes are limited. Here, we present the BSi concentration from eleven invasive macrophyte species randomly collected in three small ( 800ha) lagoons of Côte d'Ivoire during 12 months. Our data showed a large spatio-temporal variability of BSi in the three lagoons with no consistent trends. In general, the BSi concentrations obtained were high and values ranged from 0 to 54 mg g-1 through the entire sampling period, with the highest values found in Acroceras zizaniodes (emergent species of Poaceae). In general, free floating species had significantly less BSi than emergent species (Pspecies of fern, Salviniaceae) at the young stage were similar to those found in the emergent species. Based on yearly averages, highest BSi values were observed in Kodjoboué lagoon, and the lowest in the Ono lagoon that is 80% covered by macrophytes. Moreover, the dissolved silica (DSi) concentrations were systematically higher in Ono Lagoon than in Kodjoboué Lagoon. We conclude that in an eutrophic system Si accumulating in aquatic macrophytes is not related to Si availability but to other environmental factors. Jennerjahn, T.C., Knoppers, B.A., de Souze, W.F.L., Brunskill, G.J., Silva, E.I.L., Adi, S. et al., 2006. Factors controlling dissolved silica in tropical rivers. In: Ittekot, V. (ed) The silicon cycle. Island Press, Washington, D. C, pp 29-51 Schoelynck J and Struyf E, 2016. Silicon in aquatic vegetation. Functional Ecology. 30: 1323-1330. Struyf, E., Mosimane, K., Van Pelt, D., Murray-Hudson, M., Meire, P., Frings, P., Wolski, P., Schaller, J., Gondwe, M.J., Schoelynck, J. and Conley, D.J., 2015. The role of vegetation in the Okavango Delta silica sink

  11. Spatio-Temporal Variability of Summer Precipitation in Mexico under the Influence of the MJO, with Emphasis on the Bimodal Pattern

    Science.gov (United States)

    Perdigón, J.; Romero-Centeno, R.; Barrett, B.; Ordoñez-Perez, P.

    2017-12-01

    In many regions of Mexico, precipitation occurs in a very well defined annual cycle with peaks in May-June and September-October and a relative minimum in the middle of the rainy season known as the midsummer drought (MSD). The MJO is the most important mode of intraseasonal variability in the tropics, and, although some studies have shown its evident influence on summer precipitation in Mexico, its role in modulating the bimodal pattern of the summer precipitation cycle is still an open question. The spatio-temporal variability of summer precipitation in Mexico is analyzed through composite analysis according to the phases of the MJO, using the very high resolution CHIRPS precipitation data base and gridded data from the CFSR reanalysis to analyzing the MJO influence on the atmospheric circulation over Mexico and its adjacent basins. In general, during MJO phases 8-2 (4-6) rainfall is above-normal (below-normal), although, in some cases, the summer rainfall patterns during the same phase present considerable differences. The atmospheric circulation shows low (high) troposphere southwesterly (northeasterly) wind anomalies in southern Mexico under wetter conditions compared with climatological patterns, while the inverse pattern is observed under drier conditions. Composite anomalies of several variables also agreed well with those rainfall anomalies. Finally, a MJO complete cycle that reinforces (weakens) the bimodal pattern of summer rainfall in Mexico was found.

  12. Statistical methods for spatio-temporal systems

    CERN Document Server

    Finkenstadt, Barbel

    2006-01-01

    Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time co...

  13. Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

    Directory of Open Access Journals (Sweden)

    Jiangzhou Xia

    2014-02-01

    Full Text Available Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production. The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  14. Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

    Science.gov (United States)

    Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

    2017-10-18

    'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more

  15. Large-Scale Examination of Spatio-Temporal Patterns of Drifting Fish Aggregating Devices (dFADs) from Tropical Tuna Fisheries of the Indian and Atlantic Oceans.

    Science.gov (United States)

    Maufroy, Alexandra; Chassot, Emmanuel; Joo, Rocío; Kaplan, David Michael

    2015-01-01

    Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs) to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates "at sea" from "on board" buoy positions. A random forest model had the best performance, both in terms of the rate of false "at sea" predictions and the amount of over-segmentation of "at sea" trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to misclassification). Performance is improved via post-processing removing unrealistically short "at sea" trajectories. Results derived from the selected model enable us to identify the main areas and seasons of dFAD deployment and the spatial extent of their drift. We find that dFADs drift at sea on average for 39.5 days, with time at sea being shorter and distance travelled longer in the Indian than in the Atlantic Ocean. 9.9% of all trajectories end with a beaching event, suggesting that 1,500-2,000 may be lost onshore each year, potentially impacting sensitive habitat areas, such as the coral reefs of the Maldives, the Chagos Archipelago, and the Seychelles.

  16. Relationship between Spatio-Temporal Travel Patterns Derived from Smart-Card Data and Local Environmental Characteristics of Seoul, Korea

    Directory of Open Access Journals (Sweden)

    Mi-Kyeong Kim

    2018-03-01

    Full Text Available With the incorporation of an automated fare-collection system into the management of public transportation, not only can the quality of transportation services be improved but also that of the data collected from users when coupled with smart-card technology. The data collected from smart cards provide opportunities for researchers to analyze big data sets and draw meaningful information out of them. This study aims to identify the relationship between travel patterns derived from smart-card data and urban characteristics. Using seven-day transit smart-card data from the public-transportation system in Seoul, the capital city of the Republic of Korea, we investigated the temporal and spatial boarding and alighting patterns of the users. The major travel patterns, classified into five clusters, were identified by utilizing the K-Spectral Centroid clustering method. We found that the temporal pattern of urban mobility reflects daily activities in the urban area and that the spatial pattern of the five clusters classified by travel patterns was closely related to urban structure and urban function; that is, local environmental characteristics extracted from land-use and census data. This study confirmed that the travel patterns at the citywide level can be used to understand the dynamics of the urban population and the urban spatial structure. We believe that this study will provide valuable information about general patterns, which represent the possibility of finding travel patterns from individuals and urban spatial traits.

  17. Characterization of spatio-temporal patterns for various GRACE- and GLDAS-born estimates for changes of global terrestrial water storage

    Science.gov (United States)

    Yang, Tao; Wang, Chao; Yu, Zhongbo; Xu, Feng

    2013-10-01

    Since the launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided us with a new method to estimate terrestrial water storage (TWS) variations by measuring earth gravity change with unprecedented accuracy. Thus far, a number of standardized GRACE-born TWS products are published by different international research teams. However, no characterization of spatio-temporal patterns for different GRACE hydrology products from the global perspective could be found. It is still a big challenge for the science community to identify the reliable global measurement of TWS anomalies due to our limited knowledge on the true value. Hence, it is urgently necessary to evaluate the uncertainty for various global estimates of the GRACE-born TWS changes by a number of international research organizations. Toward this end, this article presents an in-depth analysis for various GRACE-born and GLDAS-based estimates for changes of global terrestrial water storage. The work characterizes the inter-annual and intra-annual variability, probability density variations, and spatial patterns among different GRACE-born TWS estimates over six major continents, and compares them with results from GLDAS simulations. The underlying causes of inconsistency between GRACE- and GLDAS-born TWS estimates are thoroughly analyzed with an aim to improve our current knowledge in monitoring global TWS change. With a comprehensive consideration of the advantages and disadvantages among GRACE- and GLDAS-born TWS anomalies, a summary is thereafter recommended as a rapid reference for scientists, end-users, and policy-makers in the practices of global TWS change research. To our best knowledge, this work is the first attempt to characterize difference and uncertainty among various GRACE-born terrestrial water storage changes over the major continents estimated by a number of international research organizations. The results can provide beneficial reference to usage of

  18. Spatio-Temporal Patterns of Cropland Conversion in Response to the “Grain for Green Project” in China’s Loess Hilly Region of Yanchuan County

    Directory of Open Access Journals (Sweden)

    Jieyong Wang

    2013-10-01

    Full Text Available To prevent environmental degradation, China’s central government launched the “Grain for Green Project” (GGP in 1999. Since its beginning, the effects and influences of the GGP have been hotly debated among domestic and international scholars and policymakers. This paper is taking the County of Yanchuan in the Loess Plateau as a case study, examines the spatio-temporal patterns of cropland conversion in response to the GGP. This research is methodologically based on remote sensing (RS and geographic information systems (GIS, and also employs personal interviews with local government officials and farmers. The results show that land use/cover patterns in Yanchuan County have changed dramatically after the implementation of GGP. Cropland has decreased remarkably, while orchard land and sparse forest has increased significantly: 23.84% of cropland was converted to orchard, and 22.25% to sparse forest. Simultaneously, the landscape has become more fragmented but also more diversified, forestland has become more dominant. A total of 61.19% of the total converted cropland was on slopes greater than 15 degrees, 64.85% of which was lower-grade land. The converted cropland is mostly located in more accessible areas for convenient management. Partially affected by farmers’ self-willingness, sloping cropland was preferred to orchard (economic forest, and some gentle slope (less than 15 degrees or higher-grade cropland were involved in the GGP. To maintain and reinforce the achievements of the GGP and further contribute to the GGP’s sustainability and rural development, the paper recommends that the Chinese government should build a continuous compensation mechanism for the households who lost cropland for the GGP while improving the productivity of flat cropland.

  19. Spatio-temporal patterns of chlorophyll fluorescence and physiological and structural indices acquired from hyperspectral imagery as compared with carbon fluxes measured with eddy covariance

    NARCIS (Netherlands)

    Zarco-Tejada, P.J.; Morales Sierra, A.; Testi, L.; Villalobos, F.

    2013-01-01

    This study provides insight into the assessment of the spatio-temporal trends of chlorophyll fluorescence, narrow-band physiological indices, and structural indices acquired with a hyperspectral imager flown over a flux tower in a canopy characterized by small seasonal structural changes and a

  20. SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

    DEFF Research Database (Denmark)

    Guisan, Antoine; Rahbek, Carsten

    2011-01-01

    Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...

  1. Spatio-Temporal Data Construction

    Directory of Open Access Journals (Sweden)

    Hai Ha Le

    2013-08-01

    Full Text Available On the route to a spatio-temporal geoscience information system, an appropriate data model for geo-objects in space and time has been developed. In this model, geo-objects are represented as sequences of geometries and properties with continuous evolution in each time interval. Because geomodeling software systems usually model objects at specific time instances, we want to interpolate the geometry and properties from two models of an object with only geometrical constraints (no physical or mechanical constraints. This process is called spatio-temporal data construction or morphological interpolation of intermediate geometries. This paper is strictly related to shape morphing, shape deformation, cross-parameterization and compatible remeshing and is only concerned with geological surfaces. In this study, two main sub-solutions construct compatible meshes and find trajectories in which vertices of the mesh evolve. This research aims to find an algorithm to construct spatio-temporal data with some constraints from the geosciences, such as cutting surfaces by faulting or fracturing phenomena and evolving boundaries attached to other surfaces. Another goal of this research is the implementation of the algorithm in a software product, namely a gOcad plug-in. The four main procedures of the algorithm are cutting the surfaces, setting up constraints, partitioning and calculating the parameterizations and trajectories. The software has been tested to construct data for a salt dome and other surfaces in regard to the geological processes of faulting, deposition and erosion. The result of this research is an algorithm and software for the construction of spatio-temporal data.

  2. Compressing spatio-temporal trajectories

    DEFF Research Database (Denmark)

    Gudmundsson, Joachim; Katajainen, Jyrki; Merrick, Damian

    2009-01-01

    such that the most common spatio-temporal queries can still be answered approximately after the compression has taken place. In the process, we develop an implementation of the Douglas–Peucker path-simplification algorithm which works efficiently even in the case where the polygonal path given as input is allowed...... to self-intersect. For a polygonal path of size n, the processing time is O(nlogkn) for k=2 or k=3 depending on the type of simplification....

  3. Spatio-temporal patterns of attacks on human and economic losses from wildlife in Chitwan National Park, Nepal

    NARCIS (Netherlands)

    Lamichhaen, B.R.; Persoon, G.A.; Leirs, H.; Poudel, S.; Subedi, N.; Pokheral, C.P.; Bhattarai, S.; Thapalia, B.P.; Iongh, de H.H.

    2018-01-01

    Wildlife attacks on humans and economic losses often result in reduced support of local communities for wildlife conservation. Information on spatial and temporal patterns of such losses in the highly affected areas contribute in designing and implementing effective mitigation measures. We analyzed

  4. Multiple remote sensing data sources to assess spatio-temporal patterns of fire incidence over Campos Amazônicos Savanna Vegetation Enclave (Brazilian Amazon).

    Science.gov (United States)

    Alves, Daniel Borini; Pérez-Cabello, Fernando

    2017-12-01

    Fire activity plays an important role in the past, present and future of Earth system behavior. Monitoring and assessing spatial and temporal fire dynamics have a fundamental relevance in the understanding of ecological processes and the human impacts on different landscapes and multiple spatial scales. This work analyzes the spatio-temporal distribution of burned areas in one of the biggest savanna vegetation enclaves in the southern Brazilian Amazon, from 2000 to 2016, deriving information from multiple remote sensing data sources (Landsat and MODIS surface reflectance, TRMM pluviometry and Vegetation Continuous Field tree cover layers). A fire scars database with 30 m spatial resolution was generated using a Landsat time series. MODIS daily surface reflectance was used for accurate dating of the fire scars. TRMM pluviometry data were analyzed to dynamically establish time limits of the yearly dry season and burning periods. Burned area extent, frequency and recurrence were quantified comparing the results annually/seasonally. Additionally, Vegetation Continuous Field tree cover layers were used to analyze fire incidence over different types of tree cover domains. In the last seventeen years, 1.03millionha were burned within the study area, distributed across 1432 fire occurrences, highlighting 2005, 2010 and 2014 as the most affected years. Middle dry season fires represent 86.21% of the total burned areas and 32.05% of fire occurrences, affecting larger amount of higher density tree surfaces than other burning periods. The results provide new insights into the analysis of burned areas of the neotropical savannas, spatially and statistically reinforcing important aspects linked to the seasonality patterns of fire incidence in this landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. The Effects of Weather Patterns on the Spatio-Temporal Distribution of SO2 over East Asia as Seen from Satellite Measurements

    Science.gov (United States)

    Dunlap, L.; Li, C.; Dickerson, R. R.; Krotkov, N. A.

    2015-12-01

    Weather systems, particularly mid-latitude wave cyclones, have been known to play an important role in the short-term variation of near-surface air pollution. Ground measurements and model simulations have demonstrated that stagnant air and minimal precipitation associated with high pressure systems are conducive to pollutant accumulation. With the passage of a cold front, built up pollution is transported downwind of the emission sources or washed out by precipitation. This concept is important to note when studying long-term changes in spatio-temporal pollution distribution, but has not been studied in detail from space. In this study, we focus on East Asia (especially the industrialized eastern China), where numerous large power plants and other point sources as well as area sources emit large amounts of SO2, an important gaseous pollutant and a precursor of aerosols. Using data from the Aura Ozone Monitoring Instrument (OMI) we show that such weather driven distribution can indeed be discerned from satellite data by utilizing probability distribution functions (PDFs) of SO2 column content. These PDFs are multimodal and give insight into the background pollution level at a given location and contribution from local and upwind emission sources. From these PDFs it is possible to determine the frequency for a given region to have SO2 loading that exceeds the background amount. By comparing OMI-observed long-term change in the frequency with meteorological data, we can gain insights into the effects of climate change (e.g., the weakening of Asian monsoon) on regional air quality. Such insight allows for better interpretation of satellite measurements as well as better prediction of future pollution distribution as a changing climate gives way to changing weather patterns.

  6. Spatio-temporal patterns of Ulva prolifera blooms and the corresponding influence on chlorophyll-a concentration in the Southern Yellow Sea, China.

    Science.gov (United States)

    Sun, Xiao; Wu, Mengquan; Xing, Qianguo; Song, Xiaodong; Zhao, Deheng; Han, Qianqian; Zhang, Guangzong

    2018-06-04

    The world's largest macroalgal blooms (MABs) caused by the Ulva prolifera outbreaks have occurred every summer since 2007 in the Southern Yellow Sea, China. Accumulating evidence showed that MABs may deteriorate the regional marine environment and influence the growth of some primary producers such as phytoplankton. In this study, we investigated the spatio-temporal patterns of U. prolifera green tides and chlorophyll-a concentration in the Southern Yellow Sea in 2015 using satellite images obtained from HJ-1 CCD, MODIS, and GOCI. The correlation between the distributions of U. prolifera abundance and chlorophyll-a concentration was analyzed quantitatively by setting up a series of 5 × 5 km experimental grids, and we also discussed the possible mechanisms about the influence of U. prolifera blooms on the other floating microalgae. The results showed that the development of U. prolifera blooms in the Southern Yellow Sea in 2015 could be featured as "appearance - development - outbreak - decline - disappearance", while the concentration of chlorophyll-a showed "increase - sharp decline - slow recovery - stabilization" from April to August. We also found that the concentration of chlorophyll-a had the following relationships with U. prolifera temporally: (1) the concentration of chlorophyll-a increased with the growth of U. prolifera from April to mid-May; (2) the chlorophyll-a concentration decreased sharply with the dramatically increased coverage of U. prolifera in June; and (3) the chlorophyll-a concentration slowly recovered and finally stabilized as U. prolifera decreased in July. Generally, there was a negative correlation between the occurrence of U. prolifera and chlorophyll-a concentration in the Southern Yellow Sea, China. Our results showed that the outbreak of U. prolifera does have a certain impact on the growth and reproduction of planktonic microalgae, and it suggests that U. prolifera blooms have potentially altered the ecological balance in

  7. Large-Scale Examination of Spatio-Temporal Patterns of Drifting Fish Aggregating Devices (dFADs from Tropical Tuna Fisheries of the Indian and Atlantic Oceans.

    Directory of Open Access Journals (Sweden)

    Alexandra Maufroy

    Full Text Available Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates "at sea" from "on board" buoy positions. A random forest model had the best performance, both in terms of the rate of false "at sea" predictions and the amount of over-segmentation of "at sea" trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to misclassification. Performance is improved via post-processing removing unrealistically short "at sea" trajectories. Results derived from the selected model enable us to identify the main areas and seasons of dFAD deployment and the spatial extent of their drift. We find that dFADs drift at sea on average for 39.5 days, with time at sea being shorter and distance travelled longer in the Indian than in the Atlantic Ocean. 9.9% of all trajectories end with a beaching event, suggesting that 1,500-2,000 may be lost onshore each year, potentially impacting sensitive habitat areas, such as the coral reefs of the Maldives, the Chagos Archipelago, and the Seychelles.

  8. Exploration of spatio-temporal patterns of students' movement in field trip by visualizing the log data

    Science.gov (United States)

    Cho, Nahye; Kang, Youngok

    2018-05-01

    A numerous log data in addition to user input data are being generated as mobile and web users continue to increase recently, and the studies in order to explore the patterns and meanings of various movement activities by making use of these log data are also rising rapidly. On the other hand, in the field of education, people have recognized the importance of field trip as the creative education is highlighted. Also, the examples which utilize the mobile devices in the field trip in accordance to the development of information technology are growing. In this study, we try to explore the patterns of student's activity by visualizing the log data generated from high school students' field trip with mobile device.

  9. Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

    Directory of Open Access Journals (Sweden)

    T. Blume

    2009-07-01

    Full Text Available Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale and binary indicator maps (for the long-term and hillslope scale. Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to

  10. Spatio-temporal and species-specific variation in PBDE levels/patterns in British Columbia's coastal waters

    International Nuclear Information System (INIS)

    Ikonomou, Michael G.; Fernandez, Marc P.; Hickman, Zachary L.

    2006-01-01

    Congener-specific levels of PBDEs were measured in the livers and some muscle tissues of Dungeness crab (Cancer magister), English sole (Pleuronectes vetulus) and spiny dogfish (Squalus acanthias). Highest concentrations (1200-560 ng/g lipid) were found in crab collected near heavily urbanized areas (pop. ∼0.3-1.8 million), followed by moderate levels at pulp/paper mills sites (∼150 ng/g), and lowest levels occurred in areas that were somewhat removed from industrial/populated areas (<24 ng/g). Temporal increases in total PBDEs and particularly in BDE-47 for Dungeness crab collected near pulp and paper and urbanized areas between 1994 and 2000 were observed. These correspond to Canadian and worldwide trends seen for PBDEs in biota. English sole and dogfish showed a pattern similar to that of the Columbia River whitefish samples, which corresponded closely to the patterns in the 'penta' commercial mixture. Conversely, Dungeness crab were enriched in lower chlorinated PBDEs, particularly BDE-47 and BDE-49, compared to the fish and shark species from BC. - PBDEs in biota and sediments from the West Coast of Canada reflect temporal, species-specific and geographic distributions

  11. Characterization of regional influenza seasonality patterns in China and implications for vaccination strategies: spatio-temporal modeling of surveillance data.

    Directory of Open Access Journals (Sweden)

    Hongjie Yu

    2013-11-01

    Full Text Available The complexity of influenza seasonal patterns in the inter-tropical zone impedes the establishment of effective routine immunization programs. China is a climatologically and economically diverse country, which has yet to establish a national influenza vaccination program. Here we characterize the diversity of influenza seasonality in China and make recommendations to guide future vaccination programs.We compiled weekly reports of laboratory-confirmed influenza A and B infections from sentinel hospitals in cities representing 30 Chinese provinces, 2005-2011, and data on population demographics, mobility patterns, socio-economic, and climate factors. We applied linear regression models with harmonic terms to estimate influenza seasonal characteristics, including the amplitude of annual and semi-annual periodicities, their ratio, and peak timing. Hierarchical Bayesian modeling and hierarchical clustering were used to identify predictors of influenza seasonal characteristics and define epidemiologically-relevant regions. The annual periodicity of influenza A epidemics increased with latitude (mean amplitude of annual cycle standardized by mean incidence, 140% [95% CI 128%-151%] in the north versus 37% [95% CI 27%-47%] in the south, p0.6 in provinces located within 27.4°N-31.3°N, slope of latitudinal gradient with latitude -0.016 [95% CI -0.025 to -0.008], p<0.001. In contrast, influenza B activity predominated in colder months throughout most of China. Climate factors were the strongest predictors of influenza seasonality, including minimum temperature, hours of sunshine, and maximum rainfall. Our main study limitations include a short surveillance period and sparse influenza sampling in some of the southern provinces.Regional-specific influenza vaccination strategies would be optimal in China; in particular, annual campaigns should be initiated 4-6 months apart in Northern and Southern China. Influenza surveillance should be strengthened in mid

  12. Spatio-temporal patterns and environmental controls of small pelagic fish body condition from contrasted Mediterranean areas

    Science.gov (United States)

    Brosset, Pablo; Fromentin, Jean-Marc; Van Beveren, Elisabeth; Lloret, Josep; Marques, Virginie; Basilone, Gualtiero; Bonanno, Angelo; Carpi, Piera; Donato, Fortunata; Čikeš Keč, Vanja; De Felice, Andrea; Ferreri, Rosalia; Gašparević, Denis; Giráldez, Ana; Gücü, Ali; Iglesias, Magdalena; Leonori, Iole; Palomera, Isabel; Somarakis, Stylianos; Tičina, Vjekoslav; Torres, Pedro; Ventero, Ana; Zorica, Barbara; Ménard, Frédéric; Saraux, Claire

    2017-02-01

    Small pelagic fish are among the most ecologically and economically important marine fish species and are characterized by large fluctuations all over the world. In the Mediterranean Sea, low catches and biomass of anchovies and sardines have been described in some areas during the last decade, resulting in important fisheries crises. Therefore, we studied anchovy and sardine body condition variability, a key index of population health and its response to environmental and anthropogenic changes. Wide temporal and spatial patterns were investigated by analyzing separately data from scientific surveys and fisheries in eight Mediterranean areas between 1975 and 2015. Results showed that anchovy and sardine body condition as well as maximum size in some areas sharply decreased in most Mediterranean areas along years (except in the Northern Alboran Sea). Despite this general pattern, well-marked environmental differences between sub-regions were highlighted by several analyses and variations in body condition were not found to be homogeneous over all the Mediterranean Sea. Further, other analyses revealed that except for the Adriatic where major changes towards a lower body condition were concomitant with a decrease in river runoffs and chl-a concentration, no concomitant environmental regime shift was detected in other areas. Together, these analyses highlighted the current poor body condition of almost all small pelagic fish populations in the Mediterranean. Yet, global environmental indices could not explain the observed changes and the general decrease in condition might more likely come from regional environmental and/or anthropogenic (fishing) effects. A prolonged state of poor fish body condition, together with an observed reduced size and early age-at-maturity may have strong ecological, economic and social consequences all around the Mediterranean Sea.

  13. Spatio-Temporal Patterns of the 2010–2015 Extreme Hydrological Drought across the Central Andes, Argentina

    Directory of Open Access Journals (Sweden)

    Juan Antonio Rivera

    2017-08-01

    Full Text Available During the period 2010–2015, the semi-arid Central Andes in Argentina (CAA experienced one of the most severe and long-lasting hydrological droughts on record. Since the snowmelt is the most important source of water, the reduced snowfall over the mountains propagated the drought signal through the streamflows in the adjacent foothills east of the Andes ranges. Motivated by the widespread impacts on the socio-economic activities in the region, this study aims to characterize the recent hydrological drought in terms of streamflow deficits. Based on streamflow data from 20 basins, we used the standardized streamflow index (SSI to characterize hydrological droughts during the period 1971–2016. We found that the regional extent of the 2010–2015 hydrological drought was limited to the basins located north of 38° S, with mean duration of 67 months and maximum drought severity exhibiting a heterogeneous pattern in terms of spatial distribution and time of occurrence. The drought event reached extreme conditions in 14 of the 15 basins in the CAA, being record-breaking drought in six of the basins. This condition was likely driven by a cooling in the tropical Pacific Ocean resembling La Niña conditions, which generated a decrease in snowfall over the Andes due to suppressed frontal activity.

  14. Spatio-temporal patterns of attacks on human and economic losses from wildlife in Chitwan National Park, Nepal.

    Science.gov (United States)

    Lamichhane, Babu Ram; Persoon, Gerard A; Leirs, Herwig; Poudel, Shashank; Subedi, Naresh; Pokheral, Chiranjibi Prasad; Bhattarai, Santosh; Thapaliya, Bishnu Prasad; de Iongh, Hans H

    2018-01-01

    Wildlife attacks on humans and economic losses often result in reduced support of local communities for wildlife conservation. Information on spatial and temporal patterns of such losses in the highly affected areas contribute in designing and implementing effective mitigation measures. We analyzed the loss of humans, livestock and property caused by wildlife during 1998 to 2016, using victim family's reports to Chitwan National Park authorities and Buffer Zone User Committees. A total of 4,014 incidents were recorded including attacks on humans, livestock depredation, property damage and crop raiding caused by 12 wildlife species. In total >400,000 US dollar was paid to the victim families as a relief over the whole period. Most of the attacks on humans were caused by rhino, sloth bear, tiger, elephant, wild boar and leopard. A significantly higher number of conflict incidents caused by rhino and elephant were observed during full moon periods. An increase in the wildlife population did not coincide with an equal rise in conflict incidents reported. Underprivileged ethnic communities were attacked by wildlife more frequently than expected. Number of attacks on humans by carnivores and herbivores did not differ significantly. An insignificant decreasing trend of wildlife attacks on humans and livestock was observed with significant variation over the years. Tiger and leopard caused >90% of livestock depredation. Tigers killed both large (cattle and buffalo) and medium sized (goat, sheep, pig) livestock but leopard mostly killed medium sized livestock. Most (87%) of the livestock killing during 2012-2016 occurred within the stall but close (conflict mitigation measures (electric and mesh wire fences) have contributed to keep the conflict incidents in control. Strengthening mitigation measures like construction of electric or mesh wire fences and predator-proof livestock corrals along with educating local communities about wildlife behavior and timely management of

  15. Spatio-temporal landscape modeling of urban growth patterns in Dhanbad Urban Agglomeration, India using geoinformatics techniques

    Directory of Open Access Journals (Sweden)

    Kanhaiya Lal

    2017-06-01

    Full Text Available The study deals with the quantification of urban sprawl and land transformation of Dhanbad Urban Agglomeration (DUA using geoinformatics and gradient modeling during last four decades (1972–2011. Various multi-temporal satellite images viz., MSS (1972, ETM+ (1999, 2011 and digital elevation model (CARTOSAT I, 2006 were used to analyse the urban expansion, land transformation, growth directions, and spatial segregations within the urban landscape to develop an understanding the nature of built-up growth in DUA. The urban area increased from 10.33 km2 to 46.70 km2 (352.08% along with high rate of population growth (160.07% during 1972–2011 exhibiting population densification in DUA. The study reveals that coal mining based city faced significant land use transformation converting vegetation (−41.33% into built-up land (352.08% exhibiting loss of productive lands for the expansion of impervious surface. The per year urban growth exhibited increasing urban growth from 0.4 km2/year to 1.51 km2/year during 1972–1999 and 1999–2011 periods with overall growth of 332.73%. The built-up growth on varied elevation zones exhibits that the elevation zones 150–200 m is the most preferred (79.01% for urban development with high growth (541.74%. The gradient modeling represents that the percentage of land (built-up gradually increased from 3.48% to 15.74% during 1972–2011. The result exhibited that the major growth took place in south-west direction followed by south direction in haphazard manner during 1971–99 period, whereas predominant built-up development was observed in north, south and south-west direction during 1999–2011 period, majorly within the municipal limits. The study provides an analytical method to evaluate the built-up growth patterns of an urban milieu combining geoinformatics and landscape matrix. The built-up growth in DUA indicates urgent imposition of building bylaws along with zoning (land use, height and density

  16. Pavlovian Prisoner's Dilemma in one-dimensional cellular automata: analytical results, the quasi-regular phase, spatio-temporal patterns and parameter space exploration

    OpenAIRE

    Pereira, Marcelo Alves; Martinez, Alexandre Souto

    2009-01-01

    The Prisoner's Dilemma (PD) game is used in several fields due to the emergence of cooperation among selfish players. Here, we have considered a one-dimensional lattice, where each cell represents a player, that can cooperate or defect. This one-dimensional geometry allows us to retrieve the results obtained for regular lattices and to keep track of the system spatio-temporal evolution. Players play PD with their neighbors and update their state using the Pavlovian Evolutionary Strategy. If t...

  17. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

    NARCIS (Netherlands)

    Zijlstra, W; Hof, AL

    2003-01-01

    This paper studies the feasibility of an analysis of spatio-temporal gait parameters based upon accelerometry. To this purpose, acceleration patterns of the trunk and their relationships with spatio-temporal gait parameters were analysed in healthy subjects. Based on model predictions of the body's

  18. Spatio-temporal patterns of hazards and their use in risk assessment and mitigation. Case study of road accidents in Romania

    Science.gov (United States)

    Catalin Stanga, Iulian

    2013-04-01

    the spatial or temporal clustering of crash accidents. Since the 1990's, Geographical Informational Systems (GIS) became a very important tool for traffic and road safety management, allowing not only the spatial and multifactorial analysis, but also graphical and non-graphical outputs. The current paper presents an accessible GIS methodology to study the spatio-temporal pattern of injury related road accidents, to identify the high density accidents zones, to make a cluster analysis, to create multicriterial typologies, to identify spatial and temporal similarities and to explain them. In this purpose, a Geographical Information System was created, allowing a complex analysis that involves not only the events, but also a large set of interrelated and spatially linked attributes. The GIS includes the accidents as georeferenced point elements with a spatially linked attribute database: identification information (date, location details); accident type; main, secondary and aggravating causes; data about driver; vehicle information; consequences (damages, injured peoples and fatalities). Each attribute has its own number code that allows both the statistical analysis and the spatial interrogation. The database includes those road accidents that led to physical injuries and loss of human lives between 2007 and 2012 and the spatial analysis was realized using TNTmips 7.3 software facilities. Data aggregation and processing allowed creating the spatial pattern of injury related road accidents through Kernel density estimation at three different levels (national - Romania; county level - Iasi County; local level - Iasi town). Spider graphs were used to create the temporal pattern or road accidents at three levels (daily, weekly and monthly) directly related to their causes. Moreover the spatial and temporal database relates the natural hazards (glazed frost, fog, and blizzard) with the human made ones, giving the opportunity to evaluate the nature of uncertainties in risk

  19. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    Science.gov (United States)

    Schöll, Eckehard

    2005-08-01

    Nonlinear transport phenomena are an increasingly important aspect of modern semiconductor research. This volume deals with complex nonlinear dynamics, pattern formation, and chaotic behavior in such systems. It bridges the gap between two well-established fields: the theory of dynamic systems and nonlinear charge transport in semiconductors. This unified approach helps reveal important electronic transport instabilities. The initial chapters lay a general framework for the theoretical description of nonlinear self-organized spatio-temporal patterns, such as current filaments, field domains, fronts, and analysis of their stability. Later chapters consider important model systems in detail: impact ionization induced impurity breakdown, Hall instabilities, superlattices, and low-dimensional structures. State-of-the-art results include chaos control, spatio-temporal chaos, multistability, pattern selection, activator-inhibitor kinetics, and global coupling, linking fundamental issues to electronic device applications. This book will be of great value to semiconductor physicists and nonlinear scientists alike.

  20. Spatio-Temporal Analysis to Predict Environmental Influence on Malaria

    Science.gov (United States)

    Baig, S.; Sarfraz, M. S.

    2018-05-01

    Malaria is a vector borne disease which is a major cause of morbidity and mortality. It is one of the major diseases in the category of infectious diseases. The survival and bionomics of malaria is affected by environmental factors such as climatic, demographic and land-use/land-cover etc. Currently, a very few under developing countries are using Geo-informatics approaches to control this disease. Gujrat a district of Pakistan, is still under threat of malaria disease. Current research is carried on malaria incidents obtained from District Executive Officer of Health Gujrat. The objective of this study was to explore the spatio-temporal patterns of malaria in district Gujrat and to identify the areas being affected by Malaria. Furthermore, it has been also analyzed the relationship between malaria incident and environmental factors in highly favorable zones. Data is analyzed based on spatial and temporal patterns using (Moran's I). Moreover cluster and hot spots analysis were performed on the incident data. This study shows positive correlation with rainfall, vegetation index, population density and water bodies; while it shows positive and negative correlation with temperature in different seasons. However, variation between amount of vegetation and water bodies were observed. Finding of this research can help the decision makers to take preventive measures and reduce the morbidity and mortality related with malaria in Gujrat, Pakistan.

  1. Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

    Science.gov (United States)

    Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

    2017-09-01

    Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

  2. Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

    Directory of Open Access Journals (Sweden)

    G. Gao

    2017-09-01

    Full Text Available Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961–2011, showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space–time variability of sediment yield was expressed notionally as a product of two factors representing (i the effect of precipitation and (ii the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation–sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

  3. Effective and efficient analysis of spatio-temporal data

    Science.gov (United States)

    Zhang, Zhongnan

    Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen

  4. Sex & vision I: Spatio-temporal resolution

    Directory of Open Access Journals (Sweden)

    Abramov Israel

    2012-09-01

    Full Text Available Abstract Background Cerebral cortex has a very large number of testosterone receptors, which could be a basis for sex differences in sensory functions. For example, audition has clear sex differences, which are related to serum testosterone levels. Of all major sensory systems only vision has not been examined for sex differences, which is surprising because occipital lobe (primary visual projection area may have the highest density of testosterone receptors in the cortex. We have examined a basic visual function: spatial and temporal pattern resolution and acuity. Methods We tested large groups of young adults with normal vision. They were screened with a battery of standard tests that examined acuity, color vision, and stereopsis. We sampled the visual system’s contrast-sensitivity function (CSF across the entire spatio-temporal space: 6 spatial frequencies at each of 5 temporal rates. Stimuli were gratings with sinusoidal luminance profiles generated on a special-purpose computer screen; their contrast was also sinusoidally modulated in time. We measured threshold contrasts using a criterion-free (forced-choice, adaptive psychophysical method (QUEST algorithm. Also, each individual’s acuity limit was estimated by fitting his or her data with a model and extrapolating to find the spatial frequency corresponding to 100% contrast. Results At a very low temporal rate, the spatial CSF was the canonical inverted-U; but for higher temporal rates, the maxima of the spatial CSFs shifted: Observers lost sensitivity at high spatial frequencies and gained sensitivity at low frequencies; also, all the maxima of the CSFs shifted by about the same amount in spatial frequency. Main effect: there was a significant (ANOVA sex difference. Across the entire spatio-temporal domain, males were more sensitive, especially at higher spatial frequencies; similarly males had significantly better acuity at all temporal rates. Conclusion As with other sensory systems

  5. How about a Bayesian M/EEG imaging method correcting for incomplete spatio-temporal priors

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke

    2013-01-01

    previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatio-temporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio......-temporal prior belief. We have tested the model on both artificial data and real EEG data in order to demonstrate the efficacy of the model. The model was tested at different SNRs (-10.0,-5.2, -3.0, -1.0, 0, 0.8, 3.0 dB) using white noise. At all SNRs the sAquavit performs best in AUC measure, e.g. at SNR=0d...

  6. Bayesian spatio-temporal modelling of tobacco-related cancer mortality in Switzerland

    Directory of Open Access Journals (Sweden)

    Verena Jürgens

    2013-05-01

    Full Text Available Tobacco smoking is a main cause of disease in Switzerland; lung cancer being the most common cancer mortality in men and the second most common in women. Although disease-specific mortality is decreasing in men, it is steadily increasing in women. The four language regions in this country might play a role in this context as they are influenced in different ways by the cultural and social behaviour of neighbouring countries. Bayesian hierarchical spatio-temporal, negative binomial models were fitted on subgroup-specific death rates indirectly standardized by national references to explore age- and gender-specific spatio-temporal patterns of mortality due to lung cancer and other tobacco-related cancers in Switzerland for the time period 1969-2002. Differences influenced by linguistic region and life in rural or urban areas were also accounted for. Male lung cancer mortality was found to be rather homogeneous in space, whereas women were confirmed to be more affected in urban regions. Compared to the German-speaking part, female mortality was higher in the French-speaking part of the country, a result contradicting other reports of similar comparisons between France and Germany. The spatio-temporal patterns of mortality were similar for lung cancer and other tobacco-related cancers. The estimated mortality maps can support the planning in health care services and evaluation of a national tobacco control programme. Better understanding of spatial and temporal variation of cancer of the lung and other tobacco-related cancers may help in allocating resources for more effective screening, diagnosis and therapy. The methodology can be applied to similar studies in other settings.

  7. Spatio-Temporal Data Exchange Standards

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Schmidt, Albrecht

    2003-01-01

    We believe that research that concerns aspects of spatio-temporal data management may benefit from taking into account the various standards for spatio-temporal data formats. For example, this may contribute to rendering prototype software “open” and more readily useful. This paper thus identifies...... and briefly surveys standardization in relation to primarily the exchange and integration of spatio-temporal data. An overview of several data exchange languages is offered, along with reviews their potential for facilitating the collection of test data and the leveraging of prototypes. The standards, most...... of which are XML-based, lend themselves to the integration of prototypes into middleware architectures, e.g., as Web services....

  8. Reliable Collaborative Filtering on Spatio-Temporal Privacy Data

    Directory of Open Access Journals (Sweden)

    Zhen Liu

    2017-01-01

    Full Text Available Lots of multilayer information, such as the spatio-temporal privacy check-in data, is accumulated in the location-based social network (LBSN. When using the collaborative filtering algorithm for LBSN location recommendation, one of the core issues is how to improve recommendation performance by combining the traditional algorithm with the multilayer information. The existing approaches of collaborative filtering use only the sparse user-item rating matrix. It entails high computational complexity and inaccurate results. A novel collaborative filtering-based location recommendation algorithm called LGP-CF, which takes spatio-temporal privacy information into account, is proposed in this paper. By mining the users check-in behavior pattern, the dataset is segmented semantically to reduce the data size that needs to be computed. Then the clustering algorithm is used to obtain and narrow the set of similar users. User-location bipartite graph is modeled using the filtered similar user set. Then LGP-CF can quickly locate the location and trajectory of users through message propagation and aggregation over the graph. Through calculating users similarity by spatio-temporal privacy data on the graph, we can finally calculate the rating of recommendable locations. Experiments results on the physical clusters indicate that compared with the existing algorithms, the proposed LGP-CF algorithm can make recommendations more accurately.

  9. Spatial and spatio-temporal analysis of malaria in the state of Acre, western Amazon, Brazil

    Directory of Open Access Journals (Sweden)

    Leonardo Augusto Kohara Melchior

    2016-11-01

    Full Text Available Since 2005, the State of Acre, western Amazon, Brazil, has reported the highest annual parasite incidence (API of malaria among the Brazilian states. This study examines malaria incidence in Acre using spatial and spatio-temporal analysis based on an ecological time series study analyzing malaria cases and deaths for the time period 1992- 2014 and using secondary data. API indexes were calculated by age, sex, parasite species, ratio of Plasmodium vivax to P. falciparum malaria, malaria mortality rate and case fatality rate. SaTScan was used to detect spatial and spatio-temporal clusters of malaria cases and data were represented in the form of choropleth maps. A high-risk cluster of malaria was detected in Vale do Juruá and three low-risk clusters in Vale do Acre for both parasite species. Those younger than 19 years of age and females showed a high incidence of malaria in Vale do Juruá, but working-age males were the most affected in Vale do Acre. The malaria mortality rate showed a decreasing trend across the state, while the case fatality rate increased only in the micro-region of Rio Branco during the study period. We conclude that malaria is a focal disease in Acre showing different spatial and spatio-temporal patterns of cases and deaths that vary by age, sex, and parasite species. Malaria incidence is thought to be influenced by factors related to regional characteristics; therefore, appropriate disease and vector control strategies must be implemented at each locality.

  10. The Voronoi spatio-temporal data structure

    Science.gov (United States)

    Mioc, Darka

    2002-04-01

    Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal

  11. A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

    OpenAIRE

    Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

    2013-01-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implem...

  12. Image sequence analysis using spatio-temporal texture

    International Nuclear Information System (INIS)

    Sengupta, S.K.; Clark, G.A.; Barnes, F.L.; Schaich, P.C.

    1994-01-01

    The authors have developed and coded an algorithm for motion pattern classification based on spatio-temporal texture. The algorithm has been implemented and tested for the detection of wakes in simulated data with a relatively low signal-to-noise ratio (0.7 dB). Using a open-quote hold one out close-quote method, a detection probability of 100% with a 0% false alarm rate has been achieved on the limited number of samples (47 in each category) tested. The actual detection can be displayed in the form of a movie that can effectively show the submarine tracks based on the detected wake locations

  13. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    OpenAIRE

    N. Mou; N. Mou; J. Li; L. Zhang; W. Liu; Y. Xu

    2017-01-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according t...

  14. What Is Spatio-Temporal Data Warehousing?

    Science.gov (United States)

    Vaisman, Alejandro; Zimányi, Esteban

    In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.

  15. Prenatal diagnosis of congenital heart disease using four-dimensional spatio-temporal image correlation (STIC) telemedicine via an Internet link: a pilot study.

    Science.gov (United States)

    Viñals, F; Mandujano, L; Vargas, G; Giuliano, A

    2005-01-01

    To assess whether the spatio-temporal image correlation (STIC) acquisition technique can be taught to a general obstetrician by e-mail; whether STIC volume datasets can be transmitted over the Internet; and whether STIC volume datasets analyzed offline at a remote setting can be used to confirm or exclude major cardiac defects (TELE-STIC). This was a prospective study involving 50 pregnant women with gestational ages ranging between 20 and 36 weeks. These patients were selected by two general obstetricians (operators) working in geographically remote areas of Chile. Although both obstetricians were users of equipment capable of four-dimensional (4D) ultrasound with STIC, they lacked skill in the performance of fetal cardiac examination. A dedicated web disk was created to upload the acquired volume datasets using an Internet broadband connection. Offline analysis was performed by a single investigator experienced in fetal echocardiography (the administrator). A telemedicine link via the Internet was possible in all cases. Seventy-seven volume datasets were sent to the web server. A complete cardiac examination according to set criteria was achieved by the administrator in 86% of the cases scanned by one operator and 95% of the cases scanned by the other operator. Three patients had cardiac defects confirmed postnatally, two fetuses had extracardiac anomalies and one fetus had a suspected cardiac defect unconfirmed by second-opinion TELE-STIC. There were two isolated major congenital heart defects. Both patients were given advice by e-mail and teleconference using a web camera about the likely outcome and benefits of scheduling in utero transport to a tertiary care center. STIC volumes can be obtained by operators inexperienced in fetal echocardiography, transmitted via the Internet, and their analysis enables recognition of most of the structures and views necessary to assess fetal cardiac anatomy. The preliminary use of TELE-STIC allowed us to demonstrate that

  16. Assessing global vegetation activity using spatio-temporal Bayesian modelling

    Science.gov (United States)

    Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

    2016-04-01

    This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

  17. Multiscale recurrence analysis of spatio-temporal data

    Science.gov (United States)

    Riedl, M.; Marwan, N.; Kurths, J.

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  18. Spatio-temporal analysis of blood perfusion by imaging photoplethysmography

    Science.gov (United States)

    Zaunseder, Sebastian; Trumpp, Alexander; Ernst, Hannes; Förster, Michael; Malberg, Hagen

    2018-02-01

    Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are influenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance.

  19. Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

    DEFF Research Database (Denmark)

    Frelat, Romain; Lindegren, Martin; Dencker, Tim Spaanheden

    2017-01-01

    it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered...... by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii...

  20. Spatio-temporal intermittency on the sandpile

    International Nuclear Information System (INIS)

    Erzan, A.; Sinha, S.

    1990-08-01

    The self-organized critical state exhibited by a sandpile model is shown to correspond to motion on an attractor characterized by an invariant distribution of the height variable. The largest Lyapunov exponent is equal to zero. The model nonetheless displays intermittent chaos, with a multifractal distribution of local expansion coefficients in history space. Laminar spatio-temporal regions are interrupted by chaotic bursts caused by avalanches. We introduce the concept of local histories in configuration space and show that their expansion parameters also exhibit a multifractal distribution in time and space. (author). 22 refs, 5 figs

  1. Spatio-temporal distribution patterns of the invasive macroalga Sargassum muticum within a Danish Sargassum-bed

    DEFF Research Database (Denmark)

    Thomsen, M. S.; Wernberg, T.; Stæhr, P. A.

    2006-01-01

    Sargassum muticum was first observed in Scandinavia in Limfjorden (Denmark) in 1984, where it is now the most abundant and conspicuous macroalga. Despite the ecological importance of Sargassum, few studies have described seasonal patterns within Scandinavian Sargassum beds. We quantified the dyna...... and sediment stress limits Sargasum in shallow waters, and the presence of stable boulder substratum facilitate Sargassum. Competition for space from other macroalgae and herbivory are probably of minor importance.......Sargassum muticum was first observed in Scandinavia in Limfjorden (Denmark) in 1984, where it is now the most abundant and conspicuous macroalga. Despite the ecological importance of Sargassum, few studies have described seasonal patterns within Scandinavian Sargassum beds. We quantified...... the dynamics of macroalgae among years and seasons along a depth transect through a typical Sargassum bed in Limfjorden. The annual investigations (summer transects 1989-1999) showed a gradual increase in the dominance of Sargassum, especially at the 2-4-m depth interval. Significant seasonal dynamics...

  2. Quantitative study on spatio-temporal change of urban landscape pattern based on RS/GIS: a case of Xi'an metropolitan area in China

    Science.gov (United States)

    Chen, Meiwu; Zong, Yueguang; Ma, Qiang; Li, Jian

    2007-06-01

    The study on landscape pattern is an important field of urban land use and ecological change. Since 1990s, the widely accepted Patch-Corridor-Matrix model is generally used in qualitative description of landscape pattern. In recent years, quantitative evaluation on urban landscape dynamics is becoming hot in research. By making a critical review on existing research methods of landscape pattern, a new approach based on RS/GIS is put forward in this paper, comprising three steps, "General pattern characteristics - Gradient differentiation feature- Directional signature of the landscape", and we call it GGD. This method is applied to the case study of Xi'an metropolitan area in China. The result shows that the method is effective on quantitative study of urban landscape. The preparation of the method GGD is setting up research platform based on RS and GIS. By using the software of Geographical Information System (Arcgis9.0 & Erdas), the authors got the interpretation of remote sensing images of different years, and carried on the division of the landscape type of the research region. By calculating various index of landscape level with software Fragstats3.3 as an assistant tool and adopting three steps of GGD combined with landscape index, this paper can assesses the landscape spatial pattern of urban area: 1) General pattern characteristics analysis is to get transition probability of various landscape through Markov chain and to predict the landscape transformation by introducing CA model. The analysis emphasizes on total landscape structure and its change over time; 2) Gradient characteristic analysis, which makes gradient zone by taking city as a center outwardly with certain distance and contrastively analyzes the landscape index of each subarea, stresses the spatial character of landscape pattern, verifies urban morphology theories and provides the quantitative warranty for establishment of urban modality. Therefore, the analysis is useful for supervising urban

  3. Summer at the beach: spatio-temporal patterns of white shark occurrence along the inshore areas of False Bay, South Africa.

    Science.gov (United States)

    Kock, Alison A; Photopoulou, Theoni; Durbach, Ian; Mauff, Katya; Meÿer, Michael; Kotze, Deon; Griffiths, Charles L; O'Riain, M Justin

    2018-01-01

    Understanding white shark ( Carcharodon carcharias ) habitat use in coastal areas adjacent to large cities, is an important step when formulating potential solutions to the conservation conflict that exists between humans and large predatory sharks. In this study, we present the findings of a 2.5-year study of white shark occurrence and movement patterns adjacent to the City of Cape Town in False Bay, South Africa, with a focus on spring and summer months. Fifty-one white sharks were monitored annually at three offshore and twelve inshore sites by VR2 acoustic receivers, over 975 days from 1 May 2005 to 31 December 2007. Occurrence patterns at inshore sites during spring and summer were analysed using a generalized additive mixed model (GAMM) with a spatial term (longitude, latitude), time of day and year included as explanatory variables for site use. We found that sharks occurred more frequently at inshore sites along the northern and northwestern shores, compared to the rest of the bay, and they transitioned most frequently between four adjacent beach sites that encompass the most popular recreational water use areas in Cape Town. There was significant diel variation, with higher shark occurrence around midday, and a peak in shark occurrence in 2005, when human-shark interactions also peaked. However, we found no effect of shark size on occurrence patterns at inshore sites. White sharks showed the highest levels of occurrence at specific inshore sites between Muizenberg and Strandfontein beach, and thus inclusion of these sites within False Bay's marine protected area (MPA) network or recognition as Ecological or Biological Significant Areas (EBSAs) should be a future consideration. These insights into white shark habitat use at inshore sites in False Bay are important for successfully applying the principles of marine spatial planning (MSP) and for making science-based policy decisions. Furthermore, this information can be used to reduce potential shark

  4. Spatio-temporal and species-specific variation in PBDE levels/patterns in British Columbia's coastal waters

    Energy Technology Data Exchange (ETDEWEB)

    Ikonomou, Michael G. [Marine Environmental Quality, Institute of Ocean Sciences, Fisheries and Oceans Canada, 9860 W. Saanich Road, Sidney, British Columbia V8L 4B2 (Canada)]. E-mail: ikonomoum@dfo-mpo.gc.ca; Fernandez, Marc P. [Marine Environmental Quality, Institute of Ocean Sciences, Fisheries and Oceans Canada, 9860 W. Saanich Road, Sidney, British Columbia V8L 4B2 (Canada); Hickman, Zachary L. [College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032 (United States)

    2006-03-15

    Congener-specific levels of PBDEs were measured in the livers and some muscle tissues of Dungeness crab (Cancer magister), English sole (Pleuronectes vetulus) and spiny dogfish (Squalus acanthias). Highest concentrations (1200-560 ng/g lipid) were found in crab collected near heavily urbanized areas (pop. {approx}0.3-1.8 million), followed by moderate levels at pulp/paper mills sites ({approx}150 ng/g), and lowest levels occurred in areas that were somewhat removed from industrial/populated areas (<24 ng/g). Temporal increases in total PBDEs and particularly in BDE-47 for Dungeness crab collected near pulp and paper and urbanized areas between 1994 and 2000 were observed. These correspond to Canadian and worldwide trends seen for PBDEs in biota. English sole and dogfish showed a pattern similar to that of the Columbia River whitefish samples, which corresponded closely to the patterns in the 'penta' commercial mixture. Conversely, Dungeness crab were enriched in lower chlorinated PBDEs, particularly BDE-47 and BDE-49, compared to the fish and shark species from BC. - PBDEs in biota and sediments from the West Coast of Canada reflect temporal, species-specific and geographic distributions.

  5. Observations on the spatio-temporal patterns of radon along the western fault of the Dead Sea Transform, NW Dead Sea

    International Nuclear Information System (INIS)

    Steinitz, G.; Piatibratova, O.; Malik, U.

    2015-01-01

    An extensive radon anomaly is developed along the western boundary fault of the Dead Sea Transform in the NW sector of the Dead Sea, extending 15-20 km north-south. The highest radon values occur in proximity to the fault scarp. Radon is measured, in gravel (depth 1.5-3 m) at sites located at a) on-fault positions, 1-30 meters east of the fault scarp, and b) off-fault positions located 600-800 the east. Prominent signals occur in the annual and daily periodicity bands, as well as non-periodic multi-day variations (2-20 days). Modulations occur among the annual variation and the multi-day and the daily signals, and between the multi-day and the daily signal. Dissimilar variation patterns occur at on-fault versus off-fault sites in the time domain, and in the relative amplitude of the daily periodicities. Variation patterns and their modulations are similar to those encountered in experimental simulations. It is concluded that: 1) above surface atmospheric influences can be excluded; 2) a remote above surface influence probably drives the periodic components in the annual and diurnal bands; 3) diurnal as well as the multi-day signals are modified and inter-modulated by near field geological (static) and geophysical (dynamic) influences. Systematically different influences are operating at on-fault versus off- fault positions, so far the natures of these near field influences are unidentified. (authors)

  6. Using Multi-Temporal Remote Sensing Data to Analyze the Spatio-Temporal Patterns of Dry Season Rice Production in Bangladesh

    Science.gov (United States)

    Shew, A. M.; Ghosh, A.

    2017-10-01

    Remote sensing in the optical domain is widely used in agricultural monitoring; however, such initiatives pose a challenge for developing countries due to a lack of high quality in situ information. Our proposed methodology could help developing countries bridge this gap by demonstrating the potential to quantify patterns of dry season rice production in Bangladesh. To analyze approximately 90,000 km2 of cultivated land in Bangladesh at 30 m spatial resolution, we used two decades of remote sensing data from the Landsat archive and Google Earth Engine (GEE), a cloud-based geospatial data analysis platform built on Google infrastructure and capable of processing petabyte-scale remote sensing data. We reconstructed the seasonal patterns of vegetation indices (VIs) for each pixel using a harmonic time series (HTS) model, which minimizes the effects of missing observations and noise. Next, we combined the seasonality information of VIs with our knowledge of rice cultivation systems in Bangladesh to delineate rice areas in the dry season, which are predominantly hybrid and High Yielding Varieties (HYV). Based on historical Landsat imagery, the harmonic time series of vegetation indices (HTS-VIs) model estimated 4.605 million ha, 3.519 million ha, and 4.021 million ha of rice production for Bangladesh in 2005, 2010, and 2015 respectively. Fine spatial scale information on HYV rice over the last 20 years will greatly improve our understanding of double-cropped rice systems, current status of production, and potential for HYV rice adoption in Bangladesh during the dry season.

  7. Spatio-temporal pattern of schistosomiasis in Anhui Province, East China: Potential effect of the Yangtze River - Huaihe River Water Transfer Project.

    Science.gov (United States)

    Cao, Zhi-Guo; Li, Si; Zhao, Ya-E; Wang, Tian-Ping; Bergquist, Robert; Huang, Yin-Yin; Gao, Feng-Hua; Hu, Yi; Zhang, Zhi-Jie

    2018-05-09

    Anhui Province has been one of typical epidemic areas of schistosomiasis in East China as a wide range of large lake and marshland regions provide an ideal environment for growth and reproduction of the intermediate snail host. With the completion of the Yangtze River-Huaihe River Water Transfer Project (YHWTP), launched by the end of 2016, the epidemic areas are expected to expand and controlling schistosomiasis remains a challenge. Based on annual surveillance data at the county level in Anhui for the period 2006-2015, spatial and temporal cluster analyses were conducted to assess the pattern of risk through spatial (Local Moran's I and flexible scan statistic) and space-time scan statistic (Kulldorff). It was found that schistosomiasis sero-prevalence was dramatically reduced and maintained at a low level. Cluster results showed that spatial extent of schistosomiasis contracted, but snail distribution remained geographically stable across the study area. Clusters, both for schistosomiasis and snail presence, were common along the Yangtze River. Considering the effect of the ongoing YHWTP on the potential spread of schistosomiasis, Zongyang County and Anqing, which will be transected by the new water-transfer route, should be given a priority for strengthened surveillance and control. Attention should also be paid to Guichi since it is close to one of the planned inlets of the YHWTP. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. Revealing spatio-temporal patterns of rabies spread among various categories of animals in the Republic of Kazakhstan, 2010-2013.

    Science.gov (United States)

    Abdrakhmanov, Sarsenbay K; Beisembayev, Kanatzhan K; Кorennoy, Fedor I; Yessembekova, Gulzhan N; Кushubaev, Dosym B; Кadyrov, Ablaikhan S

    2016-05-31

    This study estimated the basic reproductive ratio of rabies at the population level in wild animals (foxes), farm animals (cattle, camels, horses, sheep) and what we classified as domestic animals (cats, dogs) in the Republic of Kazakhstan (RK). It also aimed at forecasting the possible number of new outbreaks in case of emergence of the disease in new territories. We considered cases of rabies in animals in RK from 2010 to 2013, recorded by regional veterinary services. Statistically significant space-time clusters of outbreaks in three subpopulations were detected by means of Kulldorff Scan statistics. Theoretical curves were then fitted to epidemiological data within each cluster assuming exponential initial growth, which was followed up by calculation of the basic reproductive ratio R0. For farm animals, the value of R0 was 1.62 (1.11-2.26) and for wild animals 1.84 (1.08- 3.13), while it was close to 1 for domestic animals. Using the values obtained, an initial phase of possible epidemic was simulated in order to predict the expected number of secondary cases if the disease were introduced into a new area. The possible number of new cases for 20 weeks was estimated at 5 (1-16) for farm animals, 17 (1-113) for wild animals and about 1 in the category of domestic animals. These results have been used to produce set of recommendations for organising of preventive and contra-epizootic measures against rabies expected to be applied by state veterinarian services.

  9. Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Wipf, David

    While MEG and EEG source imaging methods have to tackle a severely ill-posed problem their success can be stated as their ability to constrain the solutions using appropriate priors. In this paper we propose a hierarchical Bayesian model facilitating spatio-temporal patterns through the use of bo...

  10. Spatio-temporal scaling of channels in braided streams.

    Science.gov (United States)

    A.G. Hunt; G.E. Grant; V.K. Gupta

    2006-01-01

    The spatio-temporal scaling relationship for individual channels in braided streams is shown to be identical to the spatio-temporal scaling associated with constant Froude number, e.g., Fr = l. A means to derive this relationship is developed from a new theory of sediment transport. The mechanism by which the Fr = l condition apparently governs the scaling seems to...

  11. Annotating spatio-temporal datasets for meaningful analysis in the Web

    Science.gov (United States)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

    More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

  12. Dying like rabbits: general determinants of spatio-temporal variability in survival.

    Science.gov (United States)

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

    1. Identifying general patterns of how and why survival rates vary across space and time is necessary to truly understand population dynamics of a species. However, this is not an easy task given the complexity and interactions of processes involved, and the interpopulation differences in main survival determinants. 2. Here, using European rabbits (Oryctolagus cuniculus) as a model and information from local studies, we investigated whether we could make inferences about trends and drivers of survival of a species that are generalizable to large spatio-temporal scales. To do this, we first focused on overall survival and then examined cause-specific mortalities, mainly predation and diseases, which may lead to those patterns. 3. Our results show that within the large-scale variability in rabbit survival, there exist general patterns that are explained by the integration of factors previously known to be important at the local level (i.e. age, climate, diseases, predation or density dependence). We found that both inter- and intrastudy survival rates increased in magnitude and decreased in variability as rabbits grow old, although this tendency was less pronounced in populations with epidemic diseases. Some causes leading to these higher mortalities in young rabbits could be the stronger effect of rainfall at those ages, as well as, other death sources like malnutrition or infanticide. 4. Predation is also greater for newborns and juveniles, especially in population without diseases. Apart from the effect of diseases, predation patterns also depended on factors, such as, density, season, and type and density of predators. Finally, we observed that infectious diseases also showed general relationships with climate, breeding (i.e. new susceptible rabbits) and age, although the association type varied between myxomatosis and rabbit haemorrhagic disease. 5. In conclusion, large-scale patterns of spatio-temporal variability in rabbit survival emerge from the combination

  13. Spatio-temporal clustering of wildfires in Portugal

    Science.gov (United States)

    Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.

    2012-04-01

    Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.

  14. Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

    Full Text Available This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.

  15. Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.

    Science.gov (United States)

    Raghavan, Ram K; Goodin, Douglas G; Neises, Daniel; Anderson, Gary A; Ganta, Roman R

    2016-01-01

    This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.

  16. Salmonella enterica Serovar Napoli Infection in Italy from 2000 to 2013: Spatial and Spatio-Temporal Analysis of Cases Distribution and the Effect of Human and Animal Density on the Risk of Infection.

    Directory of Open Access Journals (Sweden)

    Caterina Graziani

    Full Text Available Salmonella Napoli is uncommon in Europe. In Italy however, it has been growing in importance since 2000. To date, no risk factors have been identified to account for its rise. This study aims at describing the epidemiology, spatial and spatio-temporal patterns of S. Napoli in Italy from 2000 to 2013, and to explore the role of several environmental correlates, namely urbanization, altitude and number of livestock farms, on the risk of S. Napoli infection among humans.Data were obtained from Enter-Net Italy, a network of diagnostic laboratories. The data were aggregated at the municipality level. Descriptive epidemiology, multivariate regression models, spatial and spatio-temporal analyses were performed on the number of cases and incidence rates.S. Napoli showed an expanding trend at the national level, and an increasing number of cases. Compared to the other main serovars in Italy, the risk of S. Napoli infection was higher in the age group <1 year, and lower in the other age groups. Although urbanization and the number of farms were associated with the risk of S. Napoli infection to some extent, their role in the epidemiology of the disease remains inconclusive. S. Napoli cases showed a positive global spatial autocorrelation as well as a significant spatio-temporal interaction. Twenty-four spatial and spatio-temporal clusters were identified, seven purely spatial and 17 spatio-temporal, mainly in north-western Italy. Most of the clusters were in areas characterized by urban and industrial settlements surrounded by agricultural land and an abundance of freshwater bodies.Our results point to the presence, in a number of areas in Italy, of a Salmonella of public health concern originating in the environment. This highlights the increasing relevance of environmental, non-food-related sources of human exposure to enteric pathogens.

  17. Spatio-temporal problems of locomotion control

    International Nuclear Information System (INIS)

    Smolyaninov, Vladimir V

    2000-01-01

    The problem of the spatio-temporal construction of legged movements involves structural freedoms due to the multi-link structure of the extremities, kinematic freedoms of the stepping cycle, and interextremity coordination freedoms, whose purposive organization is established by means of appropriate synergies, i.e. additional functional links the brain's control system forms. The main focus of attention in this work is on the kinematic and coordination synergies of the legged movements of humans and animals. The comparative historical analysis of experimental data and modelling metaphors concentrates on obtaining a unified description, whereas the ultimate mathematical metaphor reduces to space-time geometry, with base step synergies as its invariants. Thus, the concept of a synergetic organization for biomechanical movement freedoms is transformed to the geochronometry concept, actually a modification of Minkowskian geometry. To determine the spectrum of possible geochronometries, the consequences of a generalized 'postulate of a constant speed of light' are studied and different models of wave chronometers compared. (reviews of topical problems)

  18. Markovian Limit of a Spatio-Temporal Correlated Open Systems

    Science.gov (United States)

    Monnai, T.

    Large fluctuation of Brownian particles is affected by the finiteness of the correlation length of the background noise field. Indeed a Fokker—Planck equation is derived in a Markovian limit of a spatio-temporal short correlated noise. Corresponding kinetic quantities are renormalized due to the spatio-temporal memory. We also investigate the case of open system by connecting a thermostat to the system.

  19. Initial spatio-temporal domain expansion of the Modelfest database

    Science.gov (United States)

    Carney, Thom; Mozaffari, Sahar; Sun, Sean; Johnson, Ryan; Shirvastava, Sharona; Shen, Priscilla; Ly, Emma

    2013-03-01

    The first Modelfest group publication appeared in the SPIE Human Vision and Electronic Imaging conference proceedings in 1999. "One of the group's goals is to develop a public database of test images with threshold data from multiple laboratories for designing and testing HVS (Human Vision Models)." After extended discussions the group selected a set of 45 static images thought to best meet that goal and collected psychophysical detection data which is available on the WEB and presented in the 2000 SPIE conference proceedings. Several groups have used these datasets to test spatial modeling ideas. Further discussions led to the preliminary stimulus specification for extending the database into the temporal domain which was published in the 2002 conference proceeding. After a hiatus of 12 years, some of us have collected spatio-temporal thresholds on an expanded stimulus set of 41 video clips; the original specification included 35 clips. The principal change involved adding one additional spatial pattern beyond the three originally specified. The stimuli consisted of 4 spatial patterns, Gaussian Blob, 4 c/d Gabor patch, 11.3 c/d Gabor patch and a 2D white noise patch. Across conditions the patterns were temporally modulated over a range of approximately 0-25 Hz as well as temporal edge and pulse modulation conditions. The display and data collection specifications were as specified by the Modelfest groups in the 2002 conference proceedings. To date seven subjects have participated in this phase of the data collection effort, one of which also participated in the first phase of Modelfest. Three of the spatio-temporal stimuli were identical to conditions in the original static dataset. Small differences in the thresholds were evident and may point to a stimulus limitation. The temporal CSF peaked between 4 and 8 Hz for the 0 c/d (Gaussian blob) and 4 c/d patterns. The 4 c/d and 11.3 c/d Gabor temporal CSF was low pass while the 0 c/d pattern was band pass. This

  20. Visualization and assessment of spatio-temporal covariance properties

    KAUST Repository

    Huang, Huang

    2017-11-23

    Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.

  1. Spatio-temporal and stochastic modelling of severe acute respiratory syndrome

    Directory of Open Access Journals (Sweden)

    Poh-Chin Lai

    2013-11-01

    Full Text Available This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and time to affect the patterns of disease transmission in a community. The model was validated through a comparative assessment between actual and modelled distribution of diseased locations. Our study shows that the inclusion of location-specific characteristics satisfactorily replicates the spatial dynamics of an infectious disease. The Pearson’s correlation coefficients for five trials based on 3-day aggregation of disease counts for 1-3, 4-6 and 7-9 day forecasts were 0.57- 0.95, 0.54-0.86 and 0.57-0.82, respectively, while the correlation based on 5-day aggregation for the 1-5 day forecast was 0.55- 0.94 and 0.58-0.81 for the 6-10 day forecast. The significant and strong relationship between actual results and forecast is encouraging for the potential development of an early warning system for detecting this type of disease outbreaks.

  2. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Science.gov (United States)

    Daya Sagar, B. S.

    2005-01-01

    Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  3. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2005-01-01

    Full Text Available Spatio-temporal patterns of small water bodies (SWBs under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  4. Spatio-temporal regulation of ADAR editing during development in porcine neural tissues

    DEFF Research Database (Denmark)

    Venø, Morten Trillingsgaard; Bramsen, Jesper Bertram; Bendixen, Christian

    2012-01-01

    Editing by ADAR enzymes is essential for mammalian life. Still, knowledge of the spatio-temporal editing patterns in mammals is limited. By use of 454 amplicon sequencing we examined the editing status of 12 regionally extracted mRNAs from porcine developing brain encompassing a total of 64...... putative ADAR editing sites. In total 24 brain tissues, dissected from up to five regions from embryonic gestation day 23, 42, 60, 80, 100 and 115, were examined for editing....

  5. Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance

    Directory of Open Access Journals (Sweden)

    Sebastian Meyer

    2017-05-01

    Full Text Available The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.

  6. Spatio-temporal evolution of forest fires in Portugal

    Science.gov (United States)

    Tonini, Marj; Pereira, Mário G.; Parente, Joana

    2017-04-01

    southern areas spread hot-spot are spatially randomly distributed and temporally more concentrated in the frame 2000 - 2004. To conclude, this study let us to identify a multitude of clustering space-time features of forest fires in Portugal, which can be useful for a better planning of educational activities and prevention campaigns as well as for a better allocation of monitoring systems and firefighting. References: Tonini M., Pereira M. G., Parente J. (2016) - Evolution of forest fires in Portugal: from spatio-temporal point events to smoothed density maps. Natural Hazard, doi:10.1007/s11069-016-2637-x Lu B., Harris P., Charlton M., Brunsdon C. (2014) - The GWmodel R package: further topics for exploring spatial heterogeneity using geographically weighted models. Geo-spatial Information Science, Vol. 17: 85-101 Rowlingson B., Diggle P., Bivand M.R. (2012) - Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, Vol. 19: 627-655 Acknowledgements: This work was supported by: (i) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; (ii) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033. We are especially grateful to ICNF for providing the fire.

  7. Quantification of annual wildfire risk; A spatio-temporal point process approach.

    Directory of Open Access Journals (Sweden)

    Paula Pereira

    2013-10-01

    Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.

  8. Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

    Science.gov (United States)

    Luan, Hui; Law, Jane; Quick, Matthew

    2015-12-30

    Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

  9. Spatio-temporal networks: reachability, centrality and robustness.

    Science.gov (United States)

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

  10. Aspects of second-order analysis of structured inhomogeneous spatio-temporal processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    2012-01-01

    Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for general inhomogeneous spatio-temporal point processes and for inhomogeneous spatio-temporal Cox processes. Assuming spatio......-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio-temporal Gaussian process. Another...... concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data....

  11. Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts

    Science.gov (United States)

    Wang, M.; Kamarianakis, Y.; Georgescu, M.

    2017-12-01

    A suite of 10-year ensemble-based simulations was conducted to investigate the hydroclimatic impacts due to large-scale deployment of perennial bioenergy crops across the continental United States. Given the large size of the simulated dataset (about 60Tb), traditional hierarchical spatio-temporal statistical modelling cannot be implemented for the evaluation of physics parameterizations and biofuel impacts. In this work, we propose a filtering algorithm that takes into account the spatio-temporal autocorrelation structure of the data while avoiding spatial confounding. This method is used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations and observational datasets. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.

  12. Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2017-11-01

    Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

  13. Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

  14. Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

    Science.gov (United States)

    Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

    2017-09-01

    Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

  15. State estimation of spatio-temporal phenomena

    Science.gov (United States)

    Yu, Dan

    This dissertation addresses the state estimation problem of spatio-temporal phenomena which can be modeled by partial differential equations (PDEs), such as pollutant dispersion in the atmosphere. After discretizing the PDE, the dynamical system has a large number of degrees of freedom (DOF). State estimation using Kalman Filter (KF) is computationally intractable, and hence, a reduced order model (ROM) needs to be constructed first. Moreover, the nonlinear terms, external disturbances or unknown boundary conditions can be modeled as unknown inputs, which leads to an unknown input filtering problem. Furthermore, the performance of KF could be improved by placing sensors at feasible locations. Therefore, the sensor scheduling problem to place multiple mobile sensors is of interest. The first part of the dissertation focuses on model reduction for large scale systems with a large number of inputs/outputs. A commonly used model reduction algorithm, the balanced proper orthogonal decomposition (BPOD) algorithm, is not computationally tractable for large systems with a large number of inputs/outputs. Inspired by the BPOD and randomized algorithms, we propose a randomized proper orthogonal decomposition (RPOD) algorithm and a computationally optimal RPOD (RPOD*) algorithm, which construct an ROM to capture the input-output behaviour of the full order model, while reducing the computational cost of BPOD by orders of magnitude. It is demonstrated that the proposed RPOD* algorithm could construct the ROM in real-time, and the performance of the proposed algorithms on different advection-diffusion equations. Next, we consider the state estimation problem of linear discrete-time systems with unknown inputs which can be treated as a wide-sense stationary process with rational power spectral density, while no other prior information needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input

  16. Characteristics of juvenile survivors reveal spatio-temporal differences in early life stage survival of Baltic cod

    DEFF Research Database (Denmark)

    Huwer, Bastian; Hinrichsen, H.H.; Böttcher, U.

    2014-01-01

    with previous modeling studies on the survival chances of early-stage larvae and with general spatio-temporal patterns of larval prey availability suggests that differences in survival are related to food availability during the early larval stage. Results are discussed in relation to the recruitment process...

  17. Spatio-temporal data analytics for wind energy integration

    CERN Document Server

    Yang, Lei; Zhang, Junshan

    2014-01-01

    This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic di

  18. Spatio-Temporal Data Mining for Location-Based Services

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo

    . The objectives of the presented thesis are three-fold. First, to extend popular data mining methods to the spatio-temporal domain. Second, to demonstrate the usefulness of the extended methods and the derived knowledge in promising LBS examples. Finally, to eliminate privacy concerns in connection with spatio......-temporal data mining by devising systems for privacy-preserving location data collection and mining.......Location-Based Services (LBS) are continuously gaining popularity. Innovative LBSes integrate knowledge about the users into the service. Such knowledge can be derived by analyzing the location data of users. Such data contain two unique dimensions, space and time, which need to be analyzed...

  19. Spatio-temporal modeling of nonlinear distributed parameter systems

    CERN Document Server

    Li, Han-Xiong

    2011-01-01

    The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

  20. Estimating the state of large spatio-temporally chaotic systems

    International Nuclear Information System (INIS)

    Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

    2004-01-01

    We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

  1. Climate-driven changes to the spatio-temporal distribution of the parasitic nematode, Haemonchus contortus, in sheep in Europe.

    Science.gov (United States)

    Rose, Hannah; Caminade, Cyril; Bolajoko, Muhammad Bashir; Phelan, Paul; van Dijk, Jan; Baylis, Matthew; Williams, Diana; Morgan, Eric R

    2016-03-01

    Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio-temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan-European spatio-temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within-host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2-3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary

  2. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

    Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

    2013-01-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model

  3. Spatio-temporal point process filtering methods with an application

    Czech Academy of Sciences Publication Activity Database

    Frcalová, B.; Beneš, V.; Klement, Daniel

    2010-01-01

    Roč. 21, 3-4 (2010), s. 240-252 ISSN 1180-4009 R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z50110509 Keywords : cox point process * filtering * spatio-temporal modelling * spike Subject RIV: BA - General Mathematics Impact factor: 0.750, year: 2010

  4. Spatio-temporal analysis of Salmonella surveillance data in Thailand

    DEFF Research Database (Denmark)

    Coutinho Calado Domingues, Ana Rita; Vieira, Antonio; Hendriksen, Rene S.

    2014-01-01

    This study evaluates the usefulness of spatio-temporal statistical tools to detect outbreaks using routine surveillance data where limited epidemiological information is available. A dataset from 2002 to 2007 containing information regarding date, origin, source and serotype of 29 586 Salmonella ...

  5. On spatio-temporal Lévy based Cox processes

    DEFF Research Database (Denmark)

    Prokesova, Michaela; Hellmund, Gunnar; Jensen, Eva Bjørn Vedel

    2006-01-01

    The paper discusses a new class of models for spatio-temporal Cox point processes. In these models, the driving field is defined by means of an integral of a weight function with respect to a Lévy basis. The relations to other Cox process models studied previously are discussed and formulas for t...

  6. Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

    Directory of Open Access Journals (Sweden)

    Zhiqiang Tian

    2013-03-01

    Full Text Available Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC. Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms.

  7. Spatio-temporal joins on symbolic indoor tracking data

    DEFF Research Database (Denmark)

    Lu, Hua; Yang, Bin; Jensen, Christian S.

    2011-01-01

    and studies probabilistic, spatio-temporal joins on historical indoor tracking data. Two meaningful types of join are defined. They return object pairs that satisfy spatial join predicates either at a time point or during a time interval. The predicates considered include “same X,” where X is a semantic...

  8. Control and characterization of spatio-temporal disorder in ...

    Indian Academy of Sciences (India)

    characterizing the type of spatio-temporal disorder that is embodied in this disordered ... The results from this experiment will shed light on the more general questions ... sponds to only odd or even multiples of the common frequency, ω0. Thus ...

  9. Simultaneous spatio-temporal focusing for tissue manipulation

    Directory of Open Access Journals (Sweden)

    Squier J.

    2013-11-01

    Full Text Available Simultaneous spatiotemporal focusing (SSTF is applied to lens tissue and compared directly with standard femtosecond micromachining of the tissue at the same numerical aperture. Third harmonic generation imaging is used for spatio-temporal characterization of the processing conditions obtained with both a standard and SSTF focus.

  10. Spatio-temporal gait disorder and gait fatigue index in a six-minute walk test in women with fibromyalgia.

    Science.gov (United States)

    Heredia-Jimenez, Jose; Latorre-Roman, Pedro; Santos-Campos, Maria; Orantes-Gonzalez, Eva; Soto-Hermoso, Victor M

    2016-03-01

    Gait disorders in fibromyalgia patients affect several gait parameters and different muscle recruitment patterns. The aim of this study was to assess the gait differences observed during a six-minute walk test between fibromyalgia patients and healthy controls. Forty-eight women with fibromyalgia and 15 healthy women were evaluated. Fibromyalgia patients met the American College of Rheumatology criteria for fibromyalgia selected of an ambulatory care. Both patients and controls had a negative history of musculoskeletal disease, neurological disorders, and gait abnormalities. The 15 controls were healthy women matched to the patients in age, height and body weight. Spatio-temporal gait variables and the rate of perceived exertion during the six-minute walk test (all subjects) and Fibromyalgia Impact Questionnaire (fibromyalgia subjects) were evaluated. All walking sets on the GaitRITE were collected and the gait variables were selected at three stages during the six-minute walk test: two sets at the beginning, two sets at 3 min and two sets at the end of the test. In addition, the Fibromyalgia Impact Questionnaire was used for the fibromyalgia patients. Fibromyalgia patients showed a significant decrease in all spatio-temporal gait variables at each of the three stages and had a lower walk distance covered in the six-minute walk test and higher rate of perceived exertion. No correlations were found between the Fibromyalgia Impact Questionnaire and gait variables. The fibromyalgia and control subjects showed lower gait fatigue indices between the middle and last stages. Gait analysis during a six-minute walk test is a good tool to assess the fatigue and physical symptoms of patients with fibromyalgia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010.

    Directory of Open Access Journals (Sweden)

    Juliette Paireau

    2014-05-01

    Full Text Available BACKGROUND: Epidemics of meningococcal meningitis (MM recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger. METHODOLOGY/PRINCIPAL FINDINGS: To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR = 0.656, 95% Credible Interval (CI 0.405-0.949 and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502 were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695, the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474 and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910. At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks. CONCLUSIONS: Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

  12. Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010.

    Science.gov (United States)

    Paireau, Juliette; Maïnassara, Halima B; Jusot, Jean-François; Collard, Jean-Marc; Idi, Issa; Moulia-Pelat, Jean-Paul; Mueller, Judith E; Fontanet, Arnaud

    2014-05-01

    Epidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger. To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405-0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks. Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

  13. McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

  14. A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

    Directory of Open Access Journals (Sweden)

    LI Yinchao

    2016-07-01

    Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

  15. Approximate spatio-temporal top-k publish/subscribe

    KAUST Repository

    Chen, Lisi; Shang, Shuo

    2018-01-01

    Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

  16. Spatial and spatio-temporal bayesian models with R - INLA

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

    Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

  17. Approximate spatio-temporal top-k publish/subscribe

    KAUST Repository

    Chen, Lisi

    2018-04-26

    Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

  18. A Spatio-Temporal Analysis of Mitochondrial DNA Haplogroup I

    Directory of Open Access Journals (Sweden)

    Revesz Peter Z.

    2016-01-01

    Full Text Available The recent recovery of ancient DNA from a growing number of human samples shows that mitochondrial DNA haplogroup I was introduced to Europe after the end of the Last Glacial Maximum. This paper provides a spatio-temporal analysis of the various subhaplogroups of mitochondrial DNA I. The study suggests that haplogroup I diversified into haplogroups I1, I2’3, I4 and I5 at specific regions in Eurasia and then spread southward to Crete and Egypt.

  19. Spatio-temporal reasoning and decision support tools

    OpenAIRE

    Renso, Chiara; Wachowicz, Monica

    2014-01-01

    Currently, mobility data is revolutionizing the traditional fields of spatio-temporal reasoning and decision making analysis, not only to scale-up to the large and growing data volumes, but also to address complex questions related to change, trends, duration, and evolution. In mobility data, space and time are inextricably linked, since humans, robots and systems that dynamically act, and interact within social networks, are embedded in space, and any change is often the result of actions an...

  20. Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011.

    Science.gov (United States)

    Horwood, Paul F; Karl, Stephan; Mueller, Ivo; Jonduo, Marinjho H; Pavlin, Boris I; Dagina, Rosheila; Ropa, Berry; Bieb, Sibauk; Rosewell, Alexander; Umezaki, Masahiro; Siba, Peter M; Greenhill, Andrew R

    2014-08-20

    Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in >15,500 cases and >500 deaths. Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.

  1. Brazilian Amazonia Deforestation Detection Using Spatio-Temporal Scan Statistics

    Science.gov (United States)

    Vieira, C. A. O.; Santos, N. T.; Carneiro, A. P. S.; Balieiro, A. A. S.

    2012-07-01

    The spatio-temporal models, developed for analyses of diseases, can also be used for others fields of study, including concerns about forest and deforestation. The aim of this paper is to quantitatively check priority areas in order to combat deforestation on the Amazon forest, using the space-time scan statistic. The study area location is at the south of the Amazonas State and cover around 297.183 kilometre squares, including the municipality of Boca do Acre, Labrea, Canutama, Humaita, Manicore, Novo Aripuana e Apui County on the north region of Brazil. This area has showed a significant change for land cover, which has increased the number of deforestation's alerts. Therefore this situation becomes a concern and gets more investigation, trying to stop factors that increase the number of cases in the area. The methodology includes the location and year that deforestation's alert occurred. These deforestation's alerts are mapped by the DETER (Detection System of Deforestation in Real Time in Amazonia), which is carry out by the Brazilian Space Agency (INPE). The software SatScanTM v7.0 was used in order to define space-time permutation scan statistic for detection of deforestation cases. The outcome of this experiment shows an efficient model to detect space-time clusters of deforestation's alerts. The model was efficient to detect the location, the size, the order and characteristics about activities at the end of the experiments. Two clusters were considered actives and kept actives up to the end of the study. These clusters are located in Canutama and Lábrea County. This quantitative spatial modelling of deforestation warnings allowed: firstly, identifying actives clustering of deforestation, in which the environment government official are able to concentrate their actions; secondly, identifying historic clustering of deforestation, in which the environment government official are able to monitoring in order to avoid them to became actives again; and finally

  2. BRAZILIAN AMAZONIA DEFORESTATION DETECTION USING SPATIO-TEMPORAL SCAN STATISTICS

    Directory of Open Access Journals (Sweden)

    C. A. O. Vieira

    2012-07-01

    Full Text Available The spatio-temporal models, developed for analyses of diseases, can also be used for others fields of study, including concerns about forest and deforestation. The aim of this paper is to quantitatively check priority areas in order to combat deforestation on the Amazon forest, using the space-time scan statistic. The study area location is at the south of the Amazonas State and cover around 297.183 kilometre squares, including the municipality of Boca do Acre, Labrea, Canutama, Humaita, Manicore, Novo Aripuana e Apui County on the north region of Brazil. This area has showed a significant change for land cover, which has increased the number of deforestation's alerts. Therefore this situation becomes a concern and gets more investigation, trying to stop factors that increase the number of cases in the area. The methodology includes the location and year that deforestation’s alert occurred. These deforestation's alerts are mapped by the DETER (Detection System of Deforestation in Real Time in Amazonia, which is carry out by the Brazilian Space Agency (INPE. The software SatScanTM v7.0 was used in order to define space-time permutation scan statistic for detection of deforestation cases. The outcome of this experiment shows an efficient model to detect space-time clusters of deforestation’s alerts. The model was efficient to detect the location, the size, the order and characteristics about activities at the end of the experiments. Two clusters were considered actives and kept actives up to the end of the study. These clusters are located in Canutama and Lábrea County. This quantitative spatial modelling of deforestation warnings allowed: firstly, identifying actives clustering of deforestation, in which the environment government official are able to concentrate their actions; secondly, identifying historic clustering of deforestation, in which the environment government official are able to monitoring in order to avoid them to became

  3. Visual search of cyclic spatio-temporal events

    Science.gov (United States)

    Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

    2018-05-01

    The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

  4. Spatio-temporal models of mental processes from fMRI.

    Science.gov (United States)

    Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

    2011-07-15

    Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. Spatio-temporal analysis of Modified Omori law in Bayesian framework

    Science.gov (United States)

    Rezanezhad, V.; Narteau, C.; Shebalin, P.; Zoeller, G.; Holschneider, M.

    2017-12-01

    This work presents a study of the spatio temporal evolution of the modified Omori parameters in southern California in then time period of 1981-2016. A nearest-neighbor approach is applied for earthquake clustering. This study targets small mainshocks and corresponding big aftershocks ( 2.5 ≤ mmainshocks ≤ 4.5 and 1.8 ≤ maftershocks ≤ 2.8 ). We invert for the spatio temporal behavior of c and p values (especially c) all over the area using a MCMC based maximum likelihood estimator. As parameterizing families we use Voronoi cells with randomly distributed cell centers. Considering that c value represents a physical character like stress change we expect to see a coherent c value pattern over seismologically coacting areas. This correlation of c valus can actually be seen for the San Andreas, San Jacinto and Elsinore faults. Moreover, the depth dependency of c value is studied which shows a linear behavior of log(c) with respect to aftershock's depth within 5 to 15 km depth.

  6. Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method

    International Nuclear Information System (INIS)

    Nasser, Hassan; Cessac, Bruno; Marre, Olivier

    2013-01-01

    Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles. (paper)

  7. Spatio-Temporal Encoding in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik

    2005-01-01

    In this dissertation two methods for spatio-temporal encoding in medical ultrasound imaging are investigated. The first technique is based on a frequency division approach. Here, the available spectrum of the transducer is divided into a set of narrow bands. A waveform is designed for each band...... the signal to noise ratio and simultaneously the penetration depth so that the medical doctor can image deeper lying structures. The method is tested both experimentally and in simulation and has also evaluated for the purpose of blood flow estimation. The work presented is based on four papers which...

  8. Scalable Top-k Spatio-Temporal Term Querying

    DEFF Research Database (Denmark)

    Skovsgaard, Anders; Sidlauskas, Darius; Jensen, Christian Søndergaard

    2014-01-01

    With the rapidly increasing deployment of Internet-connected, location-aware mobile devices, very large and increasing amounts of geo-tagged and timestamped user-generated content, such as microblog posts, are being generated. We present indexing, update, and query processing techniques...... that are capable of providing the top-k terms seen in posts in a user-specified spatio-temporal range. The techniques enable interactive response times in the millisecond range in a realistic setting where the arrival rate of posts exceeds today's average tweet arrival rate by a factor of 4-10. The techniques...

  9. Estimating spatio-temporal dynamics of size-structured populations

    DEFF Research Database (Denmark)

    Kristensen, Kasper; Thygesen, Uffe Høgsbro; Andersen, Ken Haste

    2014-01-01

    with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between size classes within each trawl haul due to clustering...... of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort...

  10. Using climate information to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

    Science.gov (United States)

    Dommar, C. J.; Lowe, R.; Robinson, M.; Rodó, X.

    2013-12-01

    The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

  11. Climate-driven mathematical models to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

    Science.gov (United States)

    Dommar, Carlos J.; Robinson, Marguerite; Lowe, Rachel; Conan, Anne; Buchy, Philippe; Tarantola, Arnaud; Rodó, Xavier

    2014-05-01

    The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

  12. Mortality from Suicide in the Municipalities of Mainland Portugal: Spatio-Temporal Evolution between 1980 and 2015

    Directory of Open Access Journals (Sweden)

    Adriana Loureiro

    2018-01-01

    Full Text Available Introduction: Suicide is considered a public health priority. It is a complex phenomenon resulting from the interaction of several factors, which do not depend solely on individual conditions. This study analyzes the spatio-temporal evolution of suicide mortality between 1980 and 2015, identifying areas of high risk, and their variation, in the 278 municipalities of Continental Portugal. Material and Methods: Based on the number of self-inflicted injuries and deaths from suicide and the resident population, the spatio-temporal evolution of the suicide mortality rate was assessed via: i a Poisson joinpoint regression model, and ii spatio-temporal clustering methods. Results: The suicide mortality rate evolution showed statistically significant increases over three periods (1980 - 1984; 1999 - 2002 and 2006 - 2015 and two statistically significant periods of decrease (1984 - 1995 and 1995 - 1999. The spatio-temporal analysis identified five clusters of high suicide risk (relative risk >1 and four clusters of low suicide risk (relative risk < 1. Discussion: The periods when suicide mortality increases seem to overlap with times of economic and financial instability. The geographical pattern of suicide risk has changed: presently, the suicide rates from the municipalities in the Center and North are showing more similarity with those seen in the South, thus increasing the ruralization of the phenomenon of suicide. Conclusion: Between 1980 and 2015 the spacio-temporal pattern of mortality from suicide has been changing and is a phenomenon that is currently experiencing a growing trend (since 2006 and is of higher risk in rural areas.

  13. A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

    Directory of Open Access Journals (Sweden)

    Min Deng

    2016-02-01

    Full Text Available Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed for space-time processes that exhibit stationarity in space and time. It is still challenging to model heterogeneity of space-time data in the interpolation model. To overcome this limitation, in this study, a novel space-time interpolation method considering both spatial and temporal heterogeneity is developed for estimating missing data in space-time datasets. The interpolation operation is first implemented in spatial and temporal dimensions. Heterogeneous covariance functions are constructed to obtain the best linear unbiased estimates in spatial and temporal dimensions. Spatial and temporal correlations are then considered to combine the interpolation results in spatial and temporal dimensions to estimate the missing data. The proposed method is tested on annual average temperature and precipitation data in China (1984–2009. Experimental results show that, for these datasets, the proposed method outperforms three state-of-the-art methods—e.g., spatio-temporal kriging, spatio-temporal inverse distance weighting, and point estimation model of biased hospitals-based area disease estimation methods.

  14. Trends in spatio-temporal dynamics of visceral leishmaniasis cases in a highly-endemic focus of Bihar, India: an investigation based on GIS tools.

    Science.gov (United States)

    Mandal, Rakesh; Kesari, Shreekant; Kumar, Vijay; Das, Pradeep

    2018-04-02

    Visceral leishmaniasis (VL) in Bihar State (India) continues to be endemic, despite the existence of effective treatment and a vector control program to control disease morbidity. A clear understanding of spatio-temporal distribution of VL may improve surveillance and control implementation. This study explored the trends in spatio-temporal dynamics of VL endemicity at a meso-scale level in Vaishali District, based on geographical information systems (GIS) tools and spatial statistical analysis. A GIS database was used to integrate the VL case data from the study area between 2009 and 2014. All cases were spatially linked at a meso-scale level. Geospatial techniques, such as GIS-layer overlaying and mapping, were employed to visualize and detect the spatio-temporal patterns of a VL endemic outbreak across the district. The spatial statistic Moran's I Index (Moran's I) was used to simultaneously evaluate spatial-correlation between endemic villages and the spatial distribution patterns based on both the village location and the case incidence rate (CIR). Descriptive statistics such as mean, standard error, confidence intervals and percentages were used to summarize the VL case data. There were 624 endemic villages with 2719 (average 906 cases/year) VL cases during 2012-2014. The Moran's I revealed a cluster pattern (P < 0.05) of CIR distribution at the meso-scale level. On average, 68 villages were newly-endemic each year. Of which 93.1% of villages' endemicity were found to have occurred on the peripheries of the previous year endemic villages. The mean CIR of the endemic villages that were peripheral to the following year newly-endemic villages, compared to all endemic villages of the same year, was higher (P < 0.05). The results show that the VL endemicity of new villages tends to occur on the periphery of villages endemic in the previous year. High-CIR plays a major role in the spatial dispersion of the VL cases between non-endemic and endemic villages

  15. Research on Process-oriented Spatio-temporal Data Model

    Directory of Open Access Journals (Sweden)

    XUE Cunjin

    2016-02-01

    Full Text Available According to the analysis of the present status and existing problems of spatio-temporal data models developed in last 20 years,this paper proposes a process-oriented spatio-temporal data model (POSTDM,aiming at representing,organizing and storing continuity and gradual geographical entities. The dynamic geographical entities are graded and abstracted into process objects series from their intrinsic characteristics,which are process objects,process stage objects,process sequence objects and process state objects. The logical relationships among process entities are further studied and the structure of UML models and storage are also designed. In addition,through the mechanisms of continuity and gradual changes impliedly recorded by process objects,and the modes of their procedure interfaces offered by the customized ObjcetStorageTable,the POSTDM can carry out process representation,storage and dynamic analysis of continuity and gradual geographic entities. Taking a process organization and storage of marine data as an example,a prototype system (consisting of an object-relational database and a functional analysis platform is developed for validating and evaluating the model's practicability.

  16. Spatio-temporal statistical models with applications to atmospheric processes

    International Nuclear Information System (INIS)

    Wikle, C.K.

    1996-01-01

    This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model

  17. Spatio-Temporal Dynamics of Viruses are Differentially Affected by Parasitoids Depending on the Mode of Transmission

    Directory of Open Access Journals (Sweden)

    Elisa Viñuela

    2012-11-01

    Full Text Available Relationships between agents in multitrophic systems are complex and very specific. Insect-transmitted plant viruses are completely dependent on the behaviour and distribution patterns of their vectors. The presence of natural enemies may directly affect aphid behaviour and spread of plant viruses, as the escape response of aphids might cause a potential risk for virus dispersal. The spatio-temporal dynamics of Cucumber mosaic virus (CMV and Cucurbit aphid-borne yellows virus (CABYV, transmitted by Aphis gossypii in a non-persistent and persistent manner, respectively, were evaluated at short and long term in the presence and absence of the aphid parasitoid, Aphidius colemani. SADIE methodology was used to study the distribution patterns of both the virus and its vector, and their degree of association. Results suggested that parasitoids promoted aphid dispersion at short term, which enhanced CMV spread, though consequences of parasitism suggest potential benefits for disease control at long term. Furthermore, A. colemani significantly limited the spread and incidence of the persistent virus CABYV at long term. The impact of aphid parasitoids on the dispersal of plant viruses with different transmission modes is discussed.

  18. The spatio-temporal Development of Copenhagen's bicycle infrastructure 1912-2013

    DEFF Research Database (Denmark)

    Carstensen, Trine Agervig; Olafsson, Anton Stahl; Bech, Nynne Marie

    2015-01-01

    Cycling plays an important role in low-carbon transitions. Around the globe, cities are constructing bicycle infrastructure. The city of Copenhagen has a bicycle-friendly infrastructure celebrated for its fine-meshed network. This study documents the spatio-temporal development of Copenhagen......’s bicycle infrastructure and explores how the development corresponds to other processes of urban transformation. The study builds on historical maps of bicycle infrastructure that are digitised into geographical information, which allows for a comprehensive analysis of the formation of the network....... In search for identifying drivers, the study analyses the city’s spatial growth pattern, migration pattern, development of road network and changes in the transport culture. Analyses reveal that the bicycle infrastructure expanded at a relatively constant pace during distinct periods of urban transformation...

  19. Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

    Science.gov (United States)

    Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

    2017-04-01

    Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

  20. A spatio-temporal analysis of suicide in El Salvador.

    Science.gov (United States)

    Carcach, Carlos

    2017-04-20

    In 2012, international statistics showed El Salvador's suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML) and population counts, from the Dirección General de Estadística y Censos (DIGESTYC), for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide) across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time-persistent clusters with a large rate of death by suicide. In

  1. Cartography in the Age of Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    WANG Jiayao

    2017-10-01

    Full Text Available Cartography is an ancient science with almost the same long history as the world's oldest culture.Since ancient times,the movement and change of anything and any phenomena,including human activities,have been carried out in a certain time and space.The development of science and technology and the progress of social civilization have made social management and governance more and more dependent on time and space.The information source,theme,content,carrier,form,production methods and application methods of map are different in different historical periods,so that its all-round value is different. With the arrival of the big data age,the scientific paradigm has now entered the era of "data-intensive" paradigm,so is the cartography,with obvious characteristics of big data science.All big data are caused by movement and change of all things and phenomena in the geographic world,so they have space and time characteristics and thus cannot be separated from the spatial reference and time reference.Therefore,big data is big spatio-temporal data essentially.Since the late 1950s and early 1960s,modern cartography,that is,the cartography in the information age,takes spatio-temporal data as the object,and focuses on the processing and expression of spatio-temporal data,but not in the face of the large scale multi-source heterogeneous and multi-dimensional dynamic data flow(or flow datafrom sky to the sea.The real-time dynamic nature,the theme pertinence,the content complexity,the carrier diversification,the expression form personalization,the production method modernization,the application ubiquity of the map,is incomparable in the past period,which leads to the great changes of the theory,technology and application system of cartography.And all these changes happen to occur in the 60 years since the late 1950s and early 1960s,so this article was written to commemorate the 60th anniversary of the "Acta Geodaetica et Cartographica Sinica".

  2. A spatio-temporal analysis of suicide in El Salvador

    Directory of Open Access Journals (Sweden)

    Carlos Carcach

    2017-04-01

    Full Text Available Abstract Background In 2012, international statistics showed El Salvador’s suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. Methods A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML and population counts, from the Dirección General de Estadística y Censos (DIGESTYC, for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. Results The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Conclusions Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time

  3. Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

    KAUST Repository

    Zhang, Bohai

    2014-01-01

    Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is proposed to select knots automatically from a discrete set of spatio-temporal points. Our approach is applicable to nonseparable and nonstationary spatio-temporal covariance models. We illustrate the effectiveness of our method through simulation experiments and application to an ozone measurement dataset.

  4. The surface chemistry determines the spatio-temporal interaction dynamics of quantum dots in atherosclerotic lesions.

    Science.gov (United States)

    Uhl, Bernd; Hirn, Stephanie; Mildner, Karina; Coletti, Raffaele; Massberg, Steffen; Reichel, Christoph A; Rehberg, Markus; Zeuschner, Dagmar; Krombach, Fritz

    2018-03-01

    To optimize the design of nanoparticles for diagnosis or therapy of vascular diseases, it is mandatory to characterize the determinants of nano-bio interactions in vascular lesions. Using ex vivo and in vivo microscopy, we analyzed the interactive behavior of quantum dots with different surface functionalizations in atherosclerotic lesions of ApoE-deficient mice. We demonstrate that quantum dots with different surface functionalizations exhibit specific interactive behaviors with distinct molecular and cellular components of the injured vessel wall. Moreover, we show a role for fibrinogen in the regulation of the spatio-temporal interaction dynamics in atherosclerotic lesions. Our findings emphasize the relevance of surface chemistry-driven nano-bio interactions on the differential in vivo behavior of nanoparticles in diseased tissue.

  5. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  6. A spatio-temporal extension to the map cube operator

    Science.gov (United States)

    Alzate, Juan C.; Moreno, Francisco J.; Echeverri, Jaime

    2012-09-01

    OLAP (On Line Analytical Processing) is a set of techniques and operators to facilitate the data analysis usually stored in a data warehouse. In this paper, we extend the functionality of an OLAP operator known as Map Cube with the definition and incorporation of a function that allows the formulation of spatio-temporal queries. For example, consider a data warehouse about crimes that includes data about the places where the crimes were committed. Suppose we want to find and visualize the trajectory (a trajectory is just the path that an object follows through space as a function of time) of the crimes of a suspect beginning with his oldest crime and ending with his most recent one. In order to meet this requirement, we extend the Map Cube operator.

  7. Spatio-temporal behaviour of medium-range ensemble forecasts

    Science.gov (United States)

    Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

    2010-05-01

    Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

  8. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  9. Spatio-temporal modelling of rainfall in the Murray-Darling Basin

    Science.gov (United States)

    Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

    2018-02-01

    The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

  10. Spatio-temporal regulation of circular RNA expression during porcine embryonic brain development

    DEFF Research Database (Denmark)

    Venø, Morten T; Hansen, Thomas B; Venø, Susanne T

    2015-01-01

    BACKGROUND: Recently, thousands of circular RNAs (circRNAs) have been discovered in various tissues and cell types from human, mouse, fruit fly and nematodes. However, expression of circRNAs across mammalian brain development has never been examined. RESULTS: Here we profile the expression of circ......RNA in five brain tissues at up to six time-points during fetal porcine development, constituting the first report of circRNA in the brain development of a large animal. An unbiased analysis reveals a highly complex regulation pattern of thousands of circular RNAs, with a distinct spatio-temporal expression...... are functionally conserved between mouse and human. Furthermore, we observe that "hot-spot" genes produce multiple circRNA isoforms, which are often differentially expressed across porcine brain development. A global comparison of porcine circRNAs reveals that introns flanking circularized exons are longer than...

  11. Spatio-temporal observations of the tertiary ozone maximum

    Directory of Open Access Journals (Sweden)

    V. F. Sofieva

    2009-07-01

    Full Text Available We present spatio-temporal distributions of the tertiary ozone maximum (TOM, based on GOMOS (Global Ozone Monitoring by Occultation of Stars ozone measurements in 2002–2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at an altitude of ~72 km. Although the explanation for this phenomenon has been found recently – low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses – models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time to obtain spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere.

    The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory, TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of the tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model and found that the specific features are reproduced satisfactorily by the model.

    Since ozone in the mesosphere is very sensitive to HOx concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HOx enhancement from the increased ionization.

  12. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    Science.gov (United States)

    Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.

    2015-12-01

    In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.

  13. Spatio-temporal foreshock activity during stick-slip experiments of large rock samples

    Science.gov (United States)

    Tsujimura, Y.; Kawakata, H.; Fukuyama, E.; Yamashita, F.; Xu, S.; Mizoguchi, K.; Takizawa, S.; Hirano, S.

    2016-12-01

    spatio-temporal pattern. This work was supported by NIED research project "Development of monitoring and forecasting technology for crustal activity", JSPS KAKENHI Grant Number 23340131, and MEXT of Japan, under its Earthquake and Volcano Hazards Observation and Research Program.

  14. a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

    Science.gov (United States)

    Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

    2017-09-01

    Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

  15. Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

    Science.gov (United States)

    Ironi, Liliana; Tentoni, Stefania

    2007-02-01

    This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

  16. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    Science.gov (United States)

    Lowe, R.; Chirombo, J.; Tompkins, A. M.

    2012-04-01

    the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a negative binomial generalised linear mixed model (GLMM) is adopted, which includes structured and unstructured spatial and temporal random effects. The parameters in this spatio-temporal Bayesian hierarchical model are estimated using Markov Chain Monte Carlo (MCMC). This allows posterior predictive distributions for disease risk to be derived for each spatial location and time period. A novel visualisation technique is then used to display seasonal probabilistic forecasts of malaria risk, derived from the developed model using pre-defined risk category thresholds, on a map. This technique allows decision makers to identify areas where the model predicts with certainty a particular malaria risk category (high, medium or low); in order to effectively target limited resources to those districts most at risk for a given season.

  17. Spatio-temporal regulation of Hsp90-ligand complex leads to immune activation.

    Directory of Open Access Journals (Sweden)

    Yasuaki eTamura

    2016-05-01

    Full Text Available Hsp90 is the most abundant cytosolic HSP and is known to act as a molecular chaperone. We found that an Hsp90-cancer antigen peptide complex was efficiently cross-presented by human monocyte-derived dendritic cells and induced peptide-specific cytotoxic T lymphocytes. Furthermore, we observed that the internalized Hsp90-peptide complex was strictly sorted to the Rab5+, EEA1+ static early endosome and the Hsp90-chaperoned peptide was processed and bound to MHC class I molecules through a endosome-recycling pathway. We also found that extracellular Hsp90 complexed with CpG-A or self-DNA stimulates production of a large amount of IFN-α from pDCs via static early endosome targeting. Thus, extracellular Hsp90 can target the antigen or nucleic acid to a static early endosome by spatio-temporal regulation. Moreover, we showed that Hsp90 associates with and delivers TLR7/9 from the ER to early endosomes for ligand recognition. Hsp90 inhibitor, geldanamycin derivative inhibited the Hsp90 association with TLR7/9, resulting in inhibition IFN-α production, leading to improvement of SLE symptoms. Interstingly, we observed that serum Hsp90 is clearly increased in patients with active SLE compared with that in patients with inactive disease. Serum Hsp90 detected in SLE patients binds to self-DNA and/or anti-DNA Ab, thus leading to stimulation of pDCs to produce IFN-α. Thus, Hsp90 plays a crucial role in the pathogenesis of SLE and that an Hsp90 inhibitor will therefore provide a new therapeutic approach to SLE and other nucleic acid-related autoimmune diseases. We will discuss how spatio-temporal regulation of Hsp90-ligand complexes within antigen-presenting cells affects the innate immunity and adaptive immunity.

  18. Spatio-temporal heterogeneity of riparian soil morphology in a restored floodplain

    Science.gov (United States)

    Fournier, B.; Guenat, C.; Bullinger-Weber, G.; Mitchell, E. A. D.

    2013-10-01

    Floodplains have been intensively altered in industrialized countries, but are now increasingly being restored. It is therefore important to assess the effect of these restoration projects on the aquatic and terrestrial components of ecosystems. However, despite being functionally crucial components of terrestrial ecosystems, soils are generally overlooked in floodplain restoration assessments. We studied the spatio-temporal heterogeneity of soil morphology in a restored (riverbed widening) river reach along the River Thur (Switzerland) using three criteria (soil diversity, dynamism and typicality) and their associated indicators. We hypothesized that these criteria would correctly discriminate the post-restoration changes in soil morphology, and that these changes correspond to patterns of vascular plant diversity. Soil diversity and dynamism increased 5 yr after the restoration, but some typical soils of braided rivers were still missing. Soil typicality and dynamism were correlated to vegetation changes. These results suggest a limited success of the project, in agreement with evaluations carried out at the same site using other, more resource-demanding, methods (e.g., soil fauna, fish diversity, ecosystem functioning). Soil morphology provides structural and functional information on floodplain ecosystems. The spatio-temporal heterogeneity of soil morphology represents a cost-efficient ecological indicator that could easily be integrated into rapid assessment protocols of floodplain and river restoration projects. The follow-up assessment after several major floods (≥ HQ20) should take place to allow for testing the longer-term validity of our conclusion for the River Thur site. More generally, it would be useful to apply the soil morphology indicator approach in different settings to test its broader applicability.

  19. Extensive spatio-temporal assessment of flood events by application of pair-copulas

    Directory of Open Access Journals (Sweden)

    M. Schulte

    2015-06-01

    Full Text Available Although the consequences of floods are strongly related to their peak discharges, a statistical classification of flood events that only depends on these peaks may not be sufficient for flood risk assessments. In many cases, the flood risk depends on a number of event characteristics. In case of an extreme flood, the whole river basin may be affected instead of a single watershed, and there will be superposition of peak discharges from adjoining catchments. These peaks differ in size and timing according to the spatial distribution of precipitation and watershed-specific processes of flood formation. Thus, the spatial characteristics of flood events should be considered as stochastic processes. Hence, there is a need for a multivariate statistical approach that represents the spatial interdependencies between floods from different watersheds and their coincidences. This paper addresses the question how these spatial interdependencies can be quantified. Each flood event is not only assessed with regard to its local conditions but also according to its spatio-temporal pattern within the river basin. In this paper we characterise the coincidence of floods by trivariate Joe-copula and pair-copulas. Their ability to link the marginal distributions of the variates while maintaining their dependence structure characterizes them as an adequate method. The results indicate that the trivariate copula model is able to represent the multivariate probabilities of the occurrence of simultaneous flood peaks well. It is suggested that the approach of this paper is very useful for the risk-based design of retention basins as it accounts for the complex spatio-temporal interactions of floods.

  20. Spatio-temporal changes in total annual rainfall and the annual number of rainy days

    International Nuclear Information System (INIS)

    Limjirakan, Sangchan; Limsakul, Atsamon

    2007-01-01

    Full text: Full text: Rainfall variability is a critical factor for Thailand's socioeconomic development. Thus, enhancing understanding of rainfall mechanisms and variability is of paramount importance for effective strategies in tackling the severe droughts/floods which are memorable and a recurring problem in Thailand. Through this study, we have examined the variability of total annual rainfall (R,otai) and the annual number of rainy days (Rday) in Thailand during 1951-2003, using an Empirical Orthogonal Function (EOF) analysis. The primary objective is to determine the dominant spatio-temporal patterns, and to illustrate their connection with the El Nino-Southern Oscillation (ENSO). The results reveal that the first two EOF modes, which explain nearly half of the total variance, show a good coherence of spatio-temporal structures. A salient feature of the leading modes of R,otal and Rday in Thailand is that their temporal coefficients exhibit significant relations to the ENSO. On an interannual timescale, the leading modes tended to be greater (lower) than normal during the La Nina (El Nino) phase of the ENSO. Changes in the Walker circulation appear to be the dominant mechanism whereby the ENSO exerts its influence on rainfall variability in Thailand. For an interdecadal timescale, there is evidence of the unusual and persistent deficit in Rtar accompanied by a concomitant reduction of Ranrd over the last three decades. The recent drought-like condition has been closely associated with the shift in the ENSO towards more El Nino events since the late 1970s, and coincided with the high global mean temperature. These natural/anthropogenic-induced climatic changes have important implications for rainfall forecasting, and consequently for water resource and agricultural planning and management in Thailand

  1. A hybrid spatio-temporal data indexing method for trajectory databases.

    Science.gov (United States)

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-07-21

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

  2. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Directory of Open Access Journals (Sweden)

    Shengnan Ke

    2014-07-01

    Full Text Available In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

  3. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Science.gov (United States)

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-01-01

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

  4. Building spatio-temporal database model based on ontological approach using relational database environment

    International Nuclear Information System (INIS)

    Mahmood, N.; Burney, S.M.A.

    2017-01-01

    Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges. (author)

  5. Spatio-temporal patterns of Campylobacter colonization in Danish broilers

    DEFF Research Database (Denmark)

    Chowdhury, S; Themudo, G E; Sandberg, M

    2013-01-01

    SUMMARY Despite a number of risk-factor studies in different countries, the epidemiology of Campylobacter colonization in broilers, particularly spatial dependencies, is still not well understood. A series of analyses (visualization and exploratory) were therefore conducted in order to obtain...

  6. Exploring spatio-temporal patterns in traffic congestion data

    DEFF Research Database (Denmark)

    Kveladze, Irma; Agerholm, Niels; Reinau, Kristian Hegner

    2017-01-01

    An efficient infrastructure is essential for economic development. However, economic growth has been closely connected to the increasing road transport. This increases traffic congestions significantly, and road network gets near or at its capacity limits. Hence, congestion has become a central...

  7. Assessing Spatio-temporal Patterns of Groundwater Salinity in Small ...

    African Journals Online (AJOL)

    Thus, characterization and monitoring of the freshwater lens will provide a reliable means of observing and managing anticipated climate changes on small islands. Keywords: small coral islands, Grande Glorieuse, hydrogeology, seawater intrusion, borehole monitoring, electrical resistance tomography, climate change.

  8. STSE: Spatio-Temporal Simulation Environment Dedicated to Biology

    Directory of Open Access Journals (Sweden)

    Gerber Susanne

    2011-04-01

    Full Text Available Abstract Background Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. Results The Spatio-Temporal Simulation Environment (STSE is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images. STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts

  9. STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

    Science.gov (United States)

    Stoma, Szymon; Fröhlich, Martina; Gerber, Susanne; Klipp, Edda

    2011-04-28

    Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We

  10. Self-organization of spatio-temporal earthquake clusters

    Directory of Open Access Journals (Sweden)

    S. Hainzl

    2000-01-01

    Full Text Available Cellular automaton versions of the Burridge-Knopoff model have been shown to reproduce the power law distribution of event sizes; that is, the Gutenberg-Richter law. However, they have failed to reproduce the occurrence of foreshock and aftershock sequences correlated with large earthquakes. We show that in the case of partial stress recovery due to transient creep occurring subsequently to earthquakes in the crust, such spring-block systems self-organize into a statistically stationary state characterized by a power law distribution of fracture sizes as well as by foreshocks and aftershocks accompanying large events. In particular, the increase of foreshock and the decrease of aftershock activity can be described by, aside from a prefactor, the same Omori law. The exponent of the Omori law depends on the relaxation time and on the spatial scale of transient creep. Further investigations concerning the number of aftershocks, the temporal variation of aftershock magnitudes, and the waiting time distribution support the conclusion that this model, even "more realistic" physics in missed, captures in some ways the origin of the size distribution as well as spatio-temporal clustering of earthquakes.

  11. Exploring the spatio-temporal neural basis of face learning

    Science.gov (United States)

    Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

    2017-01-01

    Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

  12. How spatio-temporal habitat connectivity affects amphibian genetic structure.

    Science.gov (United States)

    Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

    2015-01-01

    Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

  13. Spatio-temporal dynamics of the tropical rain forest

    Energy Technology Data Exchange (ETDEWEB)

    Chave, J. [CEN Saclay, Gif-sur-Yvette (France). Service de Physique de l' Etat Condense

    2000-07-01

    Mechanisms which drive the dynamics of forest ecosystems are complex, from seedling establishment to pollination, and seed dispersal by animals, running water or wind. These processes are more complex when the ecosystem shelters a large number of species and of vegetative forms, as it is the case in the tropical rainforest. To take them into account, we must develop and use models. I present a review of the fundamental mechanisms for the of a natural forest dynamics - photosynthesis, tree growth, recruitment and mortality - as well as a description of the past and of the present of tropical rainforests. This information is used to develop a spatially-explicit and individual-based forest model. Simplified models are deduced from it, and they serve to address more specific issues, such as the resilience of the forest to climate disturbances, or savanna-forest dynamics. The last topic is related to the spatio-temporal description of tropical plant biodiversity. A detailed introduction to the problem is provided, and models accounting for the maintenance of diversity are compared. These models include non spatial as well a spatial approaches (branching anihilating random walks and voter model with mutation). (orig.)

  14. Spatio-temporal effects of low impact development practices

    Science.gov (United States)

    Gilroy, Kristin L.; McCuen, Richard H.

    2009-04-01

    SummaryThe increase in land development and urbanization experienced in the US and worldwide is causing environmental degradation. Traditional off-site stormwater management does not protect small streams. To mitigate the negative effects of land development, best management practices (BMPs) are being implemented into stormwater management policies for the purposes of controlling minor flooding and improving water quality. Unfortunately, the effectiveness of BMPs has not been extensively studied. The purpose of this research was to analyze the effects of both location and quantity of two types of BMPs: cisterns and bioretention pits. A spatio-temporal model of a microwatershed was developed to determine the effects of BMPs on single-family, townhome, and commercial lots. The effects of development and the BMPs on peak runoff rates and volumes were compared to pre-development conditions. The results show that cisterns alone are capable of controlling rooftop runoff for small storms. Both the spatial location and the volume of BMP storage on a microwatershed influences the effectiveness of BMPs. The volume of BMP storage is positively correlated to the percent reduction in the peak discharge rate and total runoff volume; however, location is a factor in the peak reduction and a maximum volume of effective storage for both hydrologic metrics does exist. These results provide guidelines for developing stormwater management policies that can potentially reduce pollution of first-order streams, lower the cost and maintenance requirements, enhance aesthetics, and increase safety.

  15. Vehicle Trajectory Estimation Using Spatio-Temporal MCMC

    Directory of Open Access Journals (Sweden)

    Francois Bardet

    2010-01-01

    Full Text Available This paper presents an algorithm for modeling and tracking vehicles in video sequences within one integrated framework. Most of the solutions are based on sequential methods that make inference according to current information. In contrast, we propose a deferred logical inference method that makes a decision according to a sequence of observations, thus processing a spatio-temporal search on the whole trajectory. One of the drawbacks of deferred logical inference methods is that the solution space of hypotheses grows exponentially related to the depth of observation. Our approach takes into account both the kinematic model of the vehicle and a driver behavior model in order to reduce the space of the solutions. The resulting proposed state model explains the trajectory with only 11 parameters. The solution space is then sampled with a Markov Chain Monte Carlo (MCMC that uses a model-driven proposal distribution in order to control random walk behavior. We demonstrate our method on real video sequences from which we have ground truth provided by a RTK GPS (Real-Time Kinematic GPS. Experimental results show that the proposed algorithm outperforms a sequential inference solution (particle filter.

  16. How spatio-temporal habitat connectivity affects amphibian genetic structure

    Science.gov (United States)

    Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

    2015-01-01

    Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

  17. Spatio-temporal diffusion of dynamic PET images

    International Nuclear Information System (INIS)

    Tauber, C; Chalon, S; Guilloteau, D; Stute, S; Buvat, I; Chau, M; Spiteri, P

    2011-01-01

    Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

  18. A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. II. Spatio-temporal dynamics

    Science.gov (United States)

    Böhringer, Klaus; Hess, Ortwin

    The spatio-temporal dynamics of novel semiconductor lasers is discussed on the basis of a space- and momentum-dependent full time-domain approach. To this means the space-, time-, and momentum-dependent Full-Time Domain Maxwell Semiconductor Bloch equations, derived and discussed in our preceding paper I [K. Böhringer, O. Hess, A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. I. Theoretical formulation], are solved by direct numerical integration. Focussing on the device physics of novel semiconductor lasers that profit, in particular, from recent advances in nanoscience and nanotechnology, we discuss the examples of photonic band edge surface emitting lasers (PBE-SEL) and semiconductor disc lasers (SDLs). It is demonstrated that photonic crystal effects can be obtained for finite crystal structures, and leading to a significant improvement in laser performance such as reduced lasing thresholds. In SDLs, a modern device concept designed to increase the power output of surface-emitters in combination with near-diffraction-limited beam quality, we explore the complex interplay between the intracavity optical fields and the quantum well gain material in SDL structures. Our simulations reveal the dynamical balance between carrier generation due to pumping into high energy states, momentum relaxation of carriers, and stimulated recombination from states near the band edge. Our full time-domain approach is shown to also be an excellent framework for the modelling of the interaction of high-intensity femtosecond and picosecond pulses with semiconductor nanostructures. It is demonstrated that group velocity dispersion, dynamical gain saturation and fast self-phase modulation (SPM) are the main causes for the induced changes and asymmetries in the amplified pulse shape and spectrum of an ultrashort high-intensity pulse. We attest that the time constants of the intraband scattering processes are critical to gain recovery. Moreover, we present

  19. Diffusive spatio-temporal noise in a first-passage time model for intracellular calcium release

    KAUST Repository

    Flegg, Mark B.; Rüdiger, Sten; Erban, Radek

    2013-01-01

    The intracellular release of calcium from the endoplasmic reticulum is controlled by ion channels. The resulting calcium signals exhibit a rich spatio-temporal signature, which originates at least partly from microscopic fluctuations. While

  20. Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

    KAUST Repository

    Sun, Ying; Genton, Marc G.

    2011-01-01

    This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio

  1. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...

  2. Plant diversity increases spatio?temporal niche complementarity in plant?pollinator interactions

    OpenAIRE

    Venjakob, Christine; Klein, Alexandra?Maria; Ebeling, Anne; Tscharntke, Teja; Scherber, Christoph

    2016-01-01

    Ongoing biodiversity decline impairs ecosystem processes, including pollination. Flower visitation, an important indicator of pollination services, is influenced by plant species richness. However, the spatio-temporal responses of different pollinator groups to plant species richness have not yet been analyzed experimentally. Here, we used an experimental plant species richness gradient to analyze plant-pollinator interactions with an unprecedented spatio-temporal resolution. We observed four...

  3. Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

    OpenAIRE

    Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

    2018-01-01

    Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

  4. Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

    Science.gov (United States)

    Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

    2017-09-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

  5. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    Directory of Open Access Journals (Sweden)

    N. Mou

    2017-09-01

    Full Text Available Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.. In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method – based on grid density, which is used to cluster the OD (origin and destination data of taxi at different times. Then,combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion – spatial aggregation – spatial relative dispersion" in one day.

  6. Real-Time Earthquake Monitoring with Spatio-Temporal Fields

    Science.gov (United States)

    Whittier, J. C.; Nittel, S.; Subasinghe, I.

    2017-10-01

    With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

  7. Symbolic analysis of spatio-temporal systems: The measurement problem

    International Nuclear Information System (INIS)

    Brown, R.; Tang, Xianzhu; Tracy, E.R.

    1996-01-01

    We consider the problem of measuring physical quantities using time-series observations. The approach taken is to validate theoretical models which are derived heuristically or from first principles. The fitting of parameters in such models constitutes the measurement. This is a basic problem in measurement science and a wide array of tools are available. However, an important gap in the present toolkit exists when the system of interest, and hence the models used, exhibit chaotic or turbulent behavior. The development of reliable schemes for analyzing such signals is necessary before one can claim to have a quantitative understanding of the underlying physics. In experimental situations, the number of independently measured time-series is limited, but the number of dynamical degrees of freedom can be large. In addition, the signals of interest will typically be embedded in a noisy background. In the symbol statistics approach, the time-series is coarse-grained and converted into a long, symbol stream. The probability of occurrence of various symbol sequences of fixed length constitutes the symbol statistics. These statistics contain a wealth of information about the underlying dynamics and, as we shall discuss, can be used to validate models. Previously, we have applied this symbolic approach to low dimensional systems with great success. The symbol statistics are robust up to noise/signal ∼20%. At higher noise levels the symbol statistics are biased, but in a relatively simple manner. By including the noise characteristics into the model, we were able to use the symbol statistics to measure parameters even when signal/noise is ∼ O(1). More recently, we have extended the symbolic approach to spatio-temporal systems. We have considered both coupled-map lattices and the complex Ginzburg-Landau equation. This equation arises generically near the onset of instabilities

  8. Spatio-temporal coupling of EEG signals in epilepsy

    Science.gov (United States)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

    Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

  9. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

    Full Text Available Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  10. Spatio-temporal analysis of smear-positive tuberculosis in the Sidama Zone, southern Ethiopia.

    Directory of Open Access Journals (Sweden)

    Mesay Hailu Dangisso

    Full Text Available Tuberculosis (TB is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs. However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia.A retrospective space-time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB. Scan statistics, Global Moran's I, and Getis and Ordi (Gi* statistics were all used to help analyze the spatial distribution and clusters of the disease across settings.A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001, with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001, with 7,584 observed and 4,738 expected cases in 2003-2012.The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas

  11. Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China.

    Science.gov (United States)

    Ye, Zirong; Xu, Li; Zhou, Zi; Wu, Yafei; Fang, Ya

    2018-01-02

    Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial-temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.

  12. A Visual Analytics Approach for Extracting Spatio-Temporal Urban Mobility Information from Mobile Network Traffic

    Directory of Open Access Journals (Sweden)

    Euro Beinat

    2012-11-01

    Full Text Available In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems.

  13. A spatio-temporal analysis of BSE cases born before and after the reinforced feed ban in France.

    Science.gov (United States)

    Ducrot, Christian; Abrial, David; Calavas, Didier; Carpenter, Tim

    2005-01-01

    A spatio-temporal analysis was carried out to see how the risk distribution of bovine spongiform encephalopathy (BSE) in France changed depending on the period of birth. The data concerned the 539 BSE cases born in France after the ban (BAB) of meat and bone meal (MBM) in 1990 and detected between July 1, 2001 and December 31, 2003, when the surveillance of BSE was comprehensive. Seventy-two of these cases were born after the reinforced (second) ban (BASB) in 1996, which involved the removal of BSE-risk materials and cadavers from the processing of MBM. The Ederer-Myers-Mantel (EMM) time and space cluster test was applied, after classifying the cases by trimester and region of birth, BAB or BASB status, and dairy or beef status. Then disease mapping was performed for four successive birth periods, three for the BAB cases (January 1991 through June 1994, July 1994 through June 1995, July 1995 through June 1996), and one for the BASB (July 1996 through October 1998). It was elaborated with the Bayesian graphical modelling methods and based on a Poisson distribution with spatial smoothing. The parameters were estimated by a Markov Chain Monte Carlo (MCMC) simulation method. The main finding was that the areas with the highest risk of BSE changed largely from one birth period to another; from the west, it reached the east of France for birth cohort 1994-1995 and the southwest for birth cohort 1995-1996. The EMM test identified a peak risk in this region both for dairy and beef cattle in the fall 1995. The spatial distribution of the risk for the BASB cases matched the spatial pattern of risk for the preceding BAB birth cohort quite well; this was in favour of a common origin of the infection of the BAB and BASB cases, despite the complementary control measures.

  14. Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

    Science.gov (United States)

    Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

    2016-04-01

    Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

  15. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

    Science.gov (United States)

    Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

    2014-10-06

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  16. Local overfishing may be avoided by examining parameters of a spatio-temporal model.

    Science.gov (United States)

    Carson, Stuart; Shackell, Nancy; Mills Flemming, Joanna

    2017-01-01

    Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time), connectivity (coherence of temporal pattern over space), and spatial variance (variation across the seascape). The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua) in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.

  17. Spatio-temporal coherence of dengue, chikungunya and Zika outbreaks in Merida, Mexico.

    Directory of Open Access Journals (Sweden)

    Donal Bisanzio

    2018-03-01

    Full Text Available Response to Zika virus (ZIKV invasion in Brazil lagged a year from its estimated February 2014 introduction, and was triggered by the occurrence of severe congenital malformations. Dengue (DENV and chikungunya (CHIKV invasions tend to show similar response lags. We analyzed geo-coded symptomatic case reports from the city of Merida, Mexico, with the goal of assessing the utility of historical DENV data to infer CHIKV and ZIKV introduction and propagation. About 42% of the 40,028 DENV cases reported during 2008-2015 clustered in 27% of the city, and these clustering areas were where the first CHIKV and ZIKV cases were reported in 2015 and 2016, respectively. Furthermore, the three viruses had significant agreement in their spatio-temporal distribution (Kendall W>0.63; p<0.01. Longitudinal DENV data generated patterns indicative of the resulting introduction and transmission patterns of CHIKV and ZIKV, leading to important insights for the surveillance and targeted control to emerging Aedes-borne viruses.

  18. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

    Science.gov (United States)

    Putman, Nathan F.; Jenkins, Erica S.; Michielsens, Catherine G. J.; Noakes, David L. G.

    2014-01-01

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

  19. Local overfishing may be avoided by examining parameters of a spatio-temporal model.

    Directory of Open Access Journals (Sweden)

    Stuart Carson

    Full Text Available Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time, connectivity (coherence of temporal pattern over space, and spatial variance (variation across the seascape. The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.

  20. Spatio-Temporal Changes in Structure for a Mediterranean Urban Forest: Santiago, Chile 2002 to 2014

    Directory of Open Access Journals (Sweden)

    Francisco J. Escobedo

    2016-06-01

    Full Text Available There is little information on how urban forest ecosystems in South America and Mediterranean climates change across both space and time. This study statistically and spatially analyzed the spatio-temporal dynamics of Santiago, Chile’s urban forest using tree and plot-level data from permanent plots from 2002 to 2014. We found mortality, ingrowth, and tree cover remained stable over the analysis period and similar patterns were observed for basal area (BA and biomass. However, tree cover increased, and was greater in the highest socioeconomic stratum neighborhoods while it dropped in the medium and low strata. Growth rates for the five most common tree species averaged from 0.12 to 0.36 cm·year−1. Spatially, tree biomass and BA were greater in the affluent, northeastern sections of the city and in southwest peri-urban areas. Conversely, less affluent central, northwest, and southern areas showed temporal losses in BA and biomass. Overall, we found that Santiago’s urban forest follows similar patterns as in other parts of the world; affluent areas tend to have more and better managed urban forests than poorer areas, and changes are primarily influenced by social and ecological drivers. Nonetheless, care is warranted when comparing urban forest structural metrics measured with similar sampling-monitoring approaches across ecologically disparate regions and biomes.

  1. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.

    Science.gov (United States)

    Fried, Patrick; Sánchez-Aragón, Máximo; Aguilar-Hidalgo, Daniel; Lehtinen, Birgitta; Casares, Fernando; Iber, Dagmar

    2016-09-01

    Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.

  2. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.

    Directory of Open Access Journals (Sweden)

    Patrick Fried

    2016-09-01

    Full Text Available Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF, a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp, Hedgehog (Hh and the transcription factor Homothorax (Hth and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.

  3. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    Science.gov (United States)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal

  4. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

    Science.gov (United States)

    Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

    2015-12-30

    Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  5. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

    Directory of Open Access Journals (Sweden)

    Zhaoyuan Yu

    2015-12-01

    Full Text Available Passive infrared (PIR motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  6. Nutrients and toxin producing phytoplankton control algal blooms - a spatio-temporal study in a noisy environment.

    Science.gov (United States)

    Sarkar, Ram Rup; Malchow, Horst

    2005-12-01

    A phytoplankton-zooplankton prey-predator model has been investigated for temporal, spatial and spatio-temporal dissipative pattern formation in a deterministic and noisy environment, respectively. The overall carrying capacity for the phytoplankton population depends on the nutrient level. The role of nutrient concentrations and toxin producing phytoplankton for controlling the algal blooms has been discussed. The local analysis yields a number of stationary and/or oscillatory regimes and their combinations. Correspondingly interesting is the spatio-temporal behaviour, modelled by stochastic reaction-diffusion equations. The present study also reveals the fact that the rate of toxin production by toxin producing phytoplankton (TPP) plays an important role for controlling oscillations in the plankton system. We also observe that different mortality functions of zooplankton due to TPP have significant influence in controlling oscillations, coexistence, survival or extinction of the zoo-plankton population. External noise can enhance the survival and spread of zooplankton that would go extinct in the deterministic system due to a high rate of toxin production.

  7. Spatio-temporal distribution of soil-transmitted helminth infections in Brazil.

    Science.gov (United States)

    Chammartin, Frédérique; Guimarães, Luiz H; Scholte, Ronaldo Gc; Bavia, Mara E; Utzinger, Jürg; Vounatsou, Penelope

    2014-09-18

    In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. The analysis of the spatio-temporal aspect of the risk of infection

  8. Spatio-temporal analyses of impacts of multiple climatic hazards in a savannah ecosystem of Ghana

    Directory of Open Access Journals (Sweden)

    Gerald A.B. Yiran, PhD

    2016-01-01

    Full Text Available Ghana’s savannah ecosystem has been subjected to a number of climatic hazards of varying severity. This paper presents a spatial, time-series analysis of the impacts of multiple hazards on the ecosystem and human livelihoods over the period 1983–2012, using the Upper East Region of Ghana as a case study. Our aim is to understand the nature of hazards (their frequency, magnitude and duration and how they cumulatively affect humans. Primary data were collected using questionnaires, focus group discussions, in-depth interviews and personal observations. Secondary data were collected from documents and reports. Calculations of the standard precipitation index (SPI and crop failure index used rainfall data from 4 weather stations (Manga, Binduri, Vea and Navrongo and crop yield data of 5 major crops (maize, sorghum, millet, rice and groundnuts respectively. Temperature and windstorms were analysed from the observed weather data. We found that temperatures were consistently high and increasing. From the SPI, drought frequency varied spatially from 9 at Binduri to 13 occurrences at Vea; dry spells occurred at least twice every year and floods occurred about 6 times on average, with slight spatial variations, during 1988–2012, a period with consistent data from all stations. Impacts from each hazard varied spatio-temporally. Within the study period, more 70% of years recorded severe crop losses with greater impacts when droughts and floods occur in the same year, especially in low lying areas. The effects of crop losses were higher in districts with no/little irrigation (Talensi, Nabdam, Garu-Tempane, Kassena-Nankana East. Frequency and severity of diseases and sicknesses such as cerebrospinal meningitis, heat rashes, headaches and malaria related to both dry and wet conditions have increased steadily over time. Other impacts recorded with spatio-temporal variations included destruction to housing, displacement, injury and death of people. These

  9. Research on spatio-temporal database techniques for spatial information service

    Science.gov (United States)

    Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

    2007-06-01

    Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

  10. VISUALIZATION OF SPATIO-TEMPORAL RELATIONS IN MOVEMENT EVENT USING MULTI-VIEW

    Directory of Open Access Journals (Sweden)

    K. Zheng

    2017-09-01

    Full Text Available Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

  11. Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

    Science.gov (United States)

    Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

    2017-09-01

    Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

  12. Spatio-temporal Hotelling observer for signal detection from image sequences.

    Science.gov (United States)

    Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

    2009-06-22

    Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

  13. AN ADAPTIVE ORGANIZATION METHOD OF GEOVIDEO DATA FOR SPATIO-TEMPORAL ASSOCIATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    C. Wu

    2015-07-01

    Full Text Available Public security incidents have been increasingly challenging to address with their new features, including large-scale mobility, multi-stage dynamic evolution, spatio-temporal concurrency and uncertainty in the complex urban environment, which require spatio-temporal association analysis among multiple regional video data for global cognition. However, the existing video data organizational methods that view video as a property of the spatial object or position in space dissever the spatio-temporal relationship of scattered video shots captured from multiple video channels, limit the query functions on interactive retrieval between a camera and its video clips and hinder the comprehensive management of event-related scattered video shots. GeoVideo, which maps video frames onto a geographic space, is a new approach to represent the geographic world, promote security monitoring in a spatial perspective and provide a highly feasible solution to this problem. This paper analyzes the large-scale personnel mobility in public safety events and proposes a multi-level, event-related organization method with massive GeoVideo data by spatio-temporal trajectory. This paper designs a unified object identify(ID structure to implicitly store the spatio-temporal relationship of scattered video clips and support the distributed storage management of massive cases. Finally, the validity and feasibility of this method are demonstrated through suspect tracking experiments.

  14. Research of Cadastral Data Modelling and Database Updating Based on Spatio-temporal Process

    Directory of Open Access Journals (Sweden)

    ZHANG Feng

    2016-02-01

    Full Text Available The core of modern cadastre management is to renew the cadastre database and keep its currentness,topology consistency and integrity.This paper analyzed the changes and their linkage of various cadastral objects in the update process.Combined object-oriented modeling technique with spatio-temporal objects' evolution express,the paper proposed a cadastral data updating model based on the spatio-temporal process according to people's thought.Change rules based on the spatio-temporal topological relations of evolution cadastral spatio-temporal objects are drafted and further more cascade updating and history back trace of cadastral features,land use and buildings are realized.This model implemented in cadastral management system-ReGIS.Achieved cascade changes are triggered by the direct driving force or perceived external events.The system records spatio-temporal objects' evolution process to facilitate the reconstruction of history,change tracking,analysis and forecasting future changes.

  15. Time-Resolved and Spatio-Temporal Analysis of Complex Cognitive Processes and their Role in Disorders like Developmental Dyscalculia

    Science.gov (United States)

    Mórocz, István Akos; Janoos, Firdaus; van Gelderen, Peter; Manor, David; Karni, Avi; Breznitz, Zvia; von Aster, Michael; Kushnir, Tammar; Shalev, Ruth

    2012-01-01

    The aim of this article is to report on the importance and challenges of a time-resolved and spatio-temporal analysis of fMRI data from complex cognitive processes and associated disorders using a study on developmental dyscalculia (DD). Participants underwent fMRI while judging the incorrectness of multiplication results, and the data were analyzed using a sequence of methods, each of which progressively provided more a detailed picture of the spatio-temporal aspect of this disease. Healthy subjects and subjects with DD performed alike behaviorally though they exhibited parietal disparities using traditional voxel-based group analyses. Further and more detailed differences, however, surfaced with a time-resolved examination of the neural responses during the experiment. While performing inter-group comparisons, a third group of subjects with dyslexia (DL) but with no arithmetic difficulties was included to test the specificity of the analysis and strengthen the statistical base with overall fifty-eight subjects. Surprisingly, the analysis showed a functional dissimilarity during an initial reading phase for the group of dyslexic but otherwise normal subjects, with respect to controls, even though only numerical digits and no alphabetic characters were presented. Thus our results suggest that time-resolved multi-variate analysis of complex experimental paradigms has the ability to yield powerful new clinical insights about abnormal brain function. Similarly, a detailed compilation of aberrations in the functional cascade may have much greater potential to delineate the core processing problems in mental disorders. PMID:22368322

  16. Theoretical analysis of the spatio-temporal structure of bone multicellular units

    International Nuclear Information System (INIS)

    Buenzli, P R; Pivonka, P; Gardiner, B S; Smith, D W; Dunstan, C R; Mundy, G R

    2010-01-01

    Bone multicellular units (BMUs) maintain the viability of the skeletal tissue by coordinating locally the sequence of bone resorption and bone formation performed by cells of the osteoclastic and osteoblastic lineage. Understanding the emergence and the net bone balance of such structured microsystems out of the complex network of biochemical interactions between bone cells is fundamental for many bone-related diseases and the evaluation of fracture risk. Based on current experimental knowledge, we propose a spatio-temporal continuum model describing the interactions of osteoblastic and osteoclastic cells. We show that this model admits travelling-wave-like solutions with well-confined cell profiles upon specifying external conditions mimicking the environment encountered in cortical bone remodelling. The shapes of the various cell concentration profiles within this travelling structure are intrinsically linked to the parameters of the model such as differentiation, proliferation, and apoptosis rates of bone cells. The internal structure of BMUs is reproduced, allowing for experimental calibration. The spatial distribution of the key regulatory factors can also be exhibited, which in diseased states could give hints as to the biochemical agent most accountable for the disorder.

  17. Differential spatio-temporal expression of carotenoid cleavage dioxygenases regulates apocarotenoid fluxes during AM symbiosis.

    Science.gov (United States)

    López-Ráez, Juan A; Fernández, Iván; García, Juan M; Berrio, Estefanía; Bonfante, Paola; Walter, Michael H; Pozo, María J

    2015-01-01

    Apocarotenoids are a class of compounds that play important roles in nature. In recent years, a prominent role for these compounds in arbuscular mycorrhizal (AM) symbiosis has been shown. They are derived from carotenoids by the action of the carotenoid cleavage dioxygenase (CCD) enzyme family. In the present study, using tomato as a model, the spatio-temporal expression pattern of the CCD genes during AM symbiosis establishment and functioning was investigated. In addition, the levels of the apocarotenoids strigolactones (SLs), C13 α-ionol and C14 mycorradicin (C13/C14) derivatives were analyzed. The results suggest an increase in SLs promoted by the presence of the AM fungus at the early stages of the interaction, which correlated with an induction of the SL biosynthesis gene SlCCD7. At later stages, induction of SlCCD7 and SlCCD1 expression in arbusculated cells promoted the production of C13/C14 apocarotenoid derivatives. We show here that the biosynthesis of apocarotenoids during AM symbiosis is finely regulated throughout the entire process at the gene expression level, and that CCD7 constitutes a key player in this regulation. Once the symbiosis is established, apocarotenoid flux would be turned towards the production of C13/C14 derivatives, thus reducing SL biosynthesis and maintaining a functional symbiosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

    KAUST Repository

    Sun, Ying

    2011-10-24

    This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.

  19. Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

    Directory of Open Access Journals (Sweden)

    Mohammad Nur Shodiq

    2016-03-01

    Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

  20. Dynamic computed tomography based on spatio-temporal analysis in acute stroke: Preliminary study

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ha Young; Pyeon, Do Yeong; Kim, Da Hye; Jung, Young Jin [Dongseo University, Busan (Korea, Republic of)

    2016-12-15

    Acute stroke is a one of common disease that require fast diagnosis and treatment to save patients life. however, the acute stroke may cause lifelong disability due to brain damage with no prompt surgical procedure. In order to diagnose the Stroke, brain perfusion CT examination and possible rapid implementation of 3D angiography has been widely used. However, a low-dose technique should be applied for the examination since a lot of radiation exposure to the patient may cause secondary damage for the patients. Therefore, the degradation of the measured CT images may interferes with a clinical check in that blood vessel shapes o n the CT image are significantly affected by gaussian noise. In this study, we employed the spatio-temporal technique to analyze dynamic (brain perfusion) CT data to improve an image quality for successful clinical diagnosis. As a results, proposed technique could remove gaussian noise successfully, demonstrated a possibility of new image segmentation technique for CT angiography. Qualitative evaluation was conducted by skilled radiological technologists, indicated significant quality improvement of dynamic CT images. the proposed technique will be useful tools as a clinical application for brain perfusion CT examination.

  1. Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios

    Science.gov (United States)

    Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

    2012-08-01

    Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, such as mean duration, mean affected area and total magnitude. This paper addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to simulate spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century? (3) How to use standardized drought indices to represent theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-yr multilevel and multiscale drought reanalysis over France. Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index and the Standardized Soil Wetness Index, respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well simulated by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals, either retrospective or prospective. The perceived spatio-temporal characteristics of drought events derived from these theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of

  2. Nonlinear system identification NARMAX methods in the time, frequency, and spatio-temporal domains

    CERN Document Server

    Billings, Stephen A

    2013-01-01

    Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by

  3. Using a weather generator to downscale spatio-temporal precipitation at urban scale

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing; Arnbjerg-Nielsen, Karsten

    In recent years, urban flooding has occurred in Denmark due to very local extreme precipitation events with very short lifetime. Several of these floods have been among the most severe ever experienced. The current study demonstrates the applicability of the Spatio-Temporal Neyman-Scott Rectangular...... the observed spatio-temporal differences at very fine scale for all measured parameters. For downscaling, perturbation with a climate change signal, precipitation from four different regional climate model simulations has been analysed. The analysed models are two runs from the ENSEMBLES (RACMO...

  4. Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH

    Science.gov (United States)

    Wang, H.; Ye, F.; Ouyang, S.; Li, Z.

    2018-04-01

    On the basis of introducing the SPH (Smooth Particle Hydrodynamics) simulation method, the key research problems were given solutions in this paper, which ere the spatial scale and temporal scale adapting to the GIS(Geographical Information System) application, the boundary condition equations combined with the underlying surface, and the kernel function and parameters applicable to dam-break flood simulation. In this regards, a calculation method of spatio-temporal process emulation with elaborate particles for dam-break flood was proposed. Moreover the spatio-temporal process was dynamic simulated by using GIS modelling and visualization. The results show that the method gets more information, objectiveness and real situations.

  5. Spatio-temporal dynamics of pneumonia in bighorn sheep.

    Science.gov (United States)

    Cassirer, E Frances; Plowright, Raina K; Manlove, Kezia R; Cross, Paul C; Dobson, Andrew P; Potter, Kathleen A; Hudson, Peter J

    2013-05-01

    1. Bighorn sheep mortality related to pneumonia is a primary factor limiting population recovery across western North America, but management has been constrained by an incomplete understanding of the disease. We analysed patterns of pneumonia-caused mortality over 14 years in 16 interconnected bighorn sheep populations to gain insights into underlying disease processes. 2. We observed four age-structured classes of annual pneumonia mortality patterns: all-age, lamb-only, secondary all-age and adult-only. Although there was considerable variability within classes, overall they differed in persistence within and impact on populations. Years with pneumonia-induced mortality occurring simultaneously across age classes (i.e. all-age) appeared to be a consequence of pathogen invasion into a naïve population and resulted in immediate population declines. Subsequently, low recruitment due to frequent high mortality outbreaks in lambs, probably due to association with chronically infected ewes, posed a significant obstacle to population recovery. Secondary all-age events occurred in previously exposed populations when outbreaks in lambs were followed by lower rates of pneumonia-induced mortality in adults. Infrequent pneumonia events restricted to adults were usually of short duration with low mortality. 3. Acute pneumonia-induced mortality in adults was concentrated in fall and early winter around the breeding season when rams are more mobile and the sexes commingle. In contrast, mortality restricted to lambs peaked in summer when ewes and lambs were concentrated in nursery groups. 4. We detected weak synchrony in adult pneumonia between adjacent populations, but found no evidence for landscape-scale extrinsic variables as drivers of disease. 5. We demonstrate that there was a >60% probability of a disease event each year following pneumonia invasion into bighorn sheep populations. Healthy years also occurred periodically, and understanding the factors driving these

  6. Spatio-temporal dynamics of pneumonia in bighorn sheep

    Science.gov (United States)

    Cassirer, E. Frances; Plowright, Raina K.; Manlove, Kezia R.; Cross, Paul C.; Dobson, Andrew P.; Potter, Kathleen A.; Hudson, Peter J.

    2013-01-01

    Bighorn sheep mortality related to pneumonia is a primary factor limiting population recovery across western North America, but management has been constrained by an incomplete understanding of the disease. We analysed patterns of pneumonia-caused mortality over 14 years in 16 interconnected bighorn sheep populations to gain insights into underlying disease processes. 2. We observed four age-structured classes of annual pneumonia mortality patterns: all-age, lamb-only, secondary all-age and adult-only. Although there was considerable variability within classes, overall they differed in persistence within and impact on populations. Years with pneumonia-induced mortality occurring simultaneously across age classes (i.e. all-age) appeared to be a consequence of pathogen invasion into a naïve population and resulted in immediate population declines. Subsequently, low recruitment due to frequent high mortality outbreaks in lambs, probably due to association with chronically infected ewes, posed a significant obstacle to population recovery. Secondary all-age events occurred in previously exposed populations when outbreaks in lambs were followed by lower rates of pneumonia-induced mortality in adults. Infrequent pneumonia events restricted to adults were usually of short duration with low mortality. 3. Acute pneumonia-induced mortality in adults was concentrated in fall and early winter around the breeding season when rams are more mobile and the sexes commingle. In contrast, mortality restricted to lambs peaked in summer when ewes and lambs were concentrated in nursery groups. 4. We detected weak synchrony in adult pneumonia between adjacent populations, but found no evidence for landscape-scale extrinsic variables as drivers of disease. 5. We demonstrate that there was a >60% probability of a disease event each year following pneumonia invasion into bighorn sheep populations. Healthy years also occurred periodically, and understanding the factors driving these

  7. Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging.

    Directory of Open Access Journals (Sweden)

    Karin Gorzolka

    Full Text Available MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals' germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest.

  8. Spatio-Temporal Variation in Water Quality of Orle River Basin, S.W. ...

    African Journals Online (AJOL)

    Spatio-Temporal Variation in Water Quality of Orle River Basin, S.W. Nigeria. ... Abstract. The water quality of small streams in Auchi area of Edo State, S.W. Nigeria was investigated with a view to ... and ecosystems. The study was carried out

  9. Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

    KAUST Repository

    Zhang, Bohai; Sang, Huiyan; Huang, Jianhua Z.

    2014-01-01

    of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov

  10. Spatio-Temporal Layout of Human Actions for Improved Bag-of-Words Action Detection

    NARCIS (Netherlands)

    Burghouts, G.J.; Schutte, K.

    2013-01-01

    We investigate how human action recognition can be improved by considering spatio-temporal layout of actions. From literature, we adopt a pipeline consisting of STIP features, a random forest to quantize the features into histograms, and an SVM classifier. Our goal is to detect 48 human actions,

  11. A Spatio-Temporal Based Estimation of Sequestered Carbon in the ...

    African Journals Online (AJOL)

    The vegetation in the Tarkwa Mining Area (TMA) has experienced changes as a result of population growth, urbanization, mining activities and illegal chainsaw operations and this has led to an increase in temperature over the past years. Therefore, studying its forest biomass carbon (C) stock and its spatio-temporal ...

  12. Displaced calibration of PM10 measurements using spatio-temporal models

    Directory of Open Access Journals (Sweden)

    Daniela Cocchi

    2007-12-01

    Full Text Available PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known to underestimate true levels of concentrations (non-reference samplers. In this paper we propose a hierarchical spatio-temporal Bayesian model for the calibration of measurements recorded using non-reference samplers, by borrowing strength from non co-located reference sampler measurements.

  13. Predictive spatio-temporal model for spatially sparse global solar radiation data

    International Nuclear Information System (INIS)

    André, Maïna; Dabo-Niang, Sophie; Soubdhan, Ted; Ould-Baba, Hanany

    2016-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at a located station for very short time scale. We built a multivariate model in using few stations (3 stations) separated with irregular distances from 26 km to 56 km. The proposed model is a spatio temporal vector autoregressive VAR model specifically designed for the analysis of spatially sparse spatio-temporal data. This model differs from classic linear models in using spatial and temporal parameters where the available predictors are the lagged values at each station. A spatial structure of stations is defined by the sequential introduction of predictors in the model. Moreover, an iterative strategy in the process of our model will select the necessary stations removing the uninteresting predictors and also selecting the optimal p-order. We studied the performance of this model. The metric error, the relative root mean squared error (rRMSE), is presented at different short time scales. Moreover, we compared the results of our model to simple and well known persistence model and those found in literature. - Highlights: • A spatio-temporal VAR forecast model is used for spatially sparse data solar. • Lags and locations are selected by an optimization strategy. • Definition of spatial ordering of predictors influences forecasting results. • The model shows a better performance predictive at 30 min ahead in our context. • Benchmarking study shows a more accurate forecast at 1 h ahead with spatio-temporal VAR.

  14. Effects of Spatio-Temporal Aliasing on Pilot Performance in Active Control Tasks

    Science.gov (United States)

    Zaal, Peter; Sweet, Barbara

    2010-01-01

    Spatio-temporal aliasing affects pilot performance and control behavior. For increasing refresh rates: 1) Significant change in control behavior: a) Increase in visual gain and neuromuscular frequency. b) Decrease in visual time delay. 2) Increase in tracking performance: a) Decrease in RMSe. b) Increase in crossover frequency.

  15. [Spatio-temporal variations of origin, distribution and diffusion of Oncomelania hupensis in Yangtze River Basin].

    Science.gov (United States)

    Deng, Chen; Li-Yong, Wen

    2017-10-24

    As the only intermediate host of Schistosoma japonicum, Oncomelania hupensis in China is mainly distributed in the Yangtze River Basin. The origin of the O. hupensis and the spatio-temporal variations of its distribution and diffusion in the Yangtze River Basin and the influencing factors, as well as significances in schistosomiasis elimination in China are reviewed in this paper.

  16. Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

    Science.gov (United States)

    Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

    2016-07-01

    Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

  17. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang

    2015-01-01

    When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

  18. Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution

    NARCIS (Netherlands)

    Kilibarda, M.; Hengl, T.; Heuvelink, G.B.M.; Graler, B.; Pebesma, E.; Tadic, M.P.; Bajat, B.

    2014-01-01

    Combined Global Surface Summary of Day and European Climate Assessment and Dataset daily meteorological data sets (around 9000 stations) were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1km for the global land mass. Predictions in

  19. A hierarchical Bayesian spatio-temporal model to forecast trapped particle fluxes over the SAA region

    Czech Academy of Sciences Publication Activity Database

    Suparta, W.; Gusrizal, G.; Kudela, Karel; Isa, Z.

    2017-01-01

    Roč. 28, č. 3 (2017), s. 357-370 ISSN 1017-0839 R&D Projects: GA MŠk EF15_003/0000481 Institutional support: RVO:61389005 Keywords : trapped particle * spatio-temporal * hierarchical Bayesian * forecasting Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 0.752, year: 2016

  20. Spatio-temporal map generalizations with the hierarchical Voronoi data structure

    DEFF Research Database (Denmark)

    Mioc, Darka; Anton, François; Gold, Christopher M.

    implemented in commercial GIS systems. In this research, we used the Voronoi spatial data model for map generalizations. We were able to demonstrate that the map generalization does not affect only spatial objects (points, lines or polygons), but also the events corresponding to the creation and modification...... their spatio-temporal characteristics and their dynamic behaviour....

  1. Spatio-temporal aspects of gated residential security estates in non-metropolitan Western Cape

    CSIR Research Space (South Africa)

    Spocter, M

    2011-04-01

    Full Text Available . This research attempts to address this research gap by focusing on the spatio-temporal aspects of non-metropolitan gated residential security estates in the Western Cape Province. It was found that most non-metropolitan gated residential security estates were...

  2. Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D + T

    NARCIS (Netherlands)

    Gasch, C.K.; Hengl, Tom; Gräler, Benedikt; Meyer, Hanna; Magney, T.S.; Brown, D.J.

    2015-01-01

    The paper describes a framework for modeling dynamic soil properties in 3-dimensions and time (3D + T) using soil data collected with automated sensor networks as a case study. Two approaches to geostatistical modeling and spatio-temporal predictions are described: (1) 3D + T predictive modeling

  3. Spatio-temporal population genetics of the Danish pine marten (Martes martes)

    DEFF Research Database (Denmark)

    Pertoldi, Cino; Barker, Stuart F.; Madsen, Aksel Bo

    2008-01-01

    A spatio-temporal study of genetic variation in the Danish pine marten (Martes martes) populations from the Jutland peninsula and from the island of Sealand was performed using 11 microsatellite markers. Samples obtained from 1892 to 2003 were subdivided into historical (prior to 1970) and recent...

  4. Spatio-temporal resolved diagnostics of the single filament barrier discharge in air

    International Nuclear Information System (INIS)

    Wagner, H.E.; Brandenburg, R.; Michel, P.; Kozlov, K.V.

    2001-01-01

    First experimental results on the spatio-temporal development of single filaments of DBDs in dry air at atmospheric pressure are presented. The measurements allow a detailed visualisation and interpretation of the streamer development. In combination with the kinetic model they are used to get information on the spatiotemporal development of the reduced field-strength E/n, too

  5. A test for stationarity of spatio-temporal random fields on planar and spherical domains

    KAUST Repository

    Jun, Mikyoung; Genton, Marc G.

    2012-01-01

    A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method

  6. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  7. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang; Liang, Faming; Genton, Marc G.

    2015-01-01

    method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo

  8. A Spatio-Temporal Enhanced Metadata Model for Interdisciplinary Instant Point Observations in Smart Cities

    Directory of Open Access Journals (Sweden)

    Nengcheng Chen

    2017-02-01

    Full Text Available Due to the incomprehensive and inconsistent description of spatial and temporal information for city data observed by sensors in various fields, it is a great challenge to share the massive, multi-source and heterogeneous interdisciplinary instant point observation data resources. In this paper, a spatio-temporal enhanced metadata model for point observation data sharing was proposed. The proposed Data Meta-Model (DMM focused on the spatio-temporal characteristics and formulated a ten-tuple information description structure to provide a unified and spatio-temporal enhanced description of the point observation data. To verify the feasibility of the point observation data sharing based on DMM, a prototype system was established, and the performance improvement of Sensor Observation Service (SOS for the instant access and insertion of point observation data was realized through the proposed MongoSOS, which is a Not Only SQL (NoSQL SOS based on the MongoDB database and has the capability of distributed storage. For example, the response time of the access and insertion for navigation and positioning data can be realized at the millisecond level. Case studies were conducted, including the gas concentrations monitoring for the gas leak emergency response and the smart city public vehicle monitoring based on BeiDou Navigation Satellite System (BDS used for recording the dynamic observation information. The results demonstrated the versatility and extensibility of the DMM, and the spatio-temporal enhanced sharing for interdisciplinary instant point observations in smart cities.

  9. A FRAMEWORK FOR ONLINE SPATIO-TEMPORAL DATA VISUALIZATION BASED ON HTML5

    Directory of Open Access Journals (Sweden)

    B. Mao

    2012-07-01

    Full Text Available Web is entering a new phase – HTML5. New features of HTML5 should be studied for online spatio-temporal data visualization. In the proposed framework, spatio-temporal data is stored in the data server and is sent to user browsers with WebSocket. Public geo-data such as Internet digital map is integrated into the browsers. Then animation is implemented through the canvas object defined by the HTML5 specification. To simulate the spatio-temporal data source, we collected the daily location of 15 users with GPS tracker. The current positions of the users are collected every minute and are recorded in a file. Based on this file, we generate a real time spatio-temporal data source which sends out current user location every second.By enlarging the real time scales by 60 times, we can observe the movement clearly. The data transmitted with WebSocket is the coordinates of users' current positions, which will can be demonstrated in client browsers.

  10. Mortality in Danish Swine herds: Spatio-temporal clusters and risk factors

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Ersbøll, Annette Kjær; Bihrmann, Kristine

    2017-01-01

    -temporal analysis included data description for spatial, temporal, and spatio-temporal cluster analysis for three age groups: weaners (up to 30 kg), sows and finishers. Logistic regression models were used to assess the potential factors associated with finisher and weaner herds being included within multiple...

  11. Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

    Energy Technology Data Exchange (ETDEWEB)

    Tourre, Y M [METEO-France, Meteopole, 42 Avenue Coriolis, 31057 Toulouse Cedex 1 (France); Jarlan, L [Centre d' Etudes Spatiales de la Biosphere (CESBIO), 18 avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France); Lacaux, J-P [Universite Paul Sabatier (UPS), Observatoire Midi Pyrenees (OMP), 12 Avenue Edouard Belin, 31400 Toulouse (France); Rotela, C H [Instituto de Altos Estudios Espaciales ' Mario Gulich' , Comision Nacional de Actividades Espaciales (CONAE), Universidad Nacional de Cordoba (Argentina); Lafaye, M [CNES, DSP/ARP/AV, 18 Avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France)

    2008-10-15

    Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high

  12. High resolution spatio-temporal mapping of NO2 pollution for estimating personal exposures of the Dutch population

    Science.gov (United States)

    Soenario, Ivan; Helbich, Marco; Schmitz, Oliver; Strak, Maciek; Hoek, Gerard; Karssenberg, Derek

    2017-04-01

    Air pollution has been associated with adverse health effects (e.g., cardiovascular and respiration diseases) in the urban environments. Therefore, the assessment of people's exposure to air pollution is central in epidemiological studies. The estimation of exposures on an individual level can be done by combining location information across space and over time with spatio-temporal data on air pollution concentrations. When detailed information on peoples' space-time paths (e.g. commuting patterns calculated by means of spatial routing algorithms or tracked through GPS) and peoples' major activity locations (e.g. home location, work location) are available, it is possible to calculate more precise personal exposure levels depending on peoples' individual space-time mobility patterns. This requires air pollution values not only at a high level of spatial accuracy and high temporal granularity but such data also needs to be available on a nation-wide scale. As current data is seriously limited in this respect, we introduce a novel data set of NO2 levels across the Netherlands. The provided NO2 concentrations are accessible on hourly timestamps on a 5 meter grid cell resolution for weekdays and weekends, and each month of the year. We modeled a single Land Use Regression model using a five year average of NO2 data from the Dutch NO2 measurement network consisting of N=46 sampling locations distributed over the country. Predictor variables for this model were selected in a data-driven manner using an Elastic Net and Best Subset Selection procedure from 70 candidate predictors including traffic, industry, infrastructure and population-based variables. Subsequently, to model NO2 for each time scale (hour, week, month), the LUR coefficients were fitted using the NO2 data, aggregated per time scale. Model validation was grounded on independent data collected in an ad hoc measurement campaign. Our results show a considerable difference in urban concentrations between

  13. Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

    Energy Technology Data Exchange (ETDEWEB)

    Tourre, Y M [METEO-France, Meteopole, 42 Avenue Coriolis, 31057 Toulouse Cedex 1 (France); Jarlan, L [Centre d' Etudes Spatiales de la Biosphere (CESBIO), 18 avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France); Lacaux, J-P [Universite Paul Sabatier (UPS), Observatoire Midi Pyrenees (OMP), 12 Avenue Edouard Belin, 31400 Toulouse (France); Rotela, C H [Instituto de Altos Estudios Espaciales ' Mario Gulich' , Comision Nacional de Actividades Espaciales (CONAE), Universidad Nacional de Cordoba (Argentina); Lafaye, M [CNES, DSP/ARP/AV, 18 Avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France)

    2008-10-15

    Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

  14. Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

    Science.gov (United States)

    Tourre, Y. M.; Jarlan, L.; Lacaux, J.-P.; Rotela, C. H.; Lafaye, M.

    2008-10-01

    Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

  15. Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

    International Nuclear Information System (INIS)

    Tourre, Y M; Jarlan, L; Lacaux, J-P; Rotela, C H; Lafaye, M

    2008-01-01

    Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

  16. Using Google Street View for systematic observation of the built environment: analysis of spatio-temporal instability of imagery dates.

    Science.gov (United States)

    Curtis, Jacqueline W; Curtis, Andrew; Mapes, Jennifer; Szell, Andrea B; Cinderich, Adam

    2013-12-03

    Recently, Google Street View (GSV) has been examined as a tool for remotely conducting systematic observation of the built environment. Studies have found it offers benefits over in-person audits, including efficiency, safety, cost, and the potential to expand built environment research to larger areas and more places globally. However, one limitation has been the lack of documentation on the date of imagery collection. In 2011, Google began placing a date stamp on images which now enables investigation of this concern. This study questions the spatio-temporal stability in the GSV date stamp. Specifically, is the imagery collected contemporaneously? If not, how frequently and where is imagery from different time periods woven together to represent environmental conditions in a particular place. Furthermore, how much continuity exists in imagery for a particular time period? Answering these questions will provide guidance on the use of GSV as a tool for built environment audits. GSV was used to virtually "drive" five sites that are a part of the authors' ongoing studies. Each street in the sites was "driven" one mouse-click at a time while observing the date stamp on each image. Every time the date stamp changed, this "disruption" was marked on the map. Every street segment in the site was coded by the date the imagery for that segment was collected. Spatial query and descriptive statistics were applied to understand the spatio-temporal patterns of imagery dates. Spatio-temporal instability is present in the dates of GSV imagery. Of the 353 disruptions, 82.4% occur close to (<25 m) intersections. The remainder occurs inconsistently in other locations. The extent of continuity for a set of images collected with the same date stamp ranged from 3.13 m to 3373.06 m, though the majority of continuous segments were less than 400 m. GSV offers some benefits over traditional built environment audits. However, this investigation empirically identifies a previously

  17. Design and implementation of segment oriented spatio-temporal model in urban panoramic maps

    Science.gov (United States)

    Li, Haiting; Fei, Lifan; Peng, Qingshan; Li, Yanhong

    2009-10-01

    Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes. The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is described and implemented. We take points and polylines as objects in this model in the management of panoramic map data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient in the application of urban panoramic maps.

  18. Spatio-temporal changes in precipitation over Beijing-Tianjin-Hebei region, China

    Science.gov (United States)

    Zhao, Na; Yue, Tianxiang; Li, Han; Zhang, Lili; Yin, Xiaozhe; Liu, Yi

    2018-04-01

    Changes in precipitation have a large effect on human society and are of primary importance for many scientific fields such as hydrology, agriculture and eco-environmental sciences. The present study intended to investigate the spatio-temporal characteristics of precipitation in Beijing-Tianjin-Hebei (BTH) region by using 316 meteorological stations during the period 1965-2014. Geographical Weighted Regression (GWR) method and High Accuracy Surface Modeling (HASM) method were applied to produce the precipitation patterns at different time scales. Mann-Kendall (MK) statistical test was applied to analyze the precipitation temporal variations. Results indicated that annual precipitation over the past 50 years appeared to be a non-periodic oscillation phenomenon; the number of wet years was approximately the same as that of dry years; significant positive trends were observed in spring during 1978-2014 and summer during 1996-2014; on the whole, precipitation in May, June, September, and December showed increasing trends at the 95% confidence level; and significant positive trends were also identified in July during 2000-2013 and August during 1997-2010, while slight decreasing trends were observed in February and November. Summer (June, July, and August) was the wettest season, accounting for 68.73% of annual totals in BTH. In general, northeastern BTH received the highest range of precipitation while northwestern area had the lowest. It was found that precipitation variation in this region had been closely linked to latitude, Digital Elevation Model (DEM), distance to the sea, and urbanization rate. In addition, land use played an important role in the decadal precipitation changes in BTH.

  19. Spatio-temporal variability of periphytic protozoa related to environment in the Niyang River, Tibet, China

    Science.gov (United States)

    Liu, Haiping; Ye, Shaowen; Yang, Xuefeng; Guo, Chuanbo; Zhang, Huijuan; Fan, Liqing; Zhang, Liangsong; Sovan, Lek; Li, Zhongjie

    2017-05-01

    The Niyang River, a main tributary of the Yarlung Zangbo River, is an important and typical plateau river ecosystem in Tibet, China. At present, few studies have focused on its aquatic living resources and river ecology. In this study, the composition, abundance, and diversity of periphytic protozoa were investigated across four seasons from 2008 to 2009 to better understand their spatio-temporal patterns and relationship to the environment. Our investigation shows that periphytic protozoa in the Niyang River contained 15 genera, belonged to Tubulinea, Alveolata, Discosea and Rhizaria, Alveolata possessed most genera, up to nine, with highest share in abundance, exceeding 50%, Difflugia and Glaucoma were dominant genera. Moreover, four diversity indices of periphytic protozoa, including species richness, total abundance, Shannon-Wiener diversity index and Pielou's evenness index, displayed a significant descending trend as the seasons continued, in the order of winter, spring, summer and autumn; with a significant difference existing between winter and summer (or autumn) for Shannon-Wiener diversity index and species richness ( P0.05). In addition, canonical correlation analysis (CCA) shows that the densities of Difflugia, Glaucomais, Enchelydium, Cyphoderia, and Enchelys correlate with water temperature, alkalinity, hardness, pH, and dissolved oxygen, respectively. Lastly, the relationship between periphytic protozoa diversity and the environmental factors of the Niyang River can be predicted using classification and regression trees (CART) annalysis, which suggests that the total abundance and Shannon-Wiener diversity index would be higher when the elevation is above 3 308 m. On the other hand, the Shannon-Wiener diversity index and Pielou's evenness index would be lower when pH and ammoniacal nitrogen have lower or higher values. Finally yet importantly, close attention should be paid to periphytic protozoa and its environment to ensure sustainable development

  20. Spatio Temporal EEG Source Imaging with the Hierarchical Bayesian Elastic Net and Elitist Lasso Models.

    Science.gov (United States)

    Paz-Linares, Deirel; Vega-Hernández, Mayrim; Rojas-López, Pedro A; Valdés-Hernández, Pedro A; Martínez-Montes, Eduardo; Valdés-Sosa, Pedro A

    2017-01-01

    The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods

  1. Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990-2009).

    Science.gov (United States)

    Sharma, Richa; Ghosh, Aniruddha; Joshi, Pawan Kumar

    2013-04-01

    Urbanisation is a ubiquitous phenomenon with greater prominence in developing nations. Urban expansion involves land conversions from vegetated moisture-rich to impervious moisture-deficient land surfaces. The urban land transformations alter biophysical parameters in a mode that promotes development of heat islands and degrades environmental health. This study elaborates relationships among various environmental variables using remote sensing dataset to study spatio-temporal footprint of urbanisation in Surat city. Landsat Thematic Mapper satellite data were used in conjugation with geo-spatial techniques to study urbanisation and correlation among various satellite-derived biophysical parameters, [Normalised Difference Vegetation Index, Normalised Difference Built-up Index, Normalised Difference Water Index, Normalised Difference Bareness Index, Modified NDWI and land surface temperature (LST)]. Land use land cover was prepared using hierarchical decision tree classification with an accuracy of 90.4 % (kappa = 0.88) for 1990 and 85 % (kappa = 0.81) for 2009. It was found that the city has expanded over 42.75 km(2) within a decade, and these changes resulted in elevated surface temperatures. For example, transformation from vegetation to built-up has resulted in 5.5 ± 2.6 °C increase in land surface temperature, vegetation to fallow 6.7 ± 3 °C, fallow to built-up is 3.5 ± 2.9 °C and built-up to dense built-up is 5.3 ± 2.8 °C. Directional profiling for LST was done to study spatial patterns of LST in and around Surat city. Emergence of two new LST peaks for 2009 was observed in N-S and NE-SW profiles.

  2. Spatio-temporal variability of aerosols in the tropics relationship with atmospheric and oceanic environments

    Science.gov (United States)

    Zuluaga-Arias, Manuel D.

    2011-12-01

    Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatio-temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses

  3. Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

    Directory of Open Access Journals (Sweden)

    Xian-Hong Wang

    Full Text Available BACKGROUND: Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. METHODOLOGY/PRINCIPAL FINDINGS: We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA, from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. CONCLUSION/SIGNIFICANCE: Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken

  4. Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

    Science.gov (United States)

    Wang, Xian-Hong; Zhou, Xiao-Nong; Vounatsou, Penelope; Chen, Zhao; Utzinger, Jürg; Yang, Kun; Steinmann, Peter; Wu, Xiao-Hua

    2008-06-11

    Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA), from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken into consideration when making risk prediction at small scales.

  5. How innate is locomotion in precocial animals? A study on the early development of spatio-temporal gait variables and gait symmetry in piglets.

    Science.gov (United States)

    Vanden Hole, Charlotte; Goyens, Jana; Prims, Sara; Fransen, Erik; Ayuso Hernando, Miriam; Van Cruchten, Steven; Aerts, Peter; Van Ginneken, Chris

    2017-08-01

    Locomotion is one of the most important ecological functions in animals. Precocial animals, such as pigs, are capable of independent locomotion shortly after birth. This raises the question whether coordinated movement patterns and the underlying muscular control in these animals is fully innate or whether there still exists a rapid maturation. We addressed this question by studying gait development in neonatal pigs through the analysis of spatio-temporal gait characteristics during locomotion at self-selected speed. To this end, we made video recordings of piglets walking along a corridor at several time points (from 0 h to 96 h). After digitization of the footfalls, we analysed self-selected speed and spatio-temporal characteristics (e.g. stride and step lengths, stride frequency and duty factor) to study dynamic similarity, intralimb coordination and interlimb coordination. To assess the variability of the gait pattern, left-right asymmetry was studied. To distinguish neuromotor maturation from effects caused by growth, both absolute and normalized data (according to the dynamic similarity concept) were included in the analysis. All normalized spatio-temporal variables reached stable values within 4 h of birth, with most of them showing little change after the age of 2 h. Most asymmetry indices showed stable values, hovering around 10%, within 8 h of birth. These results indicate that coordinated movement patterns are not entirely innate, but that a rapid neuromotor maturation, potentially also the result of the rearrangement or recombination of existing motor modules, takes place in these precocial animals. © 2017. Published by The Company of Biologists Ltd.

  6. Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

    Science.gov (United States)

    Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

    2017-06-15

    Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

  7. Control of spatio-temporal on-off intermittency in random driving diffusively coupled map lattices

    International Nuclear Information System (INIS)

    Ziabakhsh Deilami, M.; Rahmani Cherati, Z.; Jahed Motlagh, M.R.

    2009-01-01

    In this paper, we propose feedback methods for controlling spatio-temporal on-off intermittency which is an aperiodic switching between an 'off' state and an 'on' state. Diffusively coupled map lattice with spatially non-uniform random driving is used for showing spatio-temporal on-off intermittency. For this purpose, we apply three different feedbacks. First, we use a linear feedback which is a simple method but has a long transient time. To overcome this problem, two nonlinear feedbacks based on prediction strategy are proposed. An important advantage of the methods is that the feedback signal is vanished when control is realized. Simulation results show that all methods have suppressed the chaotic behavior.

  8. Towards human behavior recognition based on spatio temporal features and support vector machines

    Science.gov (United States)

    Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

    2017-03-01

    Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

  9. A test for stationarity of spatio-temporal random fields on planar and spherical domains

    KAUST Repository

    Jun, Mikyoung

    2012-01-01

    A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method can be applied to univariate or to multivariate random fields. Our test is based on the asymptotic normality of certain statistics that are functions of estimators of covariances at certain spatial and temporal lags under weak stationarity. Simulation results for spatial as well as spatio-temporal cases on the two types of spatial domains are reported. We describe the results of testing the stationarity of Pacific wind data, and of testing the axial symmetry of climate model errors for surface temperature using the NOAA GFDL model outputs and the observations from the Climate Research Unit in East Anglia and the Hadley Centre.

  10. Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

    Science.gov (United States)

    Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

    2012-04-01

    Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective

  11. Learning of spatio-temporal codes in a coupled oscillator system.

    Science.gov (United States)

    Orosz, Gábor; Ashwin, Peter; Townley, Stuart

    2009-07-01

    In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

  12. Spatio-Temporal Image Correlation Spectroscopy Measurements of Flow Demonstrated in Microfluidic Channels

    Science.gov (United States)

    Rossow, Molly; Mantulin, William W.; Gratton, Enrico

    2009-01-01

    Accurate blood flow measurements during surgery can improve the operations chance of success. We developed Near-infrared Spatio-Temporal Image Spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1mm in diameter) and of creating a map of blood flow rates over an area of approximately 1cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatio-temporal image correlation spectroscopy to directly—without the use of a model—extract fluid velocity from the fluctuations within an image. Here we present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS. PMID:19405744

  13. Real time eye tracking using Kalman extended spatio-temporal context learning

    Science.gov (United States)

    Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

    2017-06-01

    Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

  14. Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

    Science.gov (United States)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

    This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

  15. The use of spatio-temporal correlation to forecast critical transitions

    Science.gov (United States)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in

  16. Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models

    DEFF Research Database (Denmark)

    Yang, Bin; Guo, Chenjuan; Jensen, Christian S.

    2013-01-01

    of such time series offers insight into the underlying system and enables prediction of system behavior. While the techniques presented in the paper apply more generally, we consider the case of transportation systems and aim to predict travel cost from GPS tracking data from probe vehicles. Specifically, each...... road segment has an associated travel-cost time series, which is derived from GPS data. We use spatio-temporal hidden Markov models (STHMM) to model correlations among different traffic time series. We provide algorithms that are able to learn the parameters of an STHMM while contending...... with the sparsity, spatio-temporal correlation, and heterogeneity of the time series. Using the resulting STHMM, near future travel costs in the transportation network, e.g., travel time or greenhouse gas emissions, can be inferred, enabling a variety of routing services, e.g., eco-routing. Empirical studies...

  17. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    2017-01-01

    Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...

  18. DSTiPE Algorithm for Fuzzy Spatio-Temporal Risk Calculation in Wireless Environments

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2008-09-01

    Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculation DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.

  19. Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol.

    Directory of Open Access Journals (Sweden)

    Seul-Ki Yeom

    Full Text Available On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1 the sedative types and 2 the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9-11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC and the recovery of consciousness (ROC, patient-controlled sedation was performed using two different sedatives (midazolam (MDZ and propofol (PPF under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (15 Hz, as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (unconsciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and

  20. Epidemiologic patterns of Ross River virus disease in Queensland, Australia, 2001-2011.

    Science.gov (United States)

    Yu, Weiwei; Mengersen, Kerrie; Dale, Pat; Mackenzie, John S; Toloo, Ghasem Sam; Wang, Xiaoyu; Tong, Shilu

    2014-07-01

    Ross River virus (RRV) infection is a debilitating disease that has a significant impact on population health, economic productivity, and tourism in Australia. This study examined epidemiologic patterns of RRV disease in Queensland, Australia, during January 2001-December 2011 at a statistical local area level. Spatio-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex, and space. The results show that the mean annual incidence was 54 per 100,000 persons, with a male:female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland, and the southeast areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on high-risk regions, particularly during summer and autumn to reduce the social and economic impacts of RRV infection. © The American Society of Tropical Medicine and Hygiene.

  1. Epidemiologic Patterns of Ross River Virus Disease in Queensland, Australia, 2001–2011

    Science.gov (United States)

    Yu, Weiwei; Mengersen, Kerrie; Dale, Pat; Mackenzie, John S.; Toloo, Ghasem (Sam); Wang, Xiaoyu; Tong, Shilu

    2014-01-01

    Ross River virus (RRV) infection is a debilitating disease that has a significant impact on population health, economic productivity, and tourism in Australia. This study examined epidemiologic patterns of RRV disease in Queensland, Australia, during January 2001–December 2011 at a statistical local area level. Spatio-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex, and space. The results show that the mean annual incidence was 54 per 100,000 persons, with a male:female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland, and the southeast areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on high-risk regions, particularly during summer and autumn to reduce the social and economic impacts of RRV infection. PMID:24799374

  2. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno; Mallick, Bani K.

    2011-01-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  3. Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

    OpenAIRE

    Desai, Deshana; Nisar, Harsh; Bhardawaj, Rishab

    2016-01-01

    The last two decades have seen a tremendous surge in research on social networks and their implications. The studies includes inferring social relationships, which in turn have been used for target advertising, recommendations, search customization etc. However, the offline experiences of human, the conversations with people and face-to-face interactions that govern our lives interactions have received lesser attention. We introduce DAIICT Spatio-Temporal Network (DSSN), a spatiotemporal data...

  4. Emergence of Complex Spatio-Temporal Behavior in Nonlinear Field Theories

    International Nuclear Information System (INIS)

    Gleiser, Marcelo; Howell, Rafael C.

    2006-01-01

    We investigate the emergence of time-dependent nonperturbative configurations during the evolution of nonlinear scalar field models with symmetric and asymmetric double-well potentials. Complex spatio-temporal behavior emerges as the system seeks to establish equipartition after a fast quench. We show that fast quenches may dramatically modify the decay rate of metastable states in first order phase transitions. We discuss possible applications in condensed matter systems and early universe cosmology

  5. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno

    2011-03-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  6. Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study

    OpenAIRE

    Adepeju, M.; Rosser, G.; Cheng, T.

    2016-01-01

    Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squ...

  7. [Epidemiologic and spatio-temporal characteristics of hepatitis E in China, 2004-2014].

    Science.gov (United States)

    Liu, Z Q; Zuo, J L; Yan, Q; Fang, Q W; Zhang, T J

    2017-10-10

    Objective: To describe and analyze the epidemiologic and spatio-temporal characteristics of hepatitis E in China from 2004 to 2014. Methods: Data on the incidence of hepatitis E in 31 provinces (municipality and autonomous region) from 2004 to 2014, were collected. Empirical Mode Decomposition (EMD) was applied to decompose the time-series data to accurately describe the trend of hepatitis E incidence. Mathematic model was used to estimate the annual change of incidence in each age group and the whole province. Software ArcGIS 10.1 and SaTScan 9.01 were used to analyze the spatio-temporal clusters. Results: During 2004-2014, a total of 245 414 hepatitis E cases were reported in China. The overall incidence showed a slight increase ( OR =1.05, 95 %CI : 1.03-1.10). Incidence rates on hepatitis E were discovered different across the provinces, with significant increase appearing in the southern, central and northwestern areas. The highest increase was seen in the elderly, especially in the 65-69 and 70-74 year-olds. Results from the Local spatial autocorrelation analysis showed that the "high-high cluster" was moving from the north to the south and the "low-low cluster" disappeared as time went by. Data from Spatio-temporal scanning showed that there were five spatio-temporal clustering areas across the country. Conclusion: The overall incidence of hepatitis E was on the rise from 2004 to 2014, in China, but with differences seen across the areas and age groups.

  8. DETERMINING SPATIO-TEMPORAL CADASTRAL DATA REQUIREMENT FOR INFRASTRUCTURE OF LADM FOR TURKEY

    Directory of Open Access Journals (Sweden)

    M. Alkan

    2016-06-01

    Full Text Available Nowadays, the nature of land title and cadastral (LTC data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS, execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM. For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1 define traditional LTC system of Turkey; (2 determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.

  9. Global asymptotic behavior in a Lotka–Volterra competition system with spatio-temporal delays

    International Nuclear Information System (INIS)

    Zhang, Jia-Fang; Chen, Heshan

    2014-01-01

    This paper is concerned with a Lotka–Volterra competition system with spatio-temporal delays. By using the linearization method, we show the local asymptotic behavior of the nonnegative steady-state solutions. Especially, the global asymptotic stability of the positive steady-state solution is investigated by the method of upper and lower solutions. The result of global asymptotic stability implies that the system has no nonconstant positive steady-state solution

  10. Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform

    International Nuclear Information System (INIS)

    Tascikaraoglu, Akin; Sanandaji, Borhan M.; Poolla, Kameshwar; Varaiya, Pravin

    2016-01-01

    Highlights: • We propose a spatio-temporal approach for wind speed forecasting. • The method is based on a combination of Wavelet decomposition and structured-sparse recovery. • Our analyses confirm that low-dimensional structures govern the interactions between stations. • Our method particularly shows improvements for profiles with high ramps. • We examine our approach on real data and illustrate its superiority over a set of benchmark models. - Abstract: Integration of renewable energy resources into the power grid is essential in achieving the envisioned sustainable energy future. Stochasticity and intermittency characteristics of renewable energies, however, present challenges for integrating these resources into the existing grid in a large scale. Reliable renewable energy integration is facilitated by accurate wind forecasts. In this paper, we propose a novel wind speed forecasting method which first utilizes Wavelet Transform (WT) for decomposition of the wind speed data into more stationary components and then uses a spatio-temporal model on each sub-series for incorporating both temporal and spatial information. The proposed spatio-temporal forecasting approach on each sub-series is based on the assumption that there usually exists an intrinsic low-dimensional structure between time series data in a collection of meteorological stations. Our approach is inspired by Compressive Sensing (CS) and structured-sparse recovery algorithms. Based on detailed case studies, we show that the proposed approach based on exploiting the sparsity of correlations between a large set of meteorological stations and decomposing time series for higher-accuracy forecasts considerably improve the short-term forecasts compared to the temporal and spatio-temporal benchmark methods.

  11. Determining Spatio-Temporal Cadastral Data Requirement for Infrastructure of Ladm for Turkey

    Science.gov (United States)

    Alkan, M.; Polat, Z. A.

    2016-06-01

    Nowadays, the nature of land title and cadastral (LTC) data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS), execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM). For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1) define traditional LTC system of Turkey; (2) determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS) is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.

  12. Comparison of feature extraction methods within a spatio-temporal land cover change detection framework

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-07-01

    Full Text Available OF FEATURE EXTRACTION METHODS WITHIN A SPATIO-TEMPORAL LAND COVER CHANGE DETECTION FRAMEWORK ??W. Kleynhans,, ??B.P. Salmon, ?J.C. Olivier, ?K.J. Wessels, ?F. van den Bergh ? Electrical, Electronic and Computer Engi- neering University of Pretoria, South... Bergh, and K. Steenkamp, ?Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data,? IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 381?385, Apr. 2010. ...

  13. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  14. On the expected value and variance for an estimator of the spatio-temporal product density function

    DEFF Research Database (Denmark)

    Rodríguez-Corté, Francisco J.; Ghorbani, Mohammad; Mateu, Jorge

    Second-order characteristics are used to analyse the spatio-temporal structure of the underlying point process, and thus these methods provide a natural starting point for the analysis of spatio-temporal point process data. We restrict our attention to the spatio-temporal product density function......, and develop a non-parametric edge-corrected kernel estimate of the product density under the second-order intensity-reweighted stationary hypothesis. The expectation and variance of the estimator are obtained, and closed form expressions derived under the Poisson case. A detailed simulation study is presented...... to compare our close expression for the variance with estimated ones for Poisson cases. The simulation experiments show that the theoretical form for the variance gives acceptable values, which can be used in practice. Finally, we apply the resulting estimator to data on the spatio-temporal distribution...

  15. Spatio-temporal modeling of 210Pb transportation in lake environments

    International Nuclear Information System (INIS)

    Kuelahci, Fatih; Sen, Zekai

    2009-01-01

    Radioactive particle movement analysis in any environment gives valuable information about the effects of the concerned environment on the particle and the transportation phenomenon. In this study, the spatio-temporal point cumulative semivariogram (STPCSV) approach is proposed for the analysis of the spatio-temporal changes in the radioactive particle movement within a surface water body. This methodology is applied to the 210 Pb radioactive isotope measurements at 44 stations, which are determined beforehand in order to characterize the Keban Dam water environment on the Euphrates River in the southeastern part of Turkey. It considers the contributions coming from all the stations and provides information about the spatio-temporal behavior of 210 Pb in the water environment. After having identified the radii of influences at each station it is possible to draw maps for further interpretations. In order to see holistically the spatial changes of the radioisotope after 1st, 3rd and 5th hours, the radius of influence maps are prepared and interpreted accordingly.

  16. Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

    Science.gov (United States)

    Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

    2010-08-01

    Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

  17. The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    ZHU Qing

    2017-10-01

    Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

  18. Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

    Science.gov (United States)

    Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

    2018-03-01

    In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.

  19. Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

    Science.gov (United States)

    Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

    2016-01-01

    HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug

  20. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  1. Experimental devices for the spatio-temporal characterization of femtosecond high-power laser chains

    International Nuclear Information System (INIS)

    Gallet, Valentin

    2014-01-01

    One of the advantages of high-power femtosecond lasers (TW-PW) is to obtain, at the focus of a focusing optic, very high intensities up to 10 22 W.cm -2 (i.e. an electric field of 2.7 PV.m -1 . Therefore, these lasers chains necessarily deliver beams with large diameter (up to 40 cm) and very short pulses (of the order of tens of femto-seconds). As a consequence, the spatial and temporal properties of the pulse are generally not independent. Such dependence, called spatial-temporal coupling has the effect of increasing the pulse duration and the size of the focal spot, which can lead to a significant reduction of the maximum intensity at the focus. Metrology devices commonly used on these high-power femtosecond lasers allow retrieving the spatial and temporal profiles of the pulse only in an independent manner. The aim of this thesis was to develop techniques for measuring spatio-temporal couplings in order to quantify their effect and correct them in order to obtain the maximum intensity at focus. First of all, we adapted an existing technique of spatio-temporal characterization to the measurement of TW lasers. To avoid the issues induced at the focus, such as those related to jittering, measurements were performed on the collimated beam. By adding a reference source to the original device, we managed to take into account the measurement artifacts due to thermal and mechanical variations affecting the interferometer. With this improvement, it was possible to reconstruct the complete spatio-temporal profile of the beam, particularly its wavefront. However, the limitations imposed by this technique led to the development of a new measurement device. Based on a cross-correlation, this technique consists of making the laser beam to interfere with a part of itself, small enough not to be spatio-temporally distorted. We have also implemented a variant of this device for a single-shot measurement along one transverse dimension of the pulse. Using these techniques, we

  2. Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt.

    Science.gov (United States)

    Kühling, Insa; Broll, Gabriele; Trautz, Dieter

    2016-02-15

    The Western Siberian grain belt covers 1millionkm² in Asiatic Russia and is of global importance for agriculture. Massive land-use changes took place in that region after the dissolution of the Soviet Union and the collapse of the state farm system. Decreasing land-use intensity (LUI) in post-Soviet Western Siberia was observed on grassland due to declining livestock whilst on cropland trends of land abandonment reversed in the early 2000s. Recultivation of abandoned cropland as well as increasing fertilizer inputs and narrowing crop rotations led to increasing LUI on cropland during the last two decades. Beyond that general trend, no information is available about spatial distribution and magnitude but a crucial precondition for the development of strategies for sustainable land management. To quantify changes and patterns in LUI, we developed an intensity index that reflects the impacts of land-based agricultural production. Based on subnational yearly statistical data, we calculated two separate input-orientated indices for cropland and grassland, respectively. The indices were applied on two spatial scale: at seven provinces covering the Western Siberian grain belt (Altay Kray, Chelyabinsk, Kurgan, Novosibirsk, Omsk, Sverdlovsk and Tyumen) and at all districts of the central province Tyumen. The spatio-temporal analysis clearly showed opposite trends for the two land-use types: decreasing intensity on grassland (-0.015 LUI units per year) and intensification on cropland (+0.014 LUI units per year). Furthermore, a spatial concentration towards intensity centres occurred during transition from a planned to a market economy. A principal component analysis enabled the individual calculations of both land-use types to be combined and revealed a strong link between biophysical conditions and LUI. The findings clearly showed the need for having a different strategy for future sustainable land management for grassland (predominantly used by livestock of households

  3. Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing

    Directory of Open Access Journals (Sweden)

    Valentina Ciullo

    2018-05-01

    Full Text Available The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition or onset (temporal condition were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation.Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between

  4. Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing.

    Science.gov (United States)

    Ciullo, Valentina; Vecchio, Daniela; Gili, Tommaso; Spalletta, Gianfranco; Piras, Federica

    2018-01-01

    The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition) or onset (temporal condition) were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation. Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between explicit and

  5. Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

    Science.gov (United States)

    Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

    2014-08-01

    As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good

  6. Spatio-temporal trends of rainfall across Indian river basins

    Science.gov (United States)

    Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

    2018-04-01

    Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

  7. STABILITY AND DYNAMICS OF SPATIO-TEMPORAL STRUCTURES

    Energy Technology Data Exchange (ETDEWEB)

    Hermann Riecke

    2005-10-21

    This document constitutes the final report for the grant. It provides a complete list of publications and presentations that arose from the project as well as a brief description of the highlights of the research results. The research funded by this grant has provided insights into the spontaneous formation of structures of increasing complexity in systems driven far from thermodynamic equilibrium. A classic example of such a system is thermally driven convection in a horizontal fluid layer. Highlights of the research are: (1) explanation of the localized traveling wave pulses observed in binary-mixture convection, (2) explanation of the localized waves in electroconvection, (3) introduction of a new diagnostics for spatially and temporally chaotic states, which is based on the statistics of defect trajectories, (4) prediction of complex states in thermally driven convection in rotating systems. Additional contributions provided insight into the localization mechanism for oscillons, the prediction of a new localization mechanism for traveling waves based on a resonant periodic forcing, and an analysis of the stability of quasi-periodic patterns.

  8. Environmental and socio-economic change in Thailand: quantifying spatio-temporal risk factors of dengue to inform decision making

    Science.gov (United States)

    Rodo, X.; Lowe, R.; Karczewska-Gibert, A.; Cazelles, B.

    2013-12-01

    Dengue is a peri-urban mosquito-transmitted disease, ubiquitous in the tropics and the subtropics. The geographic distribution of dengue and its more severe form, dengue haemorrhagic fever (DHF), have expanded dramatically in the last decades and dengue is now considered to be the world's most important arboviral disease. Recent demographic changes have greatly contributed to the acceleration and spread of the disease along with uncontrolled urbanization, population growth and increased air travel, which acts as a mechanism for transporting and exchanging dengue viruses between endemic and epidemic populations. The dengue vector and virus are extremely sensitive to environmental conditions such as temperature, humidity and precipitation that influence mosquito biology, abundance and habitat and the virus replication speed. In order to control the spread of dengue and impede epidemics, decision support systems are required that take into account the multi-faceted array of factors that contribute to increased dengue risk. Due to availability of seasonal climate forecasts, that predict the average climate conditions for forthcoming months/seasons in both time and space, there is an opportunity to incorporate precursory climate information in a dengue decision support system to aid epidemic planning months in advance. Furthermore, oceanic indicators from teleconnected areas in the Pacific and Indian Ocean, that can provide some indication of the likely prevailing climate conditions in certain regions, could potentially extend predictive lead time in a dengue early warning system. In this paper we adopt a spatio-temporal Bayesian modelling framework for dengue in Thailand to support public health decision making. Monthly cases of dengue in the 76 provinces of Thailand for the period 1982-2012 are modelled using a multi-layered approach. Explanatory variables at various spatial and temporal resolutions are incorporated into a hierarchical model in order to make spatio-temporal

  9. Spatio-temporal soil moisture variability in Southwest Germany observed with a new monitoring network within the COPS domain

    Energy Technology Data Exchange (ETDEWEB)

    Krauss, Liane; Kottmeier, Christoph [Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany). Inst. for Meteorology and Climate Research; Hauck, Christian [Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany). Inst. for Meteorology and Climate Research; Fribourg Univ. (Switzerland). Dept. of Geosciences

    2010-12-15

    Within the 'Convective and Orographically-induced Precipitation Study' (COPS) 2007 in Southwest Germany and Northeast France a soil moisture monitoring network was installed. The aim of the network is to identify the interaction between the temporal and spatial variability of the soil moisture field and its influence on the energy balance and the moisture availability in the planetary boundary layer. The network is comprised of a large number of newly developed low-cost soil moisture sensors based on the frequency-domain reflectometry method (FDR). In total 47 soil moisture stations within the COPS domain were each equipped with two to four sensors simultaneously measuring vertical profiles of soil moisture and soil temperature down to 50 cm depth. This contribution describes the soil moisture network, its installation procedure and the calibration of the sensor output signal. Furthermore we discuss the soil texture distribution within the study area and present first analyses of the spatio-temporal soil moisture variability during a 13 month period from June 2007 till June 2008 based on regional differences and site specific properties (altitude and soil texture). Results show that the altitude plays a key role for the overall soil moisture pattern relative to the area mean due to the direct linkage to precipitation patterns. Soil texture controls the vertical soil moisture gradient relative to the near surface soil moisture, as their properties control water storage and drainage characteristics. Both factors significantly influence regional soil moisture patterns in Southwest Germany. (orig.)

  10. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data

    KAUST Repository

    Castruccio, Stefano

    2018-01-23

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow for accurate testing for significance in neural activity. The high dimensionality of this type of data (on the order of hundreds of thousands of voxels) poses serious modeling challenges and considerable computational constraints. For the sake of feasibility, standard models typically reduce dimensionality by modeling covariance among regions of interest (ROIs)—coarser or larger spatial units—rather than among voxels. However, ignoring spatial dependence at different scales could drastically reduce our ability to detect activation patterns in the brain and hence produce misleading results. We introduce a multi-resolution spatio-temporal model and a computationally efficient methodology to estimate cognitive control related activation and whole-brain connectivity. The proposed model allows for testing voxel-specific activation while accounting for non-stationary local spatial dependence within anatomically defined ROIs, as well as regional dependence (between-ROIs). The model is used in a motor-task fMRI study to investigate brain activation and connectivity patterns aimed at identifying associations between these patterns and regaining motor functionality following a stroke.

  11. Spatio-temporal Analysis of the Genetic Diversity of Arctic Rabies Viruses and Their Reservoir Hosts in Greenland.

    Directory of Open Access Journals (Sweden)

    Dennis Hanke

    2016-07-01

    Full Text Available There has been limited knowledge on spatio-temporal epidemiology of zoonotic arctic fox rabies among countries bordering the Arctic, in particular Greenland. Previous molecular epidemiological studies have suggested the occurrence of one particular arctic rabies virus (RABV lineage (arctic-3, but have been limited by a low number of available samples preventing in-depth high resolution phylogenetic analysis of RABVs at that time. However, an improved knowledge of the evolution, at a molecular level, of the circulating RABVs and a better understanding of the historical perspective of the disease in Greenland is necessary for better direct control measures on the island. These issues have been addressed by investigating the spatio-temporal genetic diversity of arctic RABVs and their reservoir host, the arctic fox, in Greenland using both full and partial genome sequences. Using a unique set of 79 arctic RABV full genome sequences from Greenland, Canada, USA (Alaska and Russia obtained between 1977 and 2014, a description of the historic context in relation to the genetic diversity of currently circulating RABV in Greenland and neighboring Canadian Northern territories has been provided. The phylogenetic analysis confirmed delineation into four major arctic RABV lineages (arctic 1-4 with viruses from Greenland exclusively grouping into the circumpolar arctic-3 lineage. High resolution analysis enabled distinction of seven geographically distinct subclades (3.I - 3.VII with two subclades containing viruses from both Greenland and Canada. By combining analysis of full length RABV genome sequences and host derived sequences encoding mitochondrial proteins obtained simultaneously from brain tissues of 49 arctic foxes, the interaction of viruses and their hosts was explored in detail. Such an approach can serve as a blueprint for analysis of infectious disease dynamics and virus-host interdependencies. The results showed a fine-scale spatial population

  12. Spatio-temporal variability of soil respiration in a spruce-dominated headwater catchment in western Germany

    Science.gov (United States)

    Bossa, A. Y.; Diekkrüger, B.

    2014-08-01

    CO2 production and transport from forest floors is an important component of the carbon cycle and is closely related to the global atmosphere CO2 concentration. If we are to understand the feedback between soil processes and atmospheric CO2, we need to know more about the spatio-temporal variability of this soil respiration under different environmental conditions. In this study, long-term measurements were conducted in a spruce-dominated forest ecosystem in western Germany. Multivariate analysis-based similarities between different measurement sites led to the detection of site clusters along two CO2 emission axes: (1) mainly controlled by soil temperature and moisture condition, and (2) mainly controlled by root biomass and the forest floor litter. The combined effects of soil temperature and soil moisture were used as a time-dependent rating factor affecting the optimal CO2 production and transport at cluster level. High/moderate/weak time-dependent rating factors were associated with the different clusters. The process-based, most distant clusters were identified using specified pattern characteristics: the reaction rates in the soil layers, the activation energy for bio-chemical reactions, the soil moisture dependency parameter, the root biomass factor, the litter layer factor and the organic matter factor. A HYDRUS-1D model system was inversely used to compute soil hydraulic parameters from soil moisture measurements. Heat transport parameters were calibrated based on observed soil temperatures. The results were used to adjust CO2 productions by soil microorganisms and plant roots under optimal conditions for each cluster. Although the uncertainty associated with the HYDRUS-1D simulations is higher, the results were consistent with both the multivariate clustering and the time-dependent rating of site production. Finally, four clusters with significantly different environmental conditions (i.e. permanent high soil moisture condition, accumulated litter amount

  13. Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets.

    Science.gov (United States)

    Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

    2016-04-13

    In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. © 2016 The Authors.

  14. A Fresh Look at Spatio-Temporal Remote Sensing Data: Data Formats, Processing Flow, and Visualization

    Science.gov (United States)

    Gens, R.

    2017-12-01

    With increasing number of experimental and operational satellites in orbit, remote sensing based mapping and monitoring of the dynamic Earth has entered into the realm of `big data'. Just the Landsat series of satellites provide a near continuous archive of 45 years of data. The availability of such spatio-temporal datasets has created opportunities for long-term monitoring diverse features and processes operating on the Earth's terrestrial and aquatic systems. Processes such as erosion, deposition, subsidence, uplift, evapotranspiration, urbanization, land-cover regime shifts can not only be monitored and change can be quantified using time-series data analysis. This unique opportunity comes with new challenges in management, analysis, and visualization of spatio-temporal datasets. Data need to be stored in a user-friendly format, and relevant metadata needs to be recorded, to allow maximum flexibility for data exchange and use. Specific data processing workflows need to be defined to support time-series analysis for specific applications. Value-added data products need to be generated keeping in mind the needs of the end-users, and using best practices in complex data visualization. This presentation systematically highlights the various steps for preparing spatio-temporal remote sensing data for time series analysis. It showcases a prototype workflow for remote sensing based change detection that can be generically applied while preserving the application-specific fidelity of the datasets. The prototype includes strategies for visualizing change over time. This has been exemplified using a time-series of optical and SAR images for visualizing the changing glacial, coastal, and wetland landscapes in parts of Alaska.

  15. Spatio-temporal dynamics of a pulsed microwave argon plasma: ignition and afterglow

    International Nuclear Information System (INIS)

    Carbone, Emile; Sadeghi, Nader; Vos, Erik; Hübner, Simon; Van Veldhuizen, Eddie; Van Dijk, Jan; Nijdam, Sander; Kroesen, Gerrit

    2015-01-01

    In this paper, a detailed investigation of the spatio-temporal dynamics of a pulsed microwave plasma is presented. The plasma is ignited inside a dielectric tube in a repetitively pulsed regime at pressures ranging from 1 up to 100 mbar with pulse repetition frequencies from 200 Hz up to 500 kHz. Various diagnostic techniques are employed to obtain the main plasma parameters both spatially and with high temporal resolution. Thomson scattering is used to obtain the electron density and mean electron energy at fixed positions in the dielectric tube. The temporal evolution of the two resonant and two metastable argon 4s states are measured by laser diode absorption spectroscopy. Nanosecond time-resolved imaging of the discharge allows us to follow the spatio-temporal evolution of the discharge with high temporal and spatial resolution. Finally, the temporal evolution of argon 4p and higher states is measured by optical emission spectroscopy. The combination of these various diagnostics techniques gives deeper insight on the plasma dynamics during pulsed microwave plasma operation from low to high pressure regimes. The effects of the pulse repetition frequency on the plasma ignition dynamics are discussed and the plasma-off time is found to be the relevant parameter for the observed ignition modes. Depending on the delay between two plasma pulses, the dynamics of the ionization front are found to be changing dramatically. This is also reflected in the dynamics of the electron density and temperature and argon line emission from the plasma. On the other hand, the (quasi) steady state properties of the plasma are found to depend only weakly on the pulse repetition frequency and the afterglow kinetics present an uniform spatio-temporal behavior. However, compared to continuous operation, the time-averaged metastable and resonant state 4s densities are found to be significantly larger around a few kHz pulsing frequency. (paper)

  16. Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

    Science.gov (United States)

    Varlamova, Eugenia V.; Solovyev, Vladimir S.

    2017-11-01

    Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

  17. A spatio-temporal process data model for characterizing marine disasters

    International Nuclear Information System (INIS)

    Jiang, B; Gao, T; Zhang, X; Huang, X

    2014-01-01

    Marine disasters are a more prevalent problem in China than in many other countries. Based on the development of a status quo of China's marine disaster the space-time process model is used. The model uses the ocean's temperature field, salinity field, water density field, surface wind field, wave field and other four-dimensional spatio-temporal quantities. This paper studies that model in detail. This study aims at using the theory to provide support during marine disasters in an effort to prevent or decrease their frequency in the future

  18. Joint level-set and spatio-temporal motion detection for cell segmentation.

    Science.gov (United States)

    Boukari, Fatima; Makrogiannis, Sokratis

    2016-08-10

    Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

  19. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano

    2018-02-24

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  20. Assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident

    Czech Academy of Sciences Publication Activity Database

    Hofman, Radek; Šmídl, Václav

    2010-01-01

    Roč. 18, 7/8 (2010), s. 226-228 ISSN 1210-7085 R&D Projects: GA MŠk(CZ) 1M0572; GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : decision support * early phase * Gaussian model * radioactive pollution transport Subject RIV: DL - Nuclear Waste, Radioactive Pollution ; Quality http://library.utia.cas.cz/separaty/2010/AS/hofman-assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident .pdf

  1. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano; Genton, Marc G.

    2018-01-01

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  2. On the genesis of spatio-temporal self-organized structures in plasma devices

    International Nuclear Information System (INIS)

    Talasman, S.J.; Sanduloviciu, M.

    1995-01-01

    The genesis of luminous sharply defined nearly spherical space charges structures formed in an Argon plasma column was experimental investigated. The results reveal spatio-temporal characteristics proper to systems resulting after a self-organization process. Their phenomenology involves electrical charges separation produced by symmetry breaking and spatial separation of the excitation and ionization cross sections functions in a region where electrons are accelerated and, as a result, the appearance of electrostatic forces that, acting as long range correlations, assures, together with dissipative effects, its stability. (Author) 8 Figs., 31 Refs

  3. A general science-based framework for dynamical spatio-temporal models

    Science.gov (United States)

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

  4. Spread of porcine circovirus associated disease (PCVAD in Ontario (Canada swine herds: Part I. Exploratory spatial analysis

    Directory of Open Access Journals (Sweden)

    Young Beth

    2010-12-01

    Full Text Available Abstract Background The systemic form of porcine circovirus associated disease (PCVAD, also known as postweaning multisystemic wasting syndrome (PMWS was initially detected in the early 1990s. Starting in 2004, the Canadian swine industry experienced considerable losses due to PCVAD, concurrent with a shift in genotype of porcine circovirus type 2 (PCV2. Objectives of the current study were to explore spatial characteristics of self-reported PCVAD distribution in Ontario between 2004 and 2008, and to investigate the existence and nature of local spread. Results The study included 278 swine herds from a large disease-monitoring project that included porcine reproductive and respiratory syndrome (PRRS virus-positive herds identified by the diagnostic laboratory, and PRRS virus-negative herds directly from the target population. Herds were included if they had growing pigs present on-site and available geographical coordinates for the sampling site. Furthermore, herds were defined as PCVAD-positive if a producer reported an outbreak of circovirus associated disease, or as PCVAD-negative if no outbreak was noted. Spatial trend was investigated using generalized additive models and time to PCVAD outbreak in a herd using Cox's proportional hazard model; spatial and spatio-temporal clustering was explored using K-functions; and location of most likely spatial and spatio-temporal clusters was investigated using scan statistics. Over the study period, the risk of reporting a PCVAD-positive herd tended to be higher in the eastern part of the province after adjustment for herd PRRS status (P = 0.05. This was partly confirmed for spread (Partial P P = 0.06 existence of spatio-temporal clustering of PCVAD and detection of a spatio-temporal cluster (P = 0.04. Conclusions In Ontario, PCVAD has shown a general trend, spreading from east-to-west. We interpret the existence of spatio-temporal clustering as evidence of spatio-temporal aggregation of PCVAD

  5. Automatic segmentation of 4D cardiac MR images for extraction of ventricular chambers using a spatio-temporal approach

    Science.gov (United States)

    Atehortúa, Angélica; Zuluaga, Maria A.; Ourselin, Sébastien; Giraldo, Diana; Romero, Eduardo

    2016-03-01

    An accurate ventricular function quantification is important to support evaluation, diagnosis and prognosis of several cardiac pathologies. However, expert heart delineation, specifically for the right ventricle, is a time consuming task with high inter-and-intra observer variability. A fully automatic 3D+time heart segmentation framework is herein proposed for short-axis-cardiac MRI sequences. This approach estimates the heart using exclusively information from the sequence itself without tuning any parameters. The proposed framework uses a coarse-to-fine approach, which starts by localizing the heart via spatio-temporal analysis, followed by a segmentation of the basal heart that is then propagated to the apex by using a non-rigid-registration strategy. The obtained volume is then refined by estimating the ventricular muscle by locally searching a prior endocardium- pericardium intensity pattern. The proposed framework was applied to 48 patients datasets supplied by the organizers of the MICCAI 2012 Right Ventricle segmentation challenge. Results show the robustness, efficiency and competitiveness of the proposed method both in terms of accuracy and computational load.

  6. Spatio-temporal phase retrieval in speckle interferometry with Hilbert transform and two-dimensional phase unwrapping

    Science.gov (United States)

    Li, Xiangyu; Huang, Zhanhua; Zhu, Meng; He, Jin; Zhang, Hao

    2014-12-01

    Hilbert transform (HT) is widely used in temporal speckle pattern interferometry, but errors from low modulations might propagate and corrupt the calculated phase. A spatio-temporal method for phase retrieval using temporal HT and spatial phase unwrapping is presented. In time domain, the wrapped phase difference between the initial and current states is directly determined by using HT. To avoid the influence of the low modulation intensity, the phase information between the two states is ignored. As a result, the phase unwrapping is shifted from time domain to space domain. A phase unwrapping algorithm based on discrete cosine transform is adopted by taking advantage of the information in adjacent pixels. An experiment is carried out with a Michelson-type interferometer to study the out-of-plane deformation field. High quality whole-field phase distribution maps with different fringe densities are obtained. Under the experimental conditions, the maximum number of fringes resolvable in a 416×416 frame is 30, which indicates a 15λ deformation along the direction of loading.

  7. Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya.

    Science.gov (United States)

    Olang, Luke Omondi; Kundu, Peter; Bauer, Thomas; Fürst, Josef

    2011-08-01

    The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.

  8. Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

    Directory of Open Access Journals (Sweden)

    Pan Chen

    2015-05-01

    Full Text Available Understanding the spatio-temporal variation and the potential source of water pollution could greatly improve our knowledge of human impacts on the environment. In this work, data of 11 water quality indices were collected during 2012–2014 at 10 monitoring sites in the mainstream and major tributaries of the Danjiangkou Reservoir Basin, Central China. The fuzzy comprehensive assessment (FCA, the cluster analysis (CA and the discriminant analysis (DA were used to assess the water pollution status and analyze its spatio-temporal variation. Ten sites were classified by the high pollution (HP region and the low pollution (LP region, while 12 months were divided into the wet season and the dry season. It was found that the HP region was mainly in the small tributaries with small drainage areas and low average annual discharges, and it was also found that most of these rivers went through urban areas with industrial and domestic sewages input into the water body. Principal component analysis/factor analysis (PCA/FA was applied to reveal potential pollution sources, whereas absolute principal component score-multiple linear regression (APCS-MLR was used to identify their contributions to each water quality variable. The study area was found as being generally affected by industrial and domestic sewage. Furthermore, the HP region was polluted by chemical industries, and the LP region was influenced by agricultural and livestock sewage.

  9. Spatio-Temporal Database of Places Located in the Border Area

    Directory of Open Access Journals (Sweden)

    Albina Mościcka

    2018-03-01

    Full Text Available As a result of changes in boundaries, the political affiliation of locations also changes. Data on such locations are now collected in datasets with reference to the present or to the past space. Therefore, they can refer to localities that either no longer exist, have a different name now, or lay outside of the current borders of the country. Moreover, thematic data describing the past are related to events, customs, items that are always “somewhere”. Storytelling about the past is incomplete without knowledge about the places in which the given story has happened. Therefore, the objective of the article is to discuss the concept of spatio-temporal database for border areas as an “engine” for visualization of thematic data in time-oriented geographical space. The paper focuses on studying the place names on the Polish-Ukrainian border, analyzing the changes that have occurred in this area over the past 80 years (where there were three different countries during this period, and defining the changeability rules. As a result of the research, the architecture of spatio-temporal databases is defined, as well as the rules for using them for data geovisualisation in historical context.

  10. Statistical study of spatio-temporal distribution of precursor solar flares associated with major flares

    Science.gov (United States)

    Gyenge, N.; Ballai, I.; Baranyi, T.

    2016-07-01

    The aim of the present investigation is to study the spatio-temporal distribution of precursor flares during the 24 h interval preceding M- and X-class major flares and the evolution of follower flares. Information on associated (precursor and follower) flares is provided by Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). Flare list, while the major flares are observed by the Geostationary Operational Environmental Satellite (GOES) system satellites between 2002 and 2014. There are distinct evolutionary differences between the spatio-temporal distributions of associated flares in about one-day period depending on the type of the main flare. The spatial distribution was characterized by the normalized frequency distribution of the quantity δ (the distance between the major flare and its precursor flare normalized by the sunspot group diameter) in four 6 h time intervals before the major event. The precursors of X-class flares have a double-peaked spatial distribution for more than half a day prior to the major flare, but it changes to a lognormal-like distribution roughly 6 h prior to the event. The precursors of M-class flares show lognormal-like distribution in each 6 h subinterval. The most frequent sites of the precursors in the active region are within a distance of about 0.1 diameter of sunspot group from the site of the major flare in each case. Our investigation shows that the build-up of energy is more effective than the release of energy because of precursors.

  11. Detecting spatio-temporal modes in multivariate data by entropy field decomposition

    International Nuclear Information System (INIS)

    Frank, Lawrence R; Galinsky, Vitaly L

    2016-01-01

    A new data analysis method that addresses a general problem of detecting spatio-temporal variations in multivariate data is presented. The method utilizes two recent and complimentary general approaches to data analysis, information field theory (IFT) and entropy spectrum pathways (ESPs). Both methods reformulate and incorporate Bayesian theory, thus use prior information to uncover underlying structure of the unknown signal. Unification of ESP and IFT creates an approach that is non-Gaussian and nonlinear by construction and is found to produce unique spatio-temporal modes of signal behavior that can be ranked according to their significance, from which space–time trajectories of parameter variations can be constructed and quantified. Two brief examples of real world applications of the theory to the analysis of data bearing completely different, unrelated nature, lacking any underlying similarity, are also presented. The first example provides an analysis of resting state functional magnetic resonance imaging data that allowed us to create an efficient and accurate computational method for assessing and categorizing brain activity. The second example demonstrates the potential of the method in the application to the analysis of a strong atmospheric storm circulation system during the complicated stage of tornado development and formation using data recorded by a mobile Doppler radar. Reference implementation of the method will be made available as a part of the QUEST toolkit that is currently under development at the Center for Scientific Computation in Imaging. (paper)

  12. Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-11-01

    Full Text Available Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has become an important problem called spatio-temporal fusion problem in both research and practice. A Multi-Dictionary Bayesian Spatio-Temporal Reflectance Fusion Model (MDBFM has been proposed in this paper. First, multiple dictionaries from regions of different classes are trained. Second, a Bayesian framework is constructed to solve the dictionary selection problem. A pixel-dictionary likehood function and a dictionary-dictionary prior function are constructed under the Bayesian framework. Third, remote sensing images before and after the middle moment are combined to predict images at the middle moment. Diverse shapes and textures information is learned from different landscapes in multi-dictionary learning to help dictionaries capture the distinctions between regions. The Bayesian framework makes full use of the priori information while the input image is classified. The experiments with one simulated dataset and two satellite datasets validate that the MDBFM is highly effective in both subjective and objective evaluation indexes. The results of MDBFM show more precise details and have a higher similarity with real images when dealing with both type changes and phenology changes.

  13. Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

    Science.gov (United States)

    Boverman, Gregory; Fang, Qianqian; Carp, Stefan A.; Miller, Eric L.; Brooks, Dana H.; Selb, Juliette; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

    2007-07-01

    We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatio-temporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition, localized changes are observed which correspond to the glandular region of the breast.

  14. BUILDING A BILLION SPATIO-TEMPORAL OBJECT SEARCH AND VISUALIZATION PLATFORM

    Directory of Open Access Journals (Sweden)

    D. Kakkar

    2017-10-01

    Full Text Available With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC, an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  15. Building a Billion Spatio-Temporal Object Search and Visualization Platform

    Science.gov (United States)

    Kakkar, D.; Lewis, B.

    2017-10-01

    With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  16. The Spatio-Temporal Characteristics and Modeling Research of Inter-Provincial Migration in China

    Directory of Open Access Journals (Sweden)

    Xiaomei Fan

    2018-02-01

    Full Text Available The national census data during 1995 and 2000 and during 2005 and 2010 are selected in this paper to make an analysis of the spatio-temporal characteristics of the inter-provincial population migration in China. In addition, the general regression model, the extension regression model considering the historical dependent variable and the spatial lag model are established based on the gravity model to make the regression model on China’s inter-provincial population migration over two periods of time. The results show that: (1 the inter-provincial population migration increases rapidly in size with strong geographical proximity; (2 China’s inter-provincial population migration is still in the primary stage of the general process of population migration. In other words, the inter-provincial population emigration and immigration levels have increased greatly with the economic development; (3 Statistically, the inter-provincial population migration is negatively correlated with the level of economic development in the emigrant place and the migration distance and positively correlated with the level of economic development in the immigrant place and the population scale in the emigrant and immigrant places; and (4 The spatio-temporal factor is an important explanatory variable of population migration. The introduction of the historical dependent variable and the spatial lag factor can improve the regression effect of the gravity model greatly, and the historical variable and the spatial factor have strong explanatory power for the inter-provincial population migration.

  17. Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.

    Science.gov (United States)

    Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano

    2016-11-15

    Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.

  18. Spatio-Temporal Parameters\\' Changes in Gait of Male Elderly Subjects

    Directory of Open Access Journals (Sweden)

    Heydar Sadeghi

    2010-03-01

    Full Text Available Objectives: The purpose of this study was to compare spatio-temporal gait parameters between elderly and young male subjects. Methods & Materials: 57 able-bodied elderly (72±5.5 years and 57 healthy young (25±8.5 years subjects participated in this study. A four segment model consist of trunk, hip, shank, and foot with 10 reflective markers were used to define lower limbs. Kinematic data collected using four high speed video based cameras at a sampling frequency of 90 Hz.The t-testfor independent samples (α≤0.05 applied for statistical analysis. Results: Significant differences showed longer stance phase (2%, longer push-of time (4%, slower cadence (13%, slower speed (28% and shorter step length (15% for elderly in comparison with young subjects, though no significant differences were seen in double supporttime between two groups. Conclusion: Due to results, spatio-temporal changes are mainly attributed to the age-related decreases in muscular flexibility, joints>ranges of motion and neuromuscular control in elderly people.

  19. Spatio-temporal dynamics of security investments in an interdependent risk environment

    Science.gov (United States)

    Shafi, Kamran; Bender, Axel; Zhong, Weicai; Abbass, Hussein A.

    2012-10-01

    In a globalised world where risks spread through contagion, the decision of an entity to invest in securing its premises from stochastic risks no longer depends solely on its own actions but also on the actions of other interacting entities in the system. This phenomenon is commonly seen in many domains including airline, logistics and computer security and is referred to as Interdependent Security (IDS). An IDS game models this decision problem from a game-theoretic perspective and deals with the behavioural dynamics of risk-reduction investments in such settings. This paper enhances this model and investigates the spatio-temporal aspects of the IDS games. The spatio-temporal dynamics are studied using simple replicator dynamics on a variety of network structures and for various security cost tradeoffs that lead to different Nash equilibria in an IDS game. The simulation results show that the neighbourhood configuration has a greater effect on the IDS game dynamics than network structure. An in-depth empirical analysis of game dynamics is carried out on regular graphs, which leads to the articulation of necessary and sufficient conditions for dominance in IDS games under spatial constraints.

  20. OFDM Radar Space-Time Adaptive Processing by Exploiting Spatio-Temporal Sparsity

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2013-01-01

    We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. We observe that the target and interference spectra are inherently sparse in the spatio-temporal domain. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data and produces an equivalent performance as the other existing STAP techniques. In addition, the use of an OFDM signal increases the frequency diversity of our system, as different scattering centers of a target resonate at different frequencies, and thus improves the target detectability. First, we formulate a realistic sparse-measurement model for an OFDM radar considering both the clutter and jammer as the interfering sources. Then, we apply a residual sparse-recovery technique based on the LASSO estimator to estimate the target and interference covariance matrices, and subsequently compute the optimal STAP-filter weights. Our numerical results demonstrate a comparative performance analysis of the proposed sparse-STAP algorithm with four other existing STAP methods. Furthermore, we discover that the OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

  1. Spatio-temporal distribution of fecal indicators in three rivers of the Haihe River Basin, China.

    Science.gov (United States)

    Wang, Yawei; Chen, Yanan; Zheng, Xiang; Gui, Chengmin; Wei, Yuansong

    2017-04-01

    Because of their significant impact on public health, waterborne pathogens, especially bacteria and viruses, are frequently monitored in surface water to assess microbial quality of water bodies. However, more than one billion people worldwide currently lack access to safe drinking water, and a diversity of waterborne outbreaks caused by pathogens is reported in nations at all levels of economic development. Spatio-temporal distribution of conventional pollutants and five pathogenic microorganisms were discussed for the Haihe River Basin. Land use and socio-economic assessments were coupled with comprehensive water quality monitoring. Physical, chemical, and biological parameters were measured at 20 different sites in the watershed for 1 year, including pH, temperature, conductivity, dissolved oxygen, turbidity, chemical oxygen demand, ammonia-N, total and fecal coliforms, E. coli, and Enterococcus. The results highlighted the high spatio-temporal variability in pathogen distribution at watershed scale: high concentration of somatic coliphages and fecal indicator bacteria in March and December and their very low concentration in June and September. All pathogens were positively correlated to urban/rural residential/industrial land and negatively correlated to other four land use types. Microbial pollution was greatly correlated with population density, urbanization rate, and percentage of the tertiary industry in the gross domestic product. In the future, river microbial risk control strategy should focus more on the effective management of secondary effluent of wastewater treatment plant and land around rivers.

  2. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    Science.gov (United States)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

  3. A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2017-04-01

    Full Text Available With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data.

  4. Measurement of traffic parameters in image sequence using spatio-temporal information

    International Nuclear Information System (INIS)

    Lee, Daeho; Park, Youngtae

    2008-01-01

    This paper proposes a novel method for measurement of traffic parameters, such as the number of passed vehicles, velocity and occupancy rate, by video image analysis. The method is based on a region classification followed by spatio-temporal image analysis. Local detection region images in traffic lanes are classified into one of four categories: the road, the vehicle, the reflection and the shadow, by using statistical and structural features. Misclassification at a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. This capability of error correction results in the accurate estimation of traffic parameters even in high traffic congestion. Also headlight detection is employed for nighttime operation. Experimental results show that the accuracy is more than 94% in our test database of diverse operating conditions such as daytime, shadowy daytime, highway, urban way, rural way, rainy day, snowy day, dusk and nighttime. The average processing time is 30 ms per frame when four traffic lanes are processed, and real-time operation could be realized while ensuring robust detection performance even for high-speed vehicles up to 150 km h −1

  5. Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models.

    Science.gov (United States)

    Ebrahimian, Hossein; Jalayer, Fatemeh

    2017-08-29

    In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.

  6. Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors

    Directory of Open Access Journals (Sweden)

    Danang Sri Hadmoko

    2017-07-01

    Full Text Available Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1 the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2 their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %, Central Java (29 % and East Java (4 %. Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.

  7. Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

    Science.gov (United States)

    Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

    2016-08-15

    This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Gene expression analyses of the spatio-temporal relationships of human medulloblastoma subgroups during early human neurogenesis.

    Directory of Open Access Journals (Sweden)

    Cornelia M Hooper

    Full Text Available Medulloblastoma is the most common form of malignant paediatric brain tumour and is the leading cause of childhood cancer related mortality. The four molecular subgroups of medulloblastoma that have been identified - WNT, SHH, Group 3 and Group 4 - have molecular and topographical characteristics suggestive of different cells of origin. Definitive identification of the cell(s of origin of the medulloblastoma subgroups, particularly the poorer prognosis Group 3 and Group 4 medulloblastoma, is critical to understand the pathogenesis of the disease, and ultimately for the development of more effective treatment options. To address this issue, the gene expression profiles of normal human neural tissues and cell types representing a broad neuro-developmental continuum, were compared to those of two independent cohorts of primary human medulloblastoma specimens. Clustering, co-expression network, and gene expression analyses revealed that WNT and SHH medulloblastoma may be derived from distinct neural stem cell populations during early embryonic development, while the transcriptional profiles of Group 3 and Group 4 medulloblastoma resemble cerebellar granule neuron precursors at weeks 10-15 and 20-30 of embryogenesis, respectively. Our data indicate that Group 3 medulloblastoma may arise through abnormal neuronal differentiation, whereas deregulation of synaptic pruning-associated apoptosis may be driving Group 4 tumorigenesis. Overall, these data provide significant new insight into the spatio-temporal relationships and molecular pathogenesis of the human medulloblastoma subgroups, and provide an important framework for the development of more refined model systems, and ultimately improved therapeutic strategies.

  9. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Science.gov (United States)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

    This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  10. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Directory of Open Access Journals (Sweden)

    Medyńska-Gulij Beata

    2016-06-01

    Full Text Available This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  11. Spatio-temporal coherence of free-electron laser radiation in the extreme ultraviolet determined by a Michelson interferometer

    Energy Technology Data Exchange (ETDEWEB)

    Hilbert, V.; Rödel, C.; Zastrau, U., E-mail: ulf.zastrau@uni-jena.de [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Brenner, G.; Düsterer, S.; Dziarzhytski, S.; Harmand, M.; Przystawik, A.; Redlin, H.; Toleikis, S. [Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607 Hamburg (Germany); Döppner, T.; Ma, T. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550 (United States); Fletcher, L. [Department of Physics, University of California, Berkeley, California 94720 (United States); Förster, E. [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Helmholtz-Institut Jena, Fröbelstieg 3, 07743 Jena (Germany); Glenzer, S. H.; Lee, H. J. [SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Hartley, N. J. [Department of Physics, Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU (United Kingdom); Kazak, L.; Komar, D.; Skruszewicz, S. [Institut für Physik, Universität Rostock, 18051 Rostock (Germany); and others

    2014-09-08

    A key feature of extreme ultraviolet (XUV) radiation from free-electron lasers (FELs) is its spatial and temporal coherence. We measured the spatio-temporal coherence properties of monochromatized FEL pulses at 13.5 nm using a Michelson interferometer. A temporal coherence time of (59±8) fs has been determined, which is in good agreement with the spectral bandwidth given by the monochromator. Moreover, the spatial coherence in vertical direction amounts to about 15% of the beam diameter and about 12% in horizontal direction. The feasibility of measuring spatio-temporal coherence properties of XUV FEL radiation using interferometric techniques advances machine operation and experimental studies significantly.

  12. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  13. Improving spatio-temporal model estimation of satellite-derived PM2.5 concentrations: Implications for public health

    Science.gov (United States)

    Barik, M. G.; Al-Hamdan, M. Z.; Crosson, W. L.; Yang, C. A.; Coffield, S. R.

    2017-12-01

    Satellite-derived environmental data, available in a range of spatio-temporal scales, are contributing to the growing use of health impact assessments of air pollution in the public health sector. Models developed using correlation of Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD) with ground measurements of fine particulate matter less than 2.5 microns (PM2.5) are widely applied to measure PM2.5 spatial and temporal variability. In the public health sector, associations of PM2.5 with respiratory and cardiovascular diseases are often investigated to quantify air quality impacts on these health concerns. In order to improve predictability of PM2.5 estimation using correlation models, we have included meteorological variables, higher-resolution AOD products and instantaneous PM2.5 observations into statistical estimation models. Our results showed that incorporation of high-resolution (1-km) Multi-Angle Implementation of Atmospheric Correction (MAIAC)-generated MODIS AOD, meteorological variables and instantaneous PM2.5 observations improved model performance in various parts of California (CA), USA, where single variable AOD-based models showed relatively weak performance. In this study, we further asked whether these improved models actually would be more successful for exploring associations of public health outcomes with estimated PM2.5. To answer this question, we geospatially investigated model-estimated PM2.5's relationship with respiratory and cardiovascular diseases such as asthma, high blood pressure, coronary heart disease, heart attack and stroke in CA using health data from the Centers for Disease Control and Prevention (CDC)'s Wide-ranging Online Data for Epidemiologic Research (WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). PM2.5 estimation from these improved models have the potential to improve our understanding of associations between public health concerns and air quality.

  14. Spatio-temporal characteristics of self-pulse in hollow cathode discharge

    International Nuclear Information System (INIS)

    Jing, Ha; He, Shoujie

    2015-01-01

    The characteristics of self-pulse in hollow cathode discharge at low pressure have been investigated. The voltage-current (V-I) curves, the influence of ballast resistor on the self-pulses, and the evolution of current and voltage are measured. Both the axial and radial spatio-temporal discharge images of self-pulse are recorded. The results show that there exists the hysteresis effect in the present hollow cathode discharge. The high value of ballast resistors is favourable for the observation of self-pulses. The process of the self-pulse can be divided into three stages from the temporal discharge images, i.e., the pre-discharge, the transition from mainly axial electric field to mainly radial electric field, and the decaying process. The self-pulse is suggested to originate from the mode transition of the discharge in essence

  15. Spatio-temporal chaos and thermal noise in Josephson junction series arrays

    International Nuclear Information System (INIS)

    Dominguez, D.; Cerdeira, H.A.

    1995-01-01

    We study underdamped Josephson junction series arrays that are globally coupled through a resistive shunting load and driven by an rf bias current. We find that they can be an experimental realization of many phenomena currently studied in globally coupled logistic map. Depending on the bias current the array can show Shapiro steps but also spatio-temporal chaos or ''turbulence'' in the IV characteristics. In the turbulent phase there is a saturation of the broad band noise for a large number of junctions. This corresponds to a break down of the law of large numbers as seen in globally coupled maps. We study this phenomenon as a function of thermal noise. We find that when increasing the temperature the broad band noise decreases. (author). 8 refs, 1 fig

  16. A customized light sheet microscope to measure spatio-temporal protein dynamics in small model organisms.

    Directory of Open Access Journals (Sweden)

    Matthias Rieckher

    Full Text Available We describe a customizable and cost-effective light sheet microscopy (LSM platform for rapid three-dimensional imaging of protein dynamics in small model organisms. The system is designed for high acquisition speeds and enables extended time-lapse in vivo experiments when using fluorescently labeled specimens. We demonstrate the capability of the setup to monitor gene expression and protein localization during ageing and upon starvation stress in longitudinal studies in individual or small groups of adult Caenorhabditis elegans nematodes. The system is equipped to readily perform fluorescence recovery after photobleaching (FRAP, which allows monitoring protein recovery and distribution under low photobleaching conditions. Our imaging platform is designed to easily switch between light sheet microscopy and optical projection tomography (OPT modalities. The setup permits monitoring of spatio-temporal expression and localization of ageing biomarkers of subcellular size and can be conveniently adapted to image a wide range of small model organisms and tissue samples.

  17. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

    Science.gov (United States)

    Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

    2014-01-01

    We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

  18. A collaborative large spatio-temporal data visual analytics architecture for emergence response

    International Nuclear Information System (INIS)

    Guo, D; Li, J; Zhou, Y; Cao, H

    2014-01-01

    The unconventional emergency, usually outbreaks more suddenly, and is diffused more quickly, but causes more secondary damage and derives more disaster than what it is usually expected. The data volume and urgency of emergency exceeds the capacity of current emergency management systems. In this paper, we propose a three-tier collaborative spatio-temporal visual analysis architecture to support emergency management. The prototype system, based on cloud computation environment, supports aggregation of massive unstructured and semi-structured data, integration of various computing model sand algorithms; collaborative visualization and visual analytics among users with a diversity of backgrounds. The distributed data in 100TB scale is integrated in a unified platform and shared with thousands of experts and government agencies by nearly 100 models. The users explore, visualize and analyse the big data and make a collaborative countermeasures to emergencies

  19. H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

    Science.gov (United States)

    Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

    2014-01-01

    This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

  20. Laser-Based Spatio-Temporal Characterisation of Port Fuel Injection (PFI Sprays

    Directory of Open Access Journals (Sweden)

    C. T. N. Anand

    2010-06-01

    Full Text Available In the present work, detailed laser-based diagnostic experiments were conducted to characterise the spray from low pressure 2-hole and 4-hole Port Fuel Injection (PFI injectors. The main objective of the work included obtaining quantitative information of the spatio-temporal spray structure of such low-pressure gasoline sprays. A novel approach involving a combination of techniques such as Mie scattering, Granulometry, and Laser Sheet Dropsizing (LSD was used to study the spray structure. The droplet sizes, distributions with time, Sauter Mean Diameters (SMD, droplet velocities, cone angles and spray tip penetrations of the sprays from the injectors were determined. The spray from these injectors is found to be ‘pencil like’ and not dispersed as in high pressure sprays. The application of the above mentioned techniques provides two-dimensional SMD contours of the entire spray at different instants of time, with reasonable accuracy.

  1. FACILITATING INTEGRATED SPATIO-TEMPORAL VISUALIZATION AND ANALYSIS OF HETEROGENEOUS ARCHAEOLOGICAL AND PALAEOENVIRONMENTAL RESEARCH DATA

    Directory of Open Access Journals (Sweden)

    C. Willmes

    2012-07-01

    Full Text Available In the context of the Collaborative Research Centre 806 "Our way to Europe" (CRC806, a research database is developed for integrating data from the disciplines of archaeology, the geosciences and the cultural sciences to facilitate integrated access to heterogeneous data sources. A practice-oriented data integration concept and its implementation is presented in this contribution. The data integration approach is based on the application of Semantic Web Technology and is applied to the domains of archaeological and palaeoenvironmental data. The aim is to provide integrated spatio-temporal access to an existing wealth of data to facilitate research on the integrated data basis. For the web portal of the CRC806 research database (CRC806-Database, a number of interfaces and applications have been evaluated, developed and implemented for exposing the data to interactive analysis and visualizations.

  2. VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

    Science.gov (United States)

    Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

    2017-10-02

    Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

  3. Spatio-temporal model based optimization framework to design future hydrogen infrastructure networks

    International Nuclear Information System (INIS)

    Konda, N.V.S.; Shah, N.; Brandon, N.P.

    2009-01-01

    A mixed integer programming (MIP) spatio-temporal model was used to design hydrogen infrastructure networks for the Netherlands. The detailed economic analysis was conducted using a multi-echelon model of the entire hydrogen supply chain, including feed, production, storage, and transmission-distribution systems. The study considered various near-future and commercially available technologies. A multi-period model was used to design evolutionary hydrogen supply networks in coherence with growing demand. A scenario-based analysis was conducted in order to account for uncertainties in future demand. The study showed that competitive hydrogen networks can be designed for any conceivable scenario. It was concluded that the multi-period model presented significant advantages in relation to decision-making over long time-horizons

  4. Spatio-temporal distribution of global solar radiation for Mexico using GOES data

    Science.gov (United States)

    Bonifaz, R.; Cuahutle, M.; Valdes, M.; Riveros, D.

    2013-05-01

    Increased need of sustainable and renewable energies around the world requires studies about the amount and distribution of such types of energies. Global solar radiation distribution in space and time is a key component on order to know the availability of the energy for different applications. Using GOES hourly data, the heliosat model was implemented for Mexico. Details about the model and its components are discussed step by stem an once obtained the global solar radiation images, different time datasets (hourly, daily, monthly and seasonal) were built in order to know the spatio-temporal behavior of this type of energy. Preliminary maps of the available solar global radiation energy for Mexico are presented, the amount and variation of the solar radiation by regions are analyzed and discussed. Future work includes a better parametrization of the model using calibrated ground stations data and more use of more complex models for better results.

  5. MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

    Full Text Available We present a stochastic model of an experimentmonitoring the spiking activity of a place cell of hippocampus of an experimental animal moving in an arena. Doubly stochastic spatio-temporal point process is used to model and quantify overdispersion. Stochastic intensity is modelled by a Lévy based random field while the animal path is simplified to a discrete random walk. In a simulation study first a method suggested previously is used. Then it is shown that a solution of the filtering problem yields the desired inference to the random intensity. Two approaches are suggested and the new one based on finite point process density is applied. Using Markov chain Monte Carlo we obtain numerical results from the simulated model. The methodology is discussed.

  6. Spatio-Temporal Analysis of Human Activities in Indoor Environments through Mobile Sensing

    DEFF Research Database (Denmark)

    Prentow, Thor Siiger

    with the intuition and personal experience of the planners. Lack of real-time information on task execution has made it difficult to adapt to changes in the schedules, such as delays or suddenly occurring urgent tasks. The recent advances in methods and devices for mobile sensing provides opportunities...... methods for spatio-temporal analysis of human activities in indoor environments based on mobile sensing. The methods aim to improve scheduling and facility utilization by providing information on the used route networks, transportation modes, travel times, and the flow of people through buildings....... The methods are based on large-scale real-time indoor positioning through the use of existing WiFi infrastructures, which allows for easy deployment even in very large building complexes. The methods are designed for real-time operation, which enables them to detect and adjust to changes as they occur...

  7. Spatio-temporal features for tracking and quadruped/biped discrimination

    Science.gov (United States)

    Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

    2012-05-01

    Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

  8. Spatio-temporal Characteristics of Land Use Land Cover Change Driven by Large Scale Land Transactions in Cambodia

    Science.gov (United States)

    Ghosh, A.; Smith, J. C.; Hijmans, R. J.

    2017-12-01

    Since mid-1990s, the Cambodian government granted nearly 300 `Economic Land Concessions' (ELCs), occupying approximately 2.3 million ha to foreign and domestic organizations (primarily agribusinesses). The majority of Cambodian ELC deals have been issued in areas of both relatively low population density and low agricultural productivity, dominated by smallholder production. These regions often contain highly biodiverse areas, thereby increasing the ecological cost associated with land clearing for extractive purposes. These large-scale land transactions have also resulted in substantial and rapid changes in land-use patterns and agriculture practices by smallholder farmers. In this study, we investigated the spatio-temporal characteristics of land use change associated with large-scale land transactions across Cambodia using multi-temporal multi-reolution remote sensing data. We identified major regions of deforestation during the last two decades using Landsat archive, global forest change data (2000-2014) and georeferenced database of ELC deals. We then mapped the deforestation and land clearing within ELC boundaries as well as areas bordering or near ELCs to quantify the impact of ELCs on local communities. Using time-series from MODIS Vegetation Indices products for the study period, we also estimated the time period over which any particular ELC deal initiated its proposed activity. We found evidence of similar patterns of land use change outside the boundaries of ELC deals which may be associated with i) illegal land encroachments by ELCs and/or ii) new agricultural practices adopted by local farmers near ELC boundaries. We also detected significant time gaps between ELC deal granting dates and initiation of land clearing for ELC purposes. Interestingly, we also found that not all designated areas for ELCs were put into effect indicating the possible proliferation of speculative land deals. This study demonstrates the potential of remote sensing techniques

  9. A realistic large-scale model of the cerebellum granular layer predicts circuit spatio-temporal filtering properties

    Directory of Open Access Journals (Sweden)

    Sergio Solinas

    2010-05-01

    Full Text Available The way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing and space (center-surround by network inhibition. This burst-burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100 Hz. The contrast between center and surround properties was regulated by the excitatory-inhibitory balance. The stronger excitation made the center more responsive to 10-50 Hz input frequencies and enhanced the granule cell output (with spike occurring earlier and with higher frequency and number compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations.

  10. The three α1-adrenoceptor subtypes show different spatio-temporal mechanisms of internalization and ERK1/2 phosphorylation.

    Science.gov (United States)

    Perez-Aso, M; Segura, V; Montó, F; Barettino, D; Noguera, M A; Milligan, G; D'Ocon, P

    2013-10-01

    We analyzed the kinetic and spatial patterns characterizing activation of the MAP kinases ERK 1 and 2 (ERK1/2) by the three α1-adrenoceptor (α1-AR) subtypes in HEK293 cells and the contribution of two different pathways to ERK1/2 phosphorylation: protein kinase C (PKC)-dependent ERK1/2 activation and internalization-dependent ERK1/2 activation. The different pathways of phenylephrine induced ERK phosphorylation were determined by western blot, using the PKC inhibitor Ro 31-8425, the receptor internalization inhibitor concanavalin A and the siRNA targeting β-arrestin 2. Receptor internalization properties were studied using CypHer5 technology and VSV-G epitope-tagged receptors. Activation of α1A- and α1B-ARs by phenylephrine elicited rapid ERK1/2 phosphorylation that was directed to the nucleus and inhibited by Ro 31-8425. Concomitant with phenylephrine induced receptor internalization α1A-AR, but not α1B-AR, produced a maintained and PKC-independent ERK phosphorylation, which was restricted to the cytosol and inhibited by β-arrestin 2 knockdown or concanavalin A treatment. α1D-AR displayed constitutive ERK phosphorylation, which was reduced by incubation with prazosin or the selective α1D antagonist BMY7378. Following activation by phenylephrine, α1D-AR elicited rapid, transient ERK1/2 phosphorylation that was restricted to the cytosol and not inhibited by Ro 31-8425. Internalization of the α1D-AR subtype was not observed via CypHer5 technology. The three α1-AR subtypes present different spatio-temporal patterns of receptor internalization, and only α1A-AR stimulation translates to a late, sustained ERK1/2 phosphorylation that is restricted to the cytosol and dependent on β-arrestin 2 mediated internalization. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period.

    Science.gov (United States)

    Furuya-Kanamori, Luis; Robson, Jenny; Soares Magalhães, Ricardo J; Yakob, Laith; McKenzie, Samantha J; Paterson, David L; Riley, Thomas V; Clements, Archie C A

    2014-11-01

    To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia. Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level. C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model. There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation. Copyright © 2014 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

  12. Participatory Bluetooth Sensing: A Method for Acquiring Spatio-Temporal Data about Participant Mobility and Interactions at Large Scale Events

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Larsen, Jakob Eg; Jørgensen, Sune Lehmann

    2013-01-01

    for collecting spatio-temporal data about participant mobility and social interactions uses the capabilities of Bluetooth capable smartphones carried by participants. As a proof-of-concept we present a field study with deployment of the method in a large music festival with 130 000 participants where a small...

  13. Spatio-temporal encoding using narrow-band linear frequency modulated signals in synthetic aperture ultrasound imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2005-01-01

    In this paper a method for spatio-temporal encoding is presented for synthetic transmit aperture ultrasound imaging (STA). The purpose is to excite several transmitters at the same time in order to transmit more acoustic energy in every single transmission. When increasing the transmitted acousti...

  14. Spatio-temporal spectra in the logarithmic layer of wall turbulence: large-eddy simulations and simple models

    NARCIS (Netherlands)

    Wilczek, Michael; Stevens, Richard Johannes Antonius Maria; Meneveau, Charles

    2015-01-01

    Motivated by the need to characterize the spatio-temporal structure of turbulence in wall-bounded flows, we study wavenumber–frequency spectra of the streamwise velocity component based on large-eddy simulation (LES) data. The LES data are used to measure spectra as a function of the two

  15. Spatio-temporal dynamics of the penetration resistance of recultivated soils formed after open cast mining

    Directory of Open Access Journals (Sweden)

    A. V. Zhukov

    2016-01-01

    Full Text Available On the basis of studying the spatio-temporal dynamics of soil penetration resistance we proved the existence of the technozem ecomorphs as above horizon soil formations. Research was carried out at a research center for study of recultivation processes in Ordzhonikidze city. Measurement of soils penetration was made in field conditions using an Eijkelkamp penetrometer on a regular grid at depths of up to50 cmwith intervals of5 cm. Calculation of average values and degrees of variation was performed by means of descriptive statistical tools. The extent of soil penetration spatial dependence was assessed and the existence of ecomorphs was proved by means of geostatistical analysis. The degree of associativity of spatial distribution of indicators of a soil body in different years of research was established by means of correlation analysis. The level of variation in space and in time of  technozem penetration generated on loess-like loams, grey-green, red-brown clays, and also pedozems was revealed. The degree of spatial dependence of  technozem penetration within soil layers and also the linear sizes of ecomorphs as above horizon soil structures was established. The time dynamics of  penetration of various recultozems were described. As a result of research into the spatio-temporal dynamics of penetration of technozems, data confirming the hypothesis of the existence of ecomorphs as above horizon morphological soil formations were obtained. An ecomorphic approach to the study of the morphological structure of technozems is proposed. The comparative characteristics of ecomorphs from various types of technozem are presented. The results obtained solve the problem of combining the higher and lowest levels in the hierarchical system of soil organisation as a natural body, which should raise the efficiency of the analysis of relations of morphological elements as a basis for detailed reconstruction of recultivation processes, soil formation, and

  16. Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

    Directory of Open Access Journals (Sweden)

    Delphine Nicolas

    Full Text Available The North Sea cod (Gadus morhua, L. stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature and/or indirect (i.e. changes in the quantity and quality of zooplankton prey effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.

  17. Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

    Science.gov (United States)

    Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

    2017-06-01

    The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

  18. Spatio-temporal Variability of Albedo and its Impact on Glacier Melt Modelling

    Science.gov (United States)

    Kinnard, C.; Mendoza, C.; Abermann, J.; Petlicki, M.; MacDonell, S.; Urrutia, R.

    2017-12-01

    Albedo is an important variable for the surface energy balance of glaciers, yet its representation within distributed glacier mass-balance models is often greatly simplified. Here we study the spatio-temporal evolution of albedo on Glacier Universidad, central Chile (34°S, 70°W), using time-lapse terrestrial photography, and investigate its effect on the shortwave radiation balance and modelled melt rates. A 12 megapixel digital single-lens reflex camera was setup overlooking the glacier and programmed to take three daily images of the glacier during a two-year period (2012-2014). One image was chosen for each day with no cloud shading on the glacier. The RAW images were projected onto a 10m resolution digital elevation model (DEM), using the IMGRAFT software (Messerli and Grinsted, 2015). A six-parameter camera model was calibrated using a single image and a set of 17 ground control points (GCPs), yielding a georeferencing accuracy of accounting for possible camera movement over time. The reflectance values from the projected image were corrected for topographic and atmospheric influences using a parametric solar irradiation model, following a modified algorithm based on Corripio (2004), and then converted to albedo using reference albedo measurements from an on-glacier automatic weather station (AWS). The image-based albedo was found to compare well with independent albedo observations from a second AWS in the glacier accumulation area. Analysis of the albedo maps showed that the albedo is more spatially-variable than the incoming solar radiation, making albedo a more important factor of energy balance spatial variability. The incorporation of albedo maps within an enhanced temperature index melt model revealed that the spatio-temporal variability of albedo is an important factor for the calculation of glacier-wide meltwater fluxes.

  19. Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

    Science.gov (United States)

    Kim, S. K.; Prabhat, M.; Williams, D. N.

    2017-12-01

    Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.

  20. Spatio-Temporal Simulation and Analysis of Regional Ecological Security Based on Lstm

    Science.gov (United States)

    Gong, C.; Qi, L.; Heming, L.; Karimian, H.; Yuqin, M.

    2017-10-01

    Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  1. SPATIO-TEMPORAL SIMULATION AND ANALYSIS OF REGIONAL ECOLOGICAL SECURITY BASED ON LSTM

    Directory of Open Access Journals (Sweden)

    C. Gong

    2017-10-01

    Full Text Available Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP, atmospheric optical depth (AOD, moderate-resolution imaging spectrometer (MODIS, Normalized Difference Vegetation Index (NDVI, landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  2. Adaptive OFDM Waveform Design for Spatio-Temporal-Sparsity Exploited STAP Radar

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2017-11-01

    In this chapter, we describe a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of-freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully adaptive OFDM-STAP, we develop a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain, as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we optimally design the transmit OFDM signals by maximizing the output signal-to-interference-plus-noise ratio (SINR) in order to improve the STAP performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity-based technique and adaptive waveform design.

  3. Spatio-temporal correlations in the Manna model in one, three and five dimensions

    Science.gov (United States)

    Willis, Gary; Pruessner, Gunnar

    2018-02-01

    Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five

  4. Analysis of the Mediterranean fruit fly [Ceratitis capitata (Wiedemann)] spatio-temporal distribution in relation to sex and female mating status for precision IPM.

    Science.gov (United States)

    Sciarretta, Andrea; Tabilio, Maria Rosaria; Lampazzi, Elena; Ceccaroli, Claudio; Colacci, Marco; Trematerra, Pasquale

    2018-01-01

    The Mediterranean fruit fly (medfly), Ceratitis capitata (Wiedemann), is a key pest of fruit crops in many tropical, subtropical and mild temperate areas worldwide. The economic importance of this fruit fly is increasing due to its invasion of new geographical areas. Efficient control and eradication efforts require adequate information regarding C. capitata adults in relation to environmental and physiological cues. This would allow effective characterisation of the population spatio-temporal dynamic of the C. capitata population at both the orchard level and the area-wide landscape. The aim of this study was to analyse population patterns of adult medflies caught using two trapping systems in a peach orchard located in central Italy. They were differentiated by adult sex (males or females) and mating status of females (unmated or mated females) to determine the spatio-temporal dynamic and evaluate the effect of cultivar and chemical treatments on trap catches. Female mating status was assessed by spermathecal dissection and a blind test was carried out to evaluate the reliability of the technique. Geostatistical methods, variogram and kriging, were used to produce distributional maps. Results showed a strong correlation between the distribution of males and unmated females, whereas males versus mated females and unmated females versus mated females showed a lower correlation. Both cultivar and chemical treatments had significant effects on trap catches, showing associations with sex and female mating status. Medfly adults showed aggregated distributions in the experimental field, but hot spots locations varied. The spatial pattern of unmated females reflected that of males, whereas mated females were largely distributed around ripening or ripe fruit. The results give relevant insights into pest management. Mated females may be distributed differently to unmated females and the identification of male hot spots through monitoring would allow localisation of virgin

  5. DataFed: A Federated Data System for Visualization and Analysis of Spatio-Temporal Air Quality Data

    Science.gov (United States)

    Husar, R. B.; Hoijarvi, K.

    2017-12-01

    DataFed is a distributed web-services-based computing environment for accessing, processing, and visualizing atmospheric data in support of air quality science and management. The flexible, adaptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing/visualization applications. DataFed `wrapper' components, non-intrusively wrap heterogeneous, distributed datasets for access by standards-based GIS web services. The mediator components (also web services) map the heterogeneous data into a spatio-temporal data model. Chained web services provide homogeneous data views (e.g., geospatial, time views) using a global multi-dimensional data model. In addition to data access and rendering, the data processing component services can be programmed for filtering, aggregation, and fusion of multidimensional data. A complete application software is written in a custom made data flow language. Currently, the federated data pool consists of over 50 datasets originating from globally distributed data providers delivering surface-based air quality measurements, satellite observations, emissions data as well as regional and global-scale air quality models. The web browser-based user interface allows point and click navigation and browsing the XYZT multi-dimensional data space. The key applications of DataFed are for exploring spatial pattern of pollutants, seasonal, weekly, diurnal cycles and frequency distributions for exploratory air quality research. Since 2008, DataFed has been used to support EPA in the implementation of the Exceptional Event Rule. The data system is also used at universities in the US, Europe and Asia.

  6. Climatology and Spatio-Temporal Variability of Wintertime Total and Extreme Rainfall in Thailand during 1970-2012

    Directory of Open Access Journals (Sweden)

    Atsamon Limsakul

    2017-07-01

    Full Text Available This study aims at examining wintertime (December-January-February; DJF climatology and spatio-temporal variability of Thailand’s total and extreme rainfall during 1970-2012. Analysis showed that the area along the Gulf of Thailand’s eastern coast not only received much amount of rainfall but also underwent great extremes and variances during the northeast monsoon (NEM winters. Empirical Orthogonal Function (EOF analysis similarly revealed that the leading mode of each DJF total or extreme rainfall index was marked by maximum loadings concentrated at the stations located at the exposed area of the NEM flow. Correlation analysis indicated that the leading EOF mode of DJF total and extreme indices in Thailand tended to be higher (lower than normal during strong (weak East Asian Winter Monsoon (EAWM. On longer timescales, the recent decadal change observed in the leading EOF mode of all rainfall indices has been coincident with re-amplification of the EAWM taken place since the early/mid 2000. The leading EOF mode of DJF total and extreme rainfall indices in Thailand also exhibited strong correlations with the tropical-subtropical Pacific Ocean surface temperatures. It was characterized as the Pacific Decadal Oscillation (PDO/El Niño Southern Oscillation (ENSO-related boomerang-shaped spatial patterns, resembling the typical mature phases of the La Niña event and the PDO cool epoch. Based on our analysis, it is reasonable to believe that the anomalies of the NEM and other key EAWM-related circulations are likely to be the possible causes of DJF total and extreme rainfall variations in Thailand. In addition, the ENSO and PDO as the primary global atmospheric external forcing are likely to exert their influence on wintertime Thailand’s climate via modulating the EAWM/NEM-related circulations anomalies.

  7. Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

    Science.gov (United States)

    H, V.; Karmakar, S.; Ghosh, S.

    2015-12-01

    Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.