WorldWideScience

Sample records for spatial factor analysis

  1. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  2. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  3. Spatial Factor Analysis for Aerosol Optical Depth in Metropolises in China with Regard to Spatial Heterogeneity

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    Hui Shi

    2018-04-01

    Full Text Available A substantial number of studies have analyzed how driving factors impact aerosols, but they have been little concerned with the spatial heterogeneity of aerosols and the factors that impact aerosols. The spatial distributions of the aerosol optical depth (AOD retrieved by Moderate Resolution Imaging Spectrometer (MODIS data at 550-nm and 3-km resolution for three highly developed metropolises, the Beijing-Tianjin-Hebei (BTH region, the Yangtze River Delta (YRD, and the Pearl River Delta (PRD, in China during 2015 were analyzed. Different degrees of spatial heterogeneity of the AOD were found, which were indexed by Moran’s I index giving values of 0.940, 0.715, and 0.680 in BTH, YRD, and PRD, respectively. For the spatial heterogeneity, geographically weighted regression (GWR was employed to carry out a spatial factor analysis, where terrain, climate condition, urban development, and vegetation coverage were taken as the potential driving factors. The results of the GWR imply varying relationships between the AOD and the factors. The results were generally consistent with existing studies, but the results suggest the following: (1 Elevation increase would more likely lead to a strong negative impact on aerosols (with most of the coefficients ranging from −1.5~0 in the BTH, −1.5~0 in the YRD, and −1~0 in the PRD in the places with greater elevations where the R-squared values are always larger than 0.5. However, the variation of elevations cannot explain the variation of aerosols in the places with relatively low elevations (with R-squared values approximately 0.1, ranging from 0 to 0.3, and approximately 0.1 in the BTH, YRD, and PRD, such as urban areas in the BTH and YRD. (2 The density of the built-up areas made a strong and positive impact on aerosols in the urban areas of the BTH (R-squared larger than 0.5, while the R-squared dropped to 0.1 in the places far away from the urban areas. (3 The vegetation coverage led to a stronger

  4. Prevalence, risk factors and spatial analysis of liver fluke infections in Danish cattle herds

    DEFF Research Database (Denmark)

    Olsen, Abbey; Frankena, Klaas; Bødker, Rene

    2015-01-01

    fitted the observed spatial pattern. Results: During the investigated period (2011-2013), an increase in annual herd prevalence was noted (2011-25.6%; 2012-28.4%; 2013-29.3%). The spatial analysis suggested significant clustering of positive and negative herds. Presence of streams, wetlands and pastures...... on farms showed a significant association with the presence of infection in cattle herds. Buying animals from positive herds was a risk factor on conventional farms. Additionally, risk of being infected with Fasciola hepatica was higher in non-dairy herds of medium size (>= 30 and ... to dairy and large (>= 100) cattle herds. The observed spatial pattern could be reproduced by predictions of the risk factor model. Conclusions: This study showed an increase in annual herd level prevalence (2011 to 2013) indicating that an increasing proportion of herds are infected with Fasciola hepatica...

  5. Diving into the consumer nutrition environment: A Bayesian spatial factor analysis of neighborhood restaurant environment.

    Science.gov (United States)

    Luan, Hui; Law, Jane; Lysy, Martin

    2018-02-01

    Neighborhood restaurant environment (NRE) plays a vital role in shaping residents' eating behaviors. While NRE 'healthfulness' is a multi-facet concept, most studies evaluate it based only on restaurant type, thus largely ignoring variations of in-restaurant features. In the few studies that do account for such features, healthfulness scores are simply averaged over accessible restaurants, thereby concealing any uncertainty that attributed to neighborhoods' size or spatial correlation. To address these limitations, this paper presents a Bayesian Spatial Factor Analysis for assessing NRE healthfulness in the city of Kitchener, Canada. Several in-restaurant characteristics are included. By treating NRE healthfulness as a spatially correlated latent variable, the adopted modeling approach can: (i) identify specific indicators most relevant to NRE healthfulness, (ii) provide healthfulness estimates for neighborhoods without accessible restaurants, and (iii) readily quantify uncertainties in the healthfulness index. Implications of the analysis for intervention program development and community food planning are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Prevalence, risk factors and spatial analysis of liver fluke infections in Danish cattle herds

    DEFF Research Database (Denmark)

    Olsen, Abbey; Frankena, Klaas; Bødker, Rene

    2015-01-01

    Background: Fasciola hepatica, a trematode parasite (liver fluke), infects a wide range of host species causing fasciolosis. The disease is prevalent world-wide and causes considerable economic losses to the livestock industry. Fasciolosis is regarded as an emerging food-borne zoonosis. To promote...... awareness among farmers and to implement strategies to control the infection, this study examined the prevalence, spatial distribution and risk factors for Fasciola hepatica infection in Danish cattle herds. Methods: A retrospective population based study was performed using meat inspection data...... of approximately 1.5 million cattle slaughtered in the period 2011 to 2013. Annual cumulative prevalence of recorded liver fluke findings was calculated for each year. Global and local spatial cluster analysis was used to identify and map spatial patterns of Fasciola hepatica positive and negative herds to explore...

  7. Spatial econometric analysis of factors influencing regional energy efficiency in China.

    Science.gov (United States)

    Song, Malin; Chen, Yu; An, Qingxian

    2018-05-01

    Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

  8. Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis

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    Levy Jonathan I

    2007-05-01

    Full Text Available Abstract Background There has been growing interest among exposure assessors, epidemiologists, and policymakers in the concept of "hot spots", or more broadly, the "spatial extent" of impacts from traffic-related air pollutants. This review attempts to quantitatively synthesize findings about the spatial extent under various circumstances. Methods We include both the peer-reviewed literature and government reports, and focus on four significant air pollutants: carbon monoxide, benzene, nitrogen oxides, and particulate matter (including both ultrafine particle counts and fine particle mass. From the identified studies, we extracted information about significant factors that would be hypothesized to influence the spatial extent within the study, such as the study type (e.g., monitoring, air dispersion modeling, GIS-based epidemiological studies, focus on concentrations or health risks, pollutant under study, background concentration, emission rate, and meteorological factors, as well as the study's implicit or explicit definition of spatial extent. We supplement this meta-analysis with results from some illustrative atmospheric dispersion modeling. Results We found that pollutant characteristics and background concentrations best explained variability in previously published spatial extent estimates, with a modifying influence of local meteorology, once some extreme values based on health risk estimates were removed from the analysis. As hypothesized, inert pollutants with high background concentrations had the largest spatial extent (often demonstrating no significant gradient, and pollutants formed in near-source chemical reactions (e.g., nitrogen dioxide had a larger spatial extent than pollutants depleted in near-source chemical reactions or removed through coagulation processes (e.g., nitrogen oxide and ultrafine particles. Our illustrative dispersion model illustrated the complex interplay of spatial extent definitions, emission rates

  9. [Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

    Science.gov (United States)

    Wang, Xiao-ming; Wang, Ke; Ao, Wei-jiu; Deng, Jin-song; Han, Ning; Zhu, Xiao-yun

    2008-11-01

    Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict. In this paper, the special habitat factors for T. grandis cv. Merrillii in its core region, i.e., in seven villages of Zhuji City, Zhejiang Province were analyzed with Principal Component Analysis (PCA) and a series of data, such as IKONOS image, Digital Elevation Model (DEM), and field survey data supported by the spatial information technology. The results showed that T. grandis cv. Merrillii exhibited high selectivity of environmental factors such as elevation, slope, and aspect. 96.22% of T. grandis cv. Merrillii trees were located at the elevation from 300 to 600 m, 97.52% of them were found to present on the areas whose slope was less than 300, and 74.43% of them distributed on sunny and half-sunny slopes. The results of PCA analysis indicated that the main environmental factors affecting the habitat of T. grandis cv. Merrillii were moisture, heat, and soil nutrients, and moisture might be one of the most important ecological factors for T. grandis cv. Merrillii due to the unique biological and ecological characteristics of the tree species.

  10. The Spatial Econometric Analysis of China’s Banking Competition and Its Influential Factors

    Directory of Open Access Journals (Sweden)

    Ying Li

    2015-12-01

    Full Text Available This paper determines alternative indexes to measure banking competition from the perspective of industrial economics. Spatial correlation of competition in China’s banking environment is studied from the perspective of spatial economics. A spatial panel data model is built to make an empirical study of factors influencing banking competition. The results show that the global autocorrelation test index Moran’s I indicates that China’s banking competition has obvious spatial correlation characteristics and significant spatial clustering. The space LISA map indicates that banking competition in most provinces has the characteristics of spatial dependence, and only a few provinces have the characteristics of spatial heterogeneity. Human capital, economic growth, financial scale of development, and foreign direct investment all have a significant positive effect on improving the degree of banking competition. Government intervention has a significant negative impact on the degree of banking competition, while fixed asset investment has no significant impact on it.

  11. Correlation analysis of lung cancer and urban spatial factor: based on survey in Shanghai.

    Science.gov (United States)

    Wang, Lan; Zhao, Xiaojing; Xu, Wangyue; Tang, Jian; Jiang, Xiji

    2016-09-01

    The density of particulate matter (PM) in mega-cities in China such as Beijing and Shanghai has exceeded basic standards for health in recent years. Human exposure to PMs has been identified as traceable and controllable factor among all complicated risk factors for lung cancer. While the improvement of air quality needs tremendous efforts and time, certain revision of PM's density might happen associated with the adjustment of built environment. It is also proved that urban built environment is directly relevant to respiratory disease. Studies have respectively explored the indoor and outdoor factors on respiratory diseases. More comprehensive spatial factors need to be analyzed to understand the cumulative effect of built environment upon respiratory system. This interdisciplinary study examines the impact of both indoor (including age of housing, interval after decoration, indoor humidity etc.) and outdoor spatial factors (including density, parking, green spaces etc.) on lung cancer. A survey of lung cancer patients and a control group has been conducted in 2014 and 2015. A total of 472 interviewees are randomly selected within a pool of local residents who have resided in Shanghai for more than 5 years. Data are collected including their socio-demographic factors, lifestyle factors, and external and internal residential area factors. Regression models are established based on collected data to analyze the associations between lung cancer and urban spatial factors. Regression models illustrate that lung cancer presents significantly associated with a number of spatial factors. Significant outdoor spatial factors include external traffic volume (P=0.003), main plant type (P=0.035 for trees) of internal green space, internal water body (P=0.027) and land use of surrounding blocks (P=0.005 for residential areas of 7-9 floors, P=0.000 for residential areas of 4-6 floors, P=0.006 for business/commercial areas over 10 floors, P=0.005 for business/commercial areas of

  12. Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

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    Chengjing Nie

    Full Text Available BACKGROUND: In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. METHODS: Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. RESULTS: The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

  13. Climatic factors associated with amyotrophic lateral sclerosis: a spatial analysis from Taiwan.

    Science.gov (United States)

    Tsai, Ching-Piao; Tzu-Chi Lee, Charles

    2013-11-01

    Few studies have assessed the spatial association of amyotrophic lateral sclerosis (ALS) incidence in the world. The aim of this study was to identify the association of climatic factors and ALS incidence in Taiwan. A total of 1,434 subjects with the primary diagnosis of ALS between years 1997 and 2008 were identified in the national health insurance research database. The diagnosis was also verified by the national health insurance programme, which had issued and providing them with "serious disabling disease (SDD) certificates". Local indicators of spatial association were employed to investigate spatial clustering of age-standardised incidence ratios in the townships of the study area. Spatial regression was utilised to reveal any association of annual average climatic factors and ALS incidence for the 12-year study period. The climatic factors included the annual average time of sunlight exposure, average temperature, maximum temperature, minimum temperature, atmospheric pressure, rainfall, relative humidity and wind speed with spatial autocorrelation controlled. Significant correlations were only found for exposure to sunlight and rainfall and it was similar in both genders. The annual average of the former was found to be negatively correlated with ALS, while the latter was positively correlated with ALS incidence. While accepting that ALS is most probably multifactorial, it was concluded that sunlight deprivation and/or rainfall are associated to some degree with ALS incidence in Taiwan.

  14. Analysis of spatial dynamic of epizootic process of bluetongue and its risk factors.

    Science.gov (United States)

    Bouchemla, Fayssal; Popova, Olga Mikhailovna; Agoltsov, Valerey Alexandrovich

    2017-10-01

    The study was undertaken to find out the spatial dynamic occurrence and patterns of the global spread of bluetongue (BT) disease for the period from 1996 to 2016, as well as the assessment of the risk of occurrence and its spread in 2017-2018. Outbreaks (serum samples were collected from clinically healthy as well as suspected animals in infected points) were confirmed and reported officially by veterinary departments which represent different geographical regions in the world to World Organization for Animal Health. These reports explained that ELISA and polymerase chain reaction were used to identify the BT disease, taking in the account number of infected, dead animals, and focus of BT infection in all susceptible animals from 1996 to 2016. Once conventional statistical population was defined (an observational study), we had classified data as well as possible to answer to our aim, using descriptive statistics methods, including the test of the relationship between different epizootiological indicators. The spatial dynamic study of BT's occurrence and its spread in the world over the two past decades was presented by different epizootic indicators. The given analysis includes assessment and measurement of risk factors. It was built too, regression models, and allowed to put different forecasts on the different epizootic indicators in the years 2017-2018 by the extrapolation method. We had also determined that, in 2017, BT continues to spread with the total expectancy of 3.4 focus of infection (number of diseased animals in a single unfavorable point) and mortality of about 26 %; these rates tend to decrease in 2018. At abused points by BT, up to 78.4% of animals are mixed (more than one type) and in 21.6% - uniform. By this way, the relative risk of the incidence of appearance-abused points in mixed households has 3.64, which might be considered higher for the BT dissemination. Moreover, between the enzootic index and other epizootiological indicators had

  15. Analysis of spatial dynamic of epizootic process of bluetongue and its risk factors

    Directory of Open Access Journals (Sweden)

    Fayssal Bouchemla

    2017-10-01

    Full Text Available Aim: The study was undertaken to find out the spatial dynamic occurrence and patterns of the global spread of bluetongue (BT disease for the period from 1996 to 2016, as well as the assessment of the risk of occurrence and its spread in 2017-2018. Materials and Methods: Outbreaks (serum samples were collected from clinically healthy as well as suspected animals in infected points were confirmed and reported officially by veterinary departments which represent different geographical regions in the world to World Organization for Animal Health. These reports explained that ELISA and polymerase chain reaction were used to identify the BT disease, taking in the account number of infected, dead animals, and focus of BT infection in all susceptible animals from 1996 to 2016. Once conventional statistical population was defined (an observational study, we had classified data as well as possible to answer to our aim, using descriptive statistics methods, including the test of the relationship between different epizootiological indicators. Results: The spatial dynamic study of BT's occurrence and its spread in the world over the two past decades was presented by different epizootic indicators. The given analysis includes assessment and measurement of risk factors. It was built too, regression models, and allowed to put different forecasts on the different epizootic indicators in the years 2017-2018 by the extrapolation method. We had also determined that, in 2017, BT continues to spread with the total expectancy of 3.4 focus of infection (number of diseased animals in a single unfavorable point and mortality of about 26 %; these rates tend to decrease in 2018. At abused points by BT, up to 78.4% of animals are mixed (more than one type and in 21.6% - uniform. By this way, the relative risk of the incidence of appearance-abused points in mixed households has 3.64, which might be considered higher for the BT dissemination. Moreover, between the enzootic

  16. Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors

    International Nuclear Information System (INIS)

    Long, Ruyin; Shao, Tianxiang; Chen, Hong

    2016-01-01

    Highlights: • We evaluate the industrial carbon productivity of China’s provinces. • The regional disparity and clustering features exist simultaneously. • There is evident spatial dependence in regional industrial carbon productivity. • We employ spatial panel data models to examine the impact factors. • Spatial effects are found to be important in understanding industrial CO_2 emissions. - Abstract: This study measured the industrial carbon productivity of 30 provinces in China from 2005 to 2012 and examined the space–time characteristics and the main factors of China’s industrial carbon productivity using Moran’s I index and spatial panel data models. The empirical results indicate that there is significant positive spatial dependence and clustering characteristics in China’s province-level industrial carbon productivity. The spatial dependence may create biased estimated parameters in an ordinary least squares framework; according to the analysis of our spatial panel models, industrial energy efficiency, the opening degree, technological progress, and the industrial scale structure have significantly positive effects on industrial carbon productivity whereas per-capita GDP, the industrial energy consumption structure, and the industrial ownership structure exert a negative effect on industrial carbon productivity.

  17. ANALYSIS OF SPATIAL PATTERN AND INFLUENCING FACTORS OF E-COMMERCE

    OpenAIRE

    Y. Zhang; J. Chen; S. Zhang

    2017-01-01

    This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran’s I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze R...

  18. Developing Talented Soccer Players: An Analysis of Socio-Spatial Factors as Possible Key Constraints

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    Serra-Olivares Jaime

    2016-12-01

    Full Text Available Most studies on the identification and development of soccer talent have been one-dimensional in nature. Although some multi-dimensional analyses have been conducted, few research studies have assessed in any depth the socio-spatial factors influencing talent development. The aim of this particular study was to analyse variations in the international representation of clubs (n = 821 and countries (n = 59 in the development of players who took part in the 2014 FIFA Soccer World Cup. Clubs and countries were ranked and divided into quartiles according to the number of players developed between the ages of 15 and 21 (clubs and countries that developed players for at least three years between these ages and the number of official league matches played by these players up to the age of 23. Significant variations were observed between clubs in terms of the number of developed players who took part in the World Cup and the number of official league matches played by these players up to the age of 23 (p < .05, and also between countries (p < .05. The findings reveal the need to carry out more in-depth studies into the type of training and competition engaged in by elite players in the period of development between the ages of 15 and 21. It may be the case that these factors are potentially decisive socio-spatial constraints in the development of soccer talent.

  19. Analysis of Spatial Pattern and Influencing Factors of E-Commerce

    Science.gov (United States)

    Zhang, Y.; Chen, J.; Zhang, S.

    2017-09-01

    This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran's I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze River delta. The comprehensive factors caculated through PCA are described as fundamental social productivity, resident living standard and population sex structure. The first two factors have positive correlation with e-commerce, and the intensity of effect increases yearly. However, the influence of population sex structure on the E-commerce development is not significant. Our results suggest that the clustering of e-commerce has a downward trend and the impact of driving factors on e-commerce is observably distinct from year to year in space.

  20. ANALYSIS OF SPATIAL PATTERN AND INFLUENCING FACTORS OF E-COMMERCE

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2017-09-01

    Full Text Available This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran’s I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze River delta. The comprehensive factors caculated through PCA are described as fundamental social productivity, resident living standard and population sex structure. The first two factors have positive correlation with e-commerce, and the intensity of effect increases yearly. However, the influence of population sex structure on the E-commerce development is not significant. Our results suggest that the clustering of e-commerce has a downward trend and the impact of driving factors on e-commerce is observably distinct from year to year in space.

  1. Spatial Analysis of Regional Factors and Lung Cancer Mortality in China, 1973-2013.

    Science.gov (United States)

    Shen, Xiaoping; Wang, Limin; Zhu, Li

    2017-04-01

    Background: China's lung cancer crude death rate has increased 6.9-fold from 1973 to 2014. During this time, the country experienced extremely rapid economic growth and social change. It is important to understand the effects of risk factors on lung cancer mortality (LCM) for better allocation of limited resources of cancer prevention and control in China. Methods: Using three nationwide mortality surveys from 1973 to 2005, Global Health Data Exchange data in 2013, three nationwide smoking surveys from 1984 to 2013, four population censuses from 1964 to 2000, and other datasets, we have compiled datasets and developed spatial random effect models to assess the association of various area-level-contributing factors on LCM. Spatial scan statistics are used to detect high-risk clusters of LCM. Results: LCM is higher in urban and more industrialized areas (RR = 1.17) compared with those in rural areas. The level of industrial development's effect is higher for men, which accounts for about 70% of all LCM. Smoking is positively associated with regional variation of LCM rates, and the effect is higher for women than for men. Conclusions: The geographic pattern of high LCM in China is different from that of Western countries. LCM is positively associated with higher socioeconomic status, with more urbanized areas at a higher level of industrial development. Impact: There is a need to further explore additional risk in the high-risk clusters. The study is about China, but this situation may happen in other countries experiencing rapid industrialization and other developing countries. Cancer Epidemiol Biomarkers Prev; 26(4); 569-77. ©2017 AACR See all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences." ©2017 American Association for Cancer Research.

  2. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  3. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  4. Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

    International Nuclear Information System (INIS)

    Pinho, P.; Augusto, S.; Maguas, C.; Pereira, M.J.; Soares, A.; Branquinho, C.

    2008-01-01

    The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales

  5. Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

    Energy Technology Data Exchange (ETDEWEB)

    Pinho, P.; Augusto, S.; Maguas, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Pereira, M.J.; Soares, A. [Universidade Tecnica de Lisboa, Instituto Superior Tecnico, Centro de Recursos Naturais e Ambiente (CERENA) Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Branquinho, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Universidade Atlantica, Antiga Fabrica da Polvora de Barcarena, 2745-615 Barcarena (Portugal)], E-mail: cmbranquinho@fc.ul.pt

    2008-01-15

    The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales.

  6. Temporal-spatial variations and driving factors analysis of coastal reclamation in China

    Science.gov (United States)

    Meng, Weiqing; Hu, Beibei; He, Mengxuan; Liu, Baiqiao; Mo, Xunqiang; Li, Hongyuan; Wang, Zhongliang; Zhang, Yu

    2017-05-01

    Coastal reclamation is the gain of land from the sea or coastal wetlands for agricultural purposes, industrial use or port expansions. Large-scale coastal land reclamation can have adverse effects on the coastal environment, including loss of marine habitats and deterioration of coastal water quality. In recent decades, coastal land reclamation has occurred extensively to meet the increasing needs of rapid economic development and urbanization in China. The overall objective of this study is to understand the coastal reclamation status of China from 1979 to 2014 and analyzed its driving factors for mitigating negative ecological effects. The data of coastal reclamation were done with the ERDAS Imagine V9.2 platform and ArcGIS software based on remote images including Landsat, SPOT, ZY-2 and ZY-3. Potential driving factors for sea reclamation were selected based on statistics bulletins and the knowledge of experts in coastal management. In order to understand the relationships among possible impact factors and coastal reclamation, the Partial Least-Squares Regression models was constructed. The analysis results indicated that the total area of reclamation was 11162.89 km2 based on remote sensing images between 1979 and 2014. Shandong Province is the largest reclamation area, reaching 2736.54 km2, and the reclamation is mainly concentrated in Zhejiang, Jiangsu and Liaoning, where the reclamation areas were all more than 1000 km2. According to the remote sensing images, there are three coastal reclamation hotspot regions including Bohai bay (in which is located Liaoning, Tianjin and Hebei), Jiangsu province coastal area and Hangzhou bay (in Zhejiang province). A large scale land reclamation plan of more than 5880 km2 has been made by local government and 2469 km2 has approved by the State Council. From the analyzed results, there is a significant collinearity between these indicators, and no significant correlation between the area of reclamation and selected

  7. Spatial Analysis in Determining Physical Factors of Pedestrian Space Livability, Case Study: Pedestrian Space on Jalan Kemasan, Yogyakarta

    Science.gov (United States)

    Fauzi, A. F.; Aditianata, A.

    2018-02-01

    The existence of street as a place to perform various human activities becomes an important issue nowadays. In the last few decades, cars and motorcycles dominate streets in various cities in the world. On the other hand, human activity on the street is the determinant of the city livability. Previous research has pointed out that if there is lots of human activity in the street, then the city will be interesting. Otherwise, if the street has no activity, then the city will be boring. Learning from that statement, now various cities in the world are developing the concept of livable streets. Livable streets shown by diversity of human activities conducted in the streets’ pedestrian space. In Yogyakarta, one of the streets shown diversity of human activities is Jalan Kemasan. This study attempts to determine the physical factors of pedestrian space affecting the livability in Jalan Kemasan Yogyakarta through spatial analysis. Spatial analysis was performed by overlay technique between liveable point (activity diversity) distribution map and variable distribution map. Those physical pedestrian space research variable included element of shading, street vendors, building setback, seat location, divider between street and pedestrian way, and mixed use building function. More diverse the activity of one variable, then those variable are more affected then others. Overlay result then strengthened by field observation to qualitatively ensure the deduction. In the end, this research will provide valuable input for street and pedestrian space planning that is comfortable for human activities.

  8. Analysis of factors which limited the spatial variation of barley yield on the forest-steppe chernozems of Kursk region

    Science.gov (United States)

    Belik, Anton; Vasenev, Ivan; Jablonskikh, Lidia; Bozhko, Svetlana

    2017-04-01

    The crop yield is the most important indicator of the efficiency of agricultural production. It is the function that depends on a large number of groups of independent variables, such as the weather, soil fertility and overall culture agriculture. A huge number of combinations of these factors contribute to the formation of high spatial variety of crop yields within small areas, includes the slope agrolandscapes in Kursk region. Spatial variety of yield leads to a significant reduction in the efficiency of agriculture. In this connection, evaluation and analysis of the factors, which limits the yield of field crops is a very urgent proble in agroecology. The research was conducted in the period of 2003-2004 on a representative field. The typical and leached chernozems with the varying thickness and of erosion degree are dominated in soil cover. At the time of field research studied areas were busy by barley. The reseached soils have an average and increased fertility level. Chernozem typical full-face, and the leached contain an average of 4.5-6% humus, close to neutral pH, favorable values of physico-chemical parameters, medium and high content of nutrients. The eroded chernozems differs agrogenic marked declining in fertility parameters. The diversity of meso- and micro-relief in the fields and soil cover influence to significant spatial variety of fertility. For example the content of nutrients in the soil variation can be up to 5-fold level. High spatial heterogeneity of soils fertility ifluence to barley yield variety. During research on the productivity of the field varied in the range of 20-43 c/ha, and 7-44 c/ha (2004). Analysis of the factors, which limited the yield of barley, showed that the first priorities occupy unregulated characterises: slope angle and the classification of soils (subtype and race of chernozem and the difference in the degree of erosion), which determines the development of erosion processes and redistribution available to plants

  9. Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK.

    Directory of Open Access Journals (Sweden)

    Lucy Waruguru Mburu

    Full Text Available Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use.

  10. Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK.

    Science.gov (United States)

    Mburu, Lucy Waruguru; Helbich, Marco

    2016-01-01

    Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use.

  11. Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

    International Nuclear Information System (INIS)

    Keser, Saniye; Duzgun, Sebnem; Aksoy, Aysegul

    2012-01-01

    Highlights: ► Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. ► Traditional non-spatial regression models may not provide sufficient information for better solid waste management. ► Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. ► Significances of global parameters may diminish at local scale for some provinces. ► GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation data is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global

  12. A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

    OpenAIRE

    Gonroos, M; Jacobsen, D; Hamada, N; Gothe, E; Enclada, A; Dudgeon, D; Dangles, O; Cottenie, K; Callisto, M; Brand, C; Bonada, N; Angeler, DG; Al-Shami, SA; Altermatt, F; Bini, LM

    2015-01-01

    The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second,...

  13. Spatial analysis of under-5 mortality and potential risk factors in the Basse Health and Demographic Surveillance System, the Gambia.

    Science.gov (United States)

    Quattrochi, John; Jasseh, Momodou; Mackenzie, Grant; Castro, Marcia C

    2015-07-01

    To describe the spatial pattern in under-5 mortality rates in the Basse Health and Demographic Surveillance System (BHDSS) and to test for associations between under-5 deaths and biodemographic and socio-economic risk factors. Using data on child survival from 2007 to 2011 in the BHDSS, we mapped under-5 mortality by km(2) . We tested for spatial clustering of high or low death rates using Kulldorff's spatial scan statistic. Associations between child death and a variety of biodemographic and socio-economic factors were assessed with Cox proportional hazards models, and deviance residuals from the best-fitting model were tested for spatial clustering. The overall death rate among children under 5 was 0.0195 deaths per child-year. We found two spatial clusters of high death rates and one spatial cluster of low death rates; children in the two high clusters died at a rate of 0.0264 and 0.0292 deaths per child-year, while in the low cluster, the rate was 0.0144 deaths per child-year. We also found that children born to Fula mothers experienced, on average, a higher hazard of death, whereas children born in the households in the upper two quintiles of asset ownership experienced, on average, a lower hazard of death. After accounting for the spatial distribution of biodemographic and socio-economic characteristics, we found no residual spatial pattern in child mortality risk. This study demonstrates that significant inequality in under-5 death rates can occur within a relatively small area (1100 km(2) ). Risks of under-5 mortality were associated with mother's ethnicity and household wealth. If high mortality clusters persist, then equity concerns may require additional public health efforts in those areas. © 2015 John Wiley & Sons Ltd.

  14. Characterization factors for terrestrial acidification at the global scale: a systematic analysis of spatial variability and uncertainty.

    Science.gov (United States)

    Roy, Pierre-Olivier; Azevedo, Ligia B; Margni, Manuele; van Zelm, Rosalie; Deschênes, Louise; Huijbregts, Mark A J

    2014-12-01

    Characterization factors (CFs) are used in life cycle assessment (LCA) to quantify the potential impact per unit of emission. CFs are obtained from a characterization model which assess the environmental mechanisms along the cause-effect chain linking an emission to its potential damage on a given area of protection, such as loss in ecosystem quality. Up to now, CFs for acidifying emissions did not cover the global scale and were only representative of their characterization model geographical scope. Consequently, current LCA practices implicitly assume that all emissions from a global supply chain occur within the continent referring to the characterization method geographical scope. This paper provides worldwide 2°×2.5° spatially-explicit CFs, representing the change in relative loss of terrestrial vascular plant species due to an emission change of nitrogen oxides (NOx), ammonia (NH3) and sulfur dioxide (SO2). We found that spatial variability in the CFs is much larger compared to statistical uncertainty (six orders of magnitude vs. two orders of magnitude). Spatial variability is mainly caused by the atmospheric fate factor and soil sensitivity factor, while the ecological effect factor is the dominant contributor to the statistical uncertainty. The CFs provided in our study allow the worldwide spatially explicit evaluation of life cycle impacts related to acidifying emissions. This opens the door to evaluate regional life cycle emissions of different products in a global economy. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. The AIDS epidemic and economic input impact factors in Chongqing, China, from 2006 to 2012: a spatial-temporal analysis.

    Science.gov (United States)

    Zhang, Yanqi; Xiao, Qin; Zhou, Liang; Ma, Dihui; Liu, Ling; Lu, Rongrong; Yi, Dali; Yi, Dong

    2015-03-27

    To analyse the spatial-temporal clustering of the HIV/AIDS epidemic in Chongqing and to explore its association with the economic indices of AIDS prevention and treatment. Data on the HIV/AIDS epidemic and economic indices of AIDS prevention and treatment were obtained from the annual reports of the Chongqing Municipal Center for Disease Control for 2006-2012. Spatial clustering analysis, temporal-spatial clustering analysis, and spatial regression were used to conduct statistical analysis. The annual average new HIV infection rate, incidence rate for new AIDS cases, and rate of people living with HIV in Chongqing were 5.97, 2.42 and 28.12 per 100,000, respectively, for 2006-2012. The HIV/AIDS epidemic showed a non-random spatial distribution (Moran's I≥0.310; p<0.05). The epidemic hotspots were distributed in the 15 mid-western counties. The most likely clusters were primarily located in the central region and southwest of Chongqing and occurred in 2010-2012. The regression coefficients of the total amount of special funds allocated to AIDS and to the public awareness unit for the numbers of new HIV cases, new AIDS cases, and people living with HIV were 0.775, 0.976 and 0.816, and -0.188, -0.259 and -0.215 (p<0.002), respectively. The Chongqing HIV/AIDS epidemic showed temporal-spatial clustering and was mainly clustered in the mid-western and south-western counties, showing an upward trend over time. The amount of special funds dedicated to AIDS and to the public awareness unit showed positive and negative relationships with HIV/AIDS spatial clustering, respectively. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  16. Professional analysis in spatial planning

    Directory of Open Access Journals (Sweden)

    Andrej Černe

    2005-12-01

    Full Text Available Spatial analysis contributes to accomplishment of the three basic aims of spatial planning: it is basic element for setting spatial policies, concepts and strategies, gives basic information to inhabitants, land owners, investors, planners and helps in performing spatial policies, strategies, plans, programmes and projects. Analysis in planning are generally devoted to: understand current circumstances and emerging conditions within planning decisions; determine priorities of open questions and their solutions; formulate general principles for further development.

  17. Bovine respiratory syncytial virus and bovine coronavirus antibodies in bulk tank milk - risk factors and spatial analysis.

    Science.gov (United States)

    Toftaker, Ingrid; Sanchez, Javier; Stokstad, Maria; Nødtvedt, Ane

    2016-10-01

    Bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCoV) are considered widespread among cattle in Norway and worldwide. This cross-sectional study was conducted based on antibody-ELISA of bulk tank milk (BTM) from 1347 herds in two neighboring counties in western Norway. The study aims were to determine the seroprevalence at herd level, to evaluate risk factors for BRSV and BCoV seropositivity, and to assess how these factors were associated with the spatial distribution of positive herds. The overall prevalence of BRSV and BCoV positive herds in the region was 46.2% and 72.2%, respectively. Isopleth maps of the prevalence risk distribution showed large differences in prevalence risk across the study area, with the highest prevalence in the northern region. Common risk factors of importance for both viruses were herd size, geographic location, and proximity to neighbors. Seropositivity for one virus was associated with increased odds of seropositivity for the other virus. Purchase of livestock was an additional risk factor for BCoV seropositivity, included in the model as in-degree, which was defined as the number of incoming movements from individual herds, through animal purchase, over a period of five years. Local dependence and the contribution of risk factors to this effect were assessed using the residuals from two logistic regression models for each virus. One model contained only the x- and y- coordinates as predictors, the other had all significant predictors included. Spatial clusters of high values of residuals were detected using the normal model of the spatial scan statistic and visualized on maps. Adjusting for the risk factors in the final models had different impact on the spatial clusters for the two viruses: For BRSV the number of clusters was reduced from six to four, for BCoV the number of clusters remained the same, however the log-likelihood ratios changed notably. This indicates that geographical differences in proximity to

  18. The spatial-temporal evolution of aerosol optical depth and the analysis of influence factors in Bohai Rim

    International Nuclear Information System (INIS)

    Hou, Chunliang; Jiang, Hong; Wang, Xiaoyan; Pei, Huan

    2014-01-01

    Aerosol Optical Depth (AOD) is an important parameter of aerosol optical properties and it is an important physical parameter quantity to understanding the atmospheric environment. Bohai Rim is one of the three major urban agglomeration regions with rapidly developing economy in China. The study of AOD over this region is important to understand the environment and climate in Bohai Rim. Firstly, aerosol product data from 2000 to 2010, published by NASA, were used to analyze the temporal-spatial evolution of AOD in Bohai Rim with precision evaluation. The results showed that the spatial distribution of AOD had an obvious regional characteristic. The spatial distribution characterized that a much high value existed at urban areas and plain areas. On the contrary, the low value data existed in some mountainous regions which had higher percentages of forest coverage. The AOD values fluctuated somewhat each year in the region, from the minimum annual mean in 2003 to the maximum in 2009. Generally, the highest AOD value was in summer, followed by spring, autumn and winter. In terms of monthly variation, the value of AOD reached its peak in June and the lowest value was in December. This study analyzed the relation between AOD and some influence factors such as land use types, elevation, and distribution of urban agglomeration and so on. These results provide an important basic dataset for climate and environmental research

  19. Perspectives on spatial data analysis

    CERN Document Server

    Rey, Sergio

    2010-01-01

    This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading experts in the field. Four main aspects are highlighted, dealing with spatial analysis, pattern analysis, local statistics as well as illustrative empirical applications. Researchers and students will gain an appreciation of Getis' methodological contributions to spatial analysis and the broad impact of the methods he has helped pioneer on an impressively broad array of disciplines including spatial epidemiology, demography, economics, and ecology. The volume is a compilation of high impact original contributions, as evidenced by citations, and the latest thinking on the field by leading scholars. This makes the book ideal for advanced seminars and courses in spatial analysis as well as a key resource for researchers seeking a comprehensive overview of recent advances and future directions in the field.

  20. Rock avalanche occurrence in the San Juan province (Argentina): an analysis of their spatial distribution and main forcing factors

    Science.gov (United States)

    Penna, Ivanna; Tonini, Marj; Vega Orozco, Carmen D.; Longchamp, Céline; Derron, Marc-Henri; Jaboyedoff, Michel

    2013-04-01

    Rock avalanches are frequent phenomena in the Argentinean Andes and a particular high concentration of these events is observed in the Northwest (~25°S) and in the Central Andes from 30°S until the transition with the Patagonian Andes (~38°S). Tectonic deformation and seismicity are generally proposed as main driving factors, with weather and lithologic conditions playing a subordinate role. From 28°S to 33°S, the subhorizontal subduction of the Nazca plate drives higher shortening rates than in the surrounding areas, and an intense seismicity. Main morphotectonic units in this regions are the Cordillera and Precordillera, separated by the Barreal-Calingasta depression. In the southern central part of the flat subduction area (30°30'°-32°30'S), it is observed high valley incision and maximum local relief of 2900 m, while in the Precordillera main fluvial courses developed in the inter-thrust valleys, where local relief is up to 2400 m. In both mountain ranges, we recognized 34 rock avalanches deposits with volumes up to 0.3 km3. There is no apparent lithologic control on detachments, which involved sedimentary, volcanic and granite rocks, even though ~20% of them were favored by layering orientation. However, about 50% of the inventoried rock avalanches with the greatest volumes, developed along tectonic structures or less than 1 km far from them. The main objective of the present study is to explore the spatial distribution of rock avalanche deposits, and compare it with the instrumental seismicity and landscape conditions by means of statistical tools (e.g. exploratory data analyses, Ripley's K-function). Those analyses allow to highlight the spatial correlation between the geological events. Moreover, to visually display the detected cluster spatial patterns we elaborated kernel density maps. Our findings revealed that most of the rock avalanches show a high spatial aggregation mainly between 31°20'S-31°50'S. Main concentration of bedrock landslides

  1. Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes.

    Science.gov (United States)

    Baker, Jannah; White, Nicole; Mengersen, Kerrie

    2014-11-20

    Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

  2. Analysis of Impact of Geographical Environment and Socio-economic Factors on the Spatial Distribution of Kaohsiung Dengue Fever Epidemic

    Science.gov (United States)

    Hsu, Wei-Yin; Wen, Tzai-Hung; Yu, Hwa-Lung

    2013-04-01

    Taiwan is located in subtropical and tropical regions with high temperature and high humidity in the summer. This kind of climatic condition is the hotbed for the propagation and spread of the dengue vector mosquito. Kaohsiung City has been the worst dengue fever epidemic city in Taiwan. During the study period, from January 1998 to December 2011, Taiwan CDC recorded 7071 locally dengue epidemic cases in Kaohsiung City, and the number of imported case is 118. Our research uses Quantile Regression, a spatial infection disease distribution, to analyze the correlation between dengue epidemic and geographic environmental factors and human society factors in Kaohsiung. According to our experiment statistics, agriculture and natural forest have a positive relation to dengue fever(5.5~34.39 and 3.91~15.52). The epidemic will rise when the ratio for agriculture and natural forest increases. Residential ratio has a negative relation for quantile 0.1 to 0.4(-0.005~-0.78), and a positive relation for quantile 0.5 to0.9(0.01~18.0) . The mean income is also a significant factor in social economy field, and it has a negative relation to dengue fever(-0.01~-0.04). Conclusion from our research is that the main factor affecting the degree of dengue fever in predilection area is the residential proportion and the ratio of agriculture and natural forest plays an important role affecting the degree of dengue fever in non predilection area. Moreover, the serious epidemic area located by regression model is the same as the actual condition in Kaohsiung. This model can be used to predict the serious epidemic area of dengue fever and provide some references for the Health Agencies

  3. Factor analysis

    CERN Document Server

    Gorsuch, Richard L

    2013-01-01

    Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications for effective use. This includes not only theory but also the empirical evaluations of the importance of mathematical distinctions for applied scientific analysis.

  4. Human factors issues and approaches in the spatial layout of a space station control room, including the use of virtual reality as a design analysis tool

    Science.gov (United States)

    Hale, Joseph P., II

    1994-01-01

    Human Factors Engineering support was provided for the 30% design review of the late Space Station Freedom Payload Control Area (PCA). The PCA was to be the payload operations control room, analogous to the Spacelab Payload Operations Control Center (POCC). This effort began with a systematic collection and refinement of the relevant requirements driving the spatial layout of the consoles and PCA. This information was used as input for specialized human factors analytical tools and techniques in the design and design analysis activities. Design concepts and configuration options were developed and reviewed using sketches, 2-D Computer-Aided Design (CAD) drawings, and immersive Virtual Reality (VR) mockups.

  5. Influence of Topographic and Hydrographic Factors on the Spatial Distribution of Leptospirosis Disease in São Paulo County, Brazil: An Approach Using Geospatial Techniques and GIS Analysis

    Science.gov (United States)

    Ferreira, M. C.; Ferreira, M. F. M.

    2016-06-01

    Leptospirosis is a zoonosis caused by Leptospira genus bacteria. Rodents, especially Rattus norvegicus, are the most frequent hosts of this microorganism in the cities. The human transmission occurs by contact with urine, blood or tissues of the rodent and contacting water or mud contaminated by rodent urine. Spatial patterns of concentration of leptospirosis are related to the multiple environmental and socioeconomic factors, like housing near flooding areas, domestic garbage disposal sites and high-density of peoples living in slums located near river channels. We used geospatial techniques and geographical information system (GIS) to analysing spatial relationship between the distribution of leptospirosis cases and distance from rivers, river density in the census sector and terrain slope factors, in Sao Paulo County, Brazil. To test this methodology we used a sample of 183 geocoded leptospirosis cases confirmed in 2007, ASTER GDEM2 data, hydrography and census sectors shapefiles. Our results showed that GIS and geospatial analysis techniques improved the mapping of the disease and permitted identify the spatial pattern of association between location of cases and spatial distribution of the environmental variables analyzed. This study showed also that leptospirosis cases might be more related to the census sectors located on higher river density areas and households situated at shorter distances from rivers. In the other hand, it was not possible to assert that slope terrain contributes significantly to the location of leptospirosis cases.

  6. Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

    Science.gov (United States)

    Hoos, Anne B.; McMahon, Gerard

    2009-01-01

    Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

  7. An Integrated Approach Using Spatial Analysis to Study the Risk Factors for Leishmaniasis in Area of Recent Transmission

    Directory of Open Access Journals (Sweden)

    Júlia Alves Menezes

    2015-01-01

    Full Text Available Some epidemiological aspects of leishmaniasis in the municipality of Formiga, Brazil, an important touristic site, were evaluated. Those included phlebotomine sand fly vectors, canine infection, and geoprocessing analysis for determining critical transmission areas. Sand flies (224 insects belonging to ten different species were captured. The most captured species included Lutzomyia longipalpis (35.3%, Lutzomyia cortelezzii (33.5%, and Lutzomyia whitmani (18.3%. A significant correlation between sand fly densities and climatic conditions was detected. Serological diagnosis (DPP and ELISA was performed in 570 dogs indicating a prevalence of 5.8%. After sequencing the main species circulating in the area were Leishmania infantum and Leishmania braziliensis. Spatial analysis demonstrated that vegetation and hydrography may be related to sand fly distribution and infected dogs. The municipality of Formiga has proven leishmaniasis vectors and infected dogs indicating the circulation of the parasite in the city. Correlation of those data with environmental and human cases has identified the critical areas for control interventions (south, northeast, and northwest. In conclusion, there is current transmission of visceral and canine human cases and the city is on the risk for the appearance of cutaneous cases.

  8. Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos population of Alberta, Canada.

    Directory of Open Access Journals (Sweden)

    Mathieu L Bourbonnais

    Full Text Available Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC generated from a threatened grizzly bear (Ursus arctos population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife

  9. Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada.

    Science.gov (United States)

    Bourbonnais, Mathieu L; Nelson, Trisalyn A; Cattet, Marc R L; Darimont, Chris T; Stenhouse, Gordon B

    2013-01-01

    Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others

  10. Spatial analysis of weed patterns

    NARCIS (Netherlands)

    Heijting, S.

    2007-01-01

    Keywords: Spatial analysis, weed patterns, Mead’s test, space-time correlograms, 2-D correlograms, dispersal, Generalized Linear Models, heterogeneity, soil, Taylor’s power law. Weeds in agriculture occur in patches. This thesis is a contribution to the characterization of this patchiness, to its

  11. Spatial factors as contextual qualifiers of information seeking

    Directory of Open Access Journals (Sweden)

    R. Savolainen

    2006-01-01

    Full Text Available Introduction. This paper investigates the ways in which spatial factors have been approached in information seeking studies. The main attention was focused on studies discussing information seeking on the level of source selection and use. Method. Conceptual analysis of about 100 articles and books thematizing spatial issues of information seeking. Due to research economy, the main attention was paid to studies on everyday life information seeking. Results. Three major viewpoints were identified with regard to the degree of objectivity of spatial factors. The objectifying approach conceives of spatial factors as external and entity-like qualifiers that primarly constrain information seeking. The realistic-pragmatic approach emphasizes the ways in which the availabilty of information sources in different places such as daily work environments orient information seeking. The perspectivist approach focuses on how people subjectively assess the significance of various sources by means of spatial constructs such as information horizons. Conclusion. Spatial factors are centrally important contextual qualifiers of information seeking. There is a need to further explore the potential of the above viewpoints by relating the spatial and temporal factors of information seeking.

  12. Spatial Analysis of Environmental Factors Related to Lyme Disease in Alabama by Means of NASA Earth Observation Systems

    Science.gov (United States)

    Renneboog, Nathan; Capilouto, Emily G.; Firsing, Stephen L., III; Levy, Kyle; McAllister, Marilyn; Roa, Kathryn; Setia,Shveta; Xie, Lili; Burnett, Donna; Luvall, Jeffrey C.

    2009-01-01

    This slide presentation reviews the epidemiology of Lyme Disease that accounts for more than 95% or vector borne diseases in the United States. The history, symptoms and the life cycle of the tick, the transmitting agent of Lyme Disease, a map that shows the cases reported to the CDC between1990 and 2006 and the number of cases in Alabama by year from 1986 to 2007. A NASA project is described, the goals of which are to (1) Demonstrate the presence of the chain of infection of Lyme disease in Alabama (2) Identify areas with environmental factors that support tick population using NASA Earth Observation Systems data in selected areas of Alabama and (3) Increase community awareness of Lyme disease and recommend primary and secondary prevention strategies. The remote sensing methods included: Analyzed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and DigitalGlobe Quickbird satellite imagery from summer months and Performed image analyses in ER Mapper 7.1. Views from the ASTER and Quickbird land cover are shown, the Normalized Difference Vegetation Index (NDVI) algorithm was applied to all ASTER and Quickbird imagery. The use of the images to obtain the level of soil moisture is reviewed, and this analysis was used along with the NDVI, was used to identify the areas that support the tick population.

  13. Progress in spatial analysis methods and applications

    CERN Document Server

    Páez, Antonio; Buliung, Ron N; Dall'erba, Sandy

    2010-01-01

    This book brings together developments in spatial analysis techniques, including spatial statistics, econometrics, and spatial visualization, and applications to fields such as regional studies, transportation and land use, population and health.

  14. Spatial analysis of factors associated with household subscription to the National Health Insurance Scheme in rural Ghana

    Directory of Open Access Journals (Sweden)

    Stephen Manortey

    2014-02-01

    Full Text Available The use of health insurance schemes in financing healthcare delivery and to minimize the poverty gap is gaining considerable recognition among the least developed and resource challenged countries around the world. With the implementation of the socialized health insurance scheme, Ghana has taken the lead in Sub-Saharan Africa and now working out further strategies to gain universal coverage among her citizenry. The primary goal of this study is to explore the spatial relationship between the residential homes and demographic features of the people in the Barekese subdistrict in Ghana on the probability to enroll the entire household unit in the National Health Insurance Scheme (NHIS. Household level data were gathered from 20 communities on the enrollment status into the NHIS alongside demographic and socioeconomic indicators and the spatial location of every household that participated in the study. Kulldorff’s purely spatial scan statistic was used to detect geographic clusters of areas with participatory households that have either higher or lower enrollment patterns in the insurance program. Logistic regression models on selected demographic and socioeconomic indicators were built to predict the effect on the odds of enrolling an entire household membership in the NHIS. Three clusters significantly stood out to have either high or low enrollment patterns in the health insurance program taking into accounts the number of households in those sub-zones of the study region. Households in the Cluster 1 insurance group have very high travel expenses compared to their counterparts in the other idenfied clusters. Travel cost and time to the NHIS registration center to enroll in the program were both significant predictors to participation in the program when controlling for cluster effect. Residents in the High socioeconomic group have about 1.66 [95% CI: 1.27-2.17] times the odds to enroll complete households in the insurance program compared to

  15. PREVALENCE OF THE HEPATITIS C VIRUS AMONG UNIVERSITY EMPLOYEES IN SÃO PAULO, SOUTHEASTERN BRAZIL: predictive factors and geoprocessing spatial analysis

    Directory of Open Access Journals (Sweden)

    Cássio Vieira de OLIVEIRA

    2015-03-01

    Full Text Available Background There are limited studies on the prevalence and risk factors associated with hepatitis C virus (HCV infection. Objective Identify the prevalence and risk factors for HCV infection in university employees of the state of São Paulo, Brazil. Methods Digital serological tests for anti-HCV have been performed in 3153 volunteers. For the application of digital testing was necessary to withdraw a drop of blood through a needlestick. The positive cases were performed for genotyping and RNA. Chi-square and Fisher’s exact test were used, with P-value 40 years, blood transfusion, injectable drugs, inhalable drugs (InDU, injectable Gluconergam®, glass syringes, tattoos, hemodialysis and sexual promiscuity. Age (P=0.01, OR 5.6, CI 1.4 to 22.8, InDU (P<0.0001, OR=96.8, CI 24.1 to 388.2, Gluconergam® (P=0.0009, OR=44.4, CI 4.7 to 412.7 and hemodialysis (P=0.0004, OR=90.1, CI 7.5 – 407.1 were independent predictors. Spatial analysis of the prevalence with socioeconomic indices, Gross Domestic Product and Human Development Index by the geoprocessing technique showed no positive correlation. Conclusions The prevalence of HCV infection was 0.7%. The independent risk factors for HCV infection were age, InDU, Gluconergan® and hemodialysis. There was no spatial correlation of HCV prevalence with local economic factors.

  16. Stereological analysis of spatial structures

    DEFF Research Database (Denmark)

    Hansen, Linda Vadgård

    The thesis deals with stereological analysis of spatial structures. One area of focus has been to improve the precision of well-known stereological estimators by including information that is available via automatic image analysis. Furthermore, the thesis presents a stochastic model for star......-shaped three-dimensional objects using the radial function. It appears that the model is highly fleksiblel in the sense that it can be used to describe an object with arbitrary irregular surface. Results on the distribution of well-known local stereological volume estimators are provided....

  17. Regional Convergence of Income: Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Vera Ivanovna Ivanova

    2014-12-01

    Full Text Available Russia has a huge territory and a strong interregional heterogeneity, so we can assume that geographical factors have a significant impact on the pace of economic growth in Russian regions. Therefore the article is focused on the following issues: 1 correlation between comparative advantages of geographical location and differences in growth rates; 2 impact of more developed regions on their neighbors and 3 correlation between economic growth of regions and their spatial interaction. The article is devoted to the empirical analysis of regional per capita incomes from 1996 to 2012 and explores the dynamics of the spatial autocorrelation of regional development indicator. It is shown that there is a problem of measuring the intensity of spatial dependence: factor value of Moran’s index varies greatly depending on the choice of the matrix of distances. In addition, with the help of spatial econometrics the author tests the following hypotheses: 1 there is convergence between regions for a specified period; 2 the process of beta convergence is explained by the spatial arrangement of regions and 3 there is positive impact of market size on regional growth. The author empirically confirmed all three hypotheses

  18. Geographical Inequalities and Social and Environmental Risk Factors for Under-Five Mortality in Ghana in 2000 and 2010: Bayesian Spatial Analysis of Census Data.

    Science.gov (United States)

    Arku, Raphael E; Bennett, James E; Castro, Marcia C; Agyeman-Duah, Kofi; Mintah, Samilia E; Ware, James H; Nyarko, Philomena; Spengler, John D; Agyei-Mensah, Samuel; Ezzati, Majid

    2016-06-01

    Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana. We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0) for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from 40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis. Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends.

  19. Geographical Inequalities and Social and Environmental Risk Factors for Under-Five Mortality in Ghana in 2000 and 2010: Bayesian Spatial Analysis of Census Data.

    Directory of Open Access Journals (Sweden)

    Raphael E Arku

    2016-06-01

    Full Text Available Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana.We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0 for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from 40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis.Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends.

  20. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  1. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  2. Analysis on temporal and spatial distribution of reference evapotranspiration and its possible influencing factors in Yunnan Province

    Science.gov (United States)

    Li, Yashan; Nan, Lijun; Wang, Yanjun; Xu, Chengdong; Yang, Yunyuan; Cui, Changwei; Yang, Junmei; Guo, Yuan; Li, Miaorong

    2018-04-01

    This article was based on the climate data of 125 meteorological stations from 1982 to 2011 in Yunnan Province, the daily basis ET0 was calculated with Penman-Monteith equation recommended by FAO in 1998. Then the Kriging interpolation method and related methods of climate statistical diagnosis analysis were used to analyze the features. The main results showed that the highest value of annual ET0 of Yunnan Province was the joint parts of Dali, Lijiang and Chuxiong, and also the north of Chuxiong and Kunming, while the least value was the northeast and northwest of Yunnan Province. The ET0 was showed rising trend, the speed was about 5.9mm/10a, but the rising trend was not significant. The ET0 of spring was highest, and the ET0 of summer and autumn was taken the second place, the ET0 of winter was last. The ET0 of spring, summer, autumn, winter was account for 33.35 per cent, 28.91 per cent, 20.36, per cent, 17.39 per cent of annual ET0 respectively. The ET0 of May was highest and December was least in annual. ET0 was closely related to wind speed, relative humidity, hours of sunshine and the daily maximum temperature. The correlation between wind speed, hours of sunshine, the daily maximum temperature and ET0 was very significantly positive, while the correlation between relative humidity and ET0 was very significantly negative.

  3. Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis.

    Science.gov (United States)

    Cao, Zheng; Liu, Tao; Li, Xing; Wang, Jin; Lin, Hualiang; Chen, Lingling; Wu, Zhifeng; Ma, Wenjun

    2017-07-17

    Background : Large spatial heterogeneity was observed in the dengue fever outbreak in Guangzhou in 2014, however, the underlying reasons remain unknown. We examined whether socio-ecological factors affected the spatial distribution and their interactive effects. Methods : Moran's I was applied to first examine the spatial cluster of dengue fever in Guangzhou. Nine socio-ecological factors were chosen to represent the urbanization level, economy, accessibility, environment, and the weather of the 167 townships/streets in Guangzhou, and then the geographical detector was applied to analyze the individual and interactive effects of these factors on the dengue outbreak. Results : Four clusters of dengue fever were identified in Guangzhou in 2014, including one hot spot in the central area of Guangzhou and three cold spots in the suburban districts. For individual effects, the temperature ( q = 0.33) was the dominant factor of dengue fever, followed by precipitation ( q = 0.24), road density ( q = 0.24), and water body area ( q = 0.23). For the interactive effects, the combination of high precipitation, high temperature, and high road density might result in increased dengue fever incidence. Moreover, urban villages might be the dengue fever hot spots. Conclusions : Our study suggests that some socio-ecological factors might either separately or jointly influence the spatial distribution of dengue fever in Guangzhou.

  4. Spatial analysis statistics, visualization, and computational methods

    CERN Document Server

    Oyana, Tonny J

    2015-01-01

    An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...

  5. Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001–2011

    International Nuclear Information System (INIS)

    Li, Li; Qian, Jun; Ou, Chun-Quan; Zhou, Ying-Xue; Guo, Cui; Guo, Yuming

    2014-01-01

    There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001–2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures. - Highlights: • Air pollution is still serious in Guangzhou, China. • Air Pollution Index was associated with a variety of meteorological parameters. • The temporal relationships were timescale-dependent. • The findings should be taken into account in air quality forecasts and pollution control. - Spatial and temporal variation of API and its timescale-dependent relationship with meteorological factors in Guangzhou were demonstrated

  6. Spatial analysis and planning under imprecision

    CERN Document Server

    Leung, Y

    1988-01-01

    The book deals with complexity, imprecision, human valuation, and uncertainty in spatial analysis and planning, providing a systematic exposure of a new philosophical and theoretical foundation for spatial analysis and planning under imprecision. Regional concepts and regionalization, spatial preference-utility-choice structures, spatial optimization with single and multiple objectives, dynamic spatial systems and their controls are analyzed in sequence.The analytical framework is based on fuzzy set theory. Basic concepts of fuzzy set theory are first discussed. Many numerical examples and emp

  7. Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010.

    Science.gov (United States)

    Shen, Qiu; Liang, Liang; Luo, Xiang; Li, Yanjun; Zhang, Lianpeng

    2017-08-25

    Drought is a complex natural phenomenon that can cause reduced water supplies and can consequently have substantial effects on agriculture and socioeconomic activities. The objective of this study was to gain a better understanding of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China. The Vegetation Condition Index (VCI) dataset calculated from NOAA/AVHRR images from 1982 to 2010 was used to analyse the spatial-temporal variation characteristics of vegetative drought in China. This study also examined the trends in meteorological factors and their influences on drought using monitoring data collected from 686 national ground meteorological stations. The results showed that the VCI appeared to slowly rise in China from 1982 to 2010. From 1982 to 1999, the VCI rose slowly. Then, around 2000, the VCI exhibited a severe fluctuation before it entered into a relatively stable stage. Drought frequencies in China were higher, showing a spatial distribution feature of "higher in the north and lower in the south". Based on the different levels of drought, the frequencies of mild and moderate drought in four geographical areas were higher, and the frequency of severe drought was higher only in ecologically vulnerable areas, such as the Tarim Basin and the Qaidam Basin. Drought was mainly influenced by meteorological factors, which differed regionally. In the northern region, the main influential factor was sunshine duration, while the other factors showed minimal effects. In the southern region and Tibetan Plateau, the main influential factors were sunshine duration and temperature. In the northwestern region, the main influential factors were wind velocity and station atmospheric pressure.

  8. Foundations of factor analysis

    CERN Document Server

    Mulaik, Stanley A

    2009-01-01

    Introduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMulti

  9. Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

    OpenAIRE

    Liu Xin; Zhang Shaoliang; Zheng Pulin

    2015-01-01

    Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then ...

  10. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  11. Spatial distribution and risk factors of influenza in Jiangsu province, China, based on geographical information system

    Directory of Open Access Journals (Sweden)

    Jia-Cheng Zhang

    2014-05-01

    Full Text Available Influenza poses a constant, heavy burden on society. Recent research has focused on ecological factors associated with influenza incidence and has also studied influenza with respect to its geographic spread at different scales. This research explores the temporal and spatial parameters of influenza and identifies factors influencing its transmission. A spatial autocorrelation analysis, a spatial-temporal cluster analysis and a spatial regression analysis of influenza rates, carried out in Jiangsu province from 2004 to 2011, found that influenza rates to be spatially dependent in 2004, 2005, 2006 and 2008. South-western districts consistently revealed hotspots of high-incidence influenza. The regression analysis indicates that railways, rivers and lakes are important predictive environmental variables for influenza risk. A better understanding of the epidemic pattern and ecological factors associated with pandemic influenza should benefit public health officials with respect to prevention and controlling measures during future epidemics.

  12. SPATIAL VARIETY AND DISTRIBUTION OF TRADITIONAL MARKETS IN SURAKARTA AS POTENTIAL FACTORS IN IMPROVING SPATIAL-BASED MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Istijabatul Aliyah

    2017-02-01

    Full Text Available Traditional markets function as trading place, socio-culture interaction, and recreation facility either in regional or urban scope. Distribution and variety of spatial condition influence traditional markets’ planning both physically and non-physically. Therefore, this research aimed to conduct a mapping of traditional markets’ spatial distribution and variety as potential factors to improve spatial-based management. Analysis methods including: (1 Mapping by employing Geographic Information System, (2 Category Based Analysis (CBA, and (3 Interactive Analysis were applied in Surakarta City as the research location. The result of this research signifies that spatial variety and distribution of traditional markets in Surakarta had similar pattern between one market to others; overlapping service function; specific commodity types in accordance with the market’s characteristics; diverse operating hours. Spatial variety and distribution could be potential factors to improve traditional market management as shopping service. This result was contrasted with Central Place Theory by Christaller and NÆss & Jensen’s research finding stating that distance became a key factor influencing accessibility to a number of activity facilities. Therefore, distance toward the service center is not considered as the main factor in traditional market management. The main factor in managing and controlling traditional markets’ development includes service function, commodity specification, and operating hour’s flexibility.

  13. Spatial analysis of hemorrhagic fever with renal syndrome in China

    Directory of Open Access Journals (Sweden)

    Yang Hong

    2006-04-01

    Full Text Available Abstract Background Hemorrhagic fever with renal syndrome (HFRS is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Methods Annualized average incidence at a county level was calculated using HFRS cases reported during 1994–1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Results Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's I = 0.5044 (p = 0.001. Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS.

  14. Spatial Analysis Methods of Road Traffic Collisions

    DEFF Research Database (Denmark)

    Loo, Becky P. Y.; Anderson, Tessa Kate

    Spatial Analysis Methods of Road Traffic Collisions centers on the geographical nature of road crashes, and uses spatial methods to provide a greater understanding of the patterns and processes that cause them. Written by internationally known experts in the field of transport geography, the book...... outlines the key issues in identifying hazardous road locations (HRLs), considers current approaches used for reducing and preventing road traffic collisions, and outlines a strategy for improved road safety. The book covers spatial accuracy, validation, and other statistical issues, as well as link...

  15. Statistical Analysis of the Spatial Distribution of Multi-Elements in an Island Arc Region: Complicating Factors and Transfer by Water Currents

    Directory of Open Access Journals (Sweden)

    Atsuyuki Ohta

    2017-01-01

    Full Text Available The compositions and transfer processes affecting coastal sea sediments from the Seto Inland Sea and the Pacific Ocean are examined through the construction of comprehensive terrestrial and marine geochemical maps for western Japan. Two-way analysis of variance (ANOVA suggests that the elemental concentrations of marine sediments vary with particle size, and that this has a greater effect than the regional provenance of the terrestrial material. Cluster analysis is employed to reveal similarities and differences in the geochemistry of coastal sea and stream sediments. This analysis suggests that the geochemical features of fine sands and silts in the marine environment reflect those of stream sediments in the adjacent terrestrial areas. However, gravels and coarse sands do not show this direct relationship, which is likely a result of mineral segregation by strong tidal currents and the denudation of old basement rocks. Finally, the transport processes for the fine-grained sediments are discussed, using the spatial distribution patterns of outliers for those elements enriched in silt and clay. Silty and clayey sediments are found to be transported and dispersed widely by a periodic current in the inner sea, and are selectively deposited at the boundary of different water masses in the outer sea.

  16. Field evaluation of spatial repellency of metofluthrin-impregnated latticework plastic strips against Aedes aegypti (L.) and analysis of environmental factors affecting its efficacy in My Tho City, Tien Giang, Vietnam.

    Science.gov (United States)

    Kawada, Hitoshi; Iwasaki, Tomonori; LE Loan, Luu; Tien, Tran Khanh; Mai, Nguyen Thi Nhu; Shono, Yoshinori; Katayama, Yasuyuki; Takagi, Masahiro

    2006-12-01

    Spatial repellency of metofluthrin-impregnated polyethylene latticework plastic strips against Aedes aegypti mosquitoes was evaluated. Analysis of environmental factors affecting the efficacy of these strips, such as room temperature, humidity, and house structure, was performed in a residential area in My Tho City, Tien Giang Province, Vietnam. Treatment with the strips at the rate of 1 strip per 2.6-5.52 m(2) (approximately 600 mg per 2.6-5.52 m(2)) reduced the collection of Ae. aegypti resting inside the houses for at least eight weeks. Multiple regression analysis indicated that both increase in the average room temperature and decrease in the area of openings in the rooms that were treated with the strips positively affected the spatial repellency of metofluthrin.

  17. Correlation Factors Describing Primary and Spatial Sensations of Sound Fields

    Science.gov (United States)

    ANDO, Y.

    2002-11-01

    The theory of subjective preference of the sound field in a concert hall is established based on the model of human auditory-brain system. The model consists of the autocorrelation function (ACF) mechanism and the interaural crosscorrelation function (IACF) mechanism for signals arriving at two ear entrances, and the specialization of human cerebral hemispheres. This theory can be developed to describe primary sensations such as pitch or missing fundamental, loudness, timbre and, in addition, duration sensation which is introduced here as a fourth. These four primary sensations may be formulated by the temporal factors extracted from the ACF associated with the left hemisphere and, spatial sensations such as localization in the horizontal plane, apparent source width and subjective diffuseness are described by the spatial factors extracted from the IACF associated with the right hemisphere. Any important subjective responses of sound fields may be described by both temporal and spatial factors.

  18. Factor analysis and scintigraphy

    International Nuclear Information System (INIS)

    Di Paola, R.; Penel, C.; Bazin, J.P.; Berche, C.

    1976-01-01

    The goal of factor analysis is usually to achieve reduction of a large set of data, extracting essential features without previous hypothesis. Due to the development of computerized systems, the use of largest sampling, the possibility of sequential data acquisition and the increase of dynamic studies, the problem of data compression can be encountered now in routine. Thus, results obtained for compression of scintigraphic images were first presented. Then possibilities given by factor analysis for scan processing were discussed. At last, use of this analysis for multidimensional studies and specially dynamic studies were considered for compression and processing [fr

  19. Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

    Science.gov (United States)

    Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian

    2017-11-15

    Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).

  20. Violence in public transportation: an approach based on spatial analysis.

    Science.gov (United States)

    Sousa, Daiane Castro Bittencourt de; Pitombo, Cira Souza; Rocha, Samille Santos; Salgueiro, Ana Rita; Delgado, Juan Pedro Moreno

    2017-12-11

    To carry out a spatial analysis of the occurrence of acts of violence (specifically robberies) in public transportation, identifying the regions of greater incidence, using geostatistics, and possible causes with the aid of a multicriteria analysis in the Geographic Information System. The unit of analysis is the traffic analysis zone of the survey named Origem-Destino, carried out in Salvador, state of Bahia, in 2013. The robberies recorded by the Department of Public Security of Bahia in 2013 were located and made compatible with the limits of the traffic analysis zones and, later, associated with the respective centroids. After determining the regions with the highest probability of robbery, we carried out a geographic analysis of the possible causes in the region with the highest robbery potential, considering the factors analyzed using a multicriteria analysis in a Geographic Information System environment. The execution of the two steps of this study allowed us to identify areas corresponding to the greater probability of occurrence of robberies in public transportation. In addition, the three most vulnerable road sections (Estrada da Liberdade, Rua Pero Vaz, and Avenida General San Martin) were identified in these areas. In these sections, the factors that most contribute with the potential for robbery in buses are: F1 - proximity to places that facilitate escape, F3 - great movement of persons, and F2 - absence of policing, respectively. Indicator Kriging (geostatistical estimation) can be used to construct a spatial probability surface, which can be a useful tool for the implementation of public policies. The multicriteria analysis in the Geographic Information System environment allowed us to understand the spatial factors related to the phenomenon under analysis.

  1. Spatial and null infinity via advanced and retarded conformal factors

    International Nuclear Information System (INIS)

    Hayward, Sean A.

    2003-01-01

    A new approach to space-time asymptotics is presented, refining Penrose's idea of conformal transformations with infinity represented by the conformal boundary of space-time. It is proposed that the Penrose conformal factor be a product of advanced and retarded conformal factors, which asymptotically relate physical and conformal null coordinates and vanish at future and past null infinity respectively. A refined definition of asymptotic flatness at both spatial and null infinity is given, including that the conformal boundary is locally a light cone, with spatial infinity as the vertex. It is shown how to choose the conformal factors so that this asymptotic light cone is locally a metric light cone. The theory is implemented in the spin-coefficient (or null-tetrad) formalism by a joint transformation of the spin-metric and spin-basis (or metric and tetrad). Asymptotic regularity conditions are proposed, based on the conformal boundary locally being a smoothly embedded metric light cone. These conditions ensure that the Bondi-Sachs energy-flux integrals of ingoing and outgoing gravitational radiation decay at spatial infinity such that the total radiated energy is finite, and that the Bondi-Sachs energy-momentum has a unique limit at spatial infinity, coinciding with the uniquely rendered ADM energy-momentum

  2. Spatially Resolved Analysis of Bragg Selectivity

    Directory of Open Access Journals (Sweden)

    Tina Sabel

    2015-11-01

    Full Text Available This paper targets an inherent control of optical shrinkage in photosensitive polymers, contributing by means of spatially resolved analysis of volume holographic phase gratings. Point by point scanning of the local material response to the Gaussian intensity distribution of the recording beams is accomplished. Derived information on the local grating period and grating slant is evaluated by mapping of optical shrinkage in the lateral plane as well as through the depth of the layer. The influence of recording intensity, exposure duration and the material viscosity on the Bragg selectivity is investigated.

  3. Deciphering factors controlling groundwater arsenic spatial variability in Bangladesh

    Science.gov (United States)

    Tan, Z.; Yang, Q.; Zheng, C.; Zheng, Y.

    2017-12-01

    Elevated concentrations of geogenic arsenic in groundwater have been found in many countries to exceed 10 μg/L, the WHO's guideline value for drinking water. A common yet unexplained characteristic of groundwater arsenic spatial distribution is the extensive variability at various spatial scales. This study investigates factors influencing the spatial variability of groundwater arsenic in Bangladesh to improve the accuracy of models predicting arsenic exceedance rate spatially. A novel boosted regression tree method is used to establish a weak-learning ensemble model, which is compared to a linear model using a conventional stepwise logistic regression method. The boosted regression tree models offer the advantage of parametric interaction when big datasets are analyzed in comparison to the logistic regression. The point data set (n=3,538) of groundwater hydrochemistry with 19 parameters was obtained by the British Geological Survey in 2001. The spatial data sets of geological parameters (n=13) were from the Consortium for Spatial Information, Technical University of Denmark, University of East Anglia and the FAO, while the soil parameters (n=42) were from the Harmonized World Soil Database. The aforementioned parameters were regressed to categorical groundwater arsenic concentrations below or above three thresholds: 5 μg/L, 10 μg/L and 50 μg/L to identify respective controlling factors. Boosted regression tree method outperformed logistic regression methods in all three threshold levels in terms of accuracy, specificity and sensitivity, resulting in an improvement of spatial distribution map of probability of groundwater arsenic exceeding all three thresholds when compared to disjunctive-kriging interpolated spatial arsenic map using the same groundwater arsenic dataset. Boosted regression tree models also show that the most important controlling factors of groundwater arsenic distribution include groundwater iron content and well depth for all three

  4. Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

    Directory of Open Access Journals (Sweden)

    Liu Xin

    2015-12-01

    Full Text Available Spatial local outlier factor (SLOF algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS project, the K-Nearest Neighbour (KNN graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then SLOF was adopted to calculate the outlier degrees of the monitoring points and the 3σ rule was employed to identify the spatial outlier. Finally, the selection of K value was analysed and the optimal one was selected. The results show that, compared with the static threshold method, the proposed algorithm has a higher detection precision. It can overcome the shortcomings of the static threshold method and improve the accuracy and diversity of local outlier detection, which provides a reliable reference for the safety assessment and warning of CCS monitoring.

  5. A new methodology of spatial cross-correlation analysis.

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

    Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

  6. A New Methodology of Spatial Cross-Correlation Analysis

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

    Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

  7. Spatial pattern of soil organic carbon and total nitrogen, and analysis of related factors in an agro-pastoral zone in Northern China

    Science.gov (United States)

    Wang, Xuyang; Chen, Yinping; Lian, Jie; Luo, Yongqing; Niu, Yayi; Gong, Xiangwen

    2018-01-01

    The spatial pattern of soil organic carbon (SOC) and total nitrogen (TN) densities plays a profound important role in estimating carbon and nitrogen budgets. Naiman Banner located in northern China was chosen as research site, a total of 332 soil samples were taken in a depth of 100 cm from the low hilly land in the southern part, sandy land in the middle part and an alluvial plain in the northern part of the county. The results showed that SOC and TN density initially decreased and then increased from the north to the south, The highest densities, were generally in the south, with the lowest generally in the middle part. The SOC and TN densities in cropland were significantly greater than those in woodland and grassland in the alluvial plains and for Naiman as a whole. The woodland SOC and TN density were higher than those of grassland in the low hilly land, and higher densities of SOC and TN in grassland than woodland in the sandy land and low hilly land. There were significant differences in SOC and TN densities among the five soil types of Cambisols, Arenosols, Gleysols, Argosols, and Kastanozems. In addition, SOC and TN contents generally decreased with increasing soil depth, but increased below a depth of 40 cm in the Cambisols and became roughly constant at this depth in the Kastanozems. There is considerable potential to sequester carbon and nitrogen in the soil via the conversion of degraded sandy land into woodland and grassland in alluvial plain, and more grassland should be established in sandy land and low hilly land. PMID:29771979

  8. Factors Affecting the Clinical Measurement of Visuo-Spatial Neglect

    Directory of Open Access Journals (Sweden)

    L. Pizzamiglio

    1992-01-01

    Full Text Available The present study examined a battery of tests to evaluate unilateral spatial neglect; the tests included different tasks involving several modalities of spatial exploration mapping perceptual, motor, attentional and personal or extrapersonal space dimensions. The subjects, 121 right-brain-damaged patients with unilateral neglect, were studied in seven laboratories in four European countries. Relationships among the various tests were examined by correlations, a cluster analysis and by an analysis of individual cases. Different sensitivity was found among various tests for detecting neglect performances. Both the cluster analysis and the single case analysis clearly showed a segregation between personal and extrapersonal neglect. Analysis of the large cluster, including a variety of tests of extra personal neglect, together with the study of single cases, suggests the possibility of differentiating the various manifestations of spatial neglect which can be interpreted on the basis of the descriptions of other individual cases previously reported in the literature. Finally, the present study indicated the relative stability of neglect following the acute phase and its independence from age.

  9. Spatial Epidemiology and Risk Factor Analysis of White Spot Disease in the Shrimp Farming Industry of Sinaloa, Mexico, from 2005 to 2011.

    Science.gov (United States)

    Muniesa, A; Mardones, F O; Chávez, M C; Montoya, L; Cabanillas, J A; de Blas, I; Martínez-López, B

    2017-10-01

    White spot disease (WSD), caused by the white spot syndrome virus, is currently one of the primary causes of mortality and economic losses in the shrimp farming industry worldwide. In Mexico, shrimp production is one of the most important primary activities generating an annual income of USD 711 million. However, WSD introduction in 1999 had a devastating impact for the Mexican shrimp industry. The aim of this study was to characterize the WSD spatio-temporal patterns and to identify the primary risk factors contributing to WSD occurrence from 2005 to 2011 in Sinaloa, Mexico. We used data collected by the 'Comité Estatal de Sanidad Acuícola de Sinaloa' from 2005 to 2011 regarding WSD outbreaks as well as environmental, production and husbandry factors at farm level. The spatio-temporal patterns of WSD were described using space-time scan statistics. The effect of 52 variables on the time to WSD outbreak occurrence was assessed using a multivariable Cox proportional hazards model. Results reveal that WSD risk and survival time were not homogeneously distributed as suggested by the significant clusters obtained using the space-time permutation model and the space-time exponential model, respectively. The Cox model revealed that the first production cycle [hazard ratio (HR) = 11.31], changes from 1 to 1.4°C of temperature oscillation caused by 'El Niño'/'La Niña' events (HR = 1.44) and high average daily growths (HR = 1.26) were significantly associated with lower survival (i.e. shorter time to WSD outbreak) on farm. Conversely, shrimp weight at the moment of the outbreak (HR = 0.159), changes from -0.9 to -0.5°C of temperature oscillation caused by 'El Niño'/'La Niña' events (HR = 0.540), high superficial water temperature during the pound stocking (HR = 0.823) and high (>100) number of days of culture (HR = 0.830) were factors associated with higher survival. Results are expected to inform the design of risk-based, intervention strategies to

  10. Discourse Factors Influencing Spatial Descriptions in English and German

    Science.gov (United States)

    Vorwerg, Constanze; Tenbrink, Thora

    The ways in which objects are referred to by using spatial language depend on many factors, including the spatial configuration and the discourse context. We present the results of a web experiment in which speakers were asked to either describe where a specified item was located in a picture containing several items, or which item was specified. Furthermore, conditions differed as to whether the first six configurations were specifically simple or specifically complex. Results show that speakers' spatial descriptions are more detailed if the question is where rather than which, mirroring the fact that contrasting the target item from the others in which tasks may not always require an equally detailed spatial description as in where tasks. Furthermore, speakers are influenced by the complexity of initial configurations in intricate ways: on the one hand, individual speakers tend to self-align with respect to their earlier linguistic strategies; however, also a contrast effect could be identified with respect to the usage of combined projective terms.

  11. Analyzing Spatial Factors in Crime-inducing Culture in Chaloos

    Directory of Open Access Journals (Sweden)

    Mohammad Hossein Omidi Noghlehbari

    2017-02-01

    Full Text Available Feelings of security in urban areas are one of the qualitative criteria of living space. With the rise in urbanization and increasing abnormal urban behavior, especially offenses, this issue has become of great importance. This study aims to identify and analyze the effects of spatial factors on crime-inducing culture in affluent and non-affluent neighborhoods of Chaloos. The method used in this study is analytical-descriptive and it is practical in terms of objective. In order to study and understand the status of physical-spatial structures of affluent and non-affluent neighborhoods in Chaloos, we used field study method. Data were collected through interview, notes taking and questionnaire. The results indicate that in affluent neighborhoods, all criteria components of spatial differences are above the mean (Mean=3, but in non-affluent neighborhoods, all components are lower than the mean. In addition, there is a significant relationship between criteria components of spatial differences and the formation of crime-inducing culture (except the diagnosis component in the affluent and non-affluent neighborhoods.

  12. Geospatial analysis platform: Supporting strategic spatial analysis and planning

    CSIR Research Space (South Africa)

    Naude, A

    2008-11-01

    Full Text Available Whilst there have been rapid advances in satellite imagery and related fine resolution mapping and web-based interfaces (e.g. Google Earth), the development of capabilities for strategic spatial analysis and planning support has lagged behind...

  13. Spatial Inequalities in the Incidence of Colorectal Cancer and Associated Factors in the Neighborhoods of Tehran, Iran: Bayesian Spatial Models

    Directory of Open Access Journals (Sweden)

    Kamyar Mansori

    2018-01-01

    Full Text Available Objectives The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The Besag-York-Mollié (BYM model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results The Moran index was statistically significant for all the variables studied (p<0.05. The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53, living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96, not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94 and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68 were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range and mean (standard deviation values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01 and 1.05 (1.31, respectively. Conclusions Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in atrisk areas.

  14. Spatial epidemiology of cancer: a review of data sources, methods and risk factors

    Directory of Open Access Journals (Sweden)

    Rita Roquette

    2017-05-01

    Full Text Available Cancer is a major concern among chronic diseases today. Spatial epidemiology plays a relevant role in this matter and we present here a review of this subject, including a discussion of the literature in terms of the level of geographic data aggregation, risk factors and methods used to analyse the spatial distribution of patterns and spatial clusters. For this purpose, we performed a websearch in the Pubmed and Web of Science databases including studies published between 1979 and 2015. We found 180 papers from 63 journals and noted that spatial epidemiology of cancer has been addressed with more emphasis during the last decade with research based on data mostly extracted from cancer registries and official mortality statistics. In general, the research questions present in the reviewed papers can be classified into three different sets: i analysis of spatial distribution of cancer and/or its temporal evolution; ii risk factors; iii development of data analysis methods and/or evaluation of results obtained from application of existing methods. This review is expected to help promote research in this area through the identification of relevant knowledge gaps. Cancer’s spatial epidemiology represents an important concern, mainly for public health policies design aimed to minimise the impact of chronic disease in specific populations.

  15. Participative Spatial Scenario Analysis for Alpine Ecosystems

    Science.gov (United States)

    Kohler, Marina; Stotten, Rike; Steinbacher, Melanie; Leitinger, Georg; Tasser, Erich; Schirpke, Uta; Tappeiner, Ulrike; Schermer, Markus

    2017-10-01

    Land use and land cover patterns are shaped by the interplay of human and ecological processes. Thus, heterogeneous cultural landscapes have developed, delivering multiple ecosystem services. To guarantee human well-being, the development of land use types has to be evaluated. Scenario development and land use and land cover change models are well-known tools for assessing future landscape changes. However, as social and ecological systems are inextricably linked, land use-related management decisions are difficult to identify. The concept of social-ecological resilience can thereby provide a framework for understanding complex interlinkages on multiple scales and from different disciplines. In our study site (Stubai Valley, Tyrol/Austria), we applied a sequence of steps including the characterization of the social-ecological system and identification of key drivers that influence farmers' management decisions. We then developed three scenarios, i.e., "trend", "positive" and "negative" future development of farming conditions and assessed respective future land use changes. Results indicate that within the "trend" and "positive" scenarios pluri-activity (various sources of income) prevents considerable changes in land use and land cover and promotes the resilience of farming systems. Contrarily, reductions in subsidies and changes in consumer behavior are the most important key drivers in the negative scenario and lead to distinct abandonment of grassland, predominantly in the sub-alpine zone of our study site. Our conceptual approach, i.e., the combination of social and ecological methods and the integration of local stakeholders' knowledge into spatial scenario analysis, resulted in highly detailed and spatially explicit results that can provide a basis for further community development recommendations.

  16. Supplementary Material for: Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  17. Spatial distribution of juvenile and adult stages of limnetic Cladocera in relation to selected environmental factors

    Directory of Open Access Journals (Sweden)

    Małgorzata Adamczuk

    2012-01-01

    Full Text Available Environmental factors have a varied impact on the development of juvenile and adult Cladocera, depending on their different physiological conditions and body size. The values of these factors alter spatially and temporarily, thus implying that they play a role in the spatial distribution of the pre-reproductive and potentially reproductive stages of cladocerans. The aim of the study was to determine seasonal and spatial variations in the distribution of juvenile and adult individuals of limnetic Cladocera in relation to selected physicochemical factors (temperature, conductivity, pH, concentration of dissolved oxygen, total organic carbon, total suspended solids and fish predation pressure (measured by Chesson’s coefficient λ in deep Lake Piaseczno (eastern Poland. Adult Cladocera displayed spatial distribution related to fish predation pressure. The species selectively eaten, B. coregoni and D. longispina, and non-selectively eaten, D. cucullata, selected the pelagic zone to exist, whereas those avoided by fish, D. brachyurum and B. longirostris, were evenly distributed in the littoral and pelagic zone. Juvenile cladocerans were strongly impacted by physico-chemical factors. Juvenile Daphnia, Diaphanosoma and B. longirostris showed preferences to biotic zones similar to the adults but differed in their habitat choices. Juvenile and adult stages of B. coregoni differed in their distribution, indicating that adult individuals impacted by high predation pressure alternatively modified their habitat selection. Principal component analysis (PCA ordination showed a seasonal tendency for the spatial segregation of the cladocerans, suggesting that possible competitive interactions between the studied cladocerans may also influence their distribution patterns.

  18. Temporal-spatial variation and the influence factors of precipitation in Sichuan Province, China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Precipitation is a key factor in the water cycle.At the same time,precipitation is the focus of study in meteorology and climatology,ecological environmental assessment,non-point source pollution and so on.Understanding the temporal-spatial variation and the corresponding factors of precipitation has become the object of hydrology and environmentology.Based on the annual precipitation data,we analyzed the spatial distribution of precipitation in Sichuan Province in China as well as the temporal-spatial variation and the corresponding influence factors involved.The results show that the amount of precipitation was abundant,but the spatial distribution was not consistent with it and the amount of precipitation gradually declined from the south-east to the north-west in Sichuan Province,China.Moreover,the spatial distribution was different throughout the years.The result of correlation analysis indicated that elevation,temperature and air pressure were three key factors affecting the amount and distribution of precipitation,and the correlation coefficients were -0.56,0.38 and 0.45 respectively.Notably,the relationship between the slope of topography and precipitation were significantly negative and the average correlation coefficient was -0.28.

  19. Residual analysis for spatial point processes

    DEFF Research Database (Denmark)

    Baddeley, A.; Turner, R.; Møller, Jesper

    We define residuals for point process models fitted to spatial point pattern data, and propose diagnostic plots based on these residuals. The techniques apply to any Gibbs point process model, which may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Ou...... or covariate effects. Q-Q plots of the residuals are effective in diagnosing interpoint interaction. Some existing ad hoc statistics of point patterns (quadrat counts, scan statistic, kernel smoothed intensity, Berman's diagnostic) are recovered as special cases....

  20. "Factor Analysis Using ""R"""

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2013-02-01

    Full Text Available R (R Development Core Team, 2011 is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free and flexibility (its open-source. This article gives a general introduction to using R (i.e., loading the program, using functions, importing data. Then, using data from Canivez, Konold, Collins, and Wilson (2009, this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach.

  1. UTOOLS: microcomputer software for spatial analysis and landscape visualization.

    Science.gov (United States)

    Alan A. Ager; Robert J. McGaughey

    1997-01-01

    UTOOLS is a collection of programs designed to integrate various spatial data in a way that allows versatile spatial analysis and visualization. The programs were designed for watershed-scale assessments in which a wide array of resource data must be integrated, analyzed, and interpreted. UTOOLS software combines raster, attribute, and vector data into "spatial...

  2. Spatial Econometric data analysis: moving beyond traditional models

    NARCIS (Netherlands)

    Florax, R.J.G.M.; Vlist, van der A.J.

    2003-01-01

    This article appraises recent advances in the spatial econometric literature. It serves as the introduction too collection of new papers on spatial econometric data analysis brought together in this special issue, dealing specifically with new extensions to the spatial econometric modeling

  3. Spatial analysis of NDVI readings with difference sampling density

    Science.gov (United States)

    Advanced remote sensing technologies provide research an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a complete understanding of the spatial complexity of a field and its crop. The objective of the study was...

  4. Spatial Analysis Of Human Capital Structures

    Directory of Open Access Journals (Sweden)

    Gajdos Artur

    2014-12-01

    Full Text Available The main purpose of this paper is to analyse the interdependence between labour productivity and the occupational structure of human capital in a spatial cross-section. Research indicates (see Fischer 2009 the possibility to assess the impact of the quality of human capital (measured by means of the level of education on labour productivity in a spatial cross-section.

  5. Multiscale Spatial Assessment of Determinant Factors of Land Use Change: Study at Urban Area of Yogyakarta

    Science.gov (United States)

    Susilo, Bowo

    2017-12-01

    Studies of land use change have been undertaken by different researchers using various methods. Among those methods, modelling is widely utilized. Modelling land use change required several components remarked as model variables. Those represent any conditions or factors which considered relevant or have some degree of correlation to the changes of land use. Variables which have significant correlation to land use change are referred as determinant factors or driving forces. Those factors as well as changes of land use are distributed across space and therefore referred as spatial determinant factors. The main objective of the research was to examine land use change and its determinant factors. Area and location of land use change were analysed based on three different years of land use maps, which are 1993, 2000 and 2007. Spatial and temporal analysis were performed which emphasize to the influence of scale to both of analysis’s. Urban area of Yogyakarta was selected as study area. Study area covered three different districts (kabupaten), involving 20 sub districts and totally consists of 74 villages. Result of this study shows that during 14 years periods (1993 to 2007), there were about 1,460 hectares of land use change had been taken place. Dominant type of land use change is agricultural to residential. The uses of different spatial and temporal scale in analysis were able to reveal different factors related to land use change. In general, factors influencing the quantities of land use change in the study area were population growth and the availability of land. The use of data with different spatial resolution can reveal the presence of various factors associated with the location of the change. Locations of land use change were influenced or determined by accessibility factors.

  6. Spatial smoothing coherence factor for ultrasound computed tomography

    Science.gov (United States)

    Lou, Cuijuan; Xu, Mengling; Ding, Mingyue; Yuchi, Ming

    2016-04-01

    In recent years, many research studies have been carried out on ultrasound computed tomography (USCT) for its application prospect in early diagnosis of breast cancer. This paper applies four kinds of coherence-factor-like beamforming methods to improve the image quality of synthetic aperture focusing method for USCT, including the coherence-factor (CF), the phase coherence factor (PCF), the sign coherence factor (SCF) and the spatial smoothing coherence factor (SSCF) (proposed in our previous work). The performance of these methods was tested with simulated raw data which were generated by the ultrasound simulation software PZFlex 2014. The simulated phantom was set to be water of 4cm diameter with three nylon objects of different diameters inside. The ring-type transducer had 72 elements with a center frequency of 1MHz. The results show that all the methods can reveal the biggest nylon circle with the radius of 2.5mm. SSCF gets the highest SNR among the proposed methods and provides a more homogenous background. None of these methods can reveal the two smaller nylon circles with the radius of 0.75mm and 0.25mm. This may be due to the small number of elements.

  7. Spatial Data Analysis: Recommendations for Educational Infrastructure in Sindh

    Directory of Open Access Journals (Sweden)

    Abdul Aziz Ansari

    2017-06-01

    Full Text Available Analysing the Education infrastructure has become a crucial activity in imparting quality teaching and resources to students. Facilitations required in improving current education status and future schools is an important analytical component. This is best achieved through a Geographical Information System (GIS analysis of the spatial distribution of schools. In this work, we will execute GIS Analytics on the rural and urban school distributions in Sindh, Pakistan. Using a reliable dataset collected from an international survey team, GIS analysis is done with respect to: 1 school locations, 2 school facilities (water, sanitation, class rooms etc. and 3 student’s results. We will carry out analysis at district level by presenting several spatial results. Correlational analysis of highly influential factors, which may impact the educational performance will generate recommendations for planning and development in weak areas which will provide useful insights regarding effective utilization of resources and new locations to build future schools. The time series analysis will predict the future results which may be witnessed through keen observations and data collections.

  8. Recent developments in spatial analysis spatial statistics, behavioural modelling, and computational intelligence

    CERN Document Server

    Getis, Arthur

    1997-01-01

    In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.

  9. Spatial scale effects in environmental risk-factor modelling for diseases

    Directory of Open Access Journals (Sweden)

    Ram K. Raghavan

    2013-05-01

    Full Text Available Studies attempting to identify environmental risk factors for diseases can be seen to extract candidate variables from remotely sensed datasets, using a single buffer-zone surrounding locations from where disease status are recorded. A retrospective case-control study using canine leptospirosis data was conducted to verify the effects of changing buffer-zones (spatial extents on the risk factors derived. The case-control study included 94 case dogs predominantly selected based on positive polymerase chain reaction (PCR test for leptospires in urine, and 185 control dogs based on negative PCR. Land cover features from National Land Cover Dataset (NLCD and Kansas Gap Analysis Program (KS GAP around geocoded addresses of cases/controls were extracted using multiple buffers at every 500 m up to 5,000 m, and multivariable logistic models were used to estimate the risk of different land cover variables to dogs. The types and statistical significance of risk factors identified changed with an increase in spatial extent in both datasets. Leptospirosis status in dogs was significantly associated with developed high-intensity areas in models that used variables extracted from spatial extents of 500-2000 m, developed medium-intensity areas beyond 2,000 m and up to 3,000 m, and evergreen forests beyond 3,500 m and up to 5,000 m in individual models in the NLCD. Significant associations were seen in urban areas in models that used variables extracted from spatial extents of 500-2,500 m and forest/woodland areas beyond 2,500 m and up to 5,000 m in individual models in Kansas gap analysis programme datasets. The use of ad hoc spatial extents can be misleading or wrong, and the determination of an appropriate spatial extent is critical when extracting environmental variables for studies. Potential work-arounds for this problem are discussed.

  10. Rings and sector : intrasite spatial analysis of stone age sites

    NARCIS (Netherlands)

    Stapert, Durk

    1992-01-01

    This thesis deals with intrasite spatial analysis: the analysis of spatial patterns on site level. My main concern has been to develop a simple method for analysing Stone Age sites of a special type: those characterised by the presence of a hearth closely associated in space with an artefact

  11. Statistical analysis of long term spatial and temporal trends of ...

    Indian Academy of Sciences (India)

    Statistical analysis of long term spatial and temporal trends of temperature ... CGCM3; HadCM3; modified Mann–Kendall test; statistical analysis; Sutlej basin. ... Water Resources Systems Division, National Institute of Hydrology, Roorkee 247 ...

  12. Generalised recurrence plot analysis for spatial data

    International Nuclear Information System (INIS)

    Marwan, Norbert; Kurths, Juergen; Saparin, Peter

    2007-01-01

    Recurrence plot based methods are highly efficient and widely accepted tools for the investigation of time series or one-dimensional data. We present an extension of the recurrence plots and their quantifications in order to study recurrent structures in higher-dimensional spatial data. The capability of this extension is illustrated on prototypical 2D models. Next, the tested and proved approach is applied to assess the bone structure from CT images of human proximal tibia. We find that the spatial structures in trabecular bone become more recurrent during the bone loss in osteoporosis

  13. Do the risk factors for type 2 diabetes mellitus vary by location? A spatial analysis of health insurance claims in Northeastern Germany using kernel density estimation and geographically weighted regression

    Directory of Open Access Journals (Sweden)

    Boris Kauhl

    2016-11-01

    Full Text Available Abstract Background The provision of general practitioners (GPs in Germany still relies mainly on the ratio of inhabitants to GPs at relatively large scales and barely accounts for an increased prevalence of chronic diseases among the elderly and socially underprivileged populations. Type 2 Diabetes Mellitus (T2DM is one of the major cost-intensive diseases with high rates of potentially preventable complications. Provision of healthcare and access to preventive measures is necessary to reduce the burden of T2DM. However, current studies on the spatial variation of T2DM in Germany are mostly based on survey data, which do not only underestimate the true prevalence of T2DM, but are also only available on large spatial scales. The aim of this study is therefore to analyse the spatial distribution of T2DM at fine geographic scales and to assess location-specific risk factors based on data of the AOK health insurance. Methods To display the spatial heterogeneity of T2DM, a bivariate, adaptive kernel density estimation (KDE was applied. The spatial scan statistic (SaTScan was used to detect areas of high risk. Global and local spatial regression models were then constructed to analyze socio-demographic risk factors of T2DM. Results T2DM is especially concentrated in rural areas surrounding Berlin. The risk factors for T2DM consist of proportions of 65–79 year olds, 80 + year olds, unemployment rate among the 55–65 year olds, proportion of employees covered by mandatory social security insurance, mean income tax, and proportion of non-married couples. However, the strength of the association between T2DM and the examined socio-demographic variables displayed strong regional variations. Conclusion The prevalence of T2DM varies at the very local level. Analyzing point data on T2DM of northeastern Germany’s largest health insurance provider thus allows very detailed, location-specific knowledge about increased medical needs. Risk factors

  14. Research progress and hotspot analysis of spatial interpolation

    Science.gov (United States)

    Jia, Li-juan; Zheng, Xin-qi; Miao, Jin-li

    2018-02-01

    In this paper, the literatures related to spatial interpolation between 1982 and 2017, which are included in the Web of Science core database, are used as data sources, and the visualization analysis is carried out according to the co-country network, co-category network, co-citation network, keywords co-occurrence network. It is found that spatial interpolation has experienced three stages: slow development, steady development and rapid development; The cross effect between 11 clustering groups, the main convergence of spatial interpolation theory research, the practical application and case study of spatial interpolation and research on the accuracy and efficiency of spatial interpolation. Finding the optimal spatial interpolation is the frontier and hot spot of the research. Spatial interpolation research has formed a theoretical basis and research system framework, interdisciplinary strong, is widely used in various fields.

  15. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette); V. Capasso

    2009-01-01

    htmlabstractWe give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects

  16. Sequential spatial processes for image analysis

    NARCIS (Netherlands)

    Lieshout, van M.N.M.; Capasso, V.

    2009-01-01

    We give a brief introduction to sequential spatial processes. We discuss their definition, formulate a Markov property, and indicate why such processes are natural tools in tackling high level vision problems. We focus on the problem of tracking a variable number of moving objects through a video

  17. Second order analysis for spatial Hawkes processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Torrisi, Giovanni Luca

    We derive summary statistics for stationary Hawkes processes which can be considered as spatial versions of classical Hawkes processes. Particularly, we derive the intensity, the pair correlation function and the Bartlett spectrum. Our results for Gaussian fertility rates and the extension...... to marked Hawkes processes are discussed....

  18. Spatial Data Mining for Estimating Cover Management Factor of Universal Soil Loss Equation

    Science.gov (United States)

    Tsai, F.; Lin, T. C.; Chiang, S. H.; Chen, W. W.

    2016-12-01

    Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes long-term soil erosion processes. Among the six different soil erosion risk factors of USLE, the cover-management factor (C-factor) is related to land-cover/land-use. The value of C-factor ranges from 0.001 to 1, so it alone might cause a thousandfold difference in a soil erosion analysis using USLE. The traditional methods for the estimation of USLE C-factor include in situ experiments, soil physical parameter models, USLE look-up tables with land use maps, and regression models between vegetation indices and C-factors. However, these methods are either difficult or too expensive to implement in large areas. In addition, the values of C-factor obtained using these methods can not be updated frequently, either. To address this issue, this research developed a spatial data mining approach to estimate the values of C-factor with assorted spatial datasets for a multi-temporal (2004 to 2008) annual soil loss analysis of a reservoir watershed in northern Taiwan. The idea is to establish the relationship between the USLE C-factor and spatial data consisting of vegetation indices and texture features extracted from satellite images, soil and geology attributes, digital elevation model, road and river distribution etc. A decision tree classifier was used to rank influential conditional attributes in the preliminary data mining. Then, factor simplification and separation were considered to optimize the model and the random forest classifier was used to analyze 9 simplified factor groups. Experimental results indicate that the overall accuracy of the data mining model is about 79% with a kappa value of 0.76. The estimated soil erosion amounts in 2004-2008 according to the data mining results are about 50.39 - 74.57 ton/ha-year after applying the sediment delivery ratio and correction coefficient. Comparing with estimations calculated with C-factors from look-up tables, the soil erosion

  19. Factors affecting construction performance: exploratory factor analysis

    Science.gov (United States)

    Soewin, E.; Chinda, T.

    2018-04-01

    The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

  20. A Spatial and Temporal analysis of Labour Market Characteristics

    Directory of Open Access Journals (Sweden)

    Pośpiech Ewa

    2016-12-01

    Full Text Available The use of spatial methods is becoming increasingly common in social and economic research as it emphasizes the relevance of spatiality to the understanding of socio-economic facts. Once embraced, the spatial factor can substantially help explain variations in the properties being examined, thus improving the quality of their description and supporting the development of econometric models. This paper explores some of the characteristics of Poland’s job market, making an inquiry into their spatial dependencies. The study looks at the country’s labour market from a local perspective, examining its properties for spatial autocorrelation (both global and local. Linear econometric models are subsequently built for such variables as the number of persons in employment, the number of women and men in employment. The models are further investigated to assess the applicability of spatial modelling in their development.

  1. Spatial analysis of various multiplex cinema types

    Directory of Open Access Journals (Sweden)

    Young-Seo Park

    2016-03-01

    Full Text Available This study identifies the spatial characteristics and relationships of each used space according to the multiplex type. In this study, multiplexes are classified according to screen rooms and circulation systems, and each used space is quantitatively analyzed. The multiplex type based on screen rooms and moving line systems influences the relationship and characteristics of each used space in various ways. In particular, the structure of the used space of multiplexes has a significant effect on profit generation and audience convenience.

  2. Environmental and spatial factors influencing the distribution of cladocerans in lakes across the central Canadian Arctic treeline region

    Directory of Open Access Journals (Sweden)

    John P. SMOL

    2010-02-01

    Full Text Available We examine the role of local environmental and spatial factors in explaining variation in the composition of cladoceran assemblages from surface sediments within a set of 50 lakes spanning a broad southwest to northeast transect across the central Canadian Arctic treeline region from Yellowknife (Northwest Territories to the northern boundary of the Thelon Game Sanctuary (Nunavut Territory. Within each lake, the cladoceran fauna was identified based on the subfossil exoskeletal remains preserved in recently deposited lake sediments. Physical and chemical limnological data were measured in August of 1996 and 1998. Spatial data were generated based on latitude and longitude using Principal Coordinates of Neighbors Matrices analysis (PCNM. The relationships between cladocerans and the measured environmental and spatial variables were examined using both unconstrained (Principal Components Analysis, PCA and constrained (Redundancy Analysis, RDA ordination techniques. Variance partitioning, based on partial RDAs, was used to identify the relative importance of significant environmental and spatial explanatory variables. Three environmental variables were identified as significantly influencing cladoceran community structure: surface water temperature, dissolved organic carbon (DOC, and total phosphorus (TP. Five PCNM-generated spatial variables were also significant in explaining cladoceran distributions. Variance partitioning attributed 14% of the variance in the distribution of Cladocera to spatial factors, an additional 10% to spatially-structured environmental variables, and 8% to environmental factors that were not spatially-structured. Within the central Canadian Arctic treeline region, spatial and other environmental processes had an important influence on the distribution of cladoceran communities. The strong influence of spatial factors was related to the large ecoclimatic gradient across treeline. The distribution patterns of cladocerans

  3. Spatial analysis of the electrical energy demand in Greece

    International Nuclear Information System (INIS)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2017-01-01

    The Electrical Energy Demand (EED) of the agricultural, commercial and industrial sector in Greece, as well as its use for domestic activities, public and municipal authorities and street lighting are analysed spatially using Geographical Information System and spatial statistical methods. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the NUTS (Nomenclature of Territorial Units for Statistics) level 3. The aim is to identify spatial patterns of the EED and its transformations such as the ratios of the EED to socioeconomic variables, i.e. the population, the total area, the population density and the Gross Domestic Product (GDP). Based on the analysis, Greece is divided in five regions, each one with a different development model, i.e. Attica and Thessaloniki which are two heavily populated major poles, Thessaly and Central Greece which form a connected geographical region with important agricultural and industrial sector, the islands and some coastal areas which are characterized by an important commercial sector and the rest Greek areas. The spatial patterns can provide additional information for policy decision about the electrical energy management and better representation of the regional socioeconomic conditions. - Highlights: • We visualize spatially the Electrical Energy Demand (EED) in Greece. • We apply spatial analysis methods to the EED data. • Spatial patterns of the EED are identified. • Greece is classified in five distinct groups, based on the analysis. • The results can be used for optimal planning of the electric system.

  4. Crash rates analysis in China using a spatial panel model

    Directory of Open Access Journals (Sweden)

    Wonmongo Lacina Soro

    2017-10-01

    Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.

  5. Backyard housing in Gauteng: An analysis of spatial dynamics

    African Journals Online (AJOL)

    Backyard housing in Gauteng: An analysis of spatial dynamics. Yasmin Shapurjee ... Drawing on quantitative geo-demographic data from GeoTerraImage (GTI). (2010), Knowledge .... a fundamental role in absorbing demand for low-income ...

  6. Spatial Analysis of Accident Spots Using Weighted Severity Index ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Spatial Analysis of Accident Spots Using Weighted Severity Index (WSI) and ... pedestrians avoiding the use of pedestrian bridges/aid even when they are available. ..... not minding an unforeseen obstruction, miscalculations and wrong break.

  7. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  8. Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

    Science.gov (United States)

    Zhang, S.; Wang, Y.; Ju, H.

    2017-12-01

    The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.

  9. Asymptotic analysis of spatial discretizations in implicit Monte Carlo

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2009-01-01

    We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large. We demonstrate the validity of our analysis with a set of numerical examples.

  10. Factor analysis of multivariate data

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Mahadevan, R.

    A brief introduction to factor analysis is presented. A FORTRAN program, which can perform the Q-mode and R-mode factor analysis and the singular value decomposition of a given data matrix is presented in Appendix B. This computer program, uses...

  11. Scalable group level probabilistic sparse factor analysis

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

    2017-01-01

    Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

  12. Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA: Spatial Analysis Framework

    Directory of Open Access Journals (Sweden)

    Sina Tehranchi

    2017-03-01

    Full Text Available This research presents a Geographic Information Systems (GIS and spatial analysis approach based on the global spatial autocorrelation of road traffic injuries for identifying spatial patterns. A locational spatial autocorrelation was also used for identifying traffic injury at spatial level. Data for this research study were acquired from Canadian Institute for Health Information (CIHI based on 2004 and 2011. Moran’s I statistics were used to examine spatial patterns of road traffic injuries in the Greater Toronto Area (GTA. An assessment of Getis-Ord Gi* statistic was followed as to identify hot spots and cold spots within the study area. The results revealed that Peel and Durham have the highest collision rate for other motor vehicle with motor vehicle. Geographic weighted regression (GWR technique was conducted to test the relationships between the dependent variable, number of road traffic injury incidents and independent variables such as number of seniors, low education, unemployed, vulnerable groups, people smoking and drinking, urban density and average median income. The result of this model suggested that number of seniors and low education have a very strong correlation with the number of road traffic injury incidents.

  13. Assessment of tuberculosis spatial hotspot areas in Antananarivo, Madagascar, by combining spatial analysis and genotyping.

    Science.gov (United States)

    Ratovonirina, Noël Harijaona; Rakotosamimanana, Niaina; Razafimahatratra, Solohery Lalaina; Raherison, Mamy Serge; Refrégier, Guislaine; Sola, Christophe; Rakotomanana, Fanjasoa; Rasolofo Razanamparany, Voahangy

    2017-08-14

    Tuberculosis (TB) remains a public health problem in Madagascar. A crucial element of TB control is the development of an easy and rapid method for the orientation of TB control strategies in the country. Our main objective was to develop a TB spatial hotspot identification method by combining spatial analysis and TB genotyping method in Antananarivo. Sputa of new pulmonary TB cases from 20 TB diagnosis and treatment centers (DTCs) in Antananarivo were collected from August 2013 to May 2014 for culture. Mycobacterium tuberculosis complex (MTBC) clinical isolates were typed by spoligotyping on a Luminex® 200 platform. All TB patients were respectively localized according to their neighborhood residence and the spatial distribution of all pulmonary TB patients and patients with genotypic clustered isolates were scanned respectively by the Kulldorff spatial scanning method for identification of significant spatial clustering. Areas exhibiting spatial clustering of patients with genotypic clustered isolates were considered as hotspot TB areas for transmission. Overall, 467 new cases were included in the study, and 394 spoligotypes were obtained (84.4%). New TB cases were distributed in 133 of the 192 Fokontany (administrative neighborhoods) of Antananarivo (1 to 15 clinical patients per Fokontany) and patients with genotypic clustered isolates were distributed in 127 of the 192 Fokontany (1 to 13 per Fokontany). A single spatial focal point of epidemics was detected when ignoring genotypic data (p = 0.039). One Fokontany of this focal point and three additional ones were detected to be spatially clustered when taking genotypes into account (p Madagascar and will allow better TB control strategies by public health authorities.

  14. Spatially explicit spectral analysis of point clouds and geospatial data

    Science.gov (United States)

    Buscombe, Daniel D.

    2015-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is

  15. Spatially explicit spectral analysis of point clouds and geospatial data

    Science.gov (United States)

    Buscombe, Daniel

    2016-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described

  16. Application of Fourier analysis to multispectral/spatial recognition

    Science.gov (United States)

    Hornung, R. J.; Smith, J. A.

    1973-01-01

    One approach for investigating spectral response from materials is to consider spatial features of the response. This might be accomplished by considering the Fourier spectrum of the spatial response. The Fourier Transform may be used in a one-dimensional to multidimensional analysis of more than one channel of data. The two-dimensional transform represents the Fraunhofer diffraction pattern of the image in optics and has certain invariant features. Physically the diffraction pattern contains spatial features which are possibly unique to a given configuration or classification type. Different sampling strategies may be used to either enhance geometrical differences or extract additional features.

  17. Determinants of the distribution and concentration of biogas production in Germany. A spatial econometric analysis

    International Nuclear Information System (INIS)

    Scholz, Lukas

    2015-01-01

    The biogas production in Germany is characterized by a heterogeneous distribution and the formation of regional centers. In the present study the determinants of the spatial distribution and concentration are analyzed with methods of spatial statistics and spatial econometrics. In addition to the consideration of ''classic'' site factors of agricultural production, the analysis here focuses on the possible relevance of agglomeration effects. The results of the work contribute to a better understanding of the regional distribution and concentration of the biogas production in Germany. [de

  18. SPATIAL ANALYSIS FRAMEWORK FOR MANGROVE FORESTS RESTORATION

    Directory of Open Access Journals (Sweden)

    Arimatéa de Carvalho Ximenes

    2016-09-01

    Full Text Available Mangroves are coastal ecosystems in transition between sea and land, localized worldwide on the tropical and subtropical regions. However, anthropogenic pressure in coastal areas has led to the conversion of many mangrove areas to other uses. Due to the increased awareness of the importance of mangroves worldwide, restoration methods are being studied. Our aim is to develop a framework for selecting suitable sites for red mangrove planting using Geographic Information Systems (GIS. For this reason, the methodology is based on abiotic factors that have an influence on the zonation (distribution and growing of the Rhizophora mangle. A total suitable area of 6,12 hectares was found, where 15.300 propagules could be planted.

  19. Spatial Characteristics and Driving Factors of Provincial Wastewater Discharge in China.

    Science.gov (United States)

    Chen, Kunlun; Liu, Xiaoqiong; Ding, Lei; Huang, Gengzhi; Li, Zhigang

    2016-12-09

    Based on the increasing pressure on the water environment, this study aims to clarify the overall status of wastewater discharge in China, including the spatio-temporal distribution characteristics of wastewater discharge and its driving factors, so as to provide reference for developing "emission reduction" strategies in China and discuss regional sustainable development and resources environment policies. We utilized the Exploratory Spatial Data Analysis (ESDA) method to analyze the characteristics of the spatio-temporal distribution of the total wastewater discharge among 31 provinces in China from 2002 to 2013. Then, we discussed about the driving factors, affected the wastewater discharge through the Logarithmic Mean Divisia Index (LMDI) method and classified those driving factors. Results indicate that: (1) the total wastewater discharge steadily increased, based on the social economic development, with an average growth rate of 5.3% per year; the domestic wastewater discharge is the main source of total wastewater discharge, and the amount of domestic wastewater discharge is larger than the industrial wastewater discharge. There are many spatial differences of wastewater discharge among provinces via the ESDA method. For example, provinces with high wastewater discharge are mainly the developed coastal provinces such as Jiangsu Province and Guangdong Province. Provinces and their surrounding areas with low wastewater discharge are mainly the undeveloped ones in Northwest China; (2) The dominant factors affecting wastewater discharge are the economy and technological advance; The secondary one is the efficiency of resource utilization, which brings about the unstable effect; population plays a less important role in wastewater discharge. The dominant driving factors affecting wastewater discharge among 31 provinces are divided into three types, including two-factor dominant type, three-factor leading type and four-factor antagonistic type. In addition, the

  20. Mathematical Analysis of Urban Spatial Networks

    CERN Document Server

    Blanchard, Philippe

    2009-01-01

    Cities can be considered to be among the largest and most complex artificial networks created by human beings. Due to the numerous and diverse human-driven activities, urban network topology and dynamics can differ quite substantially from that of natural networks and so call for an alternative method of analysis. The intent of the present monograph is to lay down the theoretical foundations for studying the topology of compact urban patterns, using methods from spectral graph theory and statistical physics. These methods are demonstrated as tools to investigate the structure of a number of real cities with widely differing properties: medieval German cities, the webs of city canals in Amsterdam and Venice, and a modern urban structure such as found in Manhattan. Last but not least, the book concludes by providing a brief overview of possible applications that will eventually lead to a useful body of knowledge for architects, urban planners and civil engineers.

  1. Problems in implementation of the spatial plan of the Republic of Srpska until 2015: Quantitative analysis

    Directory of Open Access Journals (Sweden)

    Bijelić Branislav

    2017-01-01

    Full Text Available The implementation of spatial plans in the Republic of Srpska is certainly the weakest phase of the process of spatial planning in this entity. It is particularly evident in the case of the Spatial Plan of the Republic of Srpska until 2015 which is the highest strategic spatial planning document in the Republic of Srpska. More precisely, the implementation of spatial plans has been defined as the carrying out of spatial planning documents, i.e. planning propositions as defined in the spatial plans. For the purpose of this paper, a quantitative analysis of the implementation of the planning propositions envisioned by this document has been carried out. The difference between what was planned and what was implemented at the end of the planning period (ex-post evaluation of planning decisions is presented in this paper. The weighting factor is defined for each thematic field and planning proposition, where the main criterion for determining the weighting factor is the share of the planning proposition and thematic field in the estimated total costs of the plan (financial criterion. The paper has also tackled the issue of the implementation of the Spatial Plan of Bosnia and Herzegovina for the period 1981 - 2000, as well as of the Spatial Plan of the Republic of Srpska 1996 - 2001 - Phased Plan for the period 1996 - 2001, as the previous strategic spatial planning documents of the highest rank covering the area of the Republic of Srpska. The research results have proven primary hypothesis of the paper that the level of the implementation of Spatial Plan of the Republic of Srpska until 2015 is less than 10%.

  2. Spatial data analysis for exploration of regional scale geothermal resources

    Science.gov (United States)

    Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

    2013-10-01

    Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

  3. Factors modulating social influence on spatial choice in rats.

    Science.gov (United States)

    Bisbing, Teagan A; Saxon, Marie; Sayde, Justin M; Brown, Michael F

    2015-07-01

    Three experiments examined the conditions under which the spatial choices of rats searching for food are influenced by the choices made by other rats. Model rats learned a consistent set of baited locations in a 5 × 5 matrix of locations, some of which contained food. In Experiment 1, subject rats could determine the baited locations after choosing 1 location because all of the baited locations were on the same side of the matrix during each trial (the baited side varied over trials). Under these conditions, the social cues provided by the model rats had little or no effect on the choices made by the subject rats. The lack of social influence on choices occurred despite a simultaneous social influence on rats' location in the testing arena (Experiment 2). When the outcome of the subject rats' own choices provided no information about the positions of other baited locations, on the other hand, social cues strongly controlled spatial choices (Experiment 3). These results indicate that social information about the location of food influences spatial choices only when those cues provide valid information that is not redundant with the information provided by other cues. This suggests that social information is learned about, processed, and controls behavior via the same mechanisms as other kinds of stimuli. (c) 2015 APA, all rights reserved).

  4. First course in factor analysis

    CERN Document Server

    Comrey, Andrew L

    2013-01-01

    The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of

  5. A digital elevation analysis: Spatially distributed flow apportioning algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang-Hyun; Kim, Kyung-Hyun [Pusan National University, Pusan(Korea); Jung, Sun-Hee [Korea Environment Institute, (Korea)

    2001-06-30

    A flow determination algorithm is proposed for the distributed hydrologic model. The advantages of a single flow direction scheme and multiple flow direction schemes are selectively considered to address the drawbacks of existing algorithms. A spatially varied flow apportioning factor is introduced in order to accommodate the accumulated area from upslope cells. The channel initiation threshold area(CIT) concept is expanded and integrated into the spatially distributed flow apportioning algorithm in order to delineate a realistic channel network. An application of a field example suggests that the linearly distributed flow apportioning scheme provides some advantages over existing approaches, such as the relaxation of over-dissipation problems near channel cells, the connectivity feature of river cells, the continuity of saturated areas and the negligence of the optimization of few parameters in existing algorithms. The effects of grid sizes are explored spatially as well as statistically. (author). 28 refs., 7 figs.

  6. Multi-spatial analysis of aeolian dune-field patterns

    Science.gov (United States)

    Ewing, Ryan C.; McDonald, George D.; Hayes, Alex G.

    2015-07-01

    Aeolian dune-fields are composed of different spatial scales of bedform patterns that respond to changes in environmental boundary conditions over a wide range of time scales. This study examines how variations in spatial scales of dune and ripple patterns found within dune fields are used in environmental reconstructions on Earth, Mars and Titan. Within a single bedform type, different spatial scales of bedforms emerge as a pattern evolves from an initial state into a well-organized pattern, such as with the transition from protodunes to dunes. Additionally, different types of bedforms, such as ripples, coarse-grained ripples and dunes, coexist at different spatial scales within a dune-field. Analysis of dune-field patterns at the intersection of different scales and types of bedforms at different stages of development provides a more comprehensive record of sediment supply and wind regime than analysis of a single scale and type of bedform. Interpretations of environmental conditions from any scale of bedform, however, are limited to environmental signals associated with the response time of that bedform. Large-scale dune-field patterns integrate signals over long-term climate cycles and reveal little about short-term variations in wind or sediment supply. Wind ripples respond instantly to changing conditions, but reveal little about longer-term variations in wind or sediment supply. Recognizing the response time scales across different spatial scales of bedforms maximizes environmental interpretations from dune-field patterns.

  7. Analysis of Spatial Concepts, Spatial Skills and Spatial Representations in New York State Regents Earth Science Examinations

    Science.gov (United States)

    Kastens, Kim A.; Pistolesi, Linda; Passow, Michael J.

    2014-01-01

    Research has shown that spatial thinking is important in science in general, and in Earth Science in particular, and that performance on spatially demanding tasks can be fostered through instruction. Because spatial thinking is rarely taught explicitly in the U.S. education system, improving spatial thinking may be "low-hanging fruit" as…

  8. Lithuanian Population Aging Factors Analysis

    Directory of Open Access Journals (Sweden)

    Agnė Garlauskaitė

    2015-05-01

    Full Text Available The aim of this article is to identify the factors that determine aging of Lithuania’s population and to assess the influence of these factors. The article shows Lithuanian population aging factors analysis, which consists of two main parts: the first describes the aging of the population and its characteristics in theoretical terms. Second part is dedicated to the assessment of trends that influence the aging population and demographic factors and also to analyse the determinants of the aging of the population of Lithuania. After analysis it is concluded in the article that the decline in the birth rate and increase in the number of emigrants compared to immigrants have the greatest impact on aging of the population, so in order to show the aging of the population, a lot of attention should be paid to management of these demographic processes.

  9. Visuo-Spatial Performance in Autism: A Meta-Analysis

    Science.gov (United States)

    Muth, Anne; Hönekopp, Johannes; Falter, Christine M.

    2014-01-01

    Visuo-spatial skills are believed to be enhanced in autism spectrum disorders (ASDs). This meta-analysis tests the current state of evidence for Figure Disembedding, Block Design, Mental Rotation and Navon tasks in ASD and neurotypicals. Block Design (d = 0.32) and Figure Disembedding (d = 0.26) showed superior performance for ASD with large…

  10. Spatial and temporal analysis of mass movement using dendrochronology

    NARCIS (Netherlands)

    Braam, R.R.; Weiss, E.E.J.; Burrough, P.A.

    1987-01-01

    Tree growth and inclination on sloping land is affected by mass movement. Suitable analysis of tree growth and tree form can therefore provide considerable information on mass movement activity. This paper reports a new, automated method for studying the temporal and spatial aspects of mass

  11. Spatial Analysis of Political Capital Citation Using Remote Sensing ...

    African Journals Online (AJOL)

    Spatial Analysis of Political Capital Citation Using Remote Sensing and GIS; A Case Study of Lokoja. ... The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader). If you would like more information about how to print, save, ...

  12. Spatial analysis of digital technologies and impact on socio - cultural ...

    African Journals Online (AJOL)

    The objective of this study was to determine the spatial distribution of digital technologies and ascertain whether digital technologies have significant impact on socio - cultural values or not. Moran's index and Getis and Ord's statistic were used for cluster and hotspots analysis. The unique locations of digital technologies ...

  13. Analysis of thrips distribution: application of spatial statistics and Kriging

    Science.gov (United States)

    John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

    1991-01-01

    Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

  14. The Structure of Spatial Ability Items: A Faceted Analysis.

    Science.gov (United States)

    Guttman, Ruth; Shoham, Ilana

    1982-01-01

    Eight spatial tests assembled with a mapping sentence of four content facets (rule type, dimensionality, presence or absence of rotation, and test format) were administered to 800 individuals. Smallest Space Analysis of an intercorrelation matrix yielded three facets which formed distinct regions in a two-dimensional projection of a…

  15. Analysis of spatial pattern of settlements in the federal capital ...

    African Journals Online (AJOL)

    Human settlements are important, seemingly static but dynamic, features of the cultural landscape that have attracted several studies due to the important role they play in human life. This paper examined the spatial distribution of settlements in the Federal Capital Territory (FCT) of Nigeria. The analysis uses vector based ...

  16. An analytical evaluation for spatial-dependent intra-pebble Dancoff factor and escape probability

    International Nuclear Information System (INIS)

    Kim, Songhyun; Kim, Hong-Chul; Kim, Jong Kyung; Kim, Soon Young; Noh, Jae Man

    2009-01-01

    The analytical evaluation of spatial-dependent intra-pebble Dancoff factors and their escape probabilities is pursued by the model developed in this study. Intra-pebble Dancoff factors and their escape probabilities are calculated as a function of fuel kernel radius, number of fuel kernels, and fuel region radius. The method in this study can be easily utilized to analyze the tendency of spatial-dependent intra-pebble Dancoff factor and spatial-dependent fuel region escape probability for the various geometries because it is faster than the MCNP method as well as good accuracy. (author)

  17. Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

    Science.gov (United States)

    1987-04-01

    mumgs0.USmusa 7.AUWOJO 4. CIUTAC Rm6ANT Wuugme*j James V/. Mlahoney DACA? 6-85-C-00 10 NOQ 1 4-85-K-O 124 Artificial Inteligence Laboratory US USS 545...0197 672 IMAGE CHUWING: DEINING SPATIAL UILDING PLOCKS FOR 142 SCENE ANRLYSIS(U) MASSACHUSETTS INST OF TECH CAIIAIDGE ARTIFICIAL INTELLIGENCE LAO J...Technical Report 980 F-Image Chunking: Defining Spatial Building Blocks for Scene DTm -Analysis S ELECTED James V. Mahoney’ MIT Artificial Intelligence

  18. Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

    Science.gov (United States)

    Nakapan, Supachai; Tripathi, Nitin Kumar; Tipdecho, Taravudh; Souris, Marc

    2012-10-24

    Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

  19. Spatial Diffusion of Influenza Outbreak-Related Climate Factors in Chiang Mai Province, Thailand

    Directory of Open Access Journals (Sweden)

    Marc Souris

    2012-10-01

    Full Text Available Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW interpolation and Geographic Information System (GIS techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

  20. Factors driving the spatial layout of distribution channels

    NARCIS (Netherlands)

    Onstein, A.T.C.; Ektesaby, M.; Rezaei, J.; Tavasszy, L.A.; van Damme, D.A.

    2017-01-01

    Research statement Our study analyses the factors that drive decision-making on distribution structures, including the layout of distribution channels and the locations of distribution centres. Distribution is a primary firm activity, which strongly influences logistics costs and logistics

  1. Spatially adaptive mixture modeling for analysis of FMRI time series.

    Science.gov (United States)

    Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

    2010-04-01

    Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

  2. Bovine spongiform encephalopathy and spatial analysis of the feed industry.

    Science.gov (United States)

    Paul, Mathilde; Abrial, David; Jarrige, Nathalie; Rican, Stéphane; Garrido, Myriam; Calavas, Didier; Ducrot, Christian

    2007-06-01

    In France, despite the ban of meat-and-bone meal (MBM) in cattle feed, bovine spongiform encephalopathy (BSE) was detected in hundreds of cattle born after the ban. To study the role of MBM, animal fat, and dicalcium phosphate on the risk for BSE after the feed ban, we conducted a spatial analysis of the feed industry. We used data from 629 BSE cases as well as data on use of each byproduct and market area of the feed factories. We mapped risk for BSE in 951 areas supplied by the same factories and connection with use of byproducts. A disease map of BSE with covariates was built with the hierarchical Bayesian modeling methods, based on Poisson distribution with spatial smoothing. Only use of MBM was spatially linked to risk for BSE, which highlights cross-contamination as the most probable source of infection after the feed ban.

  3. Quantitative analysis of spatial variability of geotechnical parameters

    Science.gov (United States)

    Fang, Xing

    2018-04-01

    Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

  4. Socio-Spatial Factors Affecting Household Recycling in Townhouses in Pretoria, South Africa

    Directory of Open Access Journals (Sweden)

    Jacques du Toit

    2017-11-01

    Full Text Available Although social factors affecting recycling have been widely researched, the effect of spatial and physical factors posed by medium-density housing, such as townhouses, is less understood. Using the Theory of Planned Behaviour, the relative effect of three sets of factors on household recycling in townhouses are examined, including ‘attitude’ (about recycling, ‘subjective norm’ (social pressure, and ‘perceived behaviour control’ (ability to recycle. A questionnaire survey of 300 households was conducted in Equestria, an enclosed middle-income residential estate consisting of several townhouse complexes. Confirmatory factor analysis verified the three factor measurement model for recycling participation. Both recyclers and non-recyclers showed positive attitudes toward recycling and felt social pressure to recycle. Non-recyclers, however, felt significantly less able to recycle. Most recyclers as well as non-recyclers indicated that certain proposals for increasing recycling may cause them to recycle more, in particular a system through which the management agency arranges access for a recycling company to collect recyclables from strategically located collection points inside the complex. Urban planning and design recommendations for facilitating recycling in townhouses are discussed.

  5. Spatial pattern of heavy metals accumulation risk in urban soils of Beijing and its influencing factors

    International Nuclear Information System (INIS)

    Liu, Rui; Wang, Meie; Chen, Weiping; Peng, Chi

    2016-01-01

    Accumulations of heavy metals in urban soils are highly spatial heterogeneity and affected by multiple factors including soil properties, land use and pattern, population and climatic conditions. We studied accumulation risks of Cd, Cu, Pb and Zn in unban soils of Beijing and their influencing based on the regression tree analysis and a GIS-based overlay model. Result shows that Zinc causes the most extensive soil pollution and Cu result in the most acute soil pollution. The soil's organic carbon content and CEC and population growth are the most significant factors affecting heavy metal accumulation. Other influence factors in land use pattern, urban landscape, and wind speed also contributed, but less pronounced. The soils in areas with higher degree of urbanization and surrounded by intense vehicular traffics have higher accumulation risk of Cd, Cu, Pb, and Zn. - Highlights: • Zn accumulations were the most extensive and Cu accumulations were the most acute. • Accumulations of Cd, Cu, Pb and Zn in urban soils were caused by different sets of influence factors. • Soil's organic carbon content and CEC and population growth were the most significant factors. • Accumulation risks were highly related with urbanization level and human activities. - A combined approach of employing geographical information systems and regression tree analyses identify the potential risks of accumulation Cd, Cu, Pb, and Zn in urban soils according to soil properties, urban land use patterns, urban landscape, demographics, and microclimatic conditions.

  6. Factor Analysis for Clustered Observations.

    Science.gov (United States)

    Longford, N. T.; Muthen, B. O.

    1992-01-01

    A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

  7. Transforming Rubrics Using Factor Analysis

    Science.gov (United States)

    Baryla, Ed; Shelley, Gary; Trainor, William

    2012-01-01

    Student learning and program effectiveness is often assessed using rubrics. While much time and effort may go into their creation, it is equally important to assess how effective and efficient the rubrics actually are in terms of measuring competencies over a number of criteria. This study demonstrates the use of common factor analysis to identify…

  8. Executive Order 12898 and Social, Economic, and Sociopolitical Factors Influencing Toxic Release Inventory Facility Location in EPA Region 6: A Multi-Scale Spatial Assessment of Environmental Justice

    Science.gov (United States)

    Moore, Andrea Lisa

    2013-01-01

    Toxic Release Inventory facilities are among the many environmental hazards shown to create environmental inequities in the United States. This project examined four factors associated with Toxic Release Inventory, specifically, manufacturing facility location at multiple spatial scales using spatial analysis techniques (i.e., O-ring statistic and…

  9. Endurance Factors Improve Hippocampal Neurogenesis and Spatial Memory in Mice

    Science.gov (United States)

    Kobilo, Tali; Yuan, Chunyan; van Praag, Henriette

    2011-01-01

    Physical activity improves learning and hippocampal neurogenesis. It is unknown whether compounds that increase endurance in muscle also enhance cognition. We investigated the effects of endurance factors, peroxisome proliferator-activated receptor [delta] agonist GW501516 and AICAR, activator of AMP-activated protein kinase on memory and…

  10. Seasonal and Spatial Variability of Anthropogenic and Natural Factors Influencing Groundwater Quality Based on Source Apportionment

    Directory of Open Access Journals (Sweden)

    Xueru Guo

    2018-02-01

    Full Text Available Globally, groundwater resources are being deteriorated by rapid social development. Thus, there is an urgent need to assess the combined impacts of natural and enhanced anthropogenic sources on groundwater chemistry. The aim of this study was to identify seasonal characteristics and spatial variations in anthropogenic and natural effects, to improve the understanding of major hydrogeochemical processes based on source apportionment. 34 groundwater points located in a riverside groundwater resource area in northeast China were sampled during the wet and dry seasons in 2015. Using principal component analysis and factor analysis, 4 principal components (PCs were extracted from 16 groundwater parameters. Three of the PCs were water-rock interaction (PC1, geogenic Fe and Mn (PC2, and agricultural pollution (PC3. A remarkable difference (PC4 was organic pollution originating from negative anthropogenic effects during the wet season, and geogenic F enrichment during the dry season. Groundwater exploitation resulted in dramatic depression cone with higher hydraulic gradient around the water source area. It not only intensified dissolution of calcite, dolomite, gypsum, Fe, Mn and fluorine minerals, but also induced more surface water recharge for the water source area. The spatial distribution of the PCs also suggested the center of the study area was extremely vulnerable to contamination by Fe, Mn, COD, and F−.

  11. Global sensitivity analysis for models with spatially dependent outputs

    International Nuclear Information System (INIS)

    Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

    2011-01-01

    The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

  12. Capacity analysis of spectrum sharing spatial multiplexing MIMO systems

    KAUST Repository

    Yang, Liang

    2014-12-01

    This paper considers a spectrum sharing (SS) multiple-input multiple-output (MIMO) system operating in a Rayleigh fading environment. First the capacity of a single-user SS spatial multiplexing system is investigated in two scenarios that assume different receivers. To explicitly show the capacity scaling law of SS MIMO systems, some approximate capacity expressions for the two scenarios are derived. Next, we extend our analysis to a multiple user system with zero-forcing receivers (ZF) under spatially-independent scheduling and analyze the sum-rate. Furthermore, we provide an asymptotic sum-rate analysis to investigate the effects of different parameters on the multiuser diversity gain. Our results show that the secondary system with a smaller number of transmit antennas Nt and a larger number of receive antennas Nr can achieve higher capacity at lower interference temperature Q, but at high Q the capacity follows the scaling law of the conventional MIMO systems. However, for a ZF SS spatial multiplexing system, the secondary system with small Nt and large Nr can achieve the highest capacity throughout the entire region of Q. For a ZF SS spatial multiplexing system with scheduling, the asymptotic sum-rate scales like Ntlog2(Q(KNtNp-1)/Nt), where Np denotes the number of antennas of the primary receiver and K represents the number of secondary transmitters.

  13. Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013.

    Directory of Open Access Journals (Sweden)

    Yan-Yan Chen

    Full Text Available Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions.In this study, spatial autocorrelation methodologies, including global Moran's I and local Getis-Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time.The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran's I > 0, P < 0.01, which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties.The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial-temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be continued, especially in the Yangtze

  14. A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002.

    Directory of Open Access Journals (Sweden)

    Daniel M Saman

    Full Text Available Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55 and 10 counties in eastern Kentucky (RR = 1.97. Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002 and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001.This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions with the intention of reducing tractor overturns in the highest risk counties in Kentucky.

  15. Analysis of spatial distribution of land cover maps accuracy

    Science.gov (United States)

    Khatami, R.; Mountrakis, G.; Stehman, S. V.

    2017-12-01

    Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain

  16. Spatial Analysis of Case-Mix and Dialysis Modality Associations.

    Science.gov (United States)

    Phirtskhalaishvili, Tamar; Bayer, Florian; Edet, Stephane; Bongiovanni, Isabelle; Hogan, Julien; Couchoud, Cécile

    2016-01-01

    ♦ Health-care systems must attempt to provide appropriate, high-quality, and economically sustainable care that meets the needs and choices of patients with end-stage renal disease (ESRD). France offers 9 different modalities of dialysis, each characterized by dialysis technique, the extent of professional assistance, and the treatment site. The aim of this study was 1) to describe the various dialysis modalities in France and the patient characteristics associated with each of them, and 2) to analyze their regional patterns to identify possible unexpected associations between case-mixes and dialysis modalities. ♦ The clinical characteristics of the 37,421 adult patients treated by dialysis were described according to their treatment modality. Agglomerative hierarchical cluster analysis was used to aggregate the regions into clusters according to their use of these modalities and the characteristics of their patients. ♦ The gradient of patient characteristics was similar from home hemodialyis (HD) to in-center HD and from non-assisted automated peritoneal dialysis (APD) to assisted continuous ambulatory peritoneal dialysis (CAPD). Analyzing their spatial distribution, we found differences in the patient case-mix on dialysis across regions but also differences in the health-care provided for them. The classification of the regions into 6 different clusters allowed us to detect some unexpected associations between case-mixes and treatment modalities. ♦ The 9 modalities of treatment available make it theoretically possible to adapt treatment to patients' clinical characteristics and abilities. However, although we found an overall appropriate association of dialysis modalities to the case-mix, major inter-region heterogeneity and the low rate of peritoneal dialysis (PD) and home HD suggest that factors besides patients' clinical conditions impact the choice of dialysis modality. The French organization should now be evaluated in terms of patients' quality of

  17. Spatial modelling of malaria risk factors in Ruhuha sector in the east ...

    African Journals Online (AJOL)

    Spatial clusters of malaria occurrence were subsequently determined using Getis and Ord spatial statistics. This cluster analysis showed that malaria distribution is characterized by zones with high malaria risk, so called hot spots, zones with moderate malaria risk known as not significant spots and zones of low malaria risk ...

  18. Application of computer intensive data analysis methods to the analysis of digital images and spatial data

    DEFF Research Database (Denmark)

    Windfeld, Kristian

    1992-01-01

    Computer-intensive methods for data analysis in a traditional setting has developed rapidly in the last decade. The application of and adaption of some of these methods to the analysis of multivariate digital images and spatial data are explored, evaluated and compared to well established classical...... into the projection pursuit is presented. Examples from remote sensing are given. The ACE algorithm for computing non-linear transformations for maximizing correlation is extended and applied to obtain a non-linear transformation that maximizes autocorrelation or 'signal' in a multivariate image....... This is a generalization of the minimum /maximum autocorrelation factors (MAF's) which is a linear method. The non-linear method is compared to the linear method when analyzing a multivariate TM image from Greenland. The ACE method is shown to give a more detailed decomposition of the image than the MAF-transformation...

  19. Spatial aspects affecting acidification factors in European acidification modelling

    NARCIS (Netherlands)

    Bellekom, S.; Hettelingh, J. -P.; Aben, J.

    Plain linear models have recently been used in methodologies to model fate and transport for assessing acidification in life cycle impact assessment (LCIA), or in support of air pollution abatement policies. These models originate from a statistical analysis of the relationship between inputs and

  20. Visuo-Spatial Performance in Autism: A Meta-analysis

    OpenAIRE

    Muth, Anne; Honekopp, Johannes; Falter, Christine

    2014-01-01

    Visuo-spatial skills are believed to be enhanced in autism spectrum disorders (ASDs). This meta-analysis tests the current state of evidence for Figure Disembedding, Block Design, Mental Rotation and Navon tasks in ASD and neurotypicals. Block Design (d = 0.32) and Figure Disembedding (d = 0.26) showed superior performance for ASD with large heterogeneity that is unaccounted for. No clear differences were found for Mental Rotation. ASD samples showed a stronger local processing preference for...

  1. Strategic Placing of Field Hospitals Using Spatial Analysis

    OpenAIRE

    Rydén, Magnus

    2011-01-01

    Humanitarian help organisations today may benefit on improving their location analysis when placing field hospitals in countries hit by a disasters or catastrophe. The main objective of this thesis is to develop and evaluate a spatial decision support method for strategic placing of field hospitals for two time perspectives, long term (months) and short term (weeks). Specifically, the possibility of combining existing infrastructure and satellite data is examined to derive a suitability map f...

  2. Spatial Analysis of Depots for Advanced Biomass Processing

    Energy Technology Data Exchange (ETDEWEB)

    Hilliard, Michael R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brandt, Craig C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Webb, Erin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sokhansanj, Shahabaddine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Eaton, Laurence M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Martinez Gonzalez, Maria I. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2014-09-01

    The objective of this work was to perform a spatial analysis of the total feedstock cost at the conversion reactor for biomass supplied by a conventional system and an advanced system with depots to densify biomass into pellets. From these cost estimates, the conditions (feedstock cost and availability) for which advanced processing depots make it possible to achieve cost and volume targets can be identified.

  3. Cultural and biological factors modulate spatial biases over development.

    Science.gov (United States)

    Girelli, Luisa; Marinelli, Chiara Valeria; Grossi, Giuseppe; Arduino, Lisa S

    2017-11-01

    Increasing evidence supports the contribution of both biological and cultural factors to visuospatial processing. The present study adds to the literature by exploring the interplay of perceptual and linguistic mechanisms in determining visuospatial asymmetries in adults (Experiment 1) and children (Experiment 2). In particular, pre-schoolers (3 and 5 year-olds), school-aged children (8 year-old), and adult participants were required to bisect different types of stimuli, that is, lines, words, and figure strings. In accordance with the literature, results yielded a leftward bias for lines and words and a rightward bias for figure strings, in adult participants. More critically, different biases were found for lines, words, and figure strings in children as a function of age, reflecting the impact of both cultural and biological factors on the processing of different visuospatial materials. Specifically, an adult-like pattern of results emerged only in the older group of children (8 year-old), but not in pre-schoolers. Results are discussed in terms of literacy, reading habits exposure, and biological maturation.

  4. Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia

    Science.gov (United States)

    Teurlai, Magali; Menkès, Christophe Eugène; Cavarero, Virgil; Degallier, Nicolas; Descloux, Elodie; Grangeon, Jean-Paul; Guillaumot, Laurent; Libourel, Thérèse; Lucio, Paulo Sergio; Mathieu-Daudé, Françoise; Mangeas, Morgan

    2015-01-01

    Background/Objectives Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. Methods We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. Results The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double. Conclusion In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a

  5. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    Science.gov (United States)

    Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

    2014-02-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

  6. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    International Nuclear Information System (INIS)

    Rasam, A R A; Ghazali, R; Noor, A M M; Mohd, W M N W; Hamid, J R A; Bazlan, M J; Ahmad, N

    2014-01-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia

  7. Concept of spatial channel theory applied to reactor shielding analysis

    International Nuclear Information System (INIS)

    Williams, M.L.; Engle, W.W. Jr.

    1977-01-01

    The concept of channel theory is used to locate spatial regions that are important in contributing to a shielding response. The method is analogous to the channel-theory method developed for ascertaining important energy channels in cross-section analysis. The mathematical basis for the theory is shown to be the generalized reciprocity relation, and sample problems are given to exhibit and verify properties predicted by the mathematical equations. A practical example is cited from the shielding analysis of the Fast Flux Test Facility performed at Oak Ridge National Laboratory, in which a perspective plot of channel-theory results was found useful in locating streaming paths around the reactor cavity shield

  8. Spectral theory and nonlinear analysis with applications to spatial ecology

    CERN Document Server

    Cano-Casanova, S; Mora-Corral , C

    2005-01-01

    This volume details some of the latest advances in spectral theory and nonlinear analysis through various cutting-edge theories on algebraic multiplicities, global bifurcation theory, non-linear Schrödinger equations, non-linear boundary value problems, large solutions, metasolutions, dynamical systems, and applications to spatial ecology. The main scope of the book is bringing together a series of topics that have evolved separately during the last decades around the common denominator of spectral theory and nonlinear analysis - from the most abstract developments up to the most concrete applications to population dynamics and socio-biology - in an effort to fill the existing gaps between these fields.

  9. An operational modal analysis method in frequency and spatial domain

    Science.gov (United States)

    Wang, Tong; Zhang, Lingmi; Tamura, Yukio

    2005-12-01

    A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified. Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

  10. Spatial heterogeneity analysis of brain activation in fMRI

    Directory of Open Access Journals (Sweden)

    Lalit Gupta

    2014-01-01

    Full Text Available In many brain diseases it can be qualitatively observed that spatial patterns in blood oxygenation level dependent (BOLD activation maps appear more (diffusively distributed than in healthy controls. However, measures that can quantitatively characterize this spatial distributiveness in individual subjects are lacking. In this study, we propose a number of spatial heterogeneity measures to characterize brain activation maps. The proposed methods focus on different aspects of heterogeneity, including the shape (compactness, complexity in the distribution of activated regions (fractal dimension and co-occurrence matrix, and gappiness between activated regions (lacunarity. To this end, functional MRI derived activation maps of a language and a motor task were obtained in language impaired children with (Rolandic epilepsy and compared to age-matched healthy controls. Group analysis of the activation maps revealed no significant differences between patients and controls for both tasks. However, for the language task the activation maps in patients appeared more heterogeneous than in controls. Lacunarity was the best measure to discriminate activation patterns of patients from controls (sensitivity 74%, specificity 70% and illustrates the increased irregularity of gaps between activated regions in patients. The combination of heterogeneity measures and a support vector machine approach yielded further increase in sensitivity and specificity to 78% and 80%, respectively. This illustrates that activation distributions in impaired brains can be complex and more heterogeneous than in normal brains and cannot be captured fully by a single quantity. In conclusion, heterogeneity analysis has potential to robustly characterize the increased distributiveness of brain activation in individual patients.

  11. Spatial Durbin model analysis macroeconomic loss due to natural disasters

    Science.gov (United States)

    Kusrini, D. E.; Mukhtasor

    2015-03-01

    Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

  12. Spatial Variation of Magnitude Scaling Factors During the 2010 Darfield and 2011 Christchurch, New Zealand, Earthquakes

    OpenAIRE

    Carter, William Lake

    2016-01-01

    Magnitude Scaling Factors (MSF) account for the durational effects of strong ground shaking on the inducement of liquefaction within the simplified liquefaction evaluation procedure which is the most commonly used approach for assessing liquefaction potential worldwide. Within the context of the simplified procedure, the spatial variation in the seismic demand imposed on the soil traditionally has been assumed to be solely a function of the spatial variation of the peak amplitude of the groun...

  13. SPATIAL ANALYSIS TO SUPPORT GEOGRAPHIC TARGETING OF GENOTYPES TO ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    Glenn eHyman

    2013-03-01

    Full Text Available Crop improvement efforts have benefited greatly from advances in available data, computing technology and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps and assess environment change. Climate, elevation and vegetation data sets are now widely available, supporting analyses that were much more difficult even five or ten years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts.

  14. Spatial analysis and characteristics of pig farming in Thailand.

    Science.gov (United States)

    Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

    2016-10-06

    In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed

  15. TEMPORAL AND SPATIAL ANALYSIS OF EXTREME RAINFALL ON THE SLOPE AREA OF MT. MERAPI

    Directory of Open Access Journals (Sweden)

    Dhian Dharma Prayuda

    2015-02-01

    Full Text Available Rainfall has temporal and spatial characteristics with certain pattern which are affected by topographic variations and climatology of an area. The intensity of extreme rainfall is one of important characteristics related to the trigger factors for debris flow. This research will discuss the result of analysis on short duration rainfall data in the south and west slope of Mt. Merapi. Measured hourly rainfall data in 14 rainfall stations for the last 27 years were used as analysis input. The rainfall intensity-duration-frequency relationship (IDF was derived using empirical formula of Sherman, Kimijima, Haspers, and Mononobe method. The analysis on the characteristics of extreme rainfall intensity was performed by conducting spatial interpolation using Inverse Distance Weighted (IDW method. Result of analysis shows that IDF of rainfall in the research area fits to Sherman’s formula. Besides, the spatial distribution pattern of maximum rainfall intensity was assessed on the basis of area rainfall. Furthermore, the difference on the result of spatial map for one hour extreme rainfall based on isolated event and non-isolated event method can be evaluated. The result of this preliminary research is expected to be inputs in the establishment of debris flow early warning in Mt. Merapi slope area.

  16. An analysis of spatial representativeness of air temperature monitoring stations

    Science.gov (United States)

    Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen

    2018-05-01

    Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.

  17. A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

    Science.gov (United States)

    Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

    2013-04-15

    Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these "hotspots". Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio

  18. Spatial Analysis Along Networks Statistical and Computational Methods

    CERN Document Server

    Okabe, Atsuyuki

    2012-01-01

    In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process

  19. A Flood Risk Assessment of Quang Nam, Vietnam Using Spatial Multicriteria Decision Analysis

    Directory of Open Access Journals (Sweden)

    Chinh Luu

    2018-04-01

    Full Text Available Vietnam is highly vulnerable to flood and storm impacts. Holistic flood risk assessment maps that adequately consider flood risk factors of hazard, exposure, and vulnerability are not available. These are vital for flood risk preparedness and disaster mitigation measures at the local scale. Unfortunately, there is a lack of knowledge about spatial multicriteria decision analysis and flood risk analysis more broadly in Vietnam. In response to this need, we identify and quantify flood risk components in Quang Nam province through spatial multicriteria decision analysis. The study presents a new approach to local flood risk assessment mapping, which combines historical flood marks with exposure and vulnerability data. The flood risk map output could assist and empower decision-makers in undertaking flood risk management activities in the province. Our study demonstrates a methodology to build flood risk assessment maps using flood mark, exposure and vulnerability data, which could be applied in other provinces in Vietnam.

  20. Temporal and spatial variation in recent vehicular emission inventories in China based on dynamic emission factors.

    Science.gov (United States)

    Cai, Hao; Xie, Shaodong

    2013-03-01

    The vehicular emission trend in China was tracked for the recent period 2006-2009 based on a database of dynamic emission factors of CO, nonmethane volatile organic compounds (NMVOC), NOx, PM10, CO2, CH4, and N2O for all categories of on-road motor vehicles in China, which was developed at the provincial level using the COPERT 4 model, to account for the effects of rapid advances in engine technologies, implementation of improved emission standards, emission deterioration due to mileage, and fuel quality improvement. Results show that growth rates of CO and NMVOC emissions slowed down, but NOx and PM10 emissions continued rising rapidly for the period 2006-2009. Moreover CO2, CH4, and N2O emissions in 2009 almost doubled compared to those in 2005. Characteristics of recent spatial distribution of emissions and emission contributions by vehicle category revealed that priority of vehicular emission control should be put on the eastern and southeastern coastal provinces and northern regions, and passenger cars and motorcycles require stricter control for the reduction of CO and NMVOC emissions, while effective reduction of NOx and PM10 emissions can be achieved by better control of heavy-duty vehicles, buses and coaches, and passenger cars. Explicit provincial-level Monte Carlo uncertainty analysis, which quantified for the first time the Chinese vehicular emission uncertainties associated with both COPERT-derived and domestically measured emission factors by vehicle technology, showed that CO, NMVOC, and NOx emissions for the period 2006-2009 were calculated with the least uncertainty, followed by PM10 and CO2, despite relatively larger uncertainties in N2O and CH4 emissions. The quantified low uncertainties of emissions revealed a necessity of applying vehicle technology- and vehicle age-specific dynamic emission factors for vehicular emission estimation, and these improved methodologies are applicable for routine update and forecast of China's on-road motor vehicle

  1. Spatial and temporal epidemiological analysis in the Big Data era.

    Science.gov (United States)

    Pfeiffer, Dirk U; Stevens, Kim B

    2015-11-01

    Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle

  2. Influence of environmental factors on the spatial distribution and diversity of forest soil in Latvia

    Directory of Open Access Journals (Sweden)

    Raimonds Kasparinskis

    2012-02-01

    Full Text Available This study was carried out to determine the spatial relationships between environmental factors (Quaternary deposits, topographical situation, land cover, forest site types, tree species, soil texture and soil groups, and their prefix qualifiers (according to the international Food and Agricultural Organization soil classification system World Reference Base for Soil Resources [FAO WRB]. The results show that it is possible to establish relationships between the distribution of environmental factors and soil groups by applying the generalized linear models in data statistical analysis, using the R 2.11.1 software for processing data from 113 sampling plots throughout the forest territory of Latvia.A very high diversity of soil groups in a relatively similar geological structure was revealed. For various reasons there is not always close relationship between the soil group, their prefix qualifiers and Quaternary deposits, as well as between forest site types, the dominant tree species and specific soil group and its prefix qualifiers. Close correlation was established between Quaternary deposits, forest site types, dominant tree species and soil groups within nutrient-poor sediments and very rich deposits containing free carbonates. No significant relationship was detected between the CORINE Land Cover 2005 classes, topographical situation and soil group.

  3. Importance of spatial factors and temporal scales in environmental risk assessment in marine ecosystems

    International Nuclear Information System (INIS)

    Grebenkov, A.; Linkov, I.; Andrizhievski, A.; Lukashevich, A.; Trifonov, A.

    2004-01-01

    Coastal areas adjacent to the Black Sea, particularly in Crimea, have suffered from inappropriate human activities, poorly regulated industry and former naval bases. Industrial and municipal wastewater pollutants draining into the three major European rivers (the Danube, Dniestr, and Dnieper) and dumping in the open sea result in an enormous increase in contamination level of ecosystems of the Black Sea. In spite of this, Crimea and its adjacent waters is still a globally important center of biological diversity, with an enormous and exciting range of habitats within a comparatively small area. The problem now is to evaluate economically feasible remediation and ecologically sustainable cleanup/reuse alternatives for the most contaminated sites of this area. One of the principal methodological components of such evaluation is a risk-based decision protocol that provides support in analysis of ecological value and reuse options for a chosen site. This paper presents the results of development of a spatially explicit risk assessment technique to be implemented as a part of the decision-making process and gives an example of its application to contaminated marine ecosystems. The model is suggested that takes into account several principal assumptions: (i) spatial heterogeneity of contamination of forage is known and mapped within known location of receptor's habitat, and (ii) the receptor movement and timescale are determined by location, volume and attractiveness of local habitat and forage resources. This implies two models: Spatially Explicit Exposure Assessment Model that calculates internal exposure resulting from ingestion of contaminated feeds, and Probabilistic Receptor Migration Model that generates motivation of behaviour of a receptor while feeding. In the first model, time-dependent accumulation of contamination in receptor tissue is defined by the differential balance equation that takes into account forage consumption rate and excretion rate. In the

  4. A Spatial Analysis of Tourism Activity in Romania

    Directory of Open Access Journals (Sweden)

    Daniela Luminita Constantin

    2018-02-01

    Full Text Available Location is a key concept in tourism sector analysis, given the dependence of this activity on the natural, built, cultural and social characteristics of a certain territory. As a result, the tourist zoning is an important instrument for delimiting tourist areas in accordance with multiple criteria, so as to lay the foundations for finding the most suitable solutions of turning to good account the resources in this field. The modern approaches proposed in this paper use a series of analytical tools that combine GIS and spatial agglomeration analysis based techniques. They can be also employed in order to examine and explain the differences between tourist zones (and sub-zones in terms of economic and social results and thus to suggest realistic ways to improve the efficiency and effectiveness of tourist activities in various geographical areas. In the described context this paper proposes an interdisciplinary perspective (spatial statistics and Geographical Information Systems for analysing the tourism activity in Romania, mainly aiming to identify the agglomerations of companies acting in this industry and assess their performance and contribution to the economic development of the corresponding regions. It also intends to contribute to a better understanding of the way in which tourism related business activities develop, in order to enhance appropriate support networks. Territorial and spatial statistics, as well as GIS based analyses are applied, using data about all companies acting in tourism industry in Romania provided by the National Authority for Tourism as well as data from the Environmental Systems Research Institute (ESRI.

  5. [Spatial analysis of childhood obesity and overweight in Peru, 2014].

    Science.gov (United States)

    Hernández-Vásquez, Akram; Bendezú-Quispe, Guido; Díaz-Seijas, Deysi; Santero, Marilina; Minckas, Nicole; Azañedo, Diego; Antiporta, Daniel A

    2016-01-01

    To estimate regional prevalence and identify the spatial patterns of the degree of overweight and obesity by districts in under five years children in Peru during 2014. Analysis of the information reported by the Information System Nutritional Status (SIEN) of the number of cases of overweight and obesity in children under five years recorded during 2014. Regional prevalence for overweight and obesity, and their respective confidence intervals to 95% were calculated. Moran index was used to determine patterns of grouping districts with high prevalence of overweight and/or obesity. Data from 1834 districts and 2,318,980 children under five years were analyzed. 158,738 cases (6.84%; CI 95%: 6.81 to 6.87) were overweight, while 56,125 (2.42%; CI 95%: 2.40 to 2.44) obesity. The highest prevalence of overweight were identified in the regions of Tacna (13.9%), Moquegua (11.8%), Callao (10.4%), Lima (10.2%) and Ica (9.3%), and in the same regions for obesity with 5.3%; 4.3%; 4.0%; 4.0% and 3.8% respectively. The spatial analysis found grouping districts of high prevalence in 10% of all districts for both overweight and obesity, identifying 199 districts for overweight (126 urban and 73 rural), and 184 for obesity (136 urban and 48 rural). The highest prevalence of overweight and obesity were identified in the Peruvian coast regions. Moreover, these regions are predominantly exhibited a spatial clustering of districts with high prevalence of overweight and obesity.

  6. Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

    Science.gov (United States)

    Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

    2018-03-01

    GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

  7. The spatial kinetic analysis of accelerator-driven subcritical reactor

    International Nuclear Information System (INIS)

    Takahashi, H.; An, Y.; Chen, X.

    1998-02-01

    The operation of the accelerator driven reactor with subcritical condition provides a more flexible choice of the reactor materials and of design parameters. A deep subcriticality is chosen sometime from the analysis of point kinetics. When a large reactor is operated in deep subcritical condition by using a localized spallation source, the power distribution has strong spatial dependence, and point kinetics does not provide proper analysis for reactor safety. In order to analyze the spatial and energy dependent kinetic behavior in the subcritical reactor, the authors developed a computation code which is composed of two parts, the first one is for creating the group cross section and the second part solves the multi-group kinetic diffusion equations. The reactor parameters such as the cross section of fission, scattering, and energy transfer among the several energy groups and regions are calculated by using a code modified from the Monte Carlo codes MCNPA and LAHET instead of the usual analytical method of ANISN, TWOTRAN codes. Thus the complicated geometry of the accelerator driven reactor core can be precisely taken into account. The authors analyzed the subcritical minor actinide transmutor studied by Japan Atomic Energy Research Institute (JAERI) using the code

  8. Spatial and temporal analysis of postural control in dyslexic children.

    Science.gov (United States)

    Gouleme, Nathalie; Gerard, Christophe Loic; Bui-Quoc, Emmanuel; Bucci, Maria Pia

    2015-07-01

    The aim of this study is to examine postural control of dyslexic children using both spatial and temporal analysis. Thirty dyslexic (mean age 9.7±0.3years) and thirty non-dyslexic age-matched children participated in the study. Postural stability was evaluated using Multitest Equilibre from Framiral®. Posture was recorded in the following conditions: eyes open fixating a target (EO) and eyes closed (EC) on stable (-S-) and unstable (-U-) platforms. The findings of this study showed poor postural stability in dyslexic children with respect to the non-dyslexic children group, as demonstrated by both spatial and temporal analysis. In both groups of children postural control depends on the condition, and improves when the eyes are open on a stable platform. Dyslexic children have spectral power indices that are higher than in non-dyslexic children and they showed a shorter cancelling time. Poor postural control in dyslexic children could be due to a deficit in using sensory information most likely caused by impairment in cerebellar activity. The reliability of brain activation patterns, namely in using sensory input and cerebellar activity may explain the deficit in postural control in dyslexic children. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  9. SRXRF analysis with spatial resolution of dental calculus

    International Nuclear Information System (INIS)

    Sanchez, Hector Jorge; Perez, Carlos Alberto; Grenon, Miriam

    2000-01-01

    This work presents elemental-composition studies of dental calculus by X-ray fluorescence analysis using synchrotron radiation. The intrinsic characteristics of synchrotron light allow for a semi-quantitative analysis with spatial resolution. The experiments were carried out in the high-vacuum station of the XRF beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). All the measurements were performed in conventional geometry (45 deg. + 45 deg.) and the micro-collimation was attained via a pair of orthogonal slits mounted in the beamline. In this way, pixels of 50 μmx50 μm were obtained keeping a high flux of photons on the sample. Samples of human dental calculus were measured in different positions along their growing axis, in order to determine variations of the compositions in the pattern of deposit. Intensity ratios of minor elements and traces were obtained, and linear profiles and surface distributions were determined. As a general summary, we can conclude that μXRF experiments with spatial resolution on dental calculus are feasible with simple collimation and adequate positioning systems, keeping a high flux of photon. These results open interesting perspectives for the future station of the line, devoted to μXRF, which will reach resolutions of the order of 10 μm

  10. SRXRF analysis with spatial resolution of dental calculus

    Science.gov (United States)

    Sánchez, Héctor Jorge; Pérez, Carlos Alberto; Grenón, Miriam

    2000-09-01

    This work presents elemental-composition studies of dental calculus by X-ray fluorescence analysis using synchrotron radiation. The intrinsic characteristics of synchrotron light allow for a semi-quantitative analysis with spatial resolution. The experiments were carried out in the high-vacuum station of the XRF beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). All the measurements were performed in conventional geometry (45°+45°) and the micro-collimation was attained via a pair of orthogonal slits mounted in the beamline. In this way, pixels of 50 μm×50 μm were obtained keeping a high flux of photons on the sample. Samples of human dental calculus were measured in different positions along their growing axis, in order to determine variations of the compositions in the pattern of deposit. Intensity ratios of minor elements and traces were obtained, and linear profiles and surface distributions were determined. As a general summary, we can conclude that μXRF experiments with spatial resolution on dental calculus are feasible with simple collimation and adequate positioning systems, keeping a high flux of photon. These results open interesting perspectives for the future station of the line, devoted to μXRF, which will reach resolutions of the order of 10 μm.

  11. Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry

    Directory of Open Access Journals (Sweden)

    Ali Ahmadi

    2015-01-01

    Full Text Available Background: Myocardial infarction (MI is a leading cause of mortality and morbidity in Iran. No spatial analysis of MI has been conducted to date. The present study was conducted to determine the pattern of MI incidence and to identify the associated factors in Iran by province. Materials and Methods: This study has two parts. One part is prospective and hospital-based, and the other part is an ecological study. In this study, the data of 20,750 new MI cases registered in Iranian Myocardial Infarction Registry in 2012 were used. For spatial analysis in global and local, spatial autocorrelation, Moran′s I, Getis-Ord, and logistic regression models were used. Data were analyzed by Stata software and ArcGIS 9.3. Results: Based on autocorrelation coefficient, a specific pattern was observed in the distribution of MI incidence in different provinces (Moran′s I: 0.75, P < 0.001. Spatial pattern of incidence was approximately the same in men and women. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran. Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI could be mentioned. Hypertension, smoking, and BMI contributed to clustering with, respectively, 2.36, 1.31, and 1.31 odds ratio. Conclusion: Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran. Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system.

  12. An easy guide to factor analysis

    CERN Document Server

    Kline, Paul

    2014-01-01

    Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, a

  13. Spatial analysis for prevalence of type 2 diabetes mellitus - A state investigation

    Science.gov (United States)

    Zainal, Siti Salsabilah Nabilah; Masnan, Maz Jamilah; Amin, Nor Azrita Mohd; Mohamed, Nordin

    2017-11-01

    Type 2 Diabetes Mellitus (T2DM) is a chronic and non-communicable disease, which is characterized as the cause of premature deaths in the world. Unfortunately, Malaysia is one of the many countries facing this epidemic. Based on the increasing current trend of T2DM patients' cases from the National Diabetes Registry (NDR) Report from 2009 to 2012, there were approximately 2.6 million adults aged 18 years and above living with diabetes disease in Malaysia. Thus, this study aims to (i) perform preliminary spatial analysis for the prevalence of T2DM patients based on some factors, (ii) map the findings of the analyses according to some spatial properties, and (iii) analyze the pattern of diagnosed T2DM patients based on the studied factors. The studied population is one of the highest prevalence states of T2DM in Malaysia. This study is expected to reveal some demographic patterns that probably significant to this alarming epidemic.

  14. The spatial analysis on hemorrhagic fever with renal syndrome in Jiangsu province, China based on geographic information system.

    Science.gov (United States)

    Bao, Changjun; Liu, Wanwan; Zhu, Yefei; Liu, Wendong; Hu, Jianli; Liang, Qi; Cheng, Yuejia; Wu, Ying; Yu, Rongbin; Zhou, Minghao; Shen, Hongbing; Chen, Feng; Tang, Fenyang; Peng, Zhihang

    2014-01-01

    Hemorrhagic fever with renal syndrome (HFRS) is endemic in mainland China, accounting for 90% of total reported cases worldwide, and Jiangsu is one of the most severely affected provinces. In this study, the authors conducted GIS-based spatial analyses in order to determine the spatial distribution of the HFRS cases, identify key areas and explore risk factors for public health planning and resource allocation. Interpolation maps by inverse distance weighting were produced to detect the spatial distribution of HFRS cases in Jiangsu from 2001 to 2011. Spatio-temporal clustering was applied to identify clusters at the county level. Spatial correlation analysis was conducted to detect influencing factors of HFRS in Jiangsu. HFRS cases in Jiangsu from 2001 to 2011 were mapped and the results suggested that cases in Jiangsu were not distributed randomly. Cases were mainly distributed in northeastern and southwestern Jiangsu, especially in Dafeng and Sihong counties. It was notable that prior to this study, Sihong county had rarely been reported as a high-risk area of HFRS. With the maximum spatial size of 50% of the total population and the maximum temporal size of 50% of the total population, spatio-temporal clustering showed that there was one most likely cluster (LLR = 624.52, Phighways, railways, rivers and lakes. The application of GIS together with spatial interpolation, spatio-temporal clustering and spatial correlation analysis can effectively identify high-risk areas and factors influencing HFRS incidence to lay a foundation for researching its pathogenesis.

  15. Spatial analysis of the etiology of amyotrophic lateral sclerosis among 1991 Gulf War veterans.

    Science.gov (United States)

    Miranda, Marie Lynn; Alicia Overstreet Galeano, M; Tassone, Eric; Allen, Kelli D; Horner, Ronnie D

    2008-11-01

    Veterans of the 1991 Gulf War have an increased risk of amyotrophic lateral sclerosis (ALS), but the etiology is unknown. This study sought to identify geographic areas with elevated risk for the later development of ALS among military personnel who served in the first Gulf War. A unified geographic information system (GIS) was constructed to allow analysis of secondary data on troop movements in the 1991 Gulf War theatre in the Persian Gulf region including Iraq, northern Saudi Arabia, and Kuwait. We fit Bayesian Poisson regression models to adjust for potential risk factors, including one relatively discrete environmental exposure, and to identify areas associated with elevated risk of ALS. We found that service in particular locations of the Gulf was associated with an elevated risk for later developing ALS, both before and after adjustment for branch of service and potential of exposure to chemical warfare agents in and around Khamisiyah, Iraq. Specific geographic locations of troop units within the 1991 Gulf War theatre are associated with an increased risk for the subsequent development of ALS among members of those units. The identified spatial locations represent the logical starting points in the search for potential etiologic factors of ALS among Gulf War veterans. Of note, for locations where the relative odds of subsequently developing ALS are among the highest, specific risk factors, whether environmental or occupationally related, have not been identified. The results of spatial models can be used to subsequently look for risk factors that follow the spatial pattern of elevated risk.

  16. The relationship between language and spatial ability an analysis of spatial language for reconstructing the solving of spatial tasks

    CERN Document Server

    Mizzi, Angel

    2017-01-01

    This work investigates how different fifth-grade students solve spatial-verbal tasks and the role of language in this process. Based on a synthesis of theoretical foundations and methodological issues for supporting the relationship between spatial ability and language, this present study examines and classifies strategies used by students as well as the obstacles they encounter when solving spatial tasks in the reconstruction method. Contents Theoretical Framework Design and Implementation Results and Discussion from the Inductive Data Analyses Target Groups Scholars and students of mathematics education Teachers of mathematics in primary and secondary schools About the Author Angel Mizzi works as a research assistant and lecturer at the University of Duisburg-Essen, where he has successfully completed his PhD studies in mathematics education.

  17. Spatial data analysis and the use of maps in scientific health articles.

    Science.gov (United States)

    Nucci, Luciana Bertoldi; Souccar, Patrick Theodore; Castilho, Silvia Diez

    2016-07-01

    Despite the growing number of studies with a characteristic element of spatial analysis, the application of the techniques is not always clear and its continuity in epidemiological studies requires careful evaluation. To verify the spread and use of those processes in national and international scientific papers. An assessment was made of periodicals according to the impact index. Among 8,281 journals surveyed, four national and four international were selected, of which 1,274 articles were analyzed regarding the presence or absence of spatial analysis techniques. Just over 10% of articles published in 2011 in high impact journals, both national and international, showed some element of geographical location. Although these percentages vary greatly from one journal to another, denoting different publication profiles, we consider this percentage as an indication that location variables have become an important factor in studies of health.

  18. Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

    Science.gov (United States)

    Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

    2015-01-01

    The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

  19. Defensible Spaces in Philadelphia: Exploring Neighborhood Boundaries Through Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Rory Kramer

    2017-02-01

    Full Text Available Few spatial scales are as important to individual outcomes as the neighborhood. However, it is nearly impossible to define neighborhoods in a generalizable way. This article proposes that by shifting the focus to measuring neighborhood boundaries rather than neighborhoods, scholars can avoid the problem of the indefinable neighborhood and better approach questions of what predicts racial segregation across areas. By quantifying an externality space theory of neighborhood boundaries, this article introduces a novel form of spatial analysis to test where potential physical markers of neighborhood boundaries (major roads, rivers, railroads, and the like are associated with persistent racial boundaries between 1990 and 2010. Using Philadelphia as a case study, the paper identifies neighborhoods with persistent racial boundaries. It theorizes that local histories of white reactions to black in-migration explain which boundaries persistently resisted racial turnover, unlike the majority of Philadelphia’s neighborhoods, and that those racial boundaries shape the location, progress, and reaction to new residential development in those neighborhoods.

  20. Analysis Framework of China’s Grain Production System: A Spatial Resilience Perspective

    Directory of Open Access Journals (Sweden)

    Dazhuan Ge

    2017-12-01

    Full Text Available China’s grain production has transformed from absolute shortage to a current structural oversupply. High-intensity production introduced further challenges for the eco-environment, smallholder livelihood, and the man-land interrelationship. Driven by urban-rural transformation, research on food security patterns and grain production has expanded into a new field. To analyze the challenges and required countermeasures for China’s grain production system (GPS, this study constructed a theoretical GPS framework based on space resilience. Firstly, a new GPS concept was proposed and a functional system was established for protecting the regional food security, thus guaranteeing smallholder livelihood, stabilizing urban-rural transformation, and sustaining the eco-environment in terms of economic, social, and ecological attributes of the GPS. Secondly, based on a cross-scale interaction analysis that varied from a smallholder scale to a global scale, the systematic crisis of the GPS was analyzed. Thirdly, a cross-scale analytic framework of the GPS was formed from the perspective of spatial resilience, integrating both inner and external disturbance factors of the GPS. Both spatial heterogeneity and connectivity of internal and external disturbance factors are important contents of system space resilience. Finally, the hierarchy of spatial resilience of GPS became clear. The transformation of labor force and the land use transition form key thresholds of the GPS. In summary: based on protecting the basic functions of the GPS, the cross-scale effect of systematic disturbance factors and relevant countermeasures for spatial resilience are effectively influenced by the coordination of the interests of multiple stakeholders; spatial resilience is an effective analytical tool for GPS regulation, providing a reference for revealing the inherent mechanism and functional evolution of the GPS in the process of urban-rural transformation.

  1. Where do overweight women in Ghana live? Answers from exploratory spatial data analysis

    Directory of Open Access Journals (Sweden)

    Fidelia A.A. Dake

    2012-03-01

    Full Text Available Contextual influence on health outcomes is increasingly becoming an important area of research. Analytical techniques such as spatial analysis help explain the variations and dynamics in health inequalities across different context and among different population groups. This paper explores spatial clustering in body mass index among Ghanaian women by analysing data from the 2008 Ghana Demographic and Health Survey using exploratory spatial data analysis techniques. Overweight was a more common occurrence in urban areas than in rural areas. Close to a quarter of the clusters in Ghana, mostly those in the southern sector contained women who were overweight. Women who lived in clusters where the women were overweight were more likely to live around other clusters where the women were also overweight. The results suggest that the urban environment could be a potential contributing factor to the high levels of obesity in urban areas of Ghana. There is the need for researchers to include a spatial dimension to obesity research in Ghana paying particular attention the urban environment.

  2. Interactions between the spatial and temporal stimulus factors that influence multisensory integration in human performance.

    Science.gov (United States)

    Stevenson, Ryan A; Fister, Juliane Krueger; Barnett, Zachary P; Nidiffer, Aaron R; Wallace, Mark T

    2012-05-01

    In natural environments, human sensory systems work in a coordinated and integrated manner to perceive and respond to external events. Previous research has shown that the spatial and temporal relationships of sensory signals are paramount in determining how information is integrated across sensory modalities, but in ecologically plausible settings, these factors are not independent. In the current study, we provide a novel exploration of the impact on behavioral performance for systematic manipulations of the spatial location and temporal synchrony of a visual-auditory stimulus pair. Simple auditory and visual stimuli were presented across a range of spatial locations and stimulus onset asynchronies (SOAs), and participants performed both a spatial localization and simultaneity judgment task. Response times in localizing paired visual-auditory stimuli were slower in the periphery and at larger SOAs, but most importantly, an interaction was found between the two factors, in which the effect of SOA was greater in peripheral as opposed to central locations. Simultaneity judgments also revealed a novel interaction between space and time: individuals were more likely to judge stimuli as synchronous when occurring in the periphery at large SOAs. The results of this study provide novel insights into (a) how the speed of spatial localization of an audiovisual stimulus is affected by location and temporal coincidence and the interaction between these two factors and (b) how the location of a multisensory stimulus impacts judgments concerning the temporal relationship of the paired stimuli. These findings provide strong evidence for a complex interdependency between spatial location and temporal structure in determining the ultimate behavioral and perceptual outcome associated with a paired multisensory (i.e., visual-auditory) stimulus.

  3. Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China

    Science.gov (United States)

    2013-01-01

    Background Human brucellosis incidence in China has been increasing dramatically since 1999. However, epidemiological features and potential factors underlying the re-emergence of the disease remain less understood. Methods Data on human and animal brucellosis cases at the county scale were collected for the year 2004 to 2010. Also collected were environmental and socioeconomic variables. Epidemiological features including spatial and temporal patterns of the disease were characterized, and the potential factors related to the spatial heterogeneity and the temporal trend of were analysed using Poisson regression analysis, Granger causality analysis, and autoregressive distributed lag (ADL) models, respectively. Results The epidemic showed a significantly higher spatial correlation with the number of sheep and goats than swine and cattle. The disease was most prevalent in grassland areas with elevation between 800–1,600 meters. The ADL models revealed that local epidemics were correlated with comparatively lower temperatures and less sunshine in winter and spring, with a 1–7 month lag before the epidemic peak in May. Conclusions Our findings indicate that human brucellosis tended to occur most commonly in grasslands at moderate elevation where sheep and goats were the predominant livestock, and in years with cooler winter and spring or less sunshine. PMID:24238301

  4. N2O emission hotspots at different spatial scales and governing factors for small scale hotspots

    International Nuclear Information System (INIS)

    Heuvel, R.N. van den; Hefting, M.M.; Tan, N.C.G.; Jetten, M.S.M.; Verhoeven, J.T.A.

    2009-01-01

    Chronically nitrate-loaded riparian buffer zones show high N 2 O emissions. Often, a large part of the N 2 O is emitted from small surface areas, resulting in high spatial variability in these buffer zones. These small surface areas with high N 2 O emissions (hotspots) need to be investigated to generate knowledge on the factors governing N 2 O emissions. In this study the N 2 O emission variability was investigated at different spatial scales. Therefore N 2 O emissions from three 32 m 2 grids were determined in summer and winter. Spatial variation and total emission were determined on three different scales (0.3 m 2 , 0.018 m 2 and 0.0013 m 2 ) at plots with different levels of N 2 O emissions. Spatial variation was high at all scales determined and highest at the smallest scale. To test possible factors inducing small scale hotspots, soil samples were collected for slurry incubation to determine responses to increased electron donor/acceptor availability. Acetate addition did increase N 2 O production, but nitrate addition failed to increase total denitrification or net N 2 O production. N 2 O production was similar in all soil slurries, independent of their origin from high or low emission soils, indicating that environmental conditions (including physical factors like gas diffusion) rather than microbial community composition governed N 2 O emission rates

  5. Landslide susceptibility assessment using Spatial Analysis and GIS modeling in Cluj-Napoca Metropolitan Area, Romania

    Directory of Open Access Journals (Sweden)

    Bogdan Eugen Dolean

    2017-06-01

    Full Text Available In Romania, landslides together with the multitude geomorphological processes linked to them are some of the most common hazards which manifested in vulnerable areas with important human activities can induce many negative effects. From this perspective, identifying the areas affected by landslides, based on GIS spatial analysis models and statistical methods, is a subject frequently discussed in the national and international literature. This research was focused on the methods and practices of GIS spatial analysis, with a target of creating a complex model and a viable methodology of assessment the probability of occurrence of landslides, applicable within any territory. The study was based on the identification and analysis in a bivariate systemic manner of the numerous factors involved in the production of landslides, such as topography, morphology, hydrography, geological, lithology, weather, land use. The area in which the analysis has been conducted, The Metropolitan Area of Cluj-Napoca, was chosen due to the exacerbated urbanization of the recent years, coupled with a massive increase in the number of inhabitants, thus being a space of socioeconomic importance and a real challenge regarding spatial planning. Applying the model in this area has generated relatively good results, with a power of predictability of over 80%, measured in landslides sample areas used for the validation of the results, fact which attest the viability of the model and the fact that the model can be used in different areas with related morphometric and environmental characteristics.

  6. Considering the spatial-scale factor when modelling sustainable land management.

    Science.gov (United States)

    Bouma, Johan

    2015-04-01

    Considering the spatial-scale factor when modelling sustainable land management. J.Bouma Em.prof. soil science, Wageningen University, Netherlands. Modelling soil-plant processes is a necessity when exploring future effects of climate change and innovative soil management on agricultural productivity. Soil data are needed to run models and traditional soil maps and the associated databases (based on various soil Taxonomies ), have widely been applied to provide such data obtained at "representative" points in the field. Pedotransferfunctions (PTF)are used to feed simulation models, statistically relating soil survey data ( obtained at a given point in the landscape) to physical parameters for simulation, thus providing a link with soil functionality. Soil science has a basic problem: their object of study is invisible. Only point data are obtained by augering or in pits. Only occasionally roadcuts provide a better view. Extrapolating point to area data is essential for all applications and presents a basic problem for soil science, because mapping units on soil maps, named for a given soil type,may also contain other soil types and quantitative information about the composition of soil map units is usually not available. For detailed work at farm level ( 1:5000-1:10000), an alternative procedure is proposed. Based on a geostatistical analysis, onsite soil observations are made in a grid pattern with spacings based on a geostatistical analysis. Multi-year simulations are made for each point of the functional properties that are relevant for the case being studied, such as the moisture supply capacity, nitrate leaching etc. under standardized boundary conditions to allow comparisons. Functional spatial units are derived next by aggregating functional point data. These units, which have successfully functioned as the basis for precision agriculture, do not necessarily correspond with Taxonomic units but when they do the Taxonomic names should be noted . At lower

  7. Integrating the statistical analysis of spatial data in ecology

    Science.gov (United States)

    A. M. Liebhold; J. Gurevitch

    2002-01-01

    In many areas of ecology there is an increasing emphasis on spatial relationships. Often ecologists are interested in new ways of analyzing data with the objective of quantifying spatial patterns, and in designing surveys and experiments in light of the recognition that there may be underlying spatial pattern in biotic responses. In doing so, ecologists have adopted a...

  8. Spatial prediction of landslide hazard using discriminant analysis and GIS

    Science.gov (United States)

    Peter V. Gorsevski; Paul Gessler; Randy B. Foltz

    2000-01-01

    Environmental attributes relevant for spatial prediction of landslides triggered by rain and snowmelt events were derived from digital elevation model (DEM). Those data in conjunction with statistics and geographic information system (GIS) provided a detailed basis for spatial prediction of landslide hazard. The spatial prediction of landslide hazard in this paper is...

  9. The Determinants of VAT Introduction : A Spatial Duration Analysis

    NARCIS (Netherlands)

    Cizek, P.; Lei, J.; Ligthart, J.E.

    2012-01-01

    Abstract: The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. This specification relies highly on a pre-determinate covariance structure of the errors. However, the spatial effect may not only exist in the unobserved

  10. Relative risk of visceral leishmaniasis in Brazil: a spatial analysis in urban area.

    Directory of Open Access Journals (Sweden)

    Valdelaine Etelvina Miranda de Araújo

    2013-11-01

    Full Text Available BACKGROUND: Visceral leishmaniasis (VL is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission. METHODOLOGY: This is an ecological study on the relative risk of human VL. Spatial units of analysis were the coverage areas of the Basic Health Units (146 small-areas of Belo Horizonte, Minas Gerais State, Brazil. Human VL cases, from 2007 to 2009 (n = 412, were obtained in the Brazilian Reportable Disease Information System. Bayesian approach was used to model the relative risk of VL including potential risk factors involved in transmission (canine infection, socioeconomic and environmental features and to identify the small-areas of greater risk to human VL. PRINCIPAL FINDINGS: The relative risk of VL was shown to be correlated with income, education, and the number of infected dogs per inhabitants. The estimates of relative risk of VL were higher than 1.0 in 54% of the areas (79/146. The spatial modeling highlighted 14 areas with the highest relative risk of VL and 12 of them are concentrated in the northern region of the city. CONCLUSIONS: The spatial analysis used in this study is useful for the identification of small-areas according to risk of human VL and presents operational applicability in control and surveillance program in an urban environment with an unequal spatial distribution of the disease. Thus the frequent monitoring of relative risk of human VL in small-areas is important to direct and prioritize the actions of the control program in urban environment, especially in big cities.

  11. Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

    Science.gov (United States)

    Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

    2011-11-01

    The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

  12. Spatial correction factors for YALINA Booster facility loaded with medium and low enriched fuels

    International Nuclear Information System (INIS)

    Talamo, A.; Gohar, Y.; Bournos, V.; Fokov, Y.; Kiyavitskaya, H.; Routkovskaya, C.

    2012-01-01

    The Bell and Glasstone spatial correction factor is used in analyses of subcritical assemblies to correct the experimental reactivity as function of the detector position. Besides the detector position, several other parameters affect the correction factor: the energy weighting function of the detector, the detector size, the energy-angle distribution of source neutrons, and the reactivity of the subcritical assembly. This work focuses on the dependency of the correction factor on the detector material and it investigates the YALINA Booster subcritical assembly loaded with medium (36%) and low (10%) enriched fuels. (authors)

  13. Spatial correction factors for YALINA Booster facility loaded with medium and low enriched fuels

    Energy Technology Data Exchange (ETDEWEB)

    Talamo, A.; Gohar, Y. [Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439 (United States); Bournos, V.; Fokov, Y.; Kiyavitskaya, H.; Routkovskaya, C. [Joint Inst. for Power and Nuclear Research-Sosny, 99 Academician A.K.Krasin Str, Minsk 220109 (Belarus)

    2012-07-01

    The Bell and Glasstone spatial correction factor is used in analyses of subcritical assemblies to correct the experimental reactivity as function of the detector position. Besides the detector position, several other parameters affect the correction factor: the energy weighting function of the detector, the detector size, the energy-angle distribution of source neutrons, and the reactivity of the subcritical assembly. This work focuses on the dependency of the correction factor on the detector material and it investigates the YALINA Booster subcritical assembly loaded with medium (36%) and low (10%) enriched fuels. (authors)

  14. [Spatial pattern of forest biomass and its influencing factors in the Great Xing'an Mountains, Heilongjiang Province, China].

    Science.gov (United States)

    Wang, Xiao-Li; Chang, Yu; Chen, Hong-Wei; Hu, Yuan-Man; Jiao, Lin-Lin; Feng, Yu-Ting; Wu, Wen; Wu, Hai-Feng

    2014-04-01

    Based on field inventory data and vegetation index EVI (enhanced vegetation index), the spatial pattern of the forest biomass in the Great Xing'an Mountains, Heilongjiang Province was quantitatively analyzed. Using the spatial analysis and statistics tools in ArcGIS software, the impacts of climatic zone, elevation, slope, aspect and vegetation type on the spatial pattern of forest biomass were explored. The results showed that the forest biomass in the Great Xing'an Mountains was 350 Tg and spatially aggregated with great increasing potentials. Forest biomass density in the cold temperate humid zone (64.02 t x hm(-2)) was higher than that in the temperate humid zone (60.26 t x hm(-2)). The biomass density of each vegetation type was in the order of mixed coniferous forest (65.13 t x hm(-2)) > spruce-fir forest (63.92 t x hm(-2)) > Pinus pumila-Larix gmelinii forest (63.79 t x hm(-2)) > Pinus sylvestris var. mongolica forest (61.97 t x hm(-2)) > Larix gmelinii forest (61.40 t x hm(-2)) > deciduous broadleaf forest (58.96 t x hm(-2)). With the increasing elevation and slope, the forest biomass density first decreased and then increased. The forest biomass density in the shady slopes was greater than that in the sunny slopes. The spatial pattern of forest biomass in the Great Xing' an Mountains exhibited a heterogeneous pattern due to the variation of climatic zone, vegetation type and topographical factor. This spatial heterogeneity needs to be accounted when evaluating forest biomass at regional scales.

  15. Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

    Science.gov (United States)

    Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

    2016-02-01

    Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic

  16. Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

    Directory of Open Access Journals (Sweden)

    Qifang Bi

    2016-02-01

    Full Text Available Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98, type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00, and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00 exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a

  17. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    Directory of Open Access Journals (Sweden)

    Arnaud eDechesne

    2014-12-01

    Full Text Available Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays nonrandom spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH and some agricultural management practices (pesticide application, tillage, while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modelling and experimental systems that do not include soil’s full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil.

  18. A factor analysis to detect factors influencing building national brand

    Directory of Open Access Journals (Sweden)

    Naser Azad

    Full Text Available Developing a national brand is one of the most important issues for development of a brand. In this study, we present factor analysis to detect the most important factors in building a national brand. The proposed study uses factor analysis to extract the most influencing factors and the sample size has been chosen from two major auto makers in Iran called Iran Khodro and Saipa. The questionnaire was designed in Likert scale and distributed among 235 experts. Cronbach alpha is calculated as 84%, which is well above the minimum desirable limit of 0.70. The implementation of factor analysis provides six factors including “cultural image of customers”, “exciting characteristics”, “competitive pricing strategies”, “perception image” and “previous perceptions”.

  19. Factors Influencing the Spatial Difference in Household Energy Consumption in China

    Directory of Open Access Journals (Sweden)

    Yongxia Ding

    2016-12-01

    Full Text Available What factors determine the spatial heterogeneity of household energy consumption (HEC in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model and panel dataset for 30 provinces in China over the period 1997–2013, this paper investigated influences of the income per capita, urbanization level and annual average temperature on HEC, and revealed the spatial effects of these influencing factors. The results show that the income level is the main influencing factor, followed by the annual average temperature. There exists a diminishing marginal contribution with increasing income. The influence of urbanization level varies according to income level. In addition, from the eastern region to western region of China, variances largely depend upon economic level at the provincial level. From the northern region to southern region, change is mainly caused by temperature. The urbanization level has more significant impact on the structure and efficiency of household energy consumption than on its quantity. These results could provide reference for policy making and energy planning.

  20. Spatial distribution of, and risk factors for, Opisthorchis viverrini infection in southern Lao PDR.

    Directory of Open Access Journals (Sweden)

    Armelle Forrer

    Full Text Available BACKGROUND: Opisthorchis viverrini is a food-borne trematode species that might give rise to biliary diseases and the fatal cholangiocarcinoma. In Lao PDR, an estimated 2.5 million individuals are infected with O. viverrini, but epidemiological studies are scarce and the spatial distribution of infection remains to be determined. Our aim was to map the distribution of O. viverrini in southern Lao PDR, identify underlying risk factors, and predict the prevalence of O. viverrini at non-surveyed locations. METHODOLOGY: A cross-sectional parasitological and questionnaire survey was carried out in 51 villages in Champasack province in the first half of 2007. Data on demography, socioeconomic status, water supply, sanitation, and behavior were combined with remotely sensed environmental data and fed into a geographical information system. Bayesian geostatistical models were employed to identify risk factors and to investigate the spatial pattern of O. viverrini infection. Bayesian kriging was utilized to predict infection risk at non-surveyed locations. PRINCIPAL FINDINGS: The prevalence of O. viverrini among 3,371 study participants with complete data records was 61.1%. Geostatistical models identified age, Lao Loum ethnic group, educational attainment, occupation (i.e., rice farmer, fisherman, and animal breeder, and unsafe drinking water source as risk factors for infection. History of praziquantel treatment, access to sanitation, and distance to freshwater bodies were found to be protective factors. Spatial patterns of O. viverrini were mainly governed by environmental factors with predictive modeling identifying two different risk profiles: low risk of O. viverrini in the mountains and high risk in the Mekong corridor. CONCLUSIONS/SIGNIFICANCE: We present the first risk map of O. viverrini infection in Champasack province, which is important for spatial targeting of control efforts. Infection with O. viverrini appears to be strongly associated

  1. Principal factors of soil spatial heterogeneity and ecosystem services at the Central Chernozemic Region of Russia

    Science.gov (United States)

    Vasenev, Ivan; Valentini, Riccardo

    2013-04-01

    The essential spatial heterogeneity is mutual feature for most natural and man-changed soils at the Central Chernozemic Region of Russia which is not only one of the biggest «food baskets» in RF but very important regulator of ecosystem principal services at the European territory of Russia. The original spatial heterogeneity of dominated here forest-steppe and steppe Chernozems and the other soils has been further complicated by a specific land-use history and different-direction soil successions due to environmental changes and more than 1000-year history of human impacts. The carried out long-term researches of representative natural, rural and urban landscapes in Kursk, Orel, Tambov and Voronezh oblasts give us the regional multi-factorial matrix of elementary soil cover patterns (ESCP) with different land-use practices and history, soil-geomorphologic features, environmental and microclimate conditions. The validation and ranging of the limiting factors of ESCP regulation and development, ecosystem principal services, land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of regional and local GIS, soil spatial patterns mapping, traditional regression kriging, correlation tree models. The outcomes of statistical modeling show the essential amplification of erosion, dehumification and CO2 emission, acidification and alkalization, disaggregation and overcompaction processes due to violation of agroecologically sound land-use systems and traditional balances of organic matter, nutrients, Ca and Na in agrolandscapes. Due to long-term intensive and out-of-balance land-use practices the famous Russian Chernozems begin to lose not only their unique natural features of (around 1 m of humus horizon, 4-6% of Corg and favorable agrophysical features), but traditional soil cover patterns, ecosystem services and agroecological functions. Key-site monitoring

  2. Study of academic achievements using spatial analysis tools

    Science.gov (United States)

    González, C.; Velilla, C.; Sánchez-Girón, V.

    2012-04-01

    In the 2010/12 academic year the College of Agricultural Engineering of the Technical University of Madrid implemented three new degrees all of them adapted to the European Space for Higher Education. These degrees are namely: Graduate in Agricultural Engineering and Science, Graduate in Food Engineering and Graduate in Agro-Environmental Engineering. A total of 382 new incoming students were finally registered and a survey study was carried out with these students about their academic achievement with the aim of finding the level of dependence among the following variables: the final mark in their secondary studies, the option followed in the secondary studies (Art, Science and Technology, and Humanities and Social Sciences), the mark obtained in the entering examination to the university and in which of the two opportunities per year this examination takes place the latter mark was obtained. Similarly, another group of 77 students were evaluated independently to the former group. These students were those entering the College in the previous academic year (2009/10) and decided to change their curricula to the new ones. Subsequently, using the tools of spatial analysis of geographic information systems, we analyzed the possible relationship between the success or failure at school and the socioeconomic profile of new students in a grade. For this purpose every student was referenced assigning UTM coordinates to their postal addresses. Furthermore, all students' secondary schools were geographically coded considering their typology (public, private, and private subsidized) and fares. Each student was represented by its average geometric point in order to be correlated to their respective record. Following this procedure a map of the performance of each student could be drawn. This map can be used as a reference system, as it includes variables as the distance from the student home to the College, that can be used as a tool to calculate the probability of success or

  3. Tucker Tensor analysis of Matern functions in spatial statistics

    KAUST Repository

    Litvinenko, Alexander

    2018-03-09

    In this work, we describe advanced numerical tools for working with multivariate functions and for the analysis of large data sets. These tools will drastically reduce the required computing time and the storage cost, and, therefore, will allow us to consider much larger data sets or finer meshes. Covariance matrices are crucial in spatio-temporal statistical tasks, but are often very expensive to compute and store, especially in 3D. Therefore, we approximate covariance functions by cheap surrogates in a low-rank tensor format. We apply the Tucker and canonical tensor decompositions to a family of Matern- and Slater-type functions with varying parameters and demonstrate numerically that their approximations exhibit exponentially fast convergence. We prove the exponential convergence of the Tucker and canonical approximations in tensor rank parameters. Several statistical operations are performed in this low-rank tensor format, including evaluating the conditional covariance matrix, spatially averaged estimation variance, computing a quadratic form, determinant, trace, loglikelihood, inverse, and Cholesky decomposition of a large covariance matrix. Low-rank tensor approximations reduce the computing and storage costs essentially. For example, the storage cost is reduced from an exponential O(n^d) to a linear scaling O(drn), where d is the spatial dimension, n is the number of mesh points in one direction, and r is the tensor rank. Prerequisites for applicability of the proposed techniques are the assumptions that the data, locations, and measurements lie on a tensor (axes-parallel) grid and that the covariance function depends on a distance, ||x-y||.

  4. The Infinitesimal Jackknife with Exploratory Factor Analysis

    Science.gov (United States)

    Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

    2012-01-01

    The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

  5. The spatial analysis on hemorrhagic fever with renal syndrome in Jiangsu province, China based on geographic information system.

    Directory of Open Access Journals (Sweden)

    Changjun Bao

    Full Text Available Hemorrhagic fever with renal syndrome (HFRS is endemic in mainland China, accounting for 90% of total reported cases worldwide, and Jiangsu is one of the most severely affected provinces. In this study, the authors conducted GIS-based spatial analyses in order to determine the spatial distribution of the HFRS cases, identify key areas and explore risk factors for public health planning and resource allocation.Interpolation maps by inverse distance weighting were produced to detect the spatial distribution of HFRS cases in Jiangsu from 2001 to 2011. Spatio-temporal clustering was applied to identify clusters at the county level. Spatial correlation analysis was conducted to detect influencing factors of HFRS in Jiangsu.HFRS cases in Jiangsu from 2001 to 2011 were mapped and the results suggested that cases in Jiangsu were not distributed randomly. Cases were mainly distributed in northeastern and southwestern Jiangsu, especially in Dafeng and Sihong counties. It was notable that prior to this study, Sihong county had rarely been reported as a high-risk area of HFRS. With the maximum spatial size of 50% of the total population and the maximum temporal size of 50% of the total population, spatio-temporal clustering showed that there was one most likely cluster (LLR = 624.52, P<0.0001, RR = 8.19 and one second-most likely cluster (LLR = 553.97, P<0.0001, RR = 8.25, and both of these clusters appeared from 2001 to 2004. Spatial correlation analysis showed that the incidence of HFRS in Jiangsu was influenced by distances to highways, railways, rivers and lakes.The application of GIS together with spatial interpolation, spatio-temporal clustering and spatial correlation analysis can effectively identify high-risk areas and factors influencing HFRS incidence to lay a foundation for researching its pathogenesis.

  6. Persistent solar signatures in cloud cover: spatial and temporal analysis

    International Nuclear Information System (INIS)

    Voiculescu, M; Usoskin, I

    2012-01-01

    A consensus regarding the impact of solar variability on cloud cover is far from being reached. Moreover, the impact of cloud cover on climate is among the least understood of all climate components. This motivated us to analyze the persistence of solar signals in cloud cover for the time interval 1984–2009, covering two full solar cycles. A spatial and temporal investigation of the response of low, middle and high cloud data to cosmic ray induced ionization (CRII) and UV irradiance (UVI) is performed in terms of coherence analysis of the two signals. For some key geographical regions the response of clouds to UVI and CRII is persistent over the entire time interval indicating a real link. In other regions, however, the relation is not consistent, being intermittent or out of phase, suggesting that some correlations are spurious. The constant in phase or anti-phase relationship between clouds and solar proxies over some regions, especially for low clouds with UVI and CRII, middle clouds with UVI and high clouds with CRII, definitely requires more study. Our results show that solar signatures in cloud cover persist in some key climate-defining regions for the entire time period and supports the idea that, if existing, solar effects are not visible at the global level and any analysis of solar effects on cloud cover (and, consequently, on climate) should be done at the regional level. (letter)

  7. Signal Adaptive System for Space/Spatial-Frequency Analysis

    Directory of Open Access Journals (Sweden)

    Veselin N. Ivanović

    2009-01-01

    Full Text Available This paper outlines the development of a multiple-clock-cycle implementation (MCI of a signal adaptive two-dimensional (2D system for space/spatial-frequency (S/SF signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA circuit design, capable of performing S/SF analysis of 2D signals in real time.

  8. Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search.

    Science.gov (United States)

    Mena, Carlos; Sepúlveda, Cesar; Fuentes, Eduardo; Ormazábal, Yony; Palomo, Iván

    2018-05-07

    Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (e.g., rural, deprived neighbourhoods, etc.), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.

  9. Research on the Spatial Differentiation and Driving Factors of Tourism Enterprises’ Efficiency: Chinese Scenic Spots, Travel Agencies, and Hotels

    Directory of Open Access Journals (Sweden)

    Bing Xia

    2018-03-01

    Full Text Available Tourism is an important sustainable industry in the economy that optimizes the industrial structure. Thus, as a core part of this market, tourism enterprises perform a key role in the effective operation of this industry. This paper applies data envelopment analysis (DEA and Malmquist index (MI models to calculate the efficiency of Chinese tourism enterprises between 2005 and 2014. Results showed that: (1 The efficiency and the total factor productivity change index (TFPC of tourism enterprises remained low, and both have decreased. (2 The efficiency of regional tourism enterprises across China cloud be characterized as high in the east region, low in the central region, and high in both northeast and western regions. (3 The efficiency levels of the cities of Beijing and Shanghai were ahead of the country over the period of this study, while Chongqing, Tibet, Qinghai, and Ningxia all possess a number of obvious advantages in the western region. (4 Centers of overall tourism enterprise efficiency mainly moved in a southeast-to-northwest direction over the period of this research. (5 The spatial autocorrelation of tourism enterprise efficiencies is also assessed in this study, and the results show that the comprehensive efficiency (CE of tourism enterprises in southeastern coastal regions of China tended to a certain spatial agglomeration effect, while the correlation between the central region and northern China was not significant. (6 The Geodetector model is applied to analyze the key factors driving the spatial differentiation of tourism enterprise efficiencies, and the results show that the degree of opening to the outside world, potential human capital, and traffic conditions were the most important factors driving spatial differentiation in the efficiency of tourism enterprises.

  10. Fast Transient And Spatially Non-Homogenous Accident Analysis Of Two-Dimensional Cylindrical Nuclear Reactor

    International Nuclear Information System (INIS)

    Yulianti, Yanti; Su'ud, Zaki; Waris, Abdul; Khotimah, S. N.; Shafii, M. Ali

    2010-01-01

    The research about fast transient and spatially non-homogenous nuclear reactor accident analysis of two-dimensional nuclear reactor has been done. This research is about prediction of reactor behavior is during accident. In the present study, space-time diffusion equation is solved by using direct methods which consider spatial factor in detail during nuclear reactor accident simulation. Set of equations that obtained from full implicit finite-difference discretization method is solved by using iterative methods ADI (Alternating Direct Implicit). The indication of accident is decreasing macroscopic absorption cross-section that results large external reactivity. The power reactor has a peak value before reactor has new balance condition. Changing of temperature reactor produce a negative Doppler feedback reactivity. The reactivity will reduce excess positive reactivity. Temperature reactor during accident is still in below fuel melting point which is in secure condition.

  11. Temporal and spatial distribution characteristics and influencing factors of air quality index in Xuchang

    Science.gov (United States)

    Wang, Zhenghua; Tian, Zhihui

    2018-01-01

    In recent years, the problem of air pollution becomes more and more serious. Based on the geographic and seasonal climatic characteristics of Xuchang City, this paper studies the temporal and spatial distribution characteristics of air quality index. The results show that: from the time point of view, air quality index shows seasonal difference. Air quality index is highest in winter and is lowest in summer. From the space point of view, there are differences between the north and the south to a certain extent. Changge City, Yuzhou city and central Xuchang county is higher than the southeast of Xiangcheng county and Yanling county. The spatial and temporal variation characteristics of air quality index in Xuchang are influenced by natural factors and human activities, and the economic development and population are the important factors affecting the urban air quality.

  12. Spatial Distribution Analysis of Scrub Typhus in Korea

    OpenAIRE

    Jin, Hong Sung; Chu, Chaeshin; Han, Dong Yeob

    2013-01-01

    Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does...

  13. Spatial and temporal analysis of lake sedimentation under reforestation

    Directory of Open Access Journals (Sweden)

    C.M. Pilgrim

    2015-10-01

    Full Text Available Spatial and temporal land cover changes can reduce or accelerate lake sedimentation. This study was conducted to examine morphometry and bathymetry, and the long-term changes (over 75 years in sedimentation in the Lake Issaqueena reservoir, South Carolina. The watershed and catchment areas were delineated using Light Detection and Ranging (LiDAR based data. Trends in lake surface area and riparian buffer condition (vegetated or unvegetated were determined from historical aerial photography. From 1938 to 2009, the lake experienced a decrease in surface area of approximately 11.33 ha while catchment area increased by 6.99 ha, and lake volume decreased by 320,800.00 m3. Lake surface area decreased in years corresponding to equal coverage or largely unvegetated riparian buffers. Surface area and average annual precipitation were not correlated; therefore other factors such as soil type, riparian buffer condition and changes in land use likely contributed to sedimentation. Shift from agricultural land to forestland in this watershed resulted in a decrease in sedimentation rates by 88.28%. Keywords: Bathymetry, Erosion, Geographic Information Systems (GIS, Land cover, Riparian buffer, Soils

  14. Risk factors for spatial memory impairment in patients with temporal lobe epilepsy

    Czech Academy of Sciences Publication Activity Database

    Amlerová, J.; Laczó, J.; Vlček, Kamil; Javůrková, A.; Andel, R.; Marusič, P.

    2013-01-01

    Roč. 26, č. 1 (2013), s. 57-60 ISSN 1525-5050 R&D Projects: GA ČR(CZ) GA309/09/1053 Grant - others:GA MŠk(CZ) ED1.100/02/0123 Institutional research plan: CEZ:AV0Z50110509 Institutional support: RVO:67985823 Keywords : spatial navigation * temporal lobe epilepsy * Morris water maze Subject RIV: FH - Neurology Impact factor: 2.061, year: 2013

  15. Meta-analysis of field scale spatial variability of grassland soil CO2 efflux: Interaction of biotic and abiotic drivers

    Czech Academy of Sciences Publication Activity Database

    Fóti, S.; Balogh, J.; Herbst, M.; Papp, M.; Koncz, P.; Bartha, S.; Zimmermann, Z.; Komoly, C.; Szabó, G.; Margóczi, G.; Acosta, Manuel; Nagy, Z.

    2016-01-01

    Roč. 143, aug (2016), s. 78-89 ISSN 0341-8162 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : Cross-variogram * Principal component analysis * Soil CO2 efflux * Spatial pattern * Variogram Subject RIV: EH - Ecology, Behaviour Impact factor: 3.191, year: 2016

  16. Procedural Factors That Affect Psychophysical Measures of Spatial Selectivity in Cochlear Implant Users

    Directory of Open Access Journals (Sweden)

    Stefano Cosentino

    2015-09-01

    Full Text Available Behavioral measures of spatial selectivity in cochlear implants are important both for guiding the programing of individual users’ implants and for the evaluation of different stimulation methods. However, the methods used are subject to a number of confounding factors that can contaminate estimates of spatial selectivity. These factors include off-site listening, charge interactions between masker and probe pulses in interleaved masking paradigms, and confusion effects in forward masking. We review the effects of these confounds and discuss methods for minimizing them. We describe one such method in which the level of a 125-pps masker is adjusted so as to mask a 125-pps probe, and where the masker and probe pulses are temporally interleaved. Five experiments describe the method and evaluate the potential roles of the different potential confounding factors. No evidence was obtained for off-site listening of the type observed in acoustic hearing. The choice of the masking paradigm was shown to alter the measured spatial selectivity. For short gaps between masker and probe pulses, both facilitation and refractory mechanisms had an effect on masking; this finding should inform the choice of stimulation rate in interleaved masking experiments. No evidence for confusion effects in forward masking was revealed. It is concluded that the proposed method avoids many potential confounds but that the choice of method should depend on the research question under investigation.

  17. A book review of Spatial data analysis in ecology and agriculture using R

    Science.gov (United States)

    Spatial Data Analysis in Ecology and Agriculture Using R is a valuable resource to assist agricultural and ecological researchers with spatial data analyses using the R statistical software(www.r-project.org). Special emphasis is on spatial data sets; how-ever, the text also provides ample guidance ...

  18. Analysis of Spatial Voting Patterns: An Approach in Political Socialization

    Science.gov (United States)

    Klimasewski, Ted

    1973-01-01

    Passage of the 26th Amendment gave young adults the right to vote. This study attempts to further student understanding of the electoral process by presenting a method for analyzing spatial voting patterns. The spatial emphasis adds another dimension to the temporal and behavioral-structural approaches in studying the American electoral system.…

  19. Fractal Dimension analysis for seismicity spatial and temporal ...

    Indian Academy of Sciences (India)

    23

    The research can further promote the application of fractal theory in the study ... spatial-temporal propagation characteristics of seismic activities, fractal theory is not ... provide a theoretical basis for the prevention and control of earthquakes. 2. ... random self-similar structure of the earthquake in the time series and the spatial.

  20. using gis for spatial exploratory analysis of borehole data

    African Journals Online (AJOL)

    PUBLICATIONS1

    Thus, understanding the spatial structure of aquifer characteristics could be used as a resourceful tool and as a .... x is position in one dimensional space. N(h) is Pairwise ... best fitted theoretical models, the spatial struc- ture of each variable ...

  1. A Principal Components Analysis of Dynamic Spatial Memory Biases

    Science.gov (United States)

    Motes, Michael A.; Hubbard, Timothy L.; Courtney, Jon R.; Rypma, Bart

    2008-01-01

    Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed…

  2. LABOUR INPUT IN POLISH AGRICULTURE AGAINST SIZE OF AGRICULTURAL HOLDINGS – SPATIAL ANALYSIS*

    Directory of Open Access Journals (Sweden)

    Łukasz Wiśniewski

    2016-09-01

    Full Text Available The aim of this paper is to present the analysis of spatial diversifi cation in the labour input in agriculture on the basis of these selected indicators: annual work unit (AWU per 100 ha agricultural acreage; number of people per AWU; and comparison of labour input to EU-15 standards (LI-EU. Agricultural holdings have been categorised by size into three groups: 0–10 ha (small, 10–20 ha (average, and over 20 ha (large. Labour resources were subject to a comparative study of the density rates of AWUs per 100 ha agricultural acreage in Poland and the EU (EU-15. The analysis covered all of Poland with consideration of the administrative division into sixteen voivodeships (tabular analysis and 314 poviats (townships and country districts together, including regional offi ces of the Agency for Restructuring and Modernisation of Agriculture (ARiMR; cartographic analysis. The results of the Agricultural Census of 2010 were used in the study. It demonstrated a signifi cant spatial diversifi cation in labour input in agriculture in general and in each holding size group. Predominantly, the diff erences are related to historical and political factors. The analysis corroborated agrarian overpopulation in south-east Poland.

  3. Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis

    Science.gov (United States)

    Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Jiang, Baofa

    2016-01-01

    The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77–7.61), diarrhea (OR = 2.16, 95% CI = 1.24–3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04–35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region. PMID:26903612

  4. Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

    Directory of Open Access Journals (Sweden)

    S. Gaitan

    2015-06-01

    Full Text Available Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

  5. Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

    Science.gov (United States)

    Gaitan, S.; ten Veldhuis, J. A. E.

    2015-06-01

    Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

  6. Spatial Characterization of Landscapes through Multifractal Analysis of DEM

    Directory of Open Access Journals (Sweden)

    P. L. Aguado

    2014-01-01

    Full Text Available Landscape evolution is driven by abiotic, biotic, and anthropic factors. The interactions among these factors and their influence at different scales create a complex dynamic. Landscapes have been shown to exhibit numerous scaling laws, from Horton’s laws to more sophisticated scaling of heights in topography and river network topology. This scaling and multiscaling analysis has the potential to characterise the landscape in terms of the statistical signature of the measure selected. The study zone is a matrix obtained from a digital elevation model (DEM (map 10 × 10 m, and height 1 m that corresponds to homogeneous region with respect to soil characteristics and climatology known as “Monte El Pardo” although the water level of a reservoir and the topography play a main role on its organization and evolution. We have investigated whether the multifractal analysis of a DEM shows common features that can be used to reveal the underlying patterns and information associated with the landscape of the DEM mapping and studied the influence of the water level of the reservoir on the applied analysis. The results show that the use of the multifractal approach with mean absolute gradient data is a useful tool for analysing the topography represented by the DEM.

  7. Analysis of Bernstein's factorization circuit

    NARCIS (Netherlands)

    Lenstra, A.K.; Shamir, A.; Tomlinson, J.; Tromer, E.; Zheng, Y.

    2002-01-01

    In [1], Bernstein proposed a circuit-based implementation of the matrix step of the number field sieve factorization algorithm. These circuits offer an asymptotic cost reduction under the measure "construction cost x run time". We evaluate the cost of these circuits, in agreement with [1], but argue

  8. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Science.gov (United States)

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

  9. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Directory of Open Access Journals (Sweden)

    Hongoh Valerie

    2011-12-01

    Full Text Available Abstract The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector

  10. Risk factors for spatial memory impairment in patients with temporal lobe epilepsy.

    Science.gov (United States)

    Amlerova, Jana; Laczo, Jan; Vlcek, Kamil; Javurkova, Alena; Andel, Ross; Marusic, Petr

    2013-01-01

    At present, the risk factors for world-centered (allocentric) navigation impairment in patients with temporal lobe epilepsy (TLE) are not known. There is some evidence on the importance of the right hippocampus but other clinical features have not been investigated yet. In this study, we used an experimental human equivalent to the Morris water maze to examine spatial navigation performance in patients with drug-refractory unilateral TLE. We included 47 left-hemisphere speech dominant patients (25 right sided; 22 left sided). The aim of our study was to identify clinical and demographic characteristics of TLE patients who performed poorly in allocentric spatial memory tests. Our results demonstrate that poor spatial navigation is significantly associated with younger age at epilepsy onset, longer disease duration, and lower intelligence level. Allocentric navigation in TLE patients was impaired irrespective of epilepsy lateralization. Good and poor navigators did not differ in their age, gender, or preoperative/postoperative status. This study provides evidence on risk factors that increase the likelihood of allocentric navigation impairment in TLE patients. The results indicate that not only temporal lobe dysfunction itself but also low general cognitive abilities may contribute to the navigation impairment. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Impact of the neutron detector choice on Bell and Glasstone spatial correction factor for subcriticality measurement

    Energy Technology Data Exchange (ETDEWEB)

    Talamo, Alberto, E-mail: alby@anl.gov [Argonne National Laboratory, 9700S. Cass Avenue, Argonne, IL 60439 (United States); Gohar, Y.; Cao, Y.; Zhong, Z. [Argonne National Laboratory, 9700S. Cass Avenue, Argonne, IL 60439 (United States); Kiyavitskaya, H.; Bournos, V.; Fokov, Y.; Routkovskaya, C. [Joint Institute for Power and Nuclear Research-Sosny, National Academy of Sciences of Belarus, 99 acad. Krasin str., Minsk 220109 (Belarus)

    2012-03-11

    In subcritical assemblies, the Bell and Glasstone spatial correction factor is used to correct the measured reactivity from different detector positions. In addition to the measuring position, several other parameters affect the correction factor: the detector material, the detector size, and the energy-angle distribution of source neutrons. The effective multiplication factor calculated by computer codes in criticality mode slightly differs from the average value obtained from the measurements in the different experimental channels of the subcritical assembly, which are corrected by the Bell and Glasstone spatial correction factor. Generally, this difference is due to (1) neutron counting errors; (2) geometrical imperfections, which are not simulated in the calculational model, and (3) quantities and distributions of material impurities, which are missing from the material definitions. This work examines these issues and it focuses on the detector choice and the calculation methodologies. The work investigated the YALINA Booster subcritical assembly of Belarus, which has been operated with three different fuel enrichments in the fast zone either: high (90%) and medium (36%), medium (36%), or low (21%) enriched uranium fuel.

  12. Impact of the neutron detector choice on Bell and Glasstone spatial correction factor for subcriticality measurement

    International Nuclear Information System (INIS)

    Talamo, Alberto; Gohar, Y.; Cao, Y.; Zhong, Z.; Kiyavitskaya, H.; Bournos, V.; Fokov, Y.; Routkovskaya, C.

    2012-01-01

    In subcritical assemblies, the Bell and Glasstone spatial correction factor is used to correct the measured reactivity from different detector positions. In addition to the measuring position, several other parameters affect the correction factor: the detector material, the detector size, and the energy-angle distribution of source neutrons. The effective multiplication factor calculated by computer codes in criticality mode slightly differs from the average value obtained from the measurements in the different experimental channels of the subcritical assembly, which are corrected by the Bell and Glasstone spatial correction factor. Generally, this difference is due to (1) neutron counting errors; (2) geometrical imperfections, which are not simulated in the calculational model, and (3) quantities and distributions of material impurities, which are missing from the material definitions. This work examines these issues and it focuses on the detector choice and the calculation methodologies. The work investigated the YALINA Booster subcritical assembly of Belarus, which has been operated with three different fuel enrichments in the fast zone either: high (90%) and medium (36%), medium (36%), or low (21%) enriched uranium fuel.

  13. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Badawi, N.; Aamand, Jens

    2014-01-01

    across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance......Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we...... critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates...

  14. Estimation of spatial distribution of recharge factors at Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Stothoff, S.A.; Bagtzoglou, A.C.; Castellaw, H.

    1995-01-01

    Determining compliance with the performance objectives for both the repository system and the Geologic Setting (GS) requires prediction of groundwater flow. Since infiltration is the primary source of water in the subsurface, the amounts and locations of infiltration are controlling factors in the movement of groundwater throughout the GS. In fractured, unsaturated rock, such as that found at the Yucca Mountain (YM) site, occurrence of infrequent, high-intensity rainfall events will modify, perhaps drastically, the subsurface flow regime from the one predicted by assuming that all rainfall events have averaged intensities. Indeed, the DOW has concluded that the spatial and temporal distribution of infiltration may be the most important factors influencing groundwater flow path development. Deep percolation fluxes are affected by processes active in the near-surface zone, including evaporation, transpiration, liquid water flow, and vapor flow. Each of these processes is governed by several factors. For example, precipitation has been found to vary substantially over the YM region, both spatially and temporally, and winter storms are, in general, more uniform and of longer duration than summer storms (Hevesi et al., 1992a,b; 1994). These observations indicate that, especially for summer storms, a spatially uniform precipitation pattern is clearly not applicable, even at the subregional scale. Similarly, evaporation from the ground surface is affected by air temperature, atmospheric vapor pressure, wind speed profile, incident solar radiation, surface soil and rock texture, plant activity, surficial temperature, and surficial moisture content. Many of these factors, such as surficial slope and orientation (related to incident solar radiation), surficial composition, and plant distributions, are or can be mapped at the YM site

  15. Spatial Data Envelopment Analysis Method for the Evaluation of Regional Infrastructure Disparities

    Directory of Open Access Journals (Sweden)

    Birutė Galinienė

    2012-12-01

    Full Text Available Purpose—to achieve a more detailed assessment of regional differences, exploring regional infrastructure and human capital usage efficiency and to display analysis capabilities of spatial data efficient frontier method.Design/methodology/approach—the data envelopment analysis (DEA is applied to find the efficient frontier, which extends the application of production function of the regions. This method of mathematical programming optimization allows assessing the effectiveness of the regional spatial aspects presented. In recent studies this method is applied for evaluating the European Union regional policy issues.Findings—the application of DEA reveals its feasibility for regional input and output studies to evaluate more detailed and more reasonable fund allocation between Lithuanian regions. This analysis shows that in the comparatively efficient Lithuanian regions, such as Vilnius and Klaipėda, “the bottleneck” of usage of transport infrastructure and regional specific human capital is reached. It is stated that decision-making units could enhance region attractiveness for private investors by improving indirect factors in these regions. For practical significance of the study the results are compared with German regional analysis, conducted by Schaffer and other researchers (2011.Practical implications—the practical value of this work is based on giving more accurate planning tools for fund allocation decisions in Lithuanian regions while planning infrastructure and human capital development. The regional indicators were analyzed for 2010.Research type—case study.

  16. Capacity analysis of spectrum sharing spatial multiplexing MIMO systems

    KAUST Repository

    Yang, Liang; Qaraqe, Khalid A.; Serpedin, Erchin; Alouini, Mohamed-Slim

    2014-01-01

    This paper considers a spectrum sharing (SS) multiple-input multiple-output (MIMO) system operating in a Rayleigh fading environment. First the capacity of a single-user SS spatial multiplexing system is investigated in two scenarios that assume

  17. A preliminary survey and analysis of the spatial distribution of ...

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River ... of taxa was recorded in marginal vegetation in the channels and lagoons, ... highlights the importance of maintaining a mosaic of aquatic habitats in the Delta.

  18. A preliminary survey and analysis of the spatial distribution of ...

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River Delta, ... seasonally-flooded pools and temporary rain-filled pools in MGR and CI. ... biodiversity of the Okavango Delta, thereby contributing to its conservation.

  19. Spatial analysis based on variance of moving window averages

    OpenAIRE

    Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J

    2006-01-01

    A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...

  20. European regional efficiency and geographical externalities: a spatial nonparametric frontier analysis

    Science.gov (United States)

    Ramajo, Julián; Cordero, José Manuel; Márquez, Miguel Ángel

    2017-10-01

    This paper analyses region-level technical efficiency in nine European countries over the 1995-2007 period. We propose the application of a nonparametric conditional frontier approach to account for the presence of heterogeneous conditions in the form of geographical externalities. Such environmental factors are beyond the control of regional authorities, but may affect the production function. Therefore, they need to be considered in the frontier estimation. Specifically, a spatial autoregressive term is included as an external conditioning factor in a robust order- m model. Thus we can test the hypothesis of non-separability (the external factor impacts both the input-output space and the distribution of efficiencies), demonstrating the existence of significant global interregional spillovers into the production process. Our findings show that geographical externalities affect both the frontier level and the probability of being more or less efficient. Specifically, the results support the fact that the spatial lag variable has an inverted U-shaped non-linear impact on the performance of regions. This finding can be interpreted as a differential effect of interregional spillovers depending on the size of the neighboring economies: positive externalities for small values, possibly related to agglomeration economies, and negative externalities for high values, indicating the possibility of production congestion. Additionally, evidence of the existence of a strong geographic pattern of European regional efficiency is reported and the levels of technical efficiency are acknowledged to have converged during the period under analysis.

  1. Remote sensing and spatial analysis based study for detecting deforestation and the associated drivers

    Science.gov (United States)

    El-Abbas, Mustafa M.; Csaplovics, Elmar; Deafalla, Taisser H.

    2013-10-01

    Nowadays, remote-sensing technologies are becoming increasingly interlinked to the issue of deforestation. They offer a systematized and objective strategy to document, understand and simulate the deforestation process and its associated causes. In this context, the main goal of this study, conducted in the Blue Nile region of Sudan, in which most of the natural habitats were dramatically destroyed, was to develop spatial methodologies to assess the deforestation dynamics and its associated factors. To achieve that, optical multispectral satellite scenes (i.e., ASTER and LANDSAT) integrated with field survey in addition to multiple data sources were used for the analyses. Spatiotemporal Object Based Image Analysis (STOBIA) was applied to assess the change dynamics within the period of study. Broadly, the above mentioned analyses include; Object Based (OB) classifications, post-classification change detection, data fusion, information extraction and spatial analysis. Hierarchical multi-scale segmentation thresholds were applied and each class was delimited with semantic meanings by a set of rules associated with membership functions. Consequently, the fused multi-temporal data were introduced to create detailed objects of change classes from the input LU/LC classes. The dynamic changes were quantified and spatially located as well as the spatial and contextual relations from adjacent areas were analyzed. The main finding of the present study is that, the forest areas were drastically decreased, while the agrarian structure in conversion of forest into agricultural fields and grassland was the main force of deforestation. In contrast, the capability of the area to recover was clearly observed. The study concludes with a brief assessment of an 'oriented' framework, focused on the alarming areas where serious dynamics are located and where urgent plans and interventions are most critical, guided with potential solutions based on the identified driving forces.

  2. Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

    Science.gov (United States)

    Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

    2016-04-01

    Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under

  3. Experimental study on the crack detection with optimized spatial wavelet analysis and windowing

    Science.gov (United States)

    Ghanbari Mardasi, Amir; Wu, Nan; Wu, Christine

    2018-05-01

    In this paper, a high sensitive crack detection is experimentally realized and presented on a beam under certain deflection by optimizing spatial wavelet analysis. Due to the crack existence in the beam structure, a perturbation/slop singularity is induced in the deflection profile. Spatial wavelet transformation works as a magnifier to amplify the small perturbation signal at the crack location to detect and localize the damage. The profile of a deflected aluminum cantilever beam is obtained for both intact and cracked beams by a high resolution laser profile sensor. Gabor wavelet transformation is applied on the subtraction of intact and cracked data sets. To improve detection sensitivity, scale factor in spatial wavelet transformation and the transformation repeat times are optimized. Furthermore, to detect the possible crack close to the measurement boundaries, wavelet transformation edge effect, which induces large values of wavelet coefficient around the measurement boundaries, is efficiently reduced by introducing different windowing functions. The result shows that a small crack with depth of less than 10% of the beam height can be localized with a clear perturbation. Moreover, the perturbation caused by a crack at 0.85 mm away from one end of the measurement range, which is covered by wavelet transform edge effect, emerges by applying proper window functions.

  4. High resolution or optimum resolution? Spatial analysis of the Federmesser site at Andernach, Germany

    NARCIS (Netherlands)

    Stapert, D; Street, M

    1997-01-01

    This paper discusses spatial analysis at site level. It is suggested that spatial analysis has to proceed in several levels, from global to more detailed questions, and that optimum resolution should be established when applying any quantitative methods in this field. As an example, the ring and

  5. Comparative analysis of time efficiency and spatial resolution between different EIT reconstruction algorithms

    International Nuclear Information System (INIS)

    Kacarska, Marija; Loskovska, Suzana

    2002-01-01

    In this paper comparative analysis between different EIT algorithms is presented. Analysis is made for spatial and temporal resolution of obtained images by several different algorithms. Discussions consider spatial resolution dependent on data acquisition method, too. Obtained results show that conventional applied-current EIT is more powerful compared to induced-current EIT. (Author)

  6. Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis

    Directory of Open Access Journals (Sweden)

    Sartorius Benn KD

    2011-11-01

    antenatal HIV sero-prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively. Conclusions This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The "novel" integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the "high impact" factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas.

  7. Reduction of spatial distribution of risk factors for transportation of contaminants released by coal mining activities.

    Science.gov (United States)

    Karan, Shivesh Kishore; Samadder, Sukha Ranjan

    2016-09-15

    It is reported that water-energy nexus composes two of the biggest development and human health challenges. In the present study we presented a Risk Potential Index (RPI) model which encapsulates Source, Vector (Transport), and Target risks for forecasting surface water contamination. The main aim of the model is to identify critical surface water risk zones for an open cast mining environment, taking Jharia Coalfield, India as the study area. The model also helps in feasible sampling design. Based on spatial analysis various risk zones were successfully delineated. Monthly RPI distribution revealed that the risk of surface water contamination was highest during the monsoon months. Surface water samples were analysed to validate the model. A GIS based alternative management option was proposed to reduce surface water contamination risk and observed 96% and 86% decrease in the spatial distribution of very high risk areas for the months June and July respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Spatial analysis of elderly access to primary care services

    Directory of Open Access Journals (Sweden)

    Lozano-Gracia Nancy

    2006-05-01

    Full Text Available Abstract Background Admissions for Ambulatory Care Sensitive Conditions (ACSCs are considered preventable admissions, because they are unlikely to occur when good preventive health care is received. Thus, high rates of admissions for ACSCs among the elderly (persons aged 65 or above who qualify for Medicare health insurance are signals of poor preventive care utilization. The relevant geographic market to use in studying these admission rates is the primary care physician market. Our conceptual model assumes that local market conditions serving as interventions along the pathways to preventive care services utilization can impact ACSC admission rates. Results We examine the relationships between market-level supply and demand factors on market-level rates of ACSC admissions among the elderly residing in the U.S. in the late 1990s. Using 6,475 natural markets in the mainland U.S. defined by The Health Resources and Services Administration's Primary Care Service Area Project, spatial regression is used to estimate the model, controlling for disease severity using detailed information from Medicare claims files. Our evidence suggests that elderly living in impoverished rural areas or in sprawling suburban places are about equally more likely to be admitted for ACSCs. Greater availability of physicians does not seem to matter, but greater prevalence of non-physician clinicians and international medical graduates, relative to U.S. medical graduates, does seem to reduce ACSC admissions, especially in poor rural areas. Conclusion The relative importance of non-physician clinicians and international medical graduates in providing primary care to the elderly in geographic areas of greatest need can inform the ongoing debate regarding whether there is an impending shortage of physicians in the United States. These findings support other authors who claim that the existing supply of physicians is perhaps adequate, however the distribution of them across

  9. [Multiple time scales analysis of spatial differentiation characteristics of non-point source nitrogen loss within watershed].

    Science.gov (United States)

    Liu, Mei-bing; Chen, Xing-wei; Chen, Ying

    2015-07-01

    Identification of the critical source areas of non-point source pollution is an important means to control the non-point source pollution within the watershed. In order to further reveal the impact of multiple time scales on the spatial differentiation characteristics of non-point source nitrogen loss, a SWAT model of Shanmei Reservoir watershed was developed. Based on the simulation of total nitrogen (TN) loss intensity of all 38 subbasins, spatial distribution characteristics of nitrogen loss and critical source areas were analyzed at three time scales of yearly average, monthly average and rainstorms flood process, respectively. Furthermore, multiple linear correlation analysis was conducted to analyze the contribution of natural environment and anthropogenic disturbance on nitrogen loss. The results showed that there were significant spatial differences of TN loss in Shanmei Reservoir watershed at different time scales, and the spatial differentiation degree of nitrogen loss was in the order of monthly average > yearly average > rainstorms flood process. TN loss load mainly came from upland Taoxi subbasin, which was identified as the critical source area. At different time scales, land use types (such as farmland and forest) were always the dominant factor affecting the spatial distribution of nitrogen loss, while the effect of precipitation and runoff on the nitrogen loss was only taken in no fertilization month and several processes of storm flood at no fertilization date. This was mainly due to the significant spatial variation of land use and fertilization, as well as the low spatial variability of precipitation and runoff.

  10. Multiple factor analysis by example using R

    CERN Document Server

    Pagès, Jérôme

    2014-01-01

    Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

  11. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    Science.gov (United States)

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

  12. The Impact of the Brain-Derived Neurotrophic Factor Gene on Trauma and Spatial Processing

    Directory of Open Access Journals (Sweden)

    Jessica K. Miller

    2017-11-01

    Full Text Available The influence of genes and the environment on the development of Post-Traumatic Stress Disorder (PTSD continues to motivate neuropsychological research, with one consistent focus being the Brain-Derived Neurotrophic Factor (BDNF gene, given its impact on the integrity of the hippocampal memory system. Research into human navigation also considers the BDNF gene in relation to hippocampal dependent spatial processing. This speculative paper brings together trauma and spatial processing for the first time and presents exploratory research into their interactions with BDNF. We propose that quantifying the impact of BDNF on trauma and spatial processing is critical and may well explain individual differences in clinical trauma treatment outcomes and in navigation performance. Research has already shown that the BDNF gene influences PTSD severity and prevalence as well as navigation behaviour. However, more data are required to demonstrate the precise hippocampal dependent processing mechanisms behind these influences in different populations and environmental conditions. This paper provides insight from recent studies and calls for further research into the relationship between allocentric processing, trauma processing and BDNF. We argue that research into these neural mechanisms could transform PTSD clinical practice and professional support for individuals in trauma-exposing occupations such as emergency response, law enforcement and the military.

  13. The Impact of the Brain-Derived Neurotrophic Factor Gene on Trauma and Spatial Processing.

    Science.gov (United States)

    Miller, Jessica K; McDougall, Siné; Thomas, Sarah; Wiener, Jan

    2017-11-27

    The influence of genes and the environment on the development of Post-Traumatic Stress Disorder (PTSD) continues to motivate neuropsychological research, with one consistent focus being the Brain-Derived Neurotrophic Factor (BDNF) gene, given its impact on the integrity of the hippocampal memory system. Research into human navigation also considers the BDNF gene in relation to hippocampal dependent spatial processing. This speculative paper brings together trauma and spatial processing for the first time and presents exploratory research into their interactions with BDNF. We propose that quantifying the impact of BDNF on trauma and spatial processing is critical and may well explain individual differences in clinical trauma treatment outcomes and in navigation performance. Research has already shown that the BDNF gene influences PTSD severity and prevalence as well as navigation behaviour. However, more data are required to demonstrate the precise hippocampal dependent processing mechanisms behind these influences in different populations and environmental conditions. This paper provides insight from recent studies and calls for further research into the relationship between allocentric processing, trauma processing and BDNF. We argue that research into these neural mechanisms could transform PTSD clinical practice and professional support for individuals in trauma-exposing occupations such as emergency response, law enforcement and the military.

  14. Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means

    Science.gov (United States)

    Song, Chengyun; Liu, Zhining; Cai, Hanpeng; Wang, Yaojun; Li, Xingming; Hu, Guangmin

    2017-12-01

    Seismic facies analysis techniques combine classification algorithms and seismic attributes to generate a map that describes main reservoir heterogeneities. However, most of the current classification algorithms only view the seismic attributes as isolated data regardless of their spatial locations, and the resulting map is generally sensitive to noise. In this paper, a regularized fuzzy c-means (RegFCM) algorithm is used for unsupervised seismic facies analysis. Due to the regularized term of the RegFCM algorithm, the data whose adjacent locations belong to same classification will play a more important role in the iterative process than other data. Therefore, this method can reduce the effect of seismic data noise presented in discontinuous regions. The synthetic data with different signal/noise values are used to demonstrate the noise tolerance ability of the RegFCM algorithm. Meanwhile, the fuzzy factor, the neighbour window size and the regularized weight are tested using various values, to provide a reference of how to set these parameters. The new approach is also applied to a real seismic data set from the F3 block of the Netherlands. The results show improved spatial continuity, with clear facies boundaries and channel morphology, which reveals that the method is an effective seismic facies analysis tool.

  15. FROM UNEMPLOYMENT TO WORK: AN ECONOMETRIC ANALYSIS WITH SPATIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    Oana Calavrezo

    2009-03-01

    Full Text Available The aim of our research is to analyze how the urban organization affects the unemployment-to-work transitions by considering several spatial indicators. This permits to capture two separate effects: "spatial mismatch" and "neighbourhood effects". In order to study the unemployment-to-work transitions, we implement survival models. They are applied on a sample obtained by merging three French databases: the "Trajectoires des demandeurs d'emplois" survey, the 1999 French census and finally, a database containing town inventory information. More precisely, in this paper, we analyze the duration of the first observed employment episode by using spatial indicators and by controlling three potential biases (endogeneity bias, selection bias and attrition bias.

  16. Spatial analysis of root hemiparasitic shrubs and their hosts

    DEFF Research Database (Denmark)

    Dueholm, Bjørn; Bruce, David; Weinstein, Philip

    2017-01-01

    to as spatial signatures of the root hemiparasites. In order to search for such spatial signatures, we investigated a population of a predominant Acacia species in Australia co-occurring with established root hemiparasitic shrubs, using intensity estimates of the Acacia and dead shrubs to be indicators...... of parasite populations. We find evidence that the root hemiparasitic shrubs, like herbaceous root hemiparasites, prefer growing at distances from neighbouring plants that fulfil resource requirements both below-ground and above-ground. Assuming that root hemiparasites are limited by their hosts, we present...

  17. Spatially Explicit Analysis of Water Footprints in the UK

    Directory of Open Access Journals (Sweden)

    John Barrett

    2010-12-01

    Full Text Available The Water Footprint, as an indicator of water consumption has become increasingly popular for analyzing environmental issues associated with the use of water resources in the global supply chain of consumer goods. This is particularly relevant for countries like the UK, which increasingly rely on products produced elsewhere in the world and thus impose pressures on foreign water resources. Existing studies calculating water footprints are mostly based on process analysis, and results are mainly available at the national level. The current paper assesses the domestic and foreign water requirements for UK final consumption by applying an environmentally extended multi-regional input-output model in combination with geo-demographic consumer segmentation data. This approach allows us to calculate water footprints (both direct and indirect for different products as well as different geographies within the UK. We distinguished between production and consumption footprints where the former is the total water consumed from the UK domestic water resources by the production activities in the UK and the latter is the total water consumed from both domestic and global water resources to satisfy the UK domestic final consumption. The results show that the production water footprint is 439 m3/cap/year, 85% of which is for the final consumption in the UK itself. The average consumption water footprint of the UK is more than three times bigger than the UK production water footprint in 2006. About half of the UK consumption water footprints were associated with imports from Non-OECD countries (many of which are water-scarce, while around 19% were from EU-OECD countries, and only 3% from Non-EU-OECD countries. We find that the water footprint differs considerably across sub-national geographies in the UK, and the differences are as big as 273 m3/cap/year for the internal water footprint and 802 m3/cap/year for the external water footprint. Our results suggest

  18. Carbon Sequestration in Colorado's Lands: A Spatial and Policy Analysis

    Science.gov (United States)

    Brandt, N.; Brazeau, A.; Browning, K.; Meier, R.

    2017-12-01

    Managing landscapes to enhance terrestrial carbon sequestration has significant potential to mitigate climate change. While a previous carbon baseline assessment in Colorado has been published (Conant et al, 2007), our study pulls from the existing literature to conduct an updated baseline assessment of carbon stocks and a unique review of carbon policies in Colorado. Through a multi-level spatial analysis based in GIS and informed by a literature review, we established a carbon stock baseline and ran four land use and carbon stock projection scenarios using Monte Carlo simulations. We identified 11 key policy recommendations for improving Colorado's carbon stocks, and evaluated each using Bardach's policy matrix approach (Bardach, 2012). We utilized a series of case studies to support our policy recommendations. We found that Colorado's lands have a carbon stock of 3,334 MMT CO2eq, with Forests and Woodlands holding the largest stocks, at 1,490 and 774 MMT CO2eq respectively. Avoided conversion of all Grasslands, Forests, and Wetlands in Colorado projected over 40 years would increase carbon stocks by 32 MMT CO2eq, 1,053 MMT CO2eq, and 36 MMT CO2eq, respectively. Over the 40-year study period, Forests and Woodlands areas are projected to shrink while Shrublands and Developed areas are projected to grow. Those projections suggest sizable increases in area of future wildfires and development in Colorado. We found that numerous policy opportunities to sequester carbon exist at different jurisdictional levels and across land cover types. The largest opportunities were found in state-level policies and policies impacting Forests, Grasslands, and Wetlands. The passage of statewide emission reduction legislation has the highest potential to impact carbon sequestration, although political and administrative feasibility of this option are relatively low. This study contributes to the broader field of carbon sequestration literature by examining the nexus of carbon stocks

  19. Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

    Science.gov (United States)

    Peng, Yu; Wang, Qinghui; Fan, Min

    2017-11-01

    When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

  20. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  1. Analysis of spatial count data using Kalman smoothing

    DEFF Research Database (Denmark)

    Dethlefsen, Claus

    2007-01-01

    We consider spatial count data from an agricultural field experiment. Counts of weed plants in a field have been recorded in a project on precision farming. Interest is in mapping the weed intensity so that the dose of herbicide applied at any location can be adjusted to the amount of weed present...

  2. Phenylketonuria and Complex Spatial Visualization: An Analysis of Information Processing.

    Science.gov (United States)

    Brunner, Robert L.; And Others

    1987-01-01

    The study of the ability of 16 early treated phenylketonuric (PKU) patients (ages 6-23 years) to solve complex spatial problems suggested that choice of problem-solving strategy, attention span, and accuracy of mental representation may be affected in PKU patients, despite efforts to maintain well-controlled phenylalanine concentrations in the…

  3. Tucker tensor analysis of Matern functions in spatial statistics

    KAUST Repository

    Litvinenko, Alexander

    2018-04-20

    Low-rank Tucker tensor methods in spatial statistics 1. Motivation: improve statistical models 2. Motivation: disadvantages of matrices 3. Tools: Tucker tensor format 4. Tensor approximation of Matern covariance function via FFT 5. Typical statistical operations in Tucker tensor format 6. Numerical experiments

  4. Geometric anisotropic spatial point pattern analysis and Cox processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Toftaker, Håkon

    . In particular we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial...

  5. Spatial and Statistical Analysis of Leptospirosis in Guilan Province, Iran

    Science.gov (United States)

    Nia, A. Mohammadi; Alimohammadi, A.; Habibi, R.; Shirzadi, M. R.

    2015-12-01

    The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009-2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran's I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.

  6. Using GIS for spatial exploratory analysis of borehole data: a ...

    African Journals Online (AJOL)

    Groundwater is an inimitable resource that provides water to communities especially in arid and semi-arid regions. However, the spatial variability of the resource as well as the heterogeneity and complex nature of aquifer systems that store groundwater presents difficulties for groundwater development. Thus ...

  7. An analysis of trends in spatial mobility of Dutch graduates

    NARCIS (Netherlands)

    Venhorst, Viktor; Van Dijk, Jouke; Van Wissen, Leo

    Considerable attention in the literature has been devoted to spatial mobility as a mechanism in the transition from study to work. In this paper, the relationships between migration and both regional economic circumstances and individual characteristics are investigated using a micro-dataset on

  8. Rockfall hazard analysis using LiDAR and spatial modeling

    Science.gov (United States)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  9. Spatial analysis of feline immunodeficiency virus infection in cougars.

    Science.gov (United States)

    Wheeler, David C; Waller, Lance A; Biek, Roman

    2010-07-01

    The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations.

  10. SPATIAL ANALYSIS OF RESIDENTS' FEAR AND FEELING OF ...

    African Journals Online (AJOL)

    Osondu

    Abstract. This study examined spatial pattern of crime and residents' fear and feeling of insecurity in Ile-Ife,. Nigeria. To obtain the primary data, Ile-Ife was stratified into four residential zones namely traditional town centre, middle income, high income and post-crisis residential areas. Sample was selected using systematic ...

  11. Spatial analysis of falls in an urban community of Hong Kong

    Directory of Open Access Journals (Sweden)

    Wong Wing C

    2009-03-01

    Full Text Available Abstract Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh and Standard Deviational Ellipse (SDE techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies.

  12. Spatial analysis of falls in an urban community of Hong Kong

    Science.gov (United States)

    Lai, Poh C; Low, Chien T; Wong, Martin; Wong, Wing C; Chan, Ming H

    2009-01-01

    Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh) and Standard Deviational Ellipse (SDE) techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies. PMID:19291326

  13. Analysis of a spatial orientation memory in Drosophila.

    Science.gov (United States)

    Neuser, Kirsa; Triphan, Tilman; Mronz, Markus; Poeck, Burkhard; Strauss, Roland

    2008-06-26

    Flexible goal-driven orientation requires that the position of a target be stored, especially in case the target moves out of sight. The capability to retain, recall and integrate such positional information into guiding behaviour has been summarized under the term spatial working memory. This kind of memory contains specific details of the presence that are not necessarily part of a long-term memory. Neurophysiological studies in primates indicate that sustained activity of neurons encodes the sensory information even though the object is no longer present. Furthermore they suggest that dopamine transmits the respective input to the prefrontal cortex, and simultaneous suppression by GABA spatially restricts this neuronal activity. Here we show that Drosophila melanogaster possesses a similar spatial memory during locomotion. Using a new detour setup, we show that flies can remember the position of an object for several seconds after it has been removed from their environment. In this setup, flies are temporarily lured away from the direction towards their hidden target, yet they are thereafter able to aim for their former target. Furthermore, we find that the GABAergic (stainable with antibodies against GABA) ring neurons of the ellipsoid body in the central brain are necessary and their plasticity is sufficient for a functional spatial orientation memory in flies. We also find that the protein kinase S6KII (ignorant) is required in a distinct subset of ring neurons to display this memory. Conditional expression of S6KII in these neurons only in adults can restore the loss of the orientation memory of the ignorant mutant. The S6KII signalling pathway therefore seems to be acutely required in the ring neurons for spatial orientation memory in flies.

  14. Advanced spatial metrics analysis in cellular automata land use and cover change modeling

    International Nuclear Information System (INIS)

    Zamyatin, Alexander; Cabral, Pedro

    2011-01-01

    This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.

  15. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jianhua Ni

    2016-08-01

    Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

  16. Analysis of technological, institutional and socioeconomic factors ...

    African Journals Online (AJOL)

    Analysis of technological, institutional and socioeconomic factors that influences poor reading culture among secondary school students in Nigeria. ... Proliferation and availability of smart phones, chatting culture and social media were identified as technological factors influencing poor reading culture among secondary ...

  17. Spatial-temporal detection of risk factors for bacillary dysentery in Beijing, Tianjin and Hebei, China

    Directory of Open Access Journals (Sweden)

    Chengdong Xu

    2017-09-01

    Full Text Available Abstract Background Bacillary dysentery is the third leading notifiable disease and remains a major public health concern in China. The Beijing–Tianjin–Hebei urban region is the biggest urban agglomeration in northern China, and it is one of the areas in the country that is most heavily infected with bacillary dysentery. The objective of the study was to analyze the spatial-temporal pattern and to determine any contributory risk factors on the bacillary dysentery. Methods Bacillary dysentery case data from 1 January 2012 to 31 December 2012 in Beijing–Tianjin– Hebei were employed. GeoDetector method was used to determine the impact of potential risk factors, and to identify regions and seasons at high risk of the disease. Results There were 36,472 cases of bacillary dysentery in 2012 in the study region. The incidence of bacillary dysentery varies widely amongst different age groups; the higher incidence of bacillary dysentery mainly occurs in the population under the age of five. Bacillary dysentery presents apparent seasonal variance, with the highest incidence occurring from June to September. In terms of the potential meteorological risk factors, mean temperature, relative humidity, precipitation, mean wind speed and sunshine hours explain the time variant of bacillary dysentery at 83%, 31%, 25%, 17% and 13%, respectively. The interactive effect between temperature and humidity has an explanatory power of 87%, indicating that a hot and humid environment is more likely to lead to the occurrence of bacillary dysentery. Socio-economic factors affect the spatial distribution of bacillary dysentery. The top four factors are age group, per capita GDP, population density and rural population proportion, and their determinant powers are 61%, 27%, 25% and 21%, respectively. The interactive effect between age group and the other factors accounts for more than 60% of bacillary dysentery transmission. Conclusions Bacillary dysentery poses a

  18. Analysis Of Influence Of Spatial Planning On Performance Of Regional Development At Waropen District. Papua Indonesia

    Directory of Open Access Journals (Sweden)

    Suwandi

    2015-08-01

    Full Text Available The various problems in regional spatial planning in Waropen District Papua shows that the Spatial Planning RTRW of Waropen District Papua drafted in 2010 has not had a positive contribution to the settlement of spatial planning problems. This is most likely caused by the inconsistency in the spatial planning. This study tried to observe the consistency of spatial planning as well as its relation to the regional development performance. The method used to observe the consistency of the preparation of guided Spatial Planning RTRW is the analysis of comparative table followed by analysis of verbal logic. In order to determine if the preparation of Spatial Planning RTRW has already paid attention on the synergy with the surrounding regions Inter-Regional Context a map overlay was conducted followed by analysis of verbal logic. To determine the performance of the regional development a Principal Components Analysis PCA was done. The analysis results showed that inconsistencies in the spatial planning had caused a variety of problems that resulted in decreased performance of the regional development. The main problems that should receive more attention are infrastructure development growth economic growth transportation aspect and new properties.

  19. Spatial pattern analysis and demography of two tropical trees in the Brazilian Caatinga

    Directory of Open Access Journals (Sweden)

    Maira Fontes Manzan

    2014-12-01

    Full Text Available Aspidosperma pyrifolium (Apocynaceae and Caesalpinia pyramidalis (Fabaceae share the same habitat in the Brazilian Caatinga domain. In this paper, we investigate the intra and inter-species interactions between these two plants using spatial pattern analysis among cohorts. The results showed that the adult trees of each species present higher densities at distances shorter than 9 m to 12 m. However, due to seed dispersal via autochory, we expected a more aggregate density for C. pyramidalis than A. pyrifolium as the later disperses seeds through anemochory. Difference in spatial aggregation among cohorts was not observed and therefore the results contradict the expectations of the Janzen-Connell hypothesis. It is likely that this is associated with anthropogenic factors in the past such as fire, animal husbandry and logging. Using a bivariate analysis of the neighborhood density, we also confirmed the significant coexistence between the two species. This coexistence could be explained by the process of positive interspecific interactions, such as facilitation, which is common in semi-arid regions under stressful conditions.

  20. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

  1. Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach

    Science.gov (United States)

    2012-05-10

    econometrics. A companion to theoretical econometrics, pages 310-330, 1988. [5] L. Anselin, J. Cohen, D. Cook, W. Gorr, and G. Tita . Spatial analyses...52] G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita . Self-exciting point process modeling of crime. Journal of the American...Systems, 9:462, 2010. [69] M. Short, P. Brantingham, A. Bertozzi, and G. Tita . Dissipation and displacement of hotspots in reaction-diffusion models

  2. Automated defect spatial signature analysis for semiconductor manufacturing process

    Science.gov (United States)

    Tobin, Jr., Kenneth W.; Gleason, Shaun S.; Karnowski, Thomas P.; Sari-Sarraf, Hamed

    1999-01-01

    An apparatus and method for performing automated defect spatial signature alysis on a data set representing defect coordinates and wafer processing information includes categorizing data from the data set into a plurality of high level categories, classifying the categorized data contained in each high level category into user-labeled signature events, and correlating the categorized, classified signature events to a present or incipient anomalous process condition.

  3. Analog model for analysis of spatial instability of neutron flux

    International Nuclear Information System (INIS)

    Radanovic, Lj.

    1964-12-01

    The objective of this task was to develop a model for analysing spatial instability of the neutron flux and defining the optimum number and position of regulating rods. The developed model enables calculation of higher harmonics to be taken into account for each type of reactor, to define zones for regulation rods, position and number of points for detecting reactor state, and number and position of the regulating rods

  4. Hand function evaluation: a factor analysis study.

    Science.gov (United States)

    Jarus, T; Poremba, R

    1993-05-01

    The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

  5. Using catchment areas analysis and GIS based spatial analysis for prioritising spatial investment in non-metro South Africa

    CSIR Research Space (South Africa)

    Green, Chéri A

    2016-09-01

    Full Text Available for social facility provision. A geo-spatially targeted hierarchy of places was also identified to prioritise investment of regional middle order facilities in “Service Malls” located in the most optimal towns to best serve non-metropolitan areas in South...

  6. Sea level rise and the geoid: factor analysis approach

    Directory of Open Access Journals (Sweden)

    Alexey Sadovski

    2013-08-01

    Full Text Available Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations.

  7. Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

    International Nuclear Information System (INIS)

    Prado, T. L.; Galuzio, P. P.; Lopes, S. R.; Viana, R. L.

    2014-01-01

    Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image

  8. Components of spatial information management in wildlife ecology: Software for statistical and modeling analysis [Chapter 14

    Science.gov (United States)

    Hawthorne L. Beyer; Jeff Jenness; Samuel A. Cushman

    2010-01-01

    Spatial information systems (SIS) is a term that describes a wide diversity of concepts, techniques, and technologies related to the capture, management, display and analysis of spatial information. It encompasses technologies such as geographic information systems (GIS), global positioning systems (GPS), remote sensing, and relational database management systems (...

  9. Integrating human factors into process hazard analysis

    International Nuclear Information System (INIS)

    Kariuki, S.G.; Loewe, K.

    2007-01-01

    A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors

  10. A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka

    Directory of Open Access Journals (Sweden)

    Müller Daniel

    2011-05-01

    Full Text Available Abstract Background The deprived physical environments present in slums are well-known to have adverse health effects on their residents. However, little is known about the health effects of the social environments in slums. Moreover, neighbourhood quantitative spatial analyses of the mental health status of slum residents are still rare. The aim of this paper is to study self-rated mental health data in several slums of Dhaka, Bangladesh, by accounting for neighbourhood social and physical associations using spatial statistics. We hypothesised that mental health would show a significant spatial pattern in different population groups, and that the spatial patterns would relate to spatially-correlated health-determining factors (HDF. Methods We applied a spatial epidemiological approach, including non-spatial ANOVA/ANCOVA, as well as global and local univariate and bivariate Moran's I statistics. The WHO-5 Well-being Index was used as a measure of self-rated mental health. Results We found that poor mental health (WHO-5 scores Conclusions Spatial patterns of mental health were detected and could be partly explained by spatially correlated HDF. We thereby showed that the socio-physical neighbourhood was significantly associated with health status, i.e., mental health at one location was spatially dependent on the mental health and HDF prevalent at neighbouring locations. Furthermore, the spatial patterns point to severe health disparities both within and between the slums. In addition to examining health outcomes, the methodology used here is also applicable to residuals of regression models, such as helping to avoid violating the assumption of data independence that underlies many statistical approaches. We assume that similar spatial structures can be found in other studies focussing on neighbourhood effects on health, and therefore argue for a more widespread incorporation of spatial statistics in epidemiological studies.

  11. Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

    Directory of Open Access Journals (Sweden)

    Ente J J Rood

    Full Text Available Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

  12. Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan

    International Nuclear Information System (INIS)

    Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C.

    2004-01-01

    Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis

  13. Spatial analysis of hypocenter to fault relationships for determining fault process zone width in Japan.

    Energy Technology Data Exchange (ETDEWEB)

    Arnold, Bill Walter; Roberts, Barry L.; McKenna, Sean Andrew; Coburn, Timothy C. (Abilene Christian University, Abilene, TX)

    2004-09-01

    Preliminary investigation areas (PIA) for a potential repository of high-level radioactive waste must be evaluated by NUMO with regard to a number of qualifying factors. One of these factors is related to earthquakes and fault activity. This study develops a spatial statistical assessment method that can be applied to the active faults in Japan to perform such screening evaluations. This analysis uses the distribution of seismicity near faults to define the width of the associated process zone. This concept is based on previous observations of aftershock earthquakes clustered near active faults and on the assumption that such seismic activity is indicative of fracturing and associated impacts on bedrock integrity. Preliminary analyses of aggregate data for all of Japan confirmed that the frequency of earthquakes is higher near active faults. Data used in the analysis were obtained from NUMO and consist of three primary sources: (1) active fault attributes compiled in a spreadsheet, (2) earthquake hypocenter data, and (3) active fault locations. Examination of these data revealed several limitations with regard to the ability to associate fault attributes from the spreadsheet to locations of individual fault trace segments. In particular, there was no direct link between attributes of the active faults in the spreadsheet and the active fault locations in the GIS database. In addition, the hypocenter location resolution in the pre-1983 data was less accurate than for later data. These pre-1983 hypocenters were eliminated from further analysis.

  14. Environmental, Spatial, and Sociodemographic Factors Associated with Nonfatal Injuries in Indonesia

    Directory of Open Access Journals (Sweden)

    Sri Irianti

    2017-01-01

    Full Text Available Background. The determinants of injuries and their reoccurrence in Indonesia are not well understood, despite their importance in the prevention of injuries. Therefore, this study seeks to investigate the environmental, spatial, and sociodemographic factors associated with the reoccurrence of injuries among Indonesian people. Methods. Data from the 2013 round of the Indonesia Baseline Health Research (IBHR 2013 were analysed using a two-part hurdle regression model. A logit regression model was chosen for the zero-hurdle part, while a zero-truncated negative binomial regression model was selected for the counts part. Odds ratio (OR and incidence rate ratio (IRR were the measures of association, respectively. Results. The results suggest that living in a household with distant drinking water source, residing in slum areas, residing in Eastern Indonesia, having low educational attainment, being men, and being poorer are positively related to the likelihood of experiencing injury. Moreover, being a farmer or fishermen, having low educational attainment, and being men are positively associated with the frequency of injuries. Conclusion. This study would be useful to prioritise injury prevention programs in Indonesia based on the environmental, spatial, and sociodemographic characteristics.

  15. High Spatial Resolution Analysis of Fungal Cell Biochemistry: Bridging the Analytical Gap using Synchrotron FTIR Spectromicroscopy

    International Nuclear Information System (INIS)

    Kaminskyj, S.; Konstantin, J.; Szeghalmi, A.; Gough, K.

    2008-01-01

    Fungi impact humans and the environment in many ways, for good and ill. Some fungi support the growth of terrestrial plants or are used in biotechnology, and yet others are established or emerging pathogens. In some cases, the same organism may play different roles depending on the context or the circumstance. A better understanding of the relationship between fungal biochemical composition as related to the fungal growth environment is essential if we are to support or control their activities. Synchrotron FTIR (sFTIR) spectromicroscopy of fungal hyphae is a major new tool for exploring cell composition at a high spatial resolution. Brilliant synchrotron light is essential for this analysis due to the small size of fungal hyphae. sFTIR biochemical characterization of subcellular variation in hyphal composition will allow detailed exploration of fungal responses to experimental treatments and to environmental factors.

  16. Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach.

    Science.gov (United States)

    Warren, Joshua L; Gordon-Larsen, Penny

    2018-06-01

    While there is a literature on the distribution of food stores across geographic and social space, much of this research uses cross-sectional data. Analyses attempting to understand whether the availability of stores across neighborhoods is associated with diet and/or health outcomes are limited by a lack of understanding of factors that shape the emergence of new stores and the closure of others. We used quarterly data on supermarket and convenience store locations spanning seven years (2006-2012) and tract-level census data in four US cities: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; San Francisco, California. A spatial discrete-time survival model was used to identify factors associated with an earlier and/or later closure time of a store. Sales volume was typically the strongest indicator of store survival. We identified heterogeneity in the association between tract-level poverty and racial composition with respect to store survival. Stores in high poverty, non-White tracts were often at a disadvantage in terms of survival length. The observed patterns of store survival varied by some of the same neighborhood sociodemographic factors associated with lifestyle and health outcomes, which could lead to confusion in interpretation in studies of the estimated effects of introduction of food stores into neighborhoods on health.

  17. Effects of oceanographic factors on spatial distribution of Whale Shark in Cendrawasih Bay National Park, West Papua

    Science.gov (United States)

    Ranintyari, Maulida; Sunarto; Syamsuddin, Mega L.; Astuty, Sri

    2018-05-01

    Whale sharks are a leading species in Cendrawasih Bay due to its benign nature and its regular appearance. Recently, whale sharks are vulnerable to scarcity and even extinction. One of the efforts to maintain the existence of the whale shark population is by knowing its spatial distribution. This study aims to analyze how the oceanographic factors affect the spatial distribution of whale sharks in Cendrawasih Bay National Park. The method used in this research is descriptive with the quantitative approach using the Generalized Additive Model (GAM) analysis. The data consisted of the whale shark monitoring data in TNTC taken by WWF-Indonesia, and image data of sea surface temperature (SST) and chlorophyll-a concentration of Aqua-MODIS, and also sea surface current from Aviso. Analyses were conducted for the period of January 2012 until March 2015. The GAM result indicated that sea surface current was better than the other environment (SST and chlorophyll-a concentration) as an oceanographic predictor of whale shark appearance. High probabilities of the whale shark’s to appear on the surface were observed in sea surface current velocities between 0.30-0.60 m/s, for SST ranged from 30.50-31.80 °C, and for chlorophyll-a concentration ranged from 0.20-0.40 mg/m3.

  18. Global Rice Watch: Spatial-temporal dynamics, driving factors, and impacts of paddy rice agriculture in the world

    Science.gov (United States)

    Xiao, X.; Dong, J.; Zhang, G.; Xin, F.; Li, X.

    2017-12-01

    Paddy rice croplands account for more than 12% of the global cropland areas, and provide food to feed more than 50% of the world population. Spatial patterns and temporal dynamics of paddy rice croplands have changed remarkably in the past decades, driven by growing human population and their changing diet structure, land use (e.g., urbanization, industrialization), climate, markets, and technologies. In this presentation, we will provide a comprehensive review of our current knowledge on (1) the spatial patterns and temporal dynamics of paddy rice croplands from agricultural statistics data and remote sensing approaches; (2) major driving factors for the observed changes in paddy rice areas, including social, economic, climate, land use, markets, crop breeding technology, and farming technology; and (3) major impacts on atmospheric methane concentration, land surface temperature, water resources and use, and so on. We will highlight the results from a few case studies in China and monsoon Asia. We will also call for a global synthesis analysis of paddy rice agriculture, and invite researchers to join the effort to write and edit a book that provides comprehensive and updated knowledge on paddy rice agriculture.

  19. Malaria prevalence, risk factors and spatial distribution in a hilly forest area of Bangladesh.

    Directory of Open Access Journals (Sweden)

    Ubydul Haque

    Full Text Available BACKGROUND: Malaria is a major public health concern in Bangladesh and it is highly endemic in the Chittagong Hill Tracts where prevalence was 11.7% in 2007. One sub-district, Rajasthali, had a prevalence of 36%. Several interventions were introduced in early 2007 to control malaria. This study was undertaken to evaluate the impacts of these intensive early stage interventions on malaria in Bangladesh. This prevalence study assesses whether or not high malaria prevalence remains, and if so, which areas and individuals remain at high risk of infection. METHODS AND PRINCIPAL FINDINGS: A 2-stage cluster sampling technique was used to sample 1,400 of 5,322 (26.3% households in Rajasthali, and screened using a rapid diagnostic test (Falci-vax. Overall malaria prevalence was 11.5%. The proportions of Plasmodium falciparum, Plasmodium vivax and infection with both species were 93.2%, 1.9% and 5.0%, respectively. Univariate, multivariate logistic regression, and spatial cluster analyses were performed separately. Sex, age, number of bed nets, forest cover, altitude and household density were potential risk factors. A statistically significant malaria cluster was identified. Significant differences among risk factors were observed between cluster and non-cluster areas. CONCLUSION AND SIGNIFICANCE: Malaria has significantly decreased within 2 years after onset of intervention program. Both aspects of the physical and social environment, as well as demographic characteristics are associated with spatial heterogeneity of risk. The ability to identify and locate these areas provides a strategy for targeting interventions during initial stages of intervention programs. However, in high risk clusters of transmission, even extensive coverage by current programs leaves transmission ongoing at reduced levels. This indicates the need for continued development of new strategies for identification and treatment as well as improved understanding of the patterns and

  20. Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia

    Energy Technology Data Exchange (ETDEWEB)

    Carranza, Emmanuel John M.; Barritt, Sally D. [Department of Earth Systems Analysis, International Institute for Geo-information Science and Earth Observation (ITC), Enschede (Netherlands); Wibowo, Hendro; Sumintadireja, Prihadi [Laboratory of Volcanology and Geothermal, Geology Department, Institute of Technology Bandung (ITB), Bandung (Indonesia)

    2008-06-15

    Conceptual modeling and predictive mapping of potential for geothermal resources at the regional-scale in West Java are supported by analysis of the spatial distribution of geothermal prospects and thermal springs, and their spatial associations with geologic features derived from publicly available regional-scale spatial data sets. Fry analysis shows that geothermal occurrences have regional-scale spatial distributions that are related to Quaternary volcanic centers and shallow earthquake epicenters. Spatial frequency distribution analysis shows that geothermal occurrences have strong positive spatial associations with Quaternary volcanic centers, Quaternary volcanic rocks, quasi-gravity lows, and NE-, NNW-, WNW-trending faults. These geological features, with their strong positive spatial associations with geothermal occurrences, constitute spatial recognition criteria of regional-scale geothermal potential in a study area. Application of data-driven evidential belief functions in GIS-based predictive mapping of regional-scale geothermal potential resulted in delineation of high potential zones occupying 25% of West Java, which is a substantial reduction of the search area for further exploration of geothermal resources. The predicted high potential zones delineate about 53-58% of the training geothermal areas and 94% of the validated geothermal occurrences. The results of this study demonstrate the value of regional-scale geothermal potential mapping in: (a) data-poor situations, such as West Java, and (b) regions with geotectonic environments similar to the study area. (author)

  1. Geoscience after ITPart G. Familiarization with spatial analysis

    Science.gov (United States)

    Pundt, Hardy; Brinkkötter-Runde, Klaus

    2000-04-01

    Field based and GPS supported GIS are increasingly applied in various spatial disciplines. Such systems represent more sophisticated, time and cost effective tools than traditional field forms for data acquisition. Meanwhile, various systems are on the market. These mostly enable the user to define geo-objects by means of GPS information, supported by functionalities to collect and analyze geometric information. The digital acquisition of application specific attributes is often underrepresented within such systems. This is surprising because pen computer based GIS can be used to collect attributes in a profitable manner, thus adequately supporting the requirements of the user. Visualization and graphic displays of spatial data are helpful means to improve such a data collection process. In section one and two basic aspects of visualization and current uses of visualization techniques for field based GIS are described. Section three mentions new developments within the framework of wearable computing and augmented reality. Section four describes current activities aimed at the realization of real time online field based GIS. This includes efforts to realize an online GIS data link to improve the efficiency and the quality of fieldwork. A brief discussion in section five leads to conclusions and some key issues for future research.

  2. The spatial expression and regulation of transcription factors IDEF1 and IDEF2

    Science.gov (United States)

    Kobayashi, Takanori; Ogo, Yuko; Aung, May Sann; Nozoye, Tomoko; Itai, Reiko Nakanishi; Nakanishi, Hiromi; Yamakawa, Takashi; Nishizawa, Naoko K.

    2010-01-01

    Background and Aims Under conditions of low iron availability, rice plants induce genes involved in iron uptake and utilization. The iron deficiency-responsive cis-acting element binding factors 1 and 2 (IDEF1 and IDEF2) regulate transcriptional response to iron deficiency in rice roots. Clarification of the functions of IDEF1 and IDEF2 could uncover the gene regulation mechanism. Methods Spatial patterns of IDEF1 and IDEF2 expression were analysed by histochemical staining of IDEF1 and IDEF2 promoter-GUS transgenic rice lines. Expression patterns of the target genes of IDEF1 and IDEF2 were analysed using transformants with induced or repressed expression of IDEF1 or IDEF2 grown in iron-rich or in iron-deficient solutions for 1 d. Key Results IDEF1 and IDEF2 were highly expressed in the basal parts of the lateral roots and vascular bundles. IDEF1 and IDEF2 expression was dominant in leaf mesophyll and vascular cells, respectively. These expression patterns were similar under both iron-deficient and iron-sufficient conditions. IDEF1 was strongly expressed in pollen, ovaries, the aleurone layer and embryo. IDEF2 was expressed in pollen, ovaries and the dorsal vascular region of the endosperm. During seed germination, IDEF1 and IDEF2 were expressed in the endosperm and embryo. Expression of IDEF1 target genes was regulated in iron-rich roots similar to early iron-deficiency stages. In addition, the expression patterns of IDEF2 target genes were similar between iron-rich conditions and early or subsequent iron deficiency. Conclusions IDEF1 and IDEF2 are constitutively expressed during both vegetative and reproductive stages. The spatial expression patterns of IDEF1 and IDEF2 overlap with their target genes in restricted cell types, but not in all cells. The spatial expression patterns and gene regulation of IDEF1 and IDEF2 in roots are generally conserved under conditions of iron sufficiency and deficiency, suggesting complicated interactions with unknown factors for

  3. Factors Impacting Spatial Patterns of Snow Distribution in a Small Catchment near Nome, AK

    Science.gov (United States)

    Chen, M.; Wilson, C. J.; Charsley-Groffman, L.; Busey, R.; Bolton, W. R.

    2017-12-01

    Snow cover plays an important role in the climate, hydrology and ecological systems of the Arctic due to its influence on the water balance, thermal regimes, vegetation and carbon flux. Thus, snow depth and coverage have been key components in all the earth system models but are often poorly represented for arctic regions, where fine scale snow distribution data is sparse. The snow data currently used in the models is at coarse resolution, which in turn leads to high uncertainty in model predictions. Through the DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic, high resolution snow distribution data is being developed and applied in catchment scale models to ultimately improve representation of snow and its interactions with other model components in the earth system models . To improve these models, it is important to identify key factors that control snow distribution and quantify the impacts of those factors on snow distribution. In this study, two intensive snow depth surveys (1 to 10 meters scale) were conducted for a 2.3 km2 catchment on the Teller road, near Nome, AK in the winter of 2016 and 2017. We used a statistical model to quantify the impacts of vegetation types, macro-topography, micro-topography, and meteorological parameters on measured snow depth. The results show that snow spatial distribution was similar between 2016 and 2017, snow depth was spatially auto correlated over small distance (2-5 meters), but not spatially auto correlated over larger distance (more than 2-5 meters). The coefficients of variation of snow depth was above 0.3 for all the snow survey transects (500-800 meters long). Variation of snow depth is governed by vegetation height, aspect, slope, surface curvature, elevation and wind speed and direction. We expect that this empirical statistical model can be used to estimate end of winter snow depth for the whole watershed and will further develop the model using data from other arctic regions to estimate

  4. a Temporal and Spatial Analysis of Urban Heat Island in Basin City Utilizing Remote Sensing Techniques

    Science.gov (United States)

    Chang, Hsiao-Tung

    2016-06-01

    Urban Heat Island (UHI) has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city's UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST) at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls "sinking heat island". From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  5. A TEMPORAL AND SPATIAL ANALYSIS OF URBAN HEAT ISLAND IN BASIN CITY UTILIZING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    H.-T. Chang

    2016-06-01

    Full Text Available Urban Heat Island (UHI has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city’s UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls “sinking heat island”. From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  6. Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

    Directory of Open Access Journals (Sweden)

    U. Mishra

    2012-09-01

    Full Text Available The direction and magnitude of soil organic carbon (SOC changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5. Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%, followed by discontinuous (28%, isolated (24.3%, and sporadic (23.6% permafrost areas. Our high-resolution mapping of soil carbon stock reveals the

  7. 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.

  8. Time dependent analysis of Xenon spatial oscillations in small power reactors

    International Nuclear Information System (INIS)

    Decco, Claudia Cristina Ghirardello

    1997-01-01

    This work presents time dependent analysis of xenon spatial oscillations studying the influence of the power density distribution, type of reactivity perturbation, power level and core size, using the one-dimensional and three-dimensional analysis with the MID2 and citation codes, respectively. It is concluded that small pressurized water reactors with height smaller than 1.5 m are stable and do not have xenon spatial oscillations. (author)

  9. Analysis of Economic Factors Affecting Stock Market

    OpenAIRE

    Xie, Linyin

    2010-01-01

    This dissertation concentrates on analysis of economic factors affecting Chinese stock market through examining relationship between stock market index and economic factors. Six economic variables are examined: industrial production, money supply 1, money supply 2, exchange rate, long-term government bond yield and real estate total value. Stock market comprises fixed interest stocks and equities shares. In this dissertation, stock market is restricted to equity market. The stock price in thi...

  10. Spatial compression algorithm for the analysis of very large multivariate images

    Science.gov (United States)

    Keenan, Michael R [Albuquerque, NM

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  11. Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis.

    Science.gov (United States)

    Mustapha, Adamu; Aris, Ahmad Zaharin

    2012-01-01

    Multivariate statistical techniques such as hierarchical Agglomerated cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and factor analysis (FA) were applied to identify the spatial variation and pollution sources of Jakara River, Kano, Nigeria. Thirty surface water samples were collected: 23 along Getsi River and 7 along the main channel of River Jakara. Twenty-three water quality parameters, namely pH, temperature, turbidity, electrical conductivity (EC), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), Faecal coliform, total solids (TS), nitrates (NO(3)(-)), phosphates (PO(4)(3-)), cobalt (Co), iron (Fe), nickel (Ni), manganese (Mn), copper (Cu), sodium (Na), potassium (K), mercury (Hg), chromium (Cr), cadmium (Cd), lead (Pb), magnesium (Mg), and calcium(Ca) were analysed. HACA grouped the sampling points into three clusters based on the similarities of river water quality characteristics: industrial, domestic, and agricultural water pollution sources. Forward and backward DA effectively discriminated 5 and 15 water quality variables, respectively, each assigned with 100% correctness from the original 23 variables. PCA and FA were used to investigate the origin of each water quality parameter due to various land use activities, 7 principal components were obtained with 77.5% total variance, and in addition PCA identified 3 latent pollution sources to support HACA. From this study, one can conclude that the application of multivariate techniques derives meaningful information from water quality data.

  12. Ecological and spatial factors drive intra- and interspecific variation in exposure of subarctic predatory bird nestlings to persistent organic pollutants.

    Science.gov (United States)

    Eulaers, Igor; Jaspers, Veerle L B; Bustnes, Jan O; Covaci, Adrian; Johnsen, Trond V; Halley, Duncan J; Moum, Truls; Ims, Rolf A; Hanssen, Sveinn A; Erikstad, Kjell E; Herzke, Dorte; Sonne, Christian; Ballesteros, Manuel; Pinxten, Rianne; Eens, Marcel

    2013-07-01

    contamination). In conclusion, the combined analysis of POPs and stable isotopes in body feathers from fully-grown nestlings has identified ecological and spatial factors that may drive POP exposure over the larger part of the nestling stage. This methodological approach further promotes the promising use of nestling predatory bird body feathers as a non-destructive sampling strategy to integrate various toxicological and ecological proxies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

    Science.gov (United States)

    Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

    2016-01-01

    Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

  14. Spatial and temporal expression analysis of D- myo -inositol 3 ...

    African Journals Online (AJOL)

    1á (eukaryotic elongation factor 1-alpha) using SYBER-Green. ... expression in the developing seed tissues and can be targeted using the dsRNA induced sequence specific RNA degradation mechanism for reduction of phytate levels without ...

  15. Spatial and environmental connectivity analysis in a cholera vaccine trial.

    Science.gov (United States)

    Emch, Michael; Ali, Mohammad; Root, Elisabeth D; Yunus, Mohammad

    2009-02-01

    This paper develops theory and methods for vaccine trials that utilize spatial and environmental information. Satellite imagery is used to identify whether households are connected to one another via water bodies in a study area in rural Bangladesh. Then relationships between neighborhood-level cholera vaccine coverage and placebo incidence and neighborhood-level spatial variables are measured. The study hypothesis is that unvaccinated people who are environmentally connected to people who have been vaccinated will be at lower risk compared to unvaccinated people who are environmentally connected to people who have not been vaccinated. We use four datasets including: a cholera vaccine trial database, a longitudinal demographic database of the rural population from which the vaccine trial participants were selected, a household-level geographic information system (GIS) database of the same study area, and high resolution Quickbird satellite imagery. An environmental connectivity metric was constructed by integrating the satellite imagery with the vaccine and demographic databases linked with GIS. The results show that there is a relationship between neighborhood rates of cholera vaccination and placebo incidence. Thus, people are indirectly protected when more people in their environmentally connected neighborhood are vaccinated. This result is similar to our previous work that used a simpler Euclidean distance neighborhood to measure neighborhood vaccine coverage [Ali, M., Emch, M., von Seidlein, L., Yunus, M., Sack, D. A., Holmgren, J., et al. (2005). Herd immunity conferred by killed oral cholera vaccines in Bangladesh. Lancet, 366(9479), 44-49]. Our new method of measuring environmental connectivity is more precise since it takes into account the transmission mode of cholera and therefore this study validates our assertion that the oral cholera vaccine provides indirect protection in addition to direct protection.

  16. Incorporating twitter-based human activity information in spatial analysis of crashes in urban areas.

    Science.gov (United States)

    Bao, Jie; Liu, Pan; Yu, Hao; Xu, Chengcheng

    2017-09-01

    The primary objective of this study was to investigate how to incorporate human activity information in spatial analysis of crashes in urban areas using Twitter check-in data. This study used the data collected from the City of Los Angeles in the United States to illustrate the procedure. The following five types of data were collected: crash data, human activity data, traditional traffic exposure variables, road network attributes and social-demographic data. A web crawler by Python was developed to collect the venue type information from the Twitter check-in data automatically. The human activities were classified into seven categories by the obtained venue types. The collected data were aggregated into 896 Traffic Analysis Zones (TAZ). Geographically weighted regression (GWR) models were developed to establish a relationship between the crash counts reported in a TAZ and various contributing factors. Comparative analyses were conducted to compare the performance of GWR models which considered traditional traffic exposure variables only, Twitter-based human activity variables only, and both traditional traffic exposure and Twitter-based human activity variables. The model specification results suggested that human activity variables significantly affected the crash counts in a TAZ. The results of comparative analyses suggested that the models which considered both traditional traffic exposure and human activity variables had the best goodness-of-fit in terms of the highest R 2 and lowest AICc values. The finding seems to confirm the benefits of incorporating human activity information in spatial analysis of crashes using Twitter check-in data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Spatially dependent biotic and abiotic factors drive survivorship and physical structure of green roof vegetation.

    Science.gov (United States)

    Aloisio, Jason M; Palmer, Matthew I; Giampieri, Mario A; Tuininga, Amy R; Lewis, James D

    2017-01-01

    Plant survivorship depends on biotic and abiotic factors that vary at local and regional scales. This survivorship, in turn, has cascading effects on community composition and the physical structure of vegetation. Survivorship of native plant species is variable among populations planted in environmentally stressful habitats like urban roofs, but the degree to which factors at different spatial scales affect survivorship in urban systems is not well understood. We evaluated the effects of biotic and abiotic factors on survivorship, composition, and physical structure of two native perennial species assemblages, one characterized by a mixture of C 4 grasses and forbs (Hempstead Plains, HP) and one characterized by a mixture of C 3 grasses and forbs (Rocky Summit, RS), that were initially sown at equal ratios of growth forms (5:1:4; grass, N-fixing forb and non-N-fixing forb) in replicate 2-m 2 plots planted on 10 roofs in New York City (New York, USA). Of 24 000 installed plants, 40% survived 23 months after planting. Within-roof factors explained 71% of variation in survivorship, with biotic (species identity and assemblage) factors accounting for 54% of the overall variation, and abiotic (growing medium depth and plot location) factors explaining 17% of the variation. Among-roof factors explained 29% of variation in survivorship and increased solar radiation correlated with decreased survivorship. While growing medium properties (pH, nutrients, metals) differed among roofs there was no correlation with survivorship. Percent cover and sward height increased with increasing survivorship. At low survivorship, cover of the HP assemblage was greater compared to the RS assemblage. Sward height of the HP assemblage was about two times greater compared to the RS assemblage. These results highlight the effects of local biotic and regional abiotic drivers on community composition and physical structure of green roof vegetation. As a result, initial green roof plant

  18. Role of Environmental Factors in Shaping Spatial Distribution of Salmonella enterica Serovar Typhi, Fiji.

    Science.gov (United States)

    de Alwis, Ruklanthi; Watson, Conall; Nikolay, Birgit; Lowry, John H; Thieu, Nga Tran Vu; Van, Tan Trinh; Ngoc, Dung Tran Thi; Rawalai, Kitione; Taufa, Mere; Coriakula, Jerimaia; Lau, Colleen L; Nilles, Eric J; Edmunds, W John; Kama, Mike; Baker, Stephen; Cano, Jorge

    2018-02-01

    Fiji recently experienced a sharp increase in reported typhoid fever cases. To investigate geographic distribution and environmental risk factors associated with Salmonella enterica serovar Typhi infection, we conducted a cross-sectional cluster survey with associated serologic testing for Vi capsular antigen-specific antibodies (a marker for exposure to Salmonella Typhi in Fiji in 2013. Hotspots with high seroprevalence of Vi-specific antibodies were identified in northeastern mainland Fiji. Risk for Vi seropositivity increased with increased annual rainfall (odds ratio [OR] 1.26/quintile increase, 95% CI 1.12-1.42), and decreased with increased distance from major rivers and creeks (OR 0.89/km increase, 95% CI 0.80-0.99) and distance to modeled flood-risk areas (OR 0.80/quintile increase, 95% CI 0.69-0.92) after being adjusted for age, typhoid fever vaccination, and home toilet type. Risk for exposure to Salmonella Typhi and its spatial distribution in Fiji are driven by environmental factors. Our findings can directly affect typhoid fever control efforts in Fiji.

  19. Spatial distribution of osteoblast-specific transcription factor Cbfa1 and bone formation in atherosclerotic arteries.

    Science.gov (United States)

    Bobryshev, Yuri V; Killingsworth, Murray C; Lord, Reginald S A

    2008-08-01

    The mechanisms of ectopic bone formation in arteries are poorly understood. Osteoblasts might originate either from stem cells that penetrate atherosclerotic plaques from the blood stream or from pluripotent mesenchymal cells that have remained in the arterial wall from embryonic stages of the development. We have examined the frequency of the expression and spatial distribution of osteoblast-specific factor-2/core binding factor-1 (Osf2/Cbfa1) in carotid and coronary arteries. Cbfa1-expressing cells were rarely observed but were found in all tissue specimens in the deep portions of atherosclerotic plaques under the necrotic cores. The deep portions of atherosclerotic plaques under the necrotic cores were characterized by the lack of capillaries of neovascularization. In contrast, plaque shoulders, which were enriched by plexuses of neovascularization, lacked Cbfa1-expressing cells. No bone formation was found in any of the 21 carotid plaques examined and ectopic bone was observed in only two of 12 coronary plaques. We speculate that the sparse invasion of sprouts of neovascularization into areas underlying the necrotic cores, where Cbfa1-expressing cells reside, might explain the rarity of events of ectopic bone formation in the arterial wall. This study has also revealed that Cbfa1-expressing cells contain alpha-smooth muscle actin and myofilaments, indicating their relationship with arterial smooth muscle cells.

  20. 3D spatially-adaptive canonical correlation analysis: Local and global methods.

    Science.gov (United States)

    Yang, Zhengshi; Zhuang, Xiaowei; Sreenivasan, Karthik; Mishra, Virendra; Curran, Tim; Byrd, Richard; Nandy, Rajesh; Cordes, Dietmar

    2018-04-01

    Local spatially-adaptive canonical correlation analysis (local CCA) with spatial constraints has been introduced to fMRI multivariate analysis for improved modeling of activation patterns. However, current algorithms require complicated spatial constraints that have only been applied to 2D local neighborhoods because the computational time would be exponentially increased if the same method is applied to 3D spatial neighborhoods. In this study, an efficient and accurate line search sequential quadratic programming (SQP) algorithm has been developed to efficiently solve the 3D local CCA problem with spatial constraints. In addition, a spatially-adaptive kernel CCA (KCCA) method is proposed to increase accuracy of fMRI activation maps. With oriented 3D spatial filters anisotropic shapes can be estimated during the KCCA analysis of fMRI time courses. These filters are orientation-adaptive leading to rotational invariance to better match arbitrary oriented fMRI activation patterns, resulting in improved sensitivity of activation detection while significantly reducing spatial blurring artifacts. The kernel method in its basic form does not require any spatial constraints and analyzes the whole-brain fMRI time series to construct an activation map. Finally, we have developed a penalized kernel CCA model that involves spatial low-pass filter constraints to increase the specificity of the method. The kernel CCA methods are compared with the standard univariate method and with two different local CCA methods that were solved by the SQP algorithm. Results show that SQP is the most efficient algorithm to solve the local constrained CCA problem, and the proposed kernel CCA methods outperformed univariate and local CCA methods in detecting activations for both simulated and real fMRI episodic memory data. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Climate Change Adaptation via U.S. Land Use Transitions: A Spatial Econometric Analysis

    OpenAIRE

    Cho, Sung Ju; McCarl, Bruce A.; Wu, Ximing

    2015-01-01

    Climate change, coupled with biofuels development and other factors may well be changing US land usage patterns. We use a spatial econometric approach to estimate the drivers of US land use transitions in recent years. We consider transitions between six major land uses: agricultural land, forest, grassland, water, urban, and other uses. To examine drivers, we use a two-step linearized, spatial, multinomial logit model and estimate land use transition probabilities. Our results indicate that ...

  2. Spatial analysis of the Rio de Janeiro metropolitan area and social and environmental management issues

    DEFF Research Database (Denmark)

    Ribeiro, Gustavo

    2005-01-01

    and infrastructural data. Through these three levels of spatial analysis it is possible to develop and to support a more comprehensible study of urban development of the Rio de Janeiro Metropolitan Area. The aim of this study is (a) to develop an alternative spatial analysis leading to a more comprehensive...... understanding of the urban development process and its correlation not just with political-administrative borders but also to ecological systems: (b) to identify the correlations between infrastructure and socio-economical data in the Rio de Janeiro Metropolitan Area (c) to evaluate urban development dynamics...... in the period between 1990 and 2000, based on the application of the above-mentioned data to the three spatial levels in question. This paper highlights the role of the hydrographical systems of the Rio de Janeiro Metropolitan Area as an important spatial unit of analysis to understand the metropolitan urban...

  3. [A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

    Science.gov (United States)

    Lakes, Tobia

    2017-12-01

    In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

  4. Factor Economic Analysis at Forestry Enterprises

    Directory of Open Access Journals (Sweden)

    M.Yu. Chik

    2018-03-01

    Full Text Available The article studies the importance of economic analysis according to the results of research of scientific works of domestic and foreign scientists. The calculation of the influence of factors on the change in the cost of harvesting timber products by cost items has been performed. The results of the calculation of the influence of factors on the change of costs on 1 UAH are determined using the full cost of sold products. The variable and fixed costs and their distribution are allocated that influences the calculation of the impact of factors on cost changes on 1 UAH of sold products. The paper singles out the general results of calculating the influence of factors on cost changes on 1 UAH of sold products. According to the results of the analysis, the list of reserves for reducing the cost of production at forest enterprises was proposed. The main sources of reserves for reducing the prime cost of forest products at forest enterprises are investigated based on the conducted factor analysis.

  5. Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

    Directory of Open Access Journals (Sweden)

    Stefanović Nebojša

    2017-01-01

    Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

  6. Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

    Science.gov (United States)

    Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

    2016-01-01

    Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.

  7. Linking the spatial patterns of organisms and abiotic factors to ecosystem function and management: insights from semi-arid environments

    Directory of Open Access Journals (Sweden)

    F. T. Maestre

    2006-12-01

    Full Text Available Numerous theoretical and modeling studies have demonstrated the ecological significance of the spatial patterning of organisms on ecosystem functioning and dynamics. However, there is a paucity of empirical evidence that quantitatively shows how changes in the spatial patterns of the organisms forming biotic communities are directly related to ecosystem structure and functioning. In this article, I review a series of experiments and observational studies conducted in semi-arid environments from Spain (degraded calcareous shrubland, steppes dominated by Stipa tenacissima, and gypsum shrublands to: 1 evaluate whether the spatial patterns of the dominant biotic elements in the community are linked to ecosystem structure and functioning, and 2 test if these patterns, and those of abiotic factors, can be used to improve ecosystem restoration. In the semiarid steppes we found a significant positive relationship between the spatial pattern of the perennial plant community and: i the water status of S. tenacissima and ii perennial species richness and diversity. Experimental plantings conducted in these steppes showed that S. tenacissima facilitated the establishment of shrub seedlings, albeit the magnitude and direction of this effect was dependent on rainfall conditions during the first yr after planting. In the gypsum shrubland, a significant, direct relationship between the spatial pattern of the biological soil crusts and surrogates of ecosystem functioning (soil bulk density and respiration was found. In a degraded shrubland with very low vegetation cover, the survival of an introduced population of the shrub Pistacia lentiscus showed marked spatial patterns, which were related to the spatial patterns of soil properties such as soil compaction and sand content. These results provide empirical evidence on the importance of spatial patterns for maintaining ecosystem structure and functioning in semi-arid ecosystems

  8. An SPSSR -Menu for Ordinal Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mario Basto

    2012-01-01

    Full Text Available Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in theR programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

  9. Biophysical and sociocultural factors underlying spatial trade-offs of ecosystem services in semiarid watersheds

    Directory of Open Access Journals (Sweden)

    Marina García-Llorente

    2015-09-01

    Full Text Available Biophysical and social systems are linked to form social-ecological systems whose sustainability depends on their capacity to absorb uncertainty and cope with disturbances. In this study, we explored the key biophysical and socio-cultural factors underlying ecosystem service supply in two semiarid watersheds of southern Spain. These included variables associated with the role that freshwater flows and biodiversity play in securing the system's capacity to sustain essential ecosystem services and their relationship with social demand for services, local water governance, and land-use intensification. Our results reveal the importance of considering the invisible dimensions of water and biodiversity, i.e. green freshwater flows and trait-based indicators, because of their relevance to the supply of ecosystem services. Furthermore, they uncover the importance of traditional irrigation canals, a local water governance system, in maintaining the ecosystems' capacity to supply services. The study also highlights the complex trade-offs that occur because of the spatial mismatch between ecosystem service supply (upstream and ecosystem service demand (downstream in watersheds. Finally, we found that land-use intensification generally resulted in losses of the biophysical factors that underpin the supply of some ecosystem services, increases in social demand for less diversified services, and the abandonment of local governance practices. Attempts to manage social-ecological systems toward sustainability at the local scale should identify the key biophysical and socio-cultural factors that are essential for maintaining ecosystem services and should recognize existing interrelationships between them. Land-use management should also take into account ecosystem service trade-offs and the consequences resulting from land-use intensification.

  10. Resources and spatial analysis at actual Nenets campsites: Ethnoarchaeological implications

    Czech Academy of Sciences Publication Activity Database

    Svoboda, J.; Sázelová, S.; Kosintsev, P. A.; Jankovská, Vlasta; Holub, M.

    2011-01-01

    Roč. 30, č. 1 (2011), s. 30-43 ISSN 0278-4165 R&D Projects: GA ČR GAP209/10/0519 Institutional research plan: CEZ:AV0Z60050516 Keywords : Ethnoarchaeology * Nenets * Polar Ural - Siberia Subject RIV: EF - Botanics Impact factor: 1.508, year: 2011

  11. Area-to-Area Poisson Kriging and Spatial Bayesian Analysis

    Science.gov (United States)

    Asmarian, Naeimehossadat; Jafari-Koshki, Tohid; Soleimani, Ali; Taghi Ayatollahi, Seyyed Mohammad

    2016-10-01

    Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Areato- area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran. Creative Commons Attribution License

  12. Advances in diagnosis and spatial analysis of cysticercosis and taeniasis.

    Science.gov (United States)

    Raoul, Francis; Li, Tiaoying; Sako, Yasuhito; Chen, Xingwang; Long, Changping; Yanagida, Tetsuya; Wu, Yunfei; Nakao, Minoru; Okamoto, Munehiro; Craig, Philip S; Giraudoux, Patrick; Ito, Akira

    2013-11-01

    Human cysticercosis, caused by accidental ingestion of eggs of Taenia solium, is one of the most pathogenic helminthiases and is listed among the 17 WHO Neglected Tropical Diseases. Controlling the life-cycle of T. solium between humans and pigs is essential for eradication of cysticercosis. One difficulty for the accurate detection and identification of T. solium species is the possible co-existence of two other human Taenia tapeworms (T. saginata and T. asiatica, which do not cause cysticercosis in humans). Several key issues for taeniasis/cysticercosis (T/C) evidence-based epidemiology and control are reviewed: (1) advances in immunological and molecular tools for screening of human and animals hosts and identification of Taenia species, with a focus on real-time detection of taeniasis carriers and infected animals in field community screenings, and (2) spatial ecological approaches that have been used to detect geospatial patterns of case distributions and to monitor pig activity and behaviour. Most recent eco-epidemiological studies undertaken in Sichuan province, China, are introduced and reviewed.

  13. Spatial analysis on human brucellosis incidence in mainland China: 2004–2010

    Science.gov (United States)

    Zhang, Junhui; Yin, Fei; Zhang, Tao; Yang, Chao; Zhang, Xingyu; Feng, Zijian; Li, Xiaosong

    2014-01-01

    Objectives China has experienced a sharply increasing rate of human brucellosis in recent years. Effective spatial monitoring of human brucellosis incidence is very important for successful implementation of control and prevention programmes. The purpose of this paper is to apply exploratory spatial data analysis (ESDA) methods and the empirical Bayes (EB) smoothing technique to monitor county-level incidence rates for human brucellosis in mainland China from 2004 to 2010 by examining spatial patterns. Methods ESDA methods were used to characterise spatial patterns of EB smoothed incidence rates for human brucellosis based on county-level data obtained from the China Information System for Disease Control and Prevention (CISDCP) in mainland China from 2004 to 2010. Results EB smoothed incidence rates for human brucellosis were spatially dependent during 2004–2010. The local Moran test identified significantly high-risk clusters of human brucellosis (all p values brucellosis incidence. PMID:24713215

  14. Spatial Analysis of International Tourist Movement to Langkawi for 2010 and 2011

    Directory of Open Access Journals (Sweden)

    Basiron Nur Fatma Zuhra

    2014-01-01

    Full Text Available Tourism is a temporary movement of people to a destination of their choice intended for leisure or recreation. The resulting of this movement can be divided into interdestination dan intradestinastion. This study is about interdestination movement which is characterised by movement from tourist-generating regions to one or more destinations. This research aims to analyse the movement of international tourist who come to Langkawi in 2010 and 2011. The application geographic information system (GIS is aids in visualizing spatial data through mapping. Regression analysis using SPSS was also used to examine the relationship between the distance and the amount of flow that exists. Map of the distribution and flow of tourist was produced to facilitate the analysis. The results of the analyses show that the tourist movement is driven by certain factors such as climatic, economic, distance and etc. Regression analysis showed the nexus between the distance and the amount of the tourist flow was not strong. Map produced can be used by LADA specifically for planning marketing strategies and etc.

  15. Algorithms for large scale singular value analysis of spatially variant tomography systems

    International Nuclear Information System (INIS)

    Cao-Huu, Tuan; Brownell, G.; Lachiver, G.

    1996-01-01

    The problem of determining the eigenvalues of large matrices occurs often in the design and analysis of modem tomography systems. As there is an interest in solving systems containing an ever-increasing number of variables, current research effort is being made to create more robust solvers which do not depend on some special feature of the matrix for convergence (e.g. block circulant), and to improve the speed of already known and understood solvers so that solving even larger systems in a reasonable time becomes viable. Our standard techniques for singular value analysis are based on sparse matrix factorization and are not applicable when the input matrices are large because the algorithms cause too much fill. Fill refers to the increase of non-zero elements in the LU decomposition of the original matrix A (the system matrix). So we have developed iterative solutions that are based on sparse direct methods. Data motion and preconditioning techniques are critical for performance. This conference paper describes our algorithmic approaches for large scale singular value analysis of spatially variant imaging systems, and in particular of PCR2, a cylindrical three-dimensional PET imager 2 built at the Massachusetts General Hospital (MGH) in Boston. We recommend the desirable features and challenges for the next generation of parallel machines for optimal performance of our solver

  16. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  17. ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

    Directory of Open Access Journals (Sweden)

    Carmen BOGHEAN

    2013-12-01

    Full Text Available Productivity in agriculture most relevantly and concisely expresses the economic efficiency of using the factors of production. Labour productivity is affected by a considerable number of variables (including the relationship system and interdependence between factors, which differ in each economic sector and influence it, giving rise to a series of technical, economic and organizational idiosyncrasies. The purpose of this paper is to analyse the underlying factors of the average work productivity in agriculture, forestry and fishing. The analysis will take into account the data concerning the economically active population and the gross added value in agriculture, forestry and fishing in Romania during 2008-2011. The distribution of the average work productivity per factors affecting it is conducted by means of the u-substitution method.

  18. Revised methane emissions factors and spatially distributed annual carbon fluxes for global livestock.

    Science.gov (United States)

    Wolf, Julie; Asrar, Ghassem R; West, Tristram O

    2017-09-29

    Livestock play an important role in carbon cycling through consumption of biomass and emissions of methane. Recent research suggests that existing bottom-up inventories of livestock methane emissions in the US, such as those made using 2006 IPCC Tier 1 livestock emissions factors, are too low. This may be due to outdated information used to develop these emissions factors. In this study, we update information for cattle and swine by region, based on reported recent changes in animal body mass, feed quality and quantity, milk productivity, and management of animals and manure. We then use this updated information to calculate new livestock methane emissions factors for enteric fermentation in cattle, and for manure management in cattle and swine. Using the new emissions factors, we estimate global livestock emissions of 119.1 ± 18.2 Tg methane in 2011; this quantity is 11% greater than that obtained using the IPCC 2006 emissions factors, encompassing an 8.4% increase in enteric fermentation methane, a 36.7% increase in manure management methane, and notable variability among regions and sources. For example, revised manure management methane emissions for 2011 in the US increased by 71.8%. For years through 2013, we present (a) annual livestock methane emissions, (b) complete annual livestock carbon budgets, including carbon dioxide emissions, and (c) spatial distributions of livestock methane and other carbon fluxes, downscaled to 0.05 × 0.05 degree resolution. Our revised bottom-up estimates of global livestock methane emissions are comparable to recently reported top-down global estimates for recent years, and account for a significant part of the increase in annual methane emissions since 2007. Our results suggest that livestock methane emissions, while not the dominant overall source of global methane emissions, may be a major contributor to the observed annual emissions increases over the 2000s to 2010s. Differences at regional and local scales may help

  19. Spatial reliability analysis of a wind turbine blade cross section subjected to multi-axial extreme loading

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Bitsche, Robert; Blasques, José Pedro Albergaria Amaral

    2017-01-01

    This paper presents a methodology for structural reliability analysis of wind turbine blades. The study introduces several novel elements by taking into account loading direction using a multiaxial probabilistic load model, considering random material strength, spatial correlation between material...... properties, progressive material failure, and system reliability effects. An example analysis of reliability against material failure is demonstrated for a blade cross section. Based on the study we discuss the implications of using a system reliability approach, the effect of spatial correlation length......, type of material degradation algorithm, and reliability methods on the system failure probability, as well as the main factors that have an influence on the reliability. (C) 2017 Elsevier Ltd. All rights reserved....

  20. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose

  1. Spatial Analysis of Thermal Aging of Overhead Transmission Conductors

    Czech Academy of Sciences Publication Activity Database

    Musílek, P.; Heckenbergerová, Jana; Bhuiyan, M.M.I.

    2012-01-01

    Roč. 27, č. 3 (2012), s. 1196-1204 ISSN 0885-8977 Grant - others:GA AV ČR(CZ) M100300904 Source of funding: V - iné verejné zdroje Keywords : aluminium conductor steel reinforced (ACSR) conductor * hot spot * loss of tensile strength * numerical weather prediction * power transmission lines * thermal aging Subject RIV: JE - Non-nuclear Energetics, Energy Consumption ; Use Impact factor: 1.519, year: 2012

  2. Spatial analysis of bus transport networks using network theory

    Science.gov (United States)

    Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

    2018-07-01

    In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

  3. Environmental Risk Assessment: Spatial Analysis of Chemical Hazards and Risks in South Korea

    Science.gov (United States)

    Yu, H.; Heo, S.; Kim, M.; Lee, W. K.; Jong-Ryeul, S.

    2017-12-01

    This study identified chemical hazard and risk levels in Korea by analyzing the spatial distribution of chemical factories and accidents. The number of chemical factories and accidents in 5-km2 grids were used as the attribute value for spatial analysis. First, semi-variograms were conducted to examine spatial distribution patterns and to identify spatial autocorrelation of chemical factories and accidents. Semi-variograms explained that the spatial distribution of chemical factories and accidents were spatially autocorrelated. Second, the results of the semi-variograms were used in Ordinary Kriging to estimate chemical hazard and risk level. The level values were extracted from the Ordinary Kriging result and their spatial similarity was examined by juxtaposing the two values with respect to their location. Six peaks were identified in both the hazard and risk estimation result, and the peaks correlated with major cities in Korea. Third, the estimated hazard and risk levels were classified with geometrical interval and could be classified into four quadrants: Low Hazard and Low Risk (LHLR), Low Hazard and High Risk (LHHR), High Hazard and Low Risk (HHLR), and High Hazard and High Risk (HHHR). The 4 groups identified different chemical safety management issues in Korea; relatively safe LHLR group, many chemical reseller factories were found in HHLR group, chemical transportation accidents were in the LHHR group, and an abundance of factories and accidents were in the HHHR group. Each quadrant represented different safety management obstacles in Korea, and studying spatial differences can support the establishment of an efficient risk management plan.

  4. Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system.

    Directory of Open Access Journals (Sweden)

    Ni Huang

    Full Text Available To examine the method for estimating the spatial patterns of soil respiration (Rs in agricultural ecosystems using remote sensing and geographical information system (GIS, Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI, canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2 s(-1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.

  5. Modeling Spatial Patterns of Soil Respiration in Maize Fields from Vegetation and Soil Property Factors with the Use of Remote Sensing and Geographical Information System

    Science.gov (United States)

    Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

    2014-01-01

    To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827

  6. Spatial correlation analysis of urban traffic state under a perspective of community detection

    Science.gov (United States)

    Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

    2018-05-01

    Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

  7. Factor analysis for exercise stress radionuclide ventriculography

    International Nuclear Information System (INIS)

    Hirota, Kazuyoshi; Yasuda, Mitsutaka; Oku, Hisao; Ikuno, Yoshiyasu; Takeuchi, Kazuhide; Takeda, Tadanao; Ochi, Hironobu

    1987-01-01

    Using factor analysis, a new image processing in exercise stress radionuclide ventriculography, changes in factors associated with exercise were evaluated in 14 patients with angina pectoris or old myocardial infarction. The patients were imaged in the left anterior oblique projection, and three factor images were presented on a color coded scale. Abnormal factors (AF) were observed in 6 patients before exercise, 13 during exercise, and 4 after exercise. In 7 patients, the occurrence of AF was associated with exercise. Five of them became free from AF after exercise. Three patients showing AF before exercise had aggravation of AF during exercise. Overall, the occurrence or aggravation of AF was associated with exercise in ten (71 %) of the patients. The other three patients, however, had disappearance of AF during exercise. In the last patient, none of the AF was observed throughout the study. In view of a high incidence of AF associated with exercise, the factor analysis may have the potential in evaluating cardiac reverse from the viewpoint of left ventricular wall motion abnormality. (Namekawa, K.)

  8. Explorative analysis of long time series of very high resolution spatial rainfall

    DEFF Research Database (Denmark)

    Thomassen, Emma Dybro; Sørup, Hjalte Jomo Danielsen; Scheibel, Marc

    2017-01-01

    . For each method a set of 17 variables are used to describe the properties of each event, e.g. duration, maximum volumes, spatial coverage and heterogeneity, and movement of cells. A total of 5-9 dimensions can be found in the data, which can be interpreted as a rough indication of how many independent...... simple scaling across the set of variables, i.e. the level of each variable varies signicantly, but not the overall structure of the spatial precipitation. The analysis show that there is a good potential for making a spatial weather generator for high spatio-temporal precipitation for precipitation...

  9. Analysis of spatial thermal field in a magnetic bearing

    Science.gov (United States)

    Wajnert, Dawid; Tomczuk, Bronisław

    2018-03-01

    This paper presents two mathematical models for temperature field analysis in a new hybrid magnetic bearing. Temperature distributions have been calculated using a three dimensional simulation and a two dimensional one. A physical model for temperature testing in the magnetic bearing has been developed. Some results obtained from computer simulations were compared with measurements.

  10. Spatial Analysis of Human Exposure and Vulnerability to Coastal ...

    African Journals Online (AJOL)

    Disasters in coastal cities have shown an ever-increasing frequency of occurrence. Population growth and urbanisation have increased the vulnerability of properties and societies in coastal flood-prone areas. Analysis of human exposure and vulnerability is one of the main strategies used to determine the necessary ...

  11. Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2009-08-01

    Full Text Available The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS, sequential Gaussian simulation (SGS and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE. Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management.

  12. Correction factor for hair analysis by PIXE

    International Nuclear Information System (INIS)

    Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

    1980-01-01

    The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of the energy loss of the incident particle with penetration depth, and X-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle. (orig.)

  13. Boolean Factor Analysis by Attractor Neural Network

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

    2007-01-01

    Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

  14. Correction factor for hair analysis by PIXE

    International Nuclear Information System (INIS)

    Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

    1979-06-01

    The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of energy loss of the incident particle with penetration depth, and x-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle.(Author) [pt

  15. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M.A. Wasiolek

    2003-07-25

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2003 [DIRS 160964]; BSC 2003 [DIRS 160965]; BSC 2003 [DIRS 160976]; BSC 2003 [DIRS 161239]; BSC 2003 [DIRS 161241]) contain detailed description of the model input parameters. This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs and conversion factors for the TSPA. The BDCFs will be used in performance assessment for calculating annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose from beta- and photon-emitting radionuclides.

  16. An exploratory spatial analysis of social vulnerability and smoke plum dispersion in the U.S

    Science.gov (United States)

    Cassandra Johnson Gaither; Scott Goodrick; Bryn Elise Murphy; Neelam Poudyal

    2015-01-01

    This study explores the spatial association between social vulnerability and smoke plume dispersion at the census block group level for the 13 southern states in the USDA Forest Service’s Region 8. Using environmental justice as a conceptual basis, we use Exploratory Spatial Data Analysis to identify clusters or “hot spots” for the incidence of both higher than average...

  17. Research on spatial Model and analysis algorithm for nuclear weapons' damage effects

    International Nuclear Information System (INIS)

    Liu Xiaohong; Meng Tao; Du Maohua; Wang Weili; Ji Wanfeng

    2011-01-01

    In order to realize the three dimension visualization of nuclear weapons' damage effects. Aiming at the characteristics of the damage effects data, a new model-MRPCT model is proposed, and this model can carry out the modeling of the three dimension spatial data of the nuclear weapons' damage effects. For the sake of saving on the memory, linear coding method is used to store the MRPCT model. On the basis of Morton code, spatial analysis of the damage effects is completed. (authors)

  18. Positive Analysis of Invasive Species Control as a Dynamic Spatial Process

    OpenAIRE

    Buyuktahtakin, Esra; Feng, Zhuo; Olsson, Aaryn; Frisvold, George B.; Szidarovszky, Ferenc

    2010-01-01

    This paper models control of invasive buffelgrass (Pennisetum ciliare), a fire-prone African bunchgrass spreading rapidly across the southern Arizona desert as a spatial dynamic process. Buffelgrass spreads over a gridded landscape. Weed carrying capacity, treatment costs, and damages vary over grid cells. Damage from buffelgrass depends on its spatial distribution in relation to valued resources. We conduct positive analysis of recommended heuristic strategies for buffelgrass control, evalua...

  19. Uplink Interference Analysis for Two-tier Cellular Networks with Diverse Users under Random Spatial Patterns

    OpenAIRE

    Bao, Wei; Liang, Ben

    2013-01-01

    Multi-tier architecture improves the spatial reuse of radio spectrum in cellular networks, but it introduces complicated heterogeneity in the spatial distribution of transmitters, which brings new challenges in interference analysis. In this work, we present a stochastic geometric model to evaluate the uplink interference in a two-tier network considering multi-type users and base stations. Each type of tier-1 users and tier-2 base stations are modeled as independent homogeneous Poisson point...

  20. Interannual and spatial variability of maple syrup yield as related to climatic factors

    Science.gov (United States)

    Houle, Daniel

    2014-01-01

    Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

  1. Spatial distribution of podoconiosis in relation to environmental factors in Ethiopia: a historical review.

    Science.gov (United States)

    Deribe, Kebede; Brooker, Simon J; Pullan, Rachel L; Hailu, Asrat; Enquselassie, Fikre; Reithinger, Richard; Newport, Melanie; Davey, Gail

    2013-01-01

    An up-to-date and reliable map of podoconiosis is needed to design geographically targeted and cost-effective intervention in Ethiopia. Identifying the ecological correlates of the distribution of podoconiosis is the first step for distribution and risk maps. The objective of this study was to investigate the spatial distribution and ecological correlates of podoconiosis using historical and contemporary survey data. Data on the observed prevalence of podoconiosis were abstracted from published and unpublished literature into a standardized database, according to strict inclusion and exclusion criteria. In total, 10 studies conducted between 1969 and 2012 were included, and data were available for 401,674 individuals older than 15 years of age from 229 locations. A range of high resolution environmental factors were investigated to determine their association with podoconiosis prevalence, using logistic regression. The prevalence of podoconiosis in Ethiopia was estimated at 3.4% (95% CI 3.3%-3.4%) with marked regional variation. We identified significant associations between mean annual Land Surface Temperature (LST), mean annual precipitation, topography of the land and fine soil texture and high prevalence of podoconiosis. The derived maps indicate both widespread occurrence of podoconiosis and a marked variability in prevalence of podoconiosis, with prevalence typically highest at altitudes >1500 m above sea level (masl), with >1500 mm annual rainfall and mean annual LST of 19-21°C. No (or very little) podoconiosis occurred at altitudes 24°C. Podoconiosis remains a public health problem in Ethiopia over considerable areas of the country, but exhibits marked geographical variation associated in part with key environmental factors. This is work in progress and the results presented here will be refined in future work.

  2. Spatial distribution of podoconiosis in relation to environmental factors in Ethiopia: a historical review.

    Directory of Open Access Journals (Sweden)

    Kebede Deribe

    Full Text Available An up-to-date and reliable map of podoconiosis is needed to design geographically targeted and cost-effective intervention in Ethiopia. Identifying the ecological correlates of the distribution of podoconiosis is the first step for distribution and risk maps. The objective of this study was to investigate the spatial distribution and ecological correlates of podoconiosis using historical and contemporary survey data.Data on the observed prevalence of podoconiosis were abstracted from published and unpublished literature into a standardized database, according to strict inclusion and exclusion criteria. In total, 10 studies conducted between 1969 and 2012 were included, and data were available for 401,674 individuals older than 15 years of age from 229 locations. A range of high resolution environmental factors were investigated to determine their association with podoconiosis prevalence, using logistic regression.The prevalence of podoconiosis in Ethiopia was estimated at 3.4% (95% CI 3.3%-3.4% with marked regional variation. We identified significant associations between mean annual Land Surface Temperature (LST, mean annual precipitation, topography of the land and fine soil texture and high prevalence of podoconiosis. The derived maps indicate both widespread occurrence of podoconiosis and a marked variability in prevalence of podoconiosis, with prevalence typically highest at altitudes >1500 m above sea level (masl, with >1500 mm annual rainfall and mean annual LST of 19-21°C. No (or very little podoconiosis occurred at altitudes 24°C.Podoconiosis remains a public health problem in Ethiopia over considerable areas of the country, but exhibits marked geographical variation associated in part with key environmental factors. This is work in progress and the results presented here will be refined in future work.

  3. Human-related factors regulate the spatial ecology of domestic cats in sensitive areas for conservation.

    Directory of Open Access Journals (Sweden)

    Joaquim P Ferreira

    Full Text Available BACKGROUND: Domestic cats ranging freely in natural areas are a conservation concern due to competition, predation, disease transmission or hybridization with wildcats. In order to improve our ability to design effective control policies, we investigate the factors affecting their numbers and space use in natural areas of continental Europe. METHODOLOGY/PRINCIPAL FINDINGS: We describe the patterns of cat presence, abundance and space use and analyse the associated environmental and human constraints in a well-preserved Mediterranean natural area with small scattered local farms. We failed in detecting cats in areas away from human settlements (trapping effort above 4000 trap-nights, while we captured 30 individuals near inhabited farms. We identified 130 cats, all of them in farms still in use by people (30% of 128 farms. All cats were free-ranging and very wary of people. The main factor explaining the presence of cats was the presence of people, while the number of cats per farm was mostly affected by the occasional food provisioning with human refuse and the presence of people. The home ranges of eight radio tagged cats were centred at inhabited farms. Males went furthest away from the farms during the mating season (3.8 km on average, maximum 6.3 km, using inhabited farms as stepping-stones in their mating displacements (2.2 km of maximum inter-farm distance moved. In their daily movements, cats notably avoided entering in areas with high fox density. CONCLUSIONS: The presence, abundance and space use of cats were heavily dependent on human settlements. Any strategy aiming at reducing their impact in areas of conservation concern should aim at the presence of settlements and their spatial spread and avoid any access to human refuse. The movements of domestic cats would be limited in areas with large patches of natural vegetation providing good conditions for other carnivore mammals such as red foxes.

  4. Spatial variation in egg size of a top predator: Interplay of body size and environmental factors?

    Science.gov (United States)

    Louzao, Maite; Igual, José M.; Genovart, Meritxell; Forero, Manuela G.; Hobson, Keith A.; Oro, Daniel

    2008-09-01

    It is expected that nearby populations are constrained by the same ecological features shaping in turn similarity in their ecological traits. Here, we studied the spatio-temporal variability in egg size among local populations of the critically endangered Balearic shearwater Puffinus mauretanicus, a top marine predator endemic to the western Mediterranean region. Specifically we assessed whether this trait was influenced by maternal body size, as an indicator of a genetic component, and feeding ecology (through stable-carbon and nitrogen-isotope measurements), as an indicator of environmental factors. We found that egg size varied among local populations, an unexpected result at such a small spatial scale. Body size differences at the local population level only partially explained such differences. Blood isotope measurements also differed among local populations. Values of δ 15N suggested inter-population differences in trophic level, showing a similar general pattern with egg size, and suggesting a nutritional link between them whereby egg size was affected by differences in feeding resources and/or behaviour. Values of δ 13C suggested that local populations did not differ in foraging habits with respect to benthic- vs. pelagic-based food-webs. Egg size did not vary among years as did breeding performance, suggesting that a differential temporal window could affect both breeding parameters in relation to food availability. The absence of a relationship between breeding performance and egg size suggested that larger eggs might only confer an advantage during harsh conditions. Alternatively parental quality could greatly affect breeding performance. We showed that inter-population differences in egg size could be influenced by both body size and environmental factors.

  5. Geo-spatial multi-criteria analysis for wave energy conversion system deployment

    Energy Technology Data Exchange (ETDEWEB)

    Nobre, Ana; Pacheco, Miguel [Data Centre, Instituto Hidrografico, Portuguese Navy, Rua das Trinas 49, 1249-093 Lisboa (Portugal); Jorge, Raquel; Lopes, M.F.P.; Gato, L.M.C. [IDMEC, Instituto Superior Tecnico, Technical University of Lisbon, Avenida Rovisco Pais 1, 1049-001, Lisboa (Portugal)

    2009-01-15

    The growing requirements for renewable energy production lead to the development of a new series of systems, including wave energy conversion systems. Due to their sensitivity and the impact of the aggressive marine environment, the selection of the most adequate location for these systems is a major and very important task. Several factors, such as technological limitations, environmental conditions, administrative and logistic conditions, have to be taken into account in order to support the decision for best location. This paper describes a geo-spatial multi-criteria analysis methodology, based on geographic information systems technology, for identification of the best location to deploy a wave energy farm. This methodology is not conversion system dependent and therefore can be easily customized for different systems and implementation conditions. Selection factors can include, for example, ocean depth, sea bottom type, existing underwater cables, marine protected areas, ports location, shoreline, power grid location, military exercise areas, climatology of wave significant height, period and power. A case study demonstrating this methodology is presented, for an area offshore the Portuguese southwest coast. The system output allows a clear differential identification of the best spots for implementing a wave energy farm. It is not just a simple Boolean result showing valid and invalid locations, but a layer with a valued suitability for farm deployment. (author)

  6. Geo-Spatial Multi-criteria Analysis for Wave Energy System Deployment

    Energy Technology Data Exchange (ETDEWEB)

    Nobre, Ana; Pacheco, Miguel (Instituto Hidrografico, Rua das Trinas, 49, Lisboa (PT)); Jorge, Raquel Lopes, M. F. P.; Gato, L. M. C. (IDMEC, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, Lisboa (PT))

    2007-07-01

    The growing requirements for renewable energy production lead to the development of a new series of systems, including wave energy conversion systems. Due to their sensitivity and the impact of the aggressive marine environment, the selection of the most adequate location for these systems is a major and very important task. Several factors, such as technological limitations, environmental conditions, administrative and logistic conditions, have to be taken into account in order to support the decision for best location. This paper describes a geo-spatial multi-criteria analysis methodology, based on geographic information systems technology, for selection of the best location to deploy a wave energy farm. This methodology is not conversion system dependent and therefore can be easily customized for different systems and conditions. Selection factors can include, for example, ocean depth, bottom type, underwater cables, marine protected areas, ports location, shoreline, power grid location, military exercise areas, climatology of wave significant height, period and direction. A case study demonstrating this methodology is presented, for an area offshore the Portuguese southwest coast. The system output allows a clear identification of the best spots for a wave energy farm. It is not just a simple Boolean result showing valid and invalid locations, but a layer with a graded suitability for farm deployment.

  7. Spatial relationship of phosphorylated epidermal growth factor receptor and activated AKT in head and neck squamous cell carcinoma

    International Nuclear Information System (INIS)

    Nijkamp, Monique M.; Hoogsteen, Ilse J.; Span, Paul N.; Takes, Robert P.; Lok, Jasper; Rijken, Paul F.; Kogel, Albert J. van der; Bussink, Johan; Kaanders, Johannes H.A.M.

    2011-01-01

    Background: Overexpression of EGFR correlates with decreased survival after radiotherapy in head and neck squamous cell carcinoma (HNSCC). However, the contribution of the activated form, pEGFR, and its downstream signaling (PI3-K/AKT) pathway is not clear yet. Methods: Fifty-eight patients with HNSCC were included in the study. pEGFR, pAKT, hypoxia, and vessels were visualized using immunohistochemistry. Fractions (defined as the tumor area positive for the respective markers relative to the total tumor area) were calculated by automated image analysis and related to clinical outcome. Results: Both pEGFR (median 0.6%, range 0–34%) and pAKT (median 1.8%, range 0–16%) expression differed between tumors. Also, a large variation in hypoxia was found (median pimonidazole fraction 3.9% 0–20%). A significant correlation between pEGFR and pAKT (r s 0.44, p = 0.004) was seen, however, analysis revealed that this was not always based on spatial coexpression. Low pAKT expression was associated with increased risk of regional recurrence (p < 0.05, log-rank) and distant metastasis (p = 0.04). Conclusion: The correlation between expression of pEGFR and pAKT is indicative of activation of the PI3-K/AKT pathway through phosphorylation of EGFR. Since not all tumors show coexpression to the same extent, other factors must be involved in the activation of this pathway as well.

  8. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M.A. Wasiolek

    2005-04-28

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis

  9. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M.A. Wasiolek

    2005-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objectives of this analysis are to develop BDCFs for the

  10. Analysis of Participatory Processes in the Formulation of Spatial Plan for Nature Park Medvednica

    Directory of Open Access Journals (Sweden)

    Nataša Lovrić

    2011-12-01

    Full Text Available Background and Purpose: This research aims to assess the stakeholders influence on spatial planning of Nature Park Medvednica, a mountainous protected area adjacent to Zagreb, the capital city of Croatia, which tries to hold on to the pressure of the urbanization. Because of the inexistence of spatial plan which is required with the Croatian laws, its area was significantly decreased in 2009. This kind of research has not been done yet for NP Medvednica, and it will provide a contribution to the process of developing a spatial Plan for NP Medvednica. Material and Methods: The study was conducted in the framework of stakeholder analysis, for which a series of in-depth interviews with - stakeholders were performed, and documents concerning the spatial plan were analysed. The data gained was processed in MAXQDA software for qualitative analysis. Results and Conclusion: The gathered data explains which are the disadvantages of the tree processes of the formulation of the spatial plan and is giving a possible theoretical explanation or a model which can be implied in any decision making process involving stakeholders in natural resources management in within a given political and cultural context. Description of the past and current spatial planning situation of the NP Medvednica was specified and issues and stakeholders concerning the creation of the spatial plan where identified. The key conflict areas that affect the formulation of spatial plan were detected and examined. The level of participation of stakeholders in the context of fulfilment of their own interests was assessed as well as the influence on participation processes of different stakeholder groups on the formulation of the spatial plan. In order to have proper citizens and stakeholders participation some changes in the legislation should take place.

  11. Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement

    Directory of Open Access Journals (Sweden)

    Ali Soleymani

    2014-06-01

    Full Text Available Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the ``reliable scale'' is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and

  12. Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

    NARCIS (Netherlands)

    Harbers, I.; Ingram, M.C.

    Mixed-methods designs, especially those where cases selected for small-N analysis (SNA) are nested within a large-N analysis (LNA), have become increasingly popular. Yet, since the LNA in this approach assumes that units are independently distributed, such designs are unable to account for spatial

  13. Confirmatory factor analysis using Microsoft Excel.

    Science.gov (United States)

    Miles, Jeremy N V

    2005-11-01

    This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

  14. Spatial Analysis of Placement and Topography of Early Iron Age Settlements in Chuvash Sura Region

    Directory of Open Access Journals (Sweden)

    Fedulov Mikhail I.

    2018-03-01

    Full Text Available An analysis of the arrangement system of ancient fortifications dating back to the Early Iron Age allowed to distinguish a special coastal group of sites located on the right bank of the Sura river within the boundaries of the Chuvash Republic. Determination of the topographical features of settlement arrangement, connection between fortified and unfortified settlements, and residential areas are the primary objectives of the spatial analysis. The authors established that the central sites of the micro-regions are settlements surrounded with several satellites located within two kilometers from the settlements. They can be individual or group sites consisting of two sites located in close proximity to each other. The cartographic method allowed to distinguish a group of coastal monuments clearly associated with the riverbank of the Sura. The settlements differ from other sites by their size and diverse system of fortifications. The association between settlements and fortifications is traced by the authors on the example of a group of sites in the vicinity of Ilyina Gora, Vyselok No. 1 and No. 2 in the Yadrinsky district. The gravitational model reveals a weak association factor due to the small size of the sites and their remoteness from each other.

  15. Toward the modeling of land use change: A spatial analysis using remote sensing and historical data

    Science.gov (United States)

    Honea, R. B.

    1976-01-01

    It was hypothesized that the chronological observation of land use change could be shown to follow a predictable pattern and these patterns could be correlated with other statistical data to develop transition probabilities suitable for modeling purposes. A literature review and preliminary research, however, indicated a totally stochastic approach was not practical for simulating land use change and thus a more deterministic approach was adopted. The approach used assumes the determinants of the land use conversion process are found in the market place, where land transactions among buyers and sellers occur. Only one side of the market transaction process is studied, however, namely, the purchaser's desires in securing an ideal or suitable site. The problem was to identify the ideal qualities, quantities or attributes desired in an industrial site (or housing development), and to formulate a general algorithmic statement capable of identifying potential development sites. Research procedures involved developing a list of variables previously noted in the literature to be related to site selection and streamlining the list to a set suitable for statistical testing. A sample of 157 industries which have located (or relocated) in the 16-county Knoxville metropolitan region since 1950 was selected for industrial location analysis. Using NASA color infrared photography and Tennessee Valley Authority historical aerial photography, data were collected on the spatial characteristics of each industrial location event. These data were then subjected to factor analysis to determine the interrelations of variables.

  16. Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

    Science.gov (United States)

    Engström, Emma; Mörtberg, Ulla; Karlström, Anders; Mangold, Mikael

    2017-06-01

    This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model ( p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

  17. Environmental factors at different spatial scales governing soil fauna community patterns in fragmented forests.

    NARCIS (Netherlands)

    Martins da Silva, P.; Berg, M.P.; Serrano, A.R.M.; Dubs, F.; Sousa, J.P.

    2012-01-01

    Spatial and temporal changes in community structure of soil organisms may result from a myriad of processes operating at a hierarchy of spatial scales, from small-scale habitat conditions to species movements among patches and large-sale landscape features. To disentangle the relative importance of

  18. Spatial Analysis of Linear Structures in the Exploration of Groundwater

    Directory of Open Access Journals (Sweden)

    Abdramane Dembele

    2017-11-01

    Full Text Available The analysis of linear structures on major geological formations plays a crucial role in resource exploration in the Inner Niger Delta. Highlighting and mapping of the large lithological units were carried out using image fusion, spectral bands (RGB coding, Principal Component Analysis (PCA, and band ratio methods. The automatic extraction method of linear structures has permitted the obtaining of a structural map with 82,659 linear structures, distributed on different stratigraphic stages. The intensity study shows an accentuation in density over 12.52% of the total area, containing 22.02% of the linear structures. The density and nodes (intersections of fractures formed by the linear structures on the different lithologies allowed to observe the behavior of the region’s aquifers in the exploration of subsoil resources. The central density, in relation to the hydrographic network of the lowlands, shows the conditioning of the flow and retention of groundwater in the region, and in-depth fluids. The node areas and high-density linear structures, have shown an ability to have rejections in deep (pores that favor the formation of structural traps for oil resources.

  19. Malaria prevalence, spatial clustering and risk factors in a low endemic area of Eastern Rwanda: a cross sectional study

    NARCIS (Netherlands)

    Rulisa, Stephen; Kateera, Fredrick; Bizimana, Jean Pierre; Agaba, Steven; Dukuzumuremyi, Javier; Baas, Lisette; de Dieu Harelimana, Jean; Mens, Petra F.; Boer, Kimberly R.; de Vries, Peter J.

    2013-01-01

    Rwanda reported significant reductions in malaria burden following scale up of control intervention from 2005 to 2010. This study sought to; measure malaria prevalence, describe spatial malaria clustering and investigate for malaria risk factors among health-centre-presumed malaria cases and their

  20. Quantifying the impact of environmental factors on arthropod communities in agricultural landscapes across organizational levels and spatial scales

    NARCIS (Netherlands)

    Schweiger, O.; Maelfait, J.P.; Wingerden, van W.K.R.E.; Hendrickx, F.; Billeter, R.; Speelmans, M.; Augenstein, I.; Aukema, B.; Aviron, S.; Bailey, D.; Bukacek, R.; Burel, F.; Diekötter, T.; Dirksen, J.; Frenzel, M.; Herzog, F.; Liira, J.; Roubalova, M.; Bugter, R.J.F.

    2005-01-01

    1. In landscapes influenced by anthropogenic activities, such as intensive agriculture, knowledge of the relative importance and interaction of environmental factors on the composition and function of local communities across a range of spatial scales is important for maintaining biodiversity. 2. We

  1. DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

    International Nuclear Information System (INIS)

    M.A. Wasiolek

    2005-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objective of this analysis was to develop the BDCFs for the volcanic

  2. Predicted stand volume for Eucalyptus plantations by spatial analysis

    Science.gov (United States)

    Latifah, Siti; Teodoro, RV; Myrna, GC; Nathaniel, CB; Leonardo, M. F.

    2018-03-01

    The main objective of the present study was to assess nonlinear models generated by integrating the stand volume growth rate to estimate the growth and yield of Eucalyptus. The primary data was done for point of interest (POI) of permanent sample plots (PSPs) and inventory sample plots, in Aek Nauli sector, Simalungun regency,North Sumatera Province,Indonesia. from December 2008- March 2009. Today,the demand for forestry information has continued to grow over recent years. Because many forest managers and decision makers face complex decisions, reliable information has become the necessity. In the assessment of natural resources including plantation forests have been widely used geospatial technology.The yield of Eucalyptus plantations represented by merchantable volume as dependent variable while factors affecting yield namely stands variables and the geographic variables as independent variables. The majority of the areas in the study site has stand volume class 0 - 50 m3/ha with 16.59 ha or 65.85 % of the total study site.

  3. Aspects of the incorporation of spatial data into radioecological and restoration analysis

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.; Arkhipov, A.; Voigt, G.

    2002-01-01

    In the last decade geographical information systems have been increasingly used to incorporate spatial data into radioecological analysis. This has allowed the development of models with spatially variable outputs. Two main approaches have been adopted in the development of spatial models. Empirical Tag based models applied across a range of spatial scales utilize underlying soil type maps and readily available radioecological data. Soil processes can also be modelled to allow the dynamic prediction of radionuclide soil to plant transfer. We discuss a dynamic semi-mechanistic radiocaesium soil to plant-transfer model, which utilizes readily available spatially variable soil parameters. Both approaches allow the identification of areas that may be vulnerable to radionuclide deposition, therefore enabling the targeting of intervention measures. Improved estimates of radionuclide fluxes and ingestion doses can be achieved by incorporating spatially varying inputs such as agricultural production and dietary habits in to these models. In this paper, aspects of such models, including data requirements, implementation and outputs are discussed and critically evaluated. The relative merits and disadvantages of the two spatial model approaches adopted within radioecology are discussed. We consider the usefulness of such models to aid decision-makers and access the requirements and potential of further application within radiological protection. (author)

  4. Spatial Analysis and Safety Assessment of Social and Economic Development of Small and Medium Cities

    Directory of Open Access Journals (Sweden)

    Elena Anatolyevna Orekhova

    2016-12-01

    Full Text Available The article discusses the spatial patterns of socio-economic development of small and medium-sized cities in the Volgograd region. We know that small and medium-sized cities as spatial socio-economic systems are not only the support frame of settlement, but the main “engine” of innovative impulses for the surrounding periphery. The scientific novelty of the study consists in the effort to implement a spatial approach to the assessment of the economic security of small and medium-sized cities (SCR. The content of the economic security of cities is determined by two system characteristics of the socio-economic system: economic activity (EA and quality of life (QL of the urban population, or SCR = F (EA; QL. For finding spatial patterns in GIS, great interest is in investigating the environment of each city by calculating the local statistical characteristics of geo-variability which allow assessing trends of spatial variation of the six components of security (human security, technosphere safety, environmental safety, etc., local variations in emissions and their values indicators Ki. The successful solution of these problems is possible with the use of tools of exploratory spatial data analysis (ESDA in ARCGIS, and in particular, the Voronoy maps. The spatial approach has allowed to perform an integrated assessment of the economic security and to evaluate safety risks in small and medium-sized cities of the Volgograd region with the security system of indicators.

  5. Spatial and temporal analysis of dry spells in Greece

    Science.gov (United States)

    Anagnostopoulou, Chr.; Maheras, P.; Karacostas, T.; Vafiadis, M.

    A spatio-temporal analysis of the dry spells that occur in the Greek area is carried out for an extended period of 40 years (1958-1997). The dry spells can be defined as a number of consecutive days with no rain. The number of days defines the length of the dry spells. The longest spells are identified in central (Cyclades) and the south-east Aegean Sea whereas dry spells with the minimum length are shown over the north-west of the Greek area that reflects the significance of the latitude and the topography. Negative Binomial Distribution and Markov Chains of second order have been used to fit the duration of the dry spells of different lengths. The study of the seasonal and annual distribution of the frequency of occurrence of dry spells revealed that the dry spells in Greece depict a seasonal character, while medium and long sequences are associated with the duration and hazards of drought.

  6. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  7. Analysis of mineral phases in coal utilizing factor analysis

    International Nuclear Information System (INIS)

    Roscoe, B.A.; Hopke, P.K.

    1982-01-01

    The mineral phase inclusions of coal are discussed. The contribution of these to a coal sample are determined utilizing several techniques. Neutron activation analysis in conjunction with coal washability studies have produced some information on the general trends of elemental variation in the mineral phases. These results have been enhanced by the use of various statistical techniques. The target transformation factor analysis is specifically discussed and shown to be able to produce elemental profiles of the mineral phases in coal. A data set consisting of physically fractionated coal samples was generated. These samples were analyzed by neutron activation analysis and then their elemental concentrations examined using TTFA. Information concerning the mineral phases in coal can thus be acquired from factor analysis even with limited data. Additional data may permit the resolution of additional mineral phases as well as refinement of theose already identified

  8. A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

    Directory of Open Access Journals (Sweden)

    An Gie Yong

    2013-10-01

    Full Text Available The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

  9. Spatial-temporal data model and fractal analysis of transportation network in GIS environment

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua; Li, Yangdong

    2008-10-01

    How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

  10. HIV/AIDS in Oyo State, Nigeria: Analysis of Spatial Pattern of ...

    African Journals Online (AJOL)

    DrNneka

    recognized in 1981 in New York, a number of factors, habits and practices have .... poses as a stimulus which catalyzes the manifestation of the symptoms of. AIDS as ... the study on the geographical or spatial distribution of HIV/AIDS cases in.

  11. Spatial prevalence of intellectual disability and related socio-demographic factors in Iran, using GWR: Case study (2006

    Directory of Open Access Journals (Sweden)

    Ali Goli

    2014-01-01

    Full Text Available Background: Although intellectual disability (ID is a common disability in Iran, there is no investigation on the spatial distribution pattern of these patients in national level and the spatial maps for recognition the areas with higher prevalence of IDs and local neighborhoods of these regions or effect of socio-demographic factor on this scattering is not still available. This proposition motivated us to assess the population with ID in our country. Methods: In a cross-sectional study, we applied Moran′s Index (Moran′s I which includes information about the strength of the neighboring association between counties, as global univariate distribution assessment. A geographically weighted regression was used to explore relation between ID patient′s prevalence and some socio-demographic factors (migration and illiteracy rate, physician number (PN/10,000 people and health-care centers (HCCs/10,000 people. Results: We found that spatial clusters of ID patients exist among Iran counties (Moran′s I = 0.36, P 0.3. Conclusions: According to the results, our Initial hypothesis about the existence of spatial clusters in distribution of people with ID in Iran was proven. Spatial autocorrelation between migration and illiteracy rate and prevalence of patients with ID was shown and was in agreement with our hypothesis. However, our supposition that the prevalence should have inverse relationship with PN and HCC was rejected.

  12. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle

  13. Neural activity associated with metaphor comprehension: spatial analysis.

    Science.gov (United States)

    Sotillo, María; Carretié, Luis; Hinojosa, José A; Tapia, Manuel; Mercado, Francisco; López-Martín, Sara; Albert, Jacobo

    2005-01-03

    Though neuropsychological data indicate that the right hemisphere (RH) plays a major role in metaphor processing, other studies suggest that, at least during some phases of this processing, a RH advantage may not exist. The present study explores, through a temporally agile neural signal--the event-related potentials (ERPs)--, and through source-localization algorithms applied to ERP recordings, whether the crucial phase of metaphor comprehension presents or not a RH advantage. Participants (n=24) were submitted to a S1-S2 experimental paradigm. S1 consisted of visually presented metaphoric sentences (e.g., "Green lung of the city"), followed by S2, which consisted of words that could (i.e., "Park") or could not (i.e., "Semaphore") be defined by S1. ERPs elicited by S2 were analyzed using temporal principal component analysis (tPCA) and source-localization algorithms. These analyses revealed that metaphorically related S2 words showed significantly higher N400 amplitudes than non-related S2 words. Source-localization algorithms showed differential activity between the two S2 conditions in the right middle/superior temporal areas. These results support the existence of an important RH contribution to (at least) one phase of metaphor processing and, furthermore, implicate the temporal cortex with respect to that contribution.

  14. Spatial temporal analysis of urban heat hazard in Tangerang City

    Science.gov (United States)

    Wibowo, Adi; Kuswantoro; Ardiansyah; Rustanto, Andry; Putut Ash Shidiq, Iqbal

    2016-11-01

    Urban heat is a natural phenomenon which might caused by human activities. The human activities were represented by various types of land-use such as urban and non-urban area. The aim of this study is to identify the urban heat behavior in Tangerang City as it might threats the urban environment. This study used three types of remote sensing data namely, Landsat TM, Landsat ETM+ and Landsat OLI-TIRS, to capture the urban heat behavior and to analysis the urban heat signature of Tangerang City in 2001, 2012, 2013, 2014, 2015 and 2016. The result showed that urban heat signature change dynamically each month based on the sun radiation. The urban heat island covered only small part of Tangerang City in 2001, but it was significantly increased and reached 50% of the area in 2012. Based on the result on urban heat signature, the threshold for threatening condition is 30 oC which recognized from land surface temperature (LST). The effective temperature (ET) index explains that condition as warm, uncomfortable, increase stress due to sweating and blood flow and may causing cardiovascular disorder.

  15. Is analysis of biological materials with nm spatial resolution possible?

    International Nuclear Information System (INIS)

    Warley, Alice

    2006-01-01

    Cells are bounded by a membrane, the plasma membrane, subcompartments within cells are also delineated by membranes, these membranes contain transporters that regulate the flow of ions across them. Fluxes of ions across the membranes underlie many of the basic properties of living material such as excitability and movement. Breakdown of membrane function ultimately leads to cell death. EM microanalysis has been instrumental in gaining understanding of how changes in element distribution affect cell behaviour and cell survival. The main problem that biologists face in undertaking such studies is that of specimen preparation. Cells consist mainly of water that needs to be either removed or stabilised before analysis can take place. Cryotechniques, fixation by rapid freezing followed by sectioning at low temperatures and freeze-drying of the sections have proved to be a reliable method for the study of intracellular element concentrations. These techniques have been used to show that elements are confined in different compartments within cells and produced results to support a new theory on the mechanism by which neutrophils kill bacteria. They have also shown that disturbance of the ionic content of mitochondria is one of the first signs in the pathway to cell death

  16. Promotional archipelagoes of change. Spatial analysis of Dinosauro

    International Nuclear Information System (INIS)

    Fratini, Noemi; Nieto, Silvia

    2009-01-01

    During the last decades, the post industrial Latin American cities have become important economic centers in the world. Their integration into the world economy helped those cities become in the favorite places for the linking functions and activities to the world nets of commerce, productions culture, etc. These urban centers which are expanding gradually into segmented developing areas have caused an apparent space duality between the private and public activities as it can be seen though the differential access to goods and services by the society. At present, there has been an increase in cultural activities which form change promoting archipelagoes subject to several dimensions of analysis. The inequity in the distribution of economic and educational resources causes unequal ways of access to consumption of these areas of cultural production, and of goods and services, what gives place to situations of social exclusion and inclusion. To understand this fact related to money behavior, we have selected an area situated in the northwest of Cordoba capital city, in Argentina, which is a shopping mall called Dinosaurio Group. In this essay we present an exploration into the conflicts caused to the cities through the expansion of the segmented urban centers, promoters of change, and its relationship with the public and private space.

  17. Determining the Number of Factors in P-Technique Factor Analysis

    Science.gov (United States)

    Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

    2017-01-01

    Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

  18. Disruptive Event Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. A. Wasiolek

    2003-07-21

    This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in

  19. Disruptive Event Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. A. Wasiolek

    2003-01-01

    This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in the biosphere. The biosphere process

  20. Spatial distribution and risk factors of Brucellosis in Iberian wild ungulates

    Directory of Open Access Journals (Sweden)

    de la Fuente José

    2010-03-01

    Full Text Available Abstract Background The role of wildlife as a brucellosis reservoir for humans and domestic livestock remains to be properly established. The aim of this work was to determine the aetiology, apparent prevalence, spatial distribution and risk factors for brucellosis transmission in several Iberian wild ungulates. Methods A multi-species indirect immunosorbent assay (iELISA using Brucella S-LPS antigen was developed. In several regions having brucellosis in livestock, individual serum samples were taken between 1999 and 2009 from 2,579 wild bovids, 6,448 wild cervids and4,454 Eurasian wild boar (Sus scrofa, and tested to assess brucellosis apparent prevalence. Strains isolated from wild boar were characterized to identify the presence of markers shared with the strains isolated from domestic pigs. Results Mean apparent prevalence below 0.5% was identified in chamois (Rupicapra pyrenaica, Iberian wild goat (Capra pyrenaica, and red deer (Cervus elaphus. Roe deer (Capreolus capreolus, fallow deer (Dama dama, mouflon (Ovis aries and Barbary sheep (Ammotragus lervia tested were seronegative. Only one red deer and one Iberian wild goat resulted positive in culture, isolating B. abortus biovar 1 and B. melitensis biovar 1, respectively. Apparent prevalence in wild boar ranged from 25% to 46% in the different regions studied, with the highest figures detected in South-Central Spain. The probability of wild boar being positive in the iELISA was also affected by age, age-by-sex interaction, sampling month, and the density of outdoor domestic pigs. A total of 104 bacterial isolates were obtained from wild boar, being all identified as B. suis biovar 2. DNA polymorphisms were similar to those found in domestic pigs. Conclusions In conclusion, brucellosis in wild boar is widespread in the Iberian Peninsula, thus representing an important threat for domestic pigs. By contrast, wild ruminants were not identified as a significant brucellosis reservoir for

  1. The impact of expert knowledge on natural hazard susceptibility assessment using spatial multi-criteria analysis

    Science.gov (United States)

    Karlsson, Caroline; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve

    2016-04-01

    Road and railway networks are one of the key factors to a country's economic growth. Inadequate infrastructural networks could be detrimental to a society if the transport between locations are hindered or delayed. Logistical hindrances can often be avoided whereas natural hindrances are more difficult to control. One natural hindrance that can have a severe adverse effect on both infrastructure and society is flooding. Intense and heavy rainfall events can trigger other natural hazards such as landslides and debris flow. Disruptions caused by landslides are similar to that of floods and increase the maintenance cost considerably. The effect on society by natural disasters is likely to increase due to a changed climate with increasing precipitation. Therefore, there is a need for risk prevention and mitigation of natural hazards. Determining susceptible areas and incorporating them in the decision process may reduce the infrastructural harm. Spatial multi-criteria analysis (SMCA) is a part of decision analysis, which provides a set of procedures for analysing complex decision problems through a Geographic Information System (GIS). The objective and aim of this study was to evaluate the usefulness of expert judgements for inundation, landslide and debris flow susceptibility assessments through a SMCA approach using hydrological, geological and land use factors. The sensitivity of the SMCA model was tested in relation to each perspective and impact on the resulting susceptibility. A least cost path function was used to compare new alternative road lines with the existing ones. This comparison was undertaken to identify the resulting differences in the susceptibility assessments using expert judgements as well as historic incidences of flooding and landslides in order to discuss the usefulness of the model in road planning.

  2. Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

    Directory of Open Access Journals (Sweden)

    Jiwei Li

    2016-11-01

    Full Text Available Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

  3. Exploratory Bi-Factor Analysis: The Oblique Case

    Science.gov (United States)

    Jennrich, Robert I.; Bentler, Peter M.

    2012-01-01

    Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

  4. Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

    Science.gov (United States)

    Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

    2014-11-01

    Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

  5. Spatial Analysis of Macro Economic in Central Java (PDRB Analysis in Year 1993-2003

    Directory of Open Access Journals (Sweden)

    Eddy Kiswanto

    2016-12-01

    Full Text Available This paper aims to study the spatial analysis macroeconomics condition in central Java from 1993-2001 base on PDRB analysis. Central Java stands in the last position in the economic in Central Java based on PDRB variable and economic growth is in the lowest category in the comparation with another provinces in Java. This is reason why Central Java is categorized as "LL" (Low low. One of the prime sectors in Central Java is small medium scale enterprises which is dominated 30% of national market, but since the economic crisis stroke in 1997 the manufacture sector, especially industry and processing had collapse. In 1996-1997, the level of manufacture growth increased to 14.4% but then decreased until minus 19.3%. This condition caused by bankruptcy to many of the industries. The poverty profile in Central Java from 1999-2003 is average 23.3% from the total population every years. Central Java stepping to number 2 in level of poverty absolute number 1. In poverty relativity level, Central Java became number 1 in Java from 2002-2003 with the level of poverty reached above the national average. This fact shows the unsuccessfully effort in reducing the poverty level.

  6. Spatially resolved δ13C analysis using laser ablation isotope ratio mass spectrometry

    Science.gov (United States)

    Moran, J.; Riha, K. M.; Nims, M. K.; Linley, T. J.; Hess, N. J.; Nico, P. S.

    2014-12-01

    Inherent geochemical, organic matter, and microbial heterogeneity over small spatial scales can complicate studies of carbon dynamics through soils. Stable isotope analysis has a strong history of helping track substrate turnover, delineate rhizosphere activity zones, and identifying transitions in vegetation cover, but most traditional isotope approaches are limited in spatial resolution by a combination of physical separation techniques (manual dissection) and IRMS instrument sensitivity. We coupled laser ablation sampling with isotope measurement via IRMS to enable spatially resolved analysis over solid surfaces. Once a targeted sample region is ablated the resulting particulates are entrained in a helium carrier gas and passed through a combustion reactor where carbon is converted to CO2. Cyrotrapping of the resulting CO2 enables a reduction in carrier gas flow which improves overall measurement sensitivity versus traditional, high flow sample introduction. Currently we are performing sample analysis at 50 μm resolution, require 65 ng C per analysis, and achieve measurement precision consistent with other continuous flow techniques. We will discuss applications of the laser ablation IRMS (LA-IRMS) system to microbial communities and fish ecology studies to demonstrate the merits of this technique and how similar analytical approaches can be transitioned to soil systems. Preliminary efforts at analyzing soil samples will be used to highlight strengths and limitations of the LA-IRMS approach, paying particular attention to sample preparation requirements, spatial resolution, sample analysis time, and the types of questions most conducive to analysis via LA-IRMS.

  7. Exploratory Bi-factor Analysis: The Oblique Case

    OpenAIRE

    Jennrich, Robert L.; Bentler, Peter M.

    2011-01-01

    Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bi-factor rotation criterion designed to produce a rotated loading mat...

  8. Sources of variation in under-5 mortality across sub-Saharan Africa: a spatial analysis.

    Science.gov (United States)

    Burke, Marshall; Heft-Neal, Sam; Bendavid, Eran

    2016-12-01

    Detailed spatial understanding of levels and trends in under-5 mortality is needed to improve the targeting of interventions to the areas of highest need, and to understand the sources of variation in mortality. To improve this understanding, we analysed local-level information on child mortality across sub-Saharan Africa between 1980-2010. We used data from 82 Demographic and Health Surveys in 28 sub-Saharan African countries, including the location and timing of 3·24 million childbirths and 393 685 deaths, to develop high-resolution spatial maps of under-5 mortality in the 1980s, 1990s, and 2000s. These estimates were at a resolution of 0·1 degree latitude by 0·1 degree longitude (roughly 10 km × 10 km). We then analysed this spatial information to distinguish within-country versus between-country sources of variation in mortality, to examine the extent to which declines in mortality have been accompanied by convergence in the distribution of mortality, and to study localised drivers of mortality differences, including temperature, malaria burden, and conflict. In our sample of sub-Saharan African countries from the 1980s to the 2000s, within-country differences in under-5 mortality accounted for 74-78% of overall variation in under-5 mortality across space and over time. Mortality differed significantly across only 8-15% of country borders, supporting the role of local, rather than national, factors in driving mortality patterns. We found that by the end of the study period, 23% of the eligible children in the study countries continue to live in mortality hotspots-areas where, if current trends continue, the Sustainable Developent Goals mortality targets will not be met. In multivariate analysis, within-country mortality levels at each pixel were significantly related to local temperature, malaria burden, and recent history of conflict. Our findings suggest that sub-national determinants explain a greater portion of under-5 mortality than do country

  9. Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

    Science.gov (United States)

    Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

    2017-02-01

    The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

  10. Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

    Science.gov (United States)

    Maksimova, L. A.; Ryabukho, P. V.; Mysina, N. Yu.; Lyakin, D. V.; Ryabukho, V. P.

    2018-04-01

    We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

  11. Sex differences in visual-spatial working memory: A meta-analysis.

    Science.gov (United States)

    Voyer, Daniel; Voyer, Susan D; Saint-Aubin, Jean

    2017-04-01

    Visual-spatial working memory measures are widely used in clinical and experimental settings. Furthermore, it has been argued that the male advantage in spatial abilities can be explained by a sex difference in visual-spatial working memory. Therefore, sex differences in visual-spatial working memory have important implication for research, theory, and practice, but they have yet to be quantified. The present meta-analysis quantified the magnitude of sex differences in visual-spatial working memory and examined variables that might moderate them. The analysis used a set of 180 effect sizes from healthy males and females drawn from 98 samples ranging in mean age from 3 to 86 years. Multilevel meta-analysis was used on the overall data set to account for non-independent effect sizes. The data also were analyzed in separate task subgroups by means of multilevel and mixed-effects models. Results showed a small but significant male advantage (mean d = 0.155, 95 % confidence interval = 0.087-0.223). All the tasks produced a male advantage, except for memory for location, where a female advantage emerged. Age of the participants was a significant moderator, indicating that sex differences in visual-spatial working memory appeared first in the 13-17 years age group. Removing memory for location tasks from the sample affected the pattern of significant moderators. The present results indicate a male advantage in visual-spatial working memory, although age and specific task modulate the magnitude and direction of the effects. Implications for clinical applications, cognitive model building, and experimental research are discussed.

  12. Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

    Science.gov (United States)

    König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

    2015-04-01

    Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we

  13. Research on the spatial analysis method of seismic hazard for island

    International Nuclear Information System (INIS)

    Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

    2017-01-01

    Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform. (paper)

  14. Research on the spatial analysis method of seismic hazard for island

    Science.gov (United States)

    Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

    2017-05-01

    Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform.

  15. Factor Analysis for Finding Invariant Neural Descriptors of Human Emotions

    Directory of Open Access Journals (Sweden)

    Vitor Pereira

    2018-01-01

    Full Text Available A major challenge in decoding human emotions from electroencephalogram (EEG data is finding representations that are invariant to inter- and intrasubject differences. Most of the previous studies are focused in building an individual discrimination model for every subject (subject dependent model. Building subject-independent models is a harder problem due to the high data variability between different subjects and different experiments with the same subject. This paper explores, for the first time, the Factor Analysis as an efficient technique to extract temporal and spatial EEG features suitable to build brain-computer interface for decoding human emotions across various subjects. Our findings show that early waves (temporal window of 200–400 ms after the stimulus onset carry more information about the valence of the emotion. Also, spatial location of features, with a stronger impact on the emotional valence, occurs in the parietal and occipital regions of the brain. All discrimination models (NN, SVM, kNN, and RF demonstrate better discrimination rate of the positive valence. These results match closely experimental psychology hypothesis that, during early periods after the stimulus presentation, the brain response—to images with highly positive valence—is stronger.

  16. An update to the analysis of the Canadian Spatial Reference System

    Science.gov (United States)

    Ferland, R.; Piraszewski, M.; Craymer, M.

    2015-12-01

    The primary objective of the Canadian Spatial Reference System (CSRS) is to provide users access to a consistent geo-referencing infrastructure over the Canadian landmass. Global Navigation Satellite System (GNSS) positioning accuracy requirements ranges from meter level to mm level (e.g.: crustal deformation). The highest level of the Canadian infrastructure consist of a network of continually operating GPS and GNSS receivers, referred to as active control stations. The network includes all Canadian public active control stations, some bordering US CORS and Alaska stations, Greenland active control stations, as well as a selection of IGS reference frame stations. The Bernese analysis software is used for the daily processing and the combination into weekly solutions which form the basis for this analysis. IGS weekly final orbit, Earth Rotation parameters (ERP's) and coordinates products are used in the processing. For the more demanding users, the time dependant changes of station coordinates is often more important.All station coordinate estimates and related covariance information is used in this analysis. For each input solution, variance factor, translation, rotation and scale (and if needed their rates) or subsets of these are estimated. In the combination of these weekly solutions, station positions and velocities are estimated. Since the time series from the stations in these networks often experience changes in behavior, new (or reuse of) parameters are generally used in these situations. As is often the case with real data, unrealistic coordinates may occur. Automatic detection and removal of outliers is used in these cases. For the transformation, position and velocity parameters loose apriori estimates and uncertainties are provided. Alignment using the usual Helmert transformation to the latest IGb08 realization of ITRF is also performed during the adjustment.

  17. Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

    Science.gov (United States)

    Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

    2016-04-01

    We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

  18. Analysis of the spatial variability of crop yield and soil properties in small agricultural plots

    Directory of Open Access Journals (Sweden)

    Vieira Sidney Rosa

    2003-01-01

    Full Text Available The objective of this study was to assess spatial variability of soil properties and crop yield under no tillage as a function of time, in two soil/climate conditions in São Paulo State, Brazil. The two sites measured approximately one hectare each and were cultivated with crop sequences which included corn, soybean, cotton, oats, black oats, wheat, rye, rice and green manure. Soil fertility, soil physical properties and crop yield were measured in a 10-m grid. The soils were a Dusky Red Latossol (Oxisol and a Red Yellow Latossol (Ultisol. Soil sampling was performed in each field every two years after harvesting of the summer crop. Crop yield was measured at the end of each crop cycle, in 2 x 2.5 m sub plots. Data were analysed using semivariogram analysis and kriging interpolation for contour map generation. Yield maps were constructed in order to visually compare the variability of yields, the variability of the yield components and related soil properties. The results show that the factors affecting the variability of crop yield varies from one crop to another. The changes in yield from one year to another suggest that the causes of variability may change with time. The changes with time for the cross semivariogram between phosphorus in leaves and soybean yield is another evidence of this result.

  19. Disruptive Event Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this

  20. Disruptive Event Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this analysis was to develop the BDCFs for the volcanic ash

  1. Spatial environmental risk factors for pedestrian injury collisions in Ciudad Juárez, Mexico (2008-2009): implications for urban planning.

    Science.gov (United States)

    Fuentes, Cesar Mario; Hernandez, Vladimir

    2013-01-01

    The aim of this study is to examine the spatial distribution of pedestrian injury collisions and analyse the environmental (social and physical) risk factors in Ciudad Juarez, Mexico. More specifically, this study investigates the influence of land use, density, traffic and socio-economic characteristics. This cross sectional study is based on pedestrian injury collision data that were collected by the Municipal Transit Police during 2008-2009. This research presents an analysis of vehicle-pedestrian collisions and their spatial risk determinants using mixed methods that included (1) spatial/geographical information systems (GIS) analysis of pedestrian collision data and (2) ordinary least squares (OLS) regression analysis to explain the density of pedestrian collisions data. In our model, we found a higher probability for pedestrian collisions in census tracts with population and employment density, large concentration of commercial/retail land uses and older people (65 and more). Interventions to alleviate this situation including transportation planning such as decentralisation of municipal transport system, investment in road infrastructure - density of traffic lights, pedestrian crossing, road design, improves lane demarcation. Besides, land use planning interventions should be implemented in commercial/retail areas, in particular separating pedestrian and vehicular spaces.

  2. Traffic-related trace elements in soils along six highway segments on the Tibetan Plateau: Influence factors and spatial variation.

    Science.gov (United States)

    Wang, Guanxing; Zeng, Chen; Zhang, Fan; Zhang, Yili; Scott, Christopher A; Yan, Xuedong

    2017-03-01

    The accumulation of traffic-related trace elements in soil as the result of anthropogenic activities raises serious concerns about environmental pollution and public health. Traffic is the main source of trace elements in roadside soil on the Tibetan Plateau, an area otherwise devoid of industrial emissions. Indeed, the rapid development of tourism and transportation in this region means it is becoming increasingly important to identify the accumulation levels, influence distance, spatial distribution, and other relevant factors influencing trace elements. In this study, 229 soil samples along six segments of the major transportation routes on the Tibetan Plateau (highways G214, S308, and G109), were collected for analysis of eight trace elements (Cr, Co, Ni, As, Cu, Zn, Cd, and Pb). The results of statistical analyses showed that of the eight trace elements in soils, Cu, Zn, Cd, and Pb were primarily derived from traffic. The relationship between the trace element accumulation levels and the distance from the roadside followed an exponential decline, with the exception of Segment 3, the only unpaved gravel road studied. In addition, the distance of influence from the roadside varied by trace element and segment, ranging from 16m to 144m. Background values for each segment were different because of soil heterogeneity, while a number of other potential influencing factors (including traffic volume, road surface material, roadside distance, land cover, terrain, and altitude) all had significant effects on trace-element concentrations. Overall, however, concentrations along most of the road segments investigated were at, or below, levels defined as low on the Nemero Synthesis index. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Spatial and temporal analysis of natural resources degradation in the Likodra River watershed

    Directory of Open Access Journals (Sweden)

    Polovina Siniša

    2016-01-01

    Full Text Available Soil is an important natural resource whose proper use requires a good knowledge of all endogenous and exogenous factors that cause different types of degradation. Erosion is one of the forms of soil degradation. Erosion processes are characterized by a distinctive complexity and the factors affecting them are dynamics and change in space and time. A complex system degradation requires a multidisciplinary approach to the use of modern methods and techniques. Today, a large number of models are available for the assessment of soil loss through erosion as well as the levels of risk from erosion, today. Most of these are based on the logics of GIS thanks to its ability to sublimate heterogeneous information. In this paper, the analysis of spatial and temporal degradation of natural resources is carried out in the Likodra River watershed. The Likodra River is located in the northwestern part of the Republic of Serbia, and is positioned in the municipality of Krupanj. The main stream in the immediate vicinity of the town of Krupanj formed from four small streams that have expressed torrential character (the Bogoštica with the Kržava and the Čađavica with the Brštica. In May 2014, the urban area and rural parts of the municipality Krupanj were affected by catastrophic flash floods that resulted in the loss of human lives and enormous material damage. Soil degradation in the study area was analyzed using the Erosion Potential Method (EPM. The method is characterized by a high degree of reliability for determining the intensity of erosion, calculation of sediment yield and transport. The advantage of this method compared to other methods its lower complexity in terms of quantity of input parameters, simplicity and the possibility of application in GIS. In addition, the method has the advantage of choice, because it was developed in this area. The method is based on the analytical processing of data on factors affecting erosion. As the erosion

  4. SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

    Science.gov (United States)

    Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan

    2017-09-01

    With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Spatial statistical analysis of basal stem root disease under natural field epidemic of oil palm

    Science.gov (United States)

    Kamu, Assis; Phin, Chong Khim; Seman, Idris Abu; Wan, Hoong Hak; Mun, Ho Chong

    2015-02-01

    Oil palm or scientifically known as Elaeis guineensis Jacq. is the most important commodity crop in Malaysia and has greatly contributed to the economy growth of the country. As far as disease is concerned in the industry, Basal Stem Rot (BSR) caused by Ganoderma boninence remains the most important disease. BSR disease is the most widely studied with information available for oil palm disease in Malaysia. However, there is still limited study on the spatial as well as temporal pattern or distribution of the disease especially under natural field epidemic condition in oil palm plantation. The objective of this study is to spatially identify the pattern of BSR disease under natural field epidemic using two geospatial analytical techniques, which are quadrat analysis for the first order properties of partial pattern analysis and nearest-neighbor analysis (NNA) for the second order properties of partial pattern analysis. Two study sites were selected with different age of tree. Both sites are located in Tawau, Sabah and managed by the same company. The results showed that at least one of the point pattern analysis used which is NNA (i.e. the second order properties of partial pattern analysis) has confirmed the disease is complete spatial randomness. This suggests the spread of the disease is not from tree to tree and the age of palm does not play a significance role in determining the spatial pattern of the disease. From the spatial pattern of the disease, it would help in the disease management program and for the industry in the future. The statistical modelling is expected to help in identifying the right model to estimate the yield loss of oil palm due to BSR disease in the future.

  6. Analysis of Regional Unemployment in Russia and Germany: Spatial-Econometric Approach

    Directory of Open Access Journals (Sweden)

    Elena Vyacheslavovna Semerikova

    2015-06-01

    Full Text Available The study was supported by the Government of the Russian Federation, grant No.11.G34.31.0059. This paper analyzes the regional unemployment in Russia and Germany in 2005-2010 and addresses issues of choosing the right specification of spatial-econometric models. The analysis based on data of 75 Russian and 370 German regions showed that for Germany the choice of the spatial weighting matrix has a more significant influence on the parameter estimates than for Russia. Presumably this is due to stronger linkages between regional labor markets in Germany compared to Russia. The authors also proposed an algorithm for choosing between spatial matrices and demonstrated the application of this algorithm on simulated Russian data. The authors found that 1 the deviation of the results from the true ones increases when the spatial dependence between regions is higher and 2 the matrix of inverse distances is more preferable than the boundary one for the analysis of regional unemployment in Russia (because of the lower value of the mean squared error. The authors are also planning to apply the proposed algorithm for simulated data of Germany. These results allow accounting the spatial dependence more correctly when modeling regional unemployment which is very important for making proper regional policy

  7. Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada.

    Science.gov (United States)

    Bertazzon, Stefania; Shahid, Rizwan

    2017-07-25

    An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children.

  8. Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada

    Science.gov (United States)

    Bertazzon, Stefania; Shahid, Rizwan

    2017-01-01

    An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children. PMID:28757577

  9. Risk Factors and Spatial Clusters of Cryptosporidium Infection among School-Age Children in a Rural Region of Eastern China.

    Science.gov (United States)

    Zheng, Hao; He, Jianfeng; Wang, Li; Zhang, Rong; Ding, Zhen; Hu, Wenbiao

    2018-05-06

    The epidemiological features of Cryptosporidium infection among school-age children in China still remain unclear. Hereby, a cross-sectional study of 1637 children aged 3⁻9 years was designed to investigate the risk factors and spatial clusters of Cryptosporidium infection in a rural region of Eastern China. Stool specimens collected from participants were examined using the auramine-phenol and modified acid-fast staining. Univariable and multivariable analyses were performed to identify the risk factors of Cryptospordium infection. The spatial clusters were analyzed by a discrete Poisson model using SaTScan software. Our results showed that the overall prevalence of Cryptosporidium infection was 11‰ in the research region. At the age of 3⁻6 years (odds ratios (OR) = 3.072, 95% confidence intervals (CI) : 1.001⁻9.427), not washing hands before eating and after defecation (OR = 3.003, 95% CI: 1.060⁻8.511) were recognized as risk factors. Furthermore, a high-risk spatial cluster (relative risk = 4.220, p = 0.025) was identified. These findings call for effective sustainable interventions including family and school-based hygienic education to reduce the prevalence of Cryptosporidium infection. Therefore, an early warning system based spatiotemporal models with risk factors is required to further improve the effectiveness and efficiency of cryptosporidiosis control in the future.

  10. Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012

    Directory of Open Access Journals (Sweden)

    Silvia Carvalho

    2017-08-01

    Full Text Available ABSTRACT OBJECTIVE Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. METHODS Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields “street” and “number” were used. The ArcGis10 program’s Geocoding tool’s automatic process was performed. The spatial analysis was done through the kernel density estimator. RESULTS Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. CONCLUSIONS The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies.

  11. Spatial, road geometric, and biotic factors associated with Barn Owl mortality along an interstate highway

    Science.gov (United States)

    Arnold, Erin M.; Hanser, Steven E.; Regan, Tempe; Thompson, Jeremy; Lowe, Melinda; Kociolek, Angela; Belthoff, James R.

    2018-01-01

    Highway programs typically focus on reducing vehicle collisions with large mammals because of economic or safety reasons while overlooking the millions of birds that die annually from traffic. We studied wildlife‐vehicle collisions along an interstate highway in southern Idaho, USA, with among the highest reported rates of American Barn Owl Tyto furcata road mortality. Carcass data from systematic and ad hoc surveys conducted in 2004–2006 and 2013–2015 were used to explore the extent to which spatial, road geometric, and biotic factors explained Barn Owl‐vehicle collisions. Barn Owls outnumbered all other identified vertebrate species of roadkill and represented > 25% of individuals and 73.6% of road‐killed birds. At a 1‐km highway segment scale, the number of dead Barn Owls decreased with increasing numbers of human structures, cumulative length of secondary roads near the highway, and width of the highway median. Number of dead Barn Owls increased with higher commercial average annual daily traffic (CAADT), small mammal abundance index, and with grass rather than shrubs in the roadside verge. The small mammal abundance index was also greater in roadsides with grass versus mixed shrubs, suggesting that Barn Owls may be attracted to grassy portions of the highway with more abundant small mammals for hunting prey. When assessed at a 3‐km highway segment scale, the number of dead Barn Owls again increased with higher CAADT as well as with greater numbers of dairy farms. At a 5‐km scale, number of dead Barn Owls increased with greater percentage of cropland near the highway. While human conversion of the environment from natural shrub‐steppe to irrigated agriculture in this region of Idaho has likely enhanced habitat for Barns Owls, it simultaneously has increased risk for owl‐vehicle collisions where an interstate highway traverses the altered landscape. We review some approaches for highway mitigation and suggest that reducing wildlife

  12. A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of ...

    African Journals Online (AJOL)

    A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of household ... conducted by the National Institute of Statistics of Rwanda in 2000-2001. ... The third region of low poverty incident has between 4-12% of its population poor.

  13. A Bayesian multidimensional scaling procedure for the spatial analysis of revealed choice data

    NARCIS (Netherlands)

    DeSarbo, WS; Kim, Y; Fong, D

    1999-01-01

    We present a new Bayesian formulation of a vector multidimensional scaling procedure for the spatial analysis of binary choice data. The Gibbs sampler is gainfully employed to estimate the posterior distribution of the specified scalar products, bilinear model parameters. The computational procedure

  14. Spatial and Angular Moment Analysis of Continuous and Discretized Transport Problems

    International Nuclear Information System (INIS)

    Brantley, Patrick S.; Larsen, Edward W.

    2000-01-01

    A new theoretical tool for analyzing continuous and discretized transport equations is presented. This technique is based on a spatial and angular moment analysis of the analytic transport equation, which yields exact expressions for the 'center of mass' and 'squared radius of gyration' of the particle distribution. Essentially the same moment analysis is applied to discretized particle transport problems to determine numerical expressions for the center of mass and squared radius of gyration. Because this technique makes no assumption about the optical thickness of the spatial cells or about the amount of absorption in the system, it is applicable to problems that cannot be analyzed by a truncation analysis or an asymptotic diffusion limit analysis. The spatial differencing schemes examined (weighted- diamond, lumped linear discontinuous, and multiple balance) yield a numerically consistent expression for computing the squared radius of gyration plus an error term that depends on the mesh spacing, quadrature constants, and material properties of the system. The numerical results presented suggest that the relative accuracy of spatial differencing schemes for different types of problems can be assessed by comparing the magnitudes of these error terms

  15. Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change

    Science.gov (United States)

    Wang, Ninghua Nathan

    2013-01-01

    Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…

  16. Spatial analysis of fuel treatment options for chaparral on the Angeles national forest

    Science.gov (United States)

    G. Jones; J. Chew; R. Silverstein; C. Stalling; J. Sullivan; J. Troutwine; D. Weise; D. Garwood

    2008-01-01

    Spatial fuel treatment schedules were developed for the chaparral vegetation type on the Angeles National Forest using the Multi-resource Analysis and Geographic Information System (MAGIS). Schedules varied by the priority given to various wildland urban interface areas and the general forest, as well as by the number of acres treated per decade. The effectiveness of...

  17. Gender, Space, and the Location Changes of Jobs and People : A Spatial Simultaneous Equations Analysis

    NARCIS (Netherlands)

    Hoogstra, Gerke J.

    This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes

  18. Ultrasonic motion analysis system - measurement of temporal and spatial gait parameters

    NARCIS (Netherlands)

    Huitema, RB; Hof, AL; Postema, K

    The duration of stance and swing phase and step and stride length are important parameters in human gait. In this technical note a low-cost ultrasonic motion analysis system is described that is capable of measuring these temporal and spatial parameters while subjects walk on the floor. By using the

  19. Spatial Spread of the Root Parasitic Weed Phelipanche aegyptiaca in Processing Tomatoes by Using Ecoinformatics and Spatial Analysis.

    Science.gov (United States)

    Cohen, Yafit; Roei, Itai; Blank, Lior; Goldshtein, Eitan; Eizenberg, Hanan

    2017-01-01

    Egyptian broomrape ( Phelipanche aegyptiaca ) is one of the main threats to tomato production in Israel. The seed bank of P. aegyptiaca rapidly develops and spreads in the field. Knowledge about the spatio-temporal distribution of such weeds is required in advance of emergence, as they emerge late in their life cycle when they have already caused major crop damage. The aim of this study is to reveal the effects of two major internal infestation sources: crop rotation and infestation history; and one external source: proximity to infested tomato fields; on infestation of P. aegyptiaca in processing tomatoes. Ecoinformatics, spatial analysis and geostatistics were used to examine these effects. A regional survey was conducted to collect data on field history from 238 tomato fields between 2000 and 2012, in a major tomato-growing region in Israel. Multivariate logistic regression in the framework of generalized linear models (GLM) has demonstrated the importance of all three variables in predicting infestation in tomato fields. The parameters of the overall model indicated a high specificity between tomatoes and P. aegyptiaca , which is potentially responsible for aggravating infestation. In addition, P. aegyptiaca infestation levels were intensively mapped in 43 of the 238 tomato fields in the years 2010-2012. Geostatistical measures showed that 40% of the fields had clustered infestation spatial patterns with infestation clusters located along the fields' borders. Strong linear and negative relationships were found between infestation level and distance from a neighboring infested field, strengthening the role of infested tomato fields in P. aegyptiaca spread. An experiment specifically designed for this study showed that during harvest, P. aegyptiaca seeds are blown from an infested field to a distance of at least 90 m, and may initiate infestation in neighboring fields. Integrating current knowledge about the role of agricultural practices on the spread of P

  20. Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

    Science.gov (United States)

    Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

    2018-03-01

    There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

  1. Training the elderly on the ability factors of spatial orientation and inductive reasoning.

    Science.gov (United States)

    Willis, S L; Schaie, K W

    1986-09-01

    We examined the effects of cognitive training with elderly participants from the Seattle Longitudinal Study. Subjects were classified as having remained stable or having declined over the previous 14-year interval on each of two primary abilities, spatial orientation and inductive reasoning. Subjects who had declined on one of these abilities received training on that ability; subjects who had declined on both abilities or who had remained stable on both were randomly assigned to the spatial orientation or inductive reasoning training programs. Training outcomes were examined within an ability-measurement framework with empirically determined factorial structure. Significant training effects, at the level of the latent ability constructs, occurred for both spatial orientation and inductive reasoning. These effects were general, in that no significant interactions with decline status or gender were found. Thus, training interventions were effective both in remediating cognitive decline on the target abilities and in improving the performance of stable subjects.

  2. The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach

    Directory of Open Access Journals (Sweden)

    Eustasius Musenge

    2013-01-01

    Full Text Available Background: South Africa accounts for more than a sixth of the global population of people infected with HIV and TB, ranking her highest in HIV/TB co-infection worldwide. Remote areas often bear the greatest burden of morbidity and mortality, yet there are spatial differences within rural settings. Objectives: The primary aim was to investigate HIV/TB mortality determinants and their spatial distribution in the rural Agincourt sub-district for children aged 1–5 years in 2004. Our secondary aim was to model how the associated factors were interrelated as either underlying or proximate factors of child mortality using pathway analysis based on a Mosley-Chen conceptual framework. Methods: We conducted a secondary data analysis based on cross-sectional data collected in 2004 from the Agincourt sub-district in rural northeast South Africa. Child HIV/TB death was the outcome measure derived from physician assessed verbal autopsy. Modelling used multiple logit regression models with and without spatial household random effects. Structural equation models were used in modelling the complex relationships between multiple exposures and the outcome (child HIV/TB mortality as relayed on a conceptual framework. Results: Fifty-four of 6,692 children aged 1–5 years died of HIV/TB, from a total of 5,084 households. Maternal death had the greatest effect on child HIV/TB mortality (adjusted odds ratio=4.00; 95% confidence interval=1.01–15.80. A protective effect was found in households with better socio-economic status and when the child was older. Spatial models disclosed that the areas which experienced the greatest child HIV/TB mortality were those without any health facility. Conclusion: Low socio-economic status and maternal deaths impacted indirectly and directly on child mortality, respectively. These factors are major concerns locally and should be used in formulating interventions to reduce child mortality. Spatial prediction maps can guide policy

  3. Spatial analysis of radiocesium food contamination in rural settlements of Belarus

    International Nuclear Information System (INIS)

    Krivoruchko, K.; Makejchik, A.

    1997-01-01

    An analysis of 53207 records of cesium 137 contents in 83 types of food products obtained in 1993 in Belarus was carried out. Internal exposure from intake of eight selected food components has been estimated. To map the non-uniformly distributed data, different geostatistical approaches are used. The results of spatial analysis of long term internal dose loads on populations under high radiation risk can be used in decision making. (authors). 9 refs., 1 tab., 4 figs

  4. Sensitive rapid analysis of iodine-labelled protein mixture on flat substrates with high spatial resolution

    International Nuclear Information System (INIS)

    Zanevskij, Yu.V.; Ivanov, A.B.; Movchan, S.A.; Peshekhonov, V.D.; Chan Dyk Tkhan'; Chernenko, S.P.; Kaminir, L.B.; Krejndlin, Eh.Ya.; Chernyj, A.A.

    1983-01-01

    Usability of rapid analysis by electrophoresis of the admixture of I 125 -labelled proteins on flat samples by means of URAN type installation developed using a multiwire proportional chamber is studied. The sensitivity of the method is better than 200 cpm/cm 2 and the spatial resolution is approximately 1 mm. The procedure of the rapid analysis is no longer than several tens of minutes

  5. Spatial and temporal expression of the Grainyhead-like transcription factor family during murine development.

    Science.gov (United States)

    Auden, Alana; Caddy, Jacinta; Wilanowski, Tomasz; Ting, Stephen B; Cunningham, John M; Jane, Stephen M

    2006-10-01

    The Drosophila transcription factor Grainyhead (grh) is expressed in ectoderm-derived tissues where it regulates several key developmental events including cuticle formation, tracheal elongation and dorsal closure. Our laboratory has recently identified three novel mammalian homologues of the grh gene, Grainyhead-like 1, -2 and -3 (Grhl1-3) that rewrite the phylogeny of this family. Using gene targeting in mice, we have shown that Grhl3 is essential for neural tube closure, skin barrier formation and wound healing. Despite their extensive sequence homology, Grhl1 and Grhl2 are unable to compensate for loss of Grhl3 in these developmental processes. To explore this lack of redundancy, and to gain further insights into the functions of this gene family in mammalian development we have performed an extensive in situ hybridisation analysis. We demonstrate that, although all three Grhl genes are highly expressed in the developing epidermis, they display subtle differences in the timing and level of expression. Surprisingly, we also demonstrate differential expression patterns in non-ectoderm-derived tissues, including the heart, the lung, and the metanephric kidney. These findings expand our understanding of the unique role of Grhl3 in neurulation and epidermal morphogenesis, and provide a focus for further functional analysis of the Grhl genes during mouse embryogenesis.

  6. Quantum diffraction and interference of spatially correlated photon pairs and its Fourier-optical analysis

    International Nuclear Information System (INIS)

    Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

    2006-01-01

    We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns

  7. Nitrogen Oxide Emission, Economic Growth and Urbanization in China: a Spatial Econometric Analysis

    Science.gov (United States)

    Zhou, Zhimin; Zhou, Yanli; Ge, Xiangyu

    2018-01-01

    This research studies the nexus of nitrogen oxide emissions and economic development/urbanization. Under the environmental Kuznets curve (EKC) hypothesis, we apply the analysis technique of spatial panel data in the STIRPAT framework, and thus obtain the estimated impacts of income/urbanization on nitrogen oxide emission systematically. The empirical findings suggest that spatial dependence on nitrogen oxide emission distribution exist at provincial level, and the inverse N-shape EKC describes both income-nitrogen oxide and urbanization-nitrogen oxide nexuses. In addition, some well-directed policy advices are made to reduce the nitrogen oxide emission in future.

  8. Spatial-temporal analysis of wind power forecast errors for West-Coast Norway

    Energy Technology Data Exchange (ETDEWEB)

    Revheim, Paal Preede; Beyer, Hans Georg [Agder Univ. (UiA), Grimstad (Norway). Dept. of Engineering Sciences

    2012-07-01

    In this paper the spatial-temporal structure of forecast errors for wind power in West-Coast Norway is analyzed. Starting on the qualitative analysis of the forecast error reduction, with respect to single site data, for the lumped conditions of groups of sites the spatial and temporal correlations of the wind power forecast errors within and between the same groups are studied in detail. Based on this, time-series regression models to be used to analytically describe the error reduction are set up. The models give an expected reduction in forecast error between 48.4% and 49%. (orig.)

  9. [Spatial-temporal pattern and obstacle factors of cultivated land ecological security in major grain producing areas of northeast China: a case study in Jilin Province].

    Science.gov (United States)

    Zhao, Hong-Bo; Ma, Yan-Ji

    2014-02-01

    According to the cultivated land ecological security in major grain production areas of Northeast China, this paper selected 48 counties of Jilin Province as the research object. Based on the PSR-EES conceptual framework model, an evaluation index system of cultivated land ecological security was built. By using the improved TOPSIS, Markov chains, GIS spatial analysis and obstacle degree models, the spatial-temporal pattern of cultivated land ecological security and the obstacle factors were analyzed from 1995 to 2011 in Jilin Province. The results indicated that, the composite index of cultivated land ecological security appeared in a rising trend in Jilin Province from 1995 to 2011, and the cultivated land ecological security level changed from being sensitive to being general. There was a pattern of 'Club Convergence' in cultivated land ecological security level in each county and the spatial discrepancy tended to become larger. The 'Polarization' trend of cultivated land ecological security level was obvious. The distributions of sensitive level and critical security level with ribbon patterns tended to be dispersed, the general security level and relative security levels concentrated, and the distributions of security level scattered. The unstable trend of cultivated land ecological security level was more and more obvious. The main obstacle factors that affected the cultivated land ecological security level in Jilin Province were rural net income per capita, economic density, the proportion of environmental protection investment in GDP, degree of machinery cultivation and the comprehensive utilization rate of industrial solid wastes.

  10. Extreme Precipitation Estimation with Typhoon Morakot Using Frequency and Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2011-01-01

    Full Text Available Typhoon Morakot lashed Taiwan and produced copious amounts of precipitation in 2009. From the point view of hydrological statistics, the impact of the precipitation from typhoon Morakot using a frequency analysis can be analyzed and discussed. The frequency curve, which was fitted mathematically to historical observed data, can be used to estimate the probability of exceedance for runoff events of a certain magnitude. The study integrates frequency analysis and spatial analysis to assess the effect of Typhoon Morakot event on rainfall frequency in the Gaoping River basin of southern Taiwan. First, extreme rainfall data are collected at sixteen stations for durations of 1, 3, 6, 12, and 24 hours and then an appropriate probability distribution was selected to analyze the impact of the extreme hydrological event. Spatial rainfall patterns for a return period of 200-yr with 24-hr duration with and without Typhoon Morakot are estimated. Results show that the rainfall amount is significantly different with long duration with and without the event for frequency analysis. Furthermore, spatial analysis shows that extreme rainfall for a return period of 200-yr is highly dependent on topography and is smaller in the southwest than that in the east. The results not only demonstrate the distinct effect of Typhoon Morakot on frequency analysis, but also could provide reference in future planning of hydrological engineering.

  11. GIS-based spatial statistical analysis of risk areas for liver flukes in Surin Province of Thailand.

    Science.gov (United States)

    Rujirakul, Ratana; Ueng-arporn, Naporn; Kaewpitoon, Soraya; Loyd, Ryan J; Kaewthani, Sarochinee; Kaewpitoon, Natthawut

    2015-01-01

    It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (R Square=0.878, and, Adjust R Square=0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mu