Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

Spatial patterns in vegetation fires in the Indian region.

PubMed

Vadrevu, Krishna Prasad; Badarinath, K V S; Anuradha, Eaturu

2008-12-01

In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.

An investigation on thermal patterns in Iran based on spatial autocorrelation

NASA Astrophysics Data System (ADS)

Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

2018-02-01

The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

Spatial arrangement of faults and opening-mode fractures

NASA Astrophysics Data System (ADS)

Laubach, S. E.; Lamarche, J.; Gauthier, B. D. M.; Dunne, W. M.; Sanderson, David J.

2018-03-01

Spatial arrangement is a fundamental characteristic of fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings. Five papers describe new methods and improvements of existing techniques to quantify spatial arrangement. One study unravels the time evolution of opening-mode fracture spatial arrangement, which are data needed to compare natural patterns with progressive fracture growth in kinematic and mechanical models. Three papers investigate the role of evolving diagenesis in localizing fractures by mechanical stratigraphy and nine discuss opening-mode fracture spatial arrangement. Two papers show the relevance of complex cluster patterns to unconventional reservoirs through examples of fractures in tight gas sandstone horizontal wells, and a study of fracture arrangement in shale. Four papers demonstrate the roles of folds in fracture localization and the development spatial patterns. One paper models along-fault friction and fluid pressure and their effects on fault-related fracture arrangement. Contributions address deformation band patterns in carbonate rocks and fault size and arrangement above a detachment fault. Three papers describe fault and fracture arrangements in basement terrains, and three document fracture patterns in shale. This collection of papers points toward improvement in field methods, continuing improvements in computer-based data analysis and creation of synthetic fracture patterns, and opportunities for further understanding fault and fracture attributes in the subsurface through coupled spatial, size, and pattern analysis.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE PAGES

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei; ...

2017-05-11

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Integrating the statistical analysis of spatial data in ecology

Treesearch

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...

Fractal analysis of time varying data

DOEpatents

Vo-Dinh, Tuan; Sadana, Ajit

2002-01-01

Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.

Spatial pattern analysis of Cu, Zn and Ni and their interpretation in the Campania region (Italy)

NASA Astrophysics Data System (ADS)

Petrik, Attila; Albanese, Stefano; Jordan, Gyozo; Rolandi, Roberto; De Vivo, Benedetto

2017-04-01

The uniquely abundant Campanian topsoil dataset enabled us to perform a spatial pattern analysis on 3 potentially toxic elements of Cu, Zn and Ni. This study is focusing on revealing the spatial texture and distribution of these elements by spatial point pattern and image processing analysis such as lineament density and spatial variability index calculation. The application of these methods on geochemical data provides a new and efficient tool to understand the spatial variation of concentrations and their background/baseline values. The determination and quantification of spatial variability is crucial to understand how fast the change in concentration is in a certain area and what processes might govern the variation. The spatial variability index calculation and image processing analysis including lineament density enables us to delineate homogenous areas and analyse them with respect to lithology and land use. Identification of spatial outliers and their patterns were also investigated by local spatial autocorrelation and image processing analysis including the determination of local minima and maxima points and singularity index analysis. The spatial variability of Cu and Zn reveals the highest zone (Cu: 0.5 MAD, Zn: 0.8-0.9 MAD, Median Deviation Index) along the coast between Campi Flegrei and the Sorrento Peninsula with the vast majority of statistically identified outliers and high-high spatial clustered points. The background/baseline maps of Cu and Zn reveals a moderate to high variability (Cu: 0.3 MAD, Zn: 0.4-0.5 MAD) NW-SE oriented zone including disrupted patches from Bisaccia to Mignano following the alluvial plains of Appenine's rivers. This zone has high abundance of anomaly concentrations identified using singularity analysis and it also has a high density of lineaments. The spatial variability of Ni shows the highest variability zone (0.6-0.7 MAD) around Campi Flegrei where the majority of low outliers are concentrated. The variability of background/baseline map of Ni reveals a shift to the east in case of highest variability zones coinciding with limestone outcrops. The high segmented area between Mignano and Bisaccia partially follows the alluvial plains of Appenine's rivers which seem to be playing a crucial role in the distribution and redistribution pattern of Cu, Zn and Ni in Campania. The high spatial variability zones of the later elements are located in topsoils on volcanoclastic rocks and are mostly related to cultivation and urbanised areas.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

NASA Astrophysics Data System (ADS)

Manson, F. J.; Loneragan, N. R.; Phinn, S. R.

2003-07-01

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.

A perturbation analysis of a mechanical model for stable spatial patterning in embryology

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1992-12-01

We investigate a mechanical cell-traction mechanism that generates stationary spatial patterns. A linear analysis highlights the model's potential for these heterogeneous solutions. We use multiple-scale perturbation techniques to study the evolution of these solutions and compare our solutions with numerical simulations of the model system. We discuss some potential biological applications among which are the formation of ridge patterns, dermatoglyphs, and wound healing.

Spatial analysis of rural land development

Treesearch

Seong-Hoon Cho; David H. Newman

2005-01-01

This article examines patterns of rural land development and density using spatial econometric models with the application of Geographical Information System (GIS). The cluster patterns of both development and high-density development indicate that the spatially continuous expansions of development and high-density development exist in relatively remote rural areas....

Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan

PubMed Central

2011-01-01

Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

NASA Astrophysics Data System (ADS)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.

Recent variations in seasonality of temperature and precipitation in Canada, 1976-95

NASA Astrophysics Data System (ADS)

Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.

2002-11-01

A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.

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

PubMed

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).

Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands.

PubMed

Yang, Jian; He, Hong S; Shifley, Stephen R

2008-07-01

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthropogenic constraints on the spatial pattern of fire occurrence with that on burn probability (i.e., the probability that fire will spread to a particular location). Spatial point pattern analysis and landscape succession fire model (LANDIS) were used to create maps to show the contrast. We quantified spatial controls on both fire occurrence and fire spread in the Midwest Ozark Highlands region, USA. This area exhibits a typical anthropogenic surface fire regime. We found that (1) human accessibility and land ownership were primary limiting factors in shaping clustered fire origin locations; (2) vegetation and topography had a negligible influence on fire occurrence in this anthropogenic regime; (3) burn probability was higher in grassland and open woodland than in closed-canopy forest, even though fire occurrence density was less in these vegetation types; and (4) biotic and abiotic factors were secondary descriptive ingredients for determining the spatial patterns of burn probability. This study demonstrates how fire occurrence and spread interact with landscape patterns to affect the spatial distribution of wildfire risk. The application of spatial point pattern data analysis would also be valuable to researchers working on landscape forest fire models to integrate historical ignition location patterns in fire simulation.

Analysis of Spatial Voting Patterns: An Approach in Political Socialization

ERIC Educational Resources Information Center

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.…

A spatial analysis of Phytophthora ramorum symptom spread using second-order point pattern and GIS-based analyses

Treesearch

Mark Spencer; Kevin O' Hara

2006-01-01

Phytophthora ramorum is a major source of tanoak (Lithocarpus densiflorus) mortality in the tanoak/redwood (Sequoia sempervirens) forests of central California. This study presents a spatial analysis of the spread of the disease using second-order point pattern and GIS analyses. Our data set includes four plots...

Research on the Spatial-Temporal Distribution Pattern of the Network Attention of Fog and Haze in China

NASA Astrophysics Data System (ADS)

Weng, Lingyan; Han, Xugao

2018-01-01

Understanding the spatial-temporal distribution pattern of fog and haze is the base to deal with them by adjusting measures to local conditions. Taking 31 provinces in China mainland as the research areas, this paper collected data from Baidu index on the network attention of fog and haze in relevant areas from 2011 to 2016, and conducted an analysis of their spatial-temporal distribution pattern by using autocorrelation analysis. The results show that the network attention of fog and haze has an overall spatial distribution pattern of “higher in the eastern and central, lower in the western China”. There are regional differences in different provinces in terms of network attention. Network attention of fog and haze indicates an obvious geographical agglomeration phenomenon, which is a gradual enlargement of the agglomeration area of higher value with a slight shrinking of those lower value agglomeration areas.

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature. PMID:23724108

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature.

GEMAS: Spatial pattern analysis of Ni by using digital image processing techniques on European agricultural soil data

NASA Astrophysics Data System (ADS)

Jordan, Gyozo; Petrik, Attila; De Vivo, Benedetto; Albanese, Stefano; Demetriades, Alecos; Sadeghi, Martiya

2017-04-01

Several studies have investigated the spatial distribution of chemical elements in topsoil (0-20 cm) within the framework of the EuroGeoSurveys Geochemistry Expert Group's 'Geochemical Mapping of Agricultural and Grazing Land Soil' project . Most of these studies used geostatistical analyses and interpolated concentration maps, Exploratory and Compositional Data and Analysis to identify anomalous patterns. The objective of our investigation is to demonstrate the use of digital image processing techniques for reproducible spatial pattern recognition and quantitative spatial feature characterisation. A single element (Ni) concentration in agricultural topsoil is used to perform the detailed spatial analysis, and to relate these features to possible underlying processes. In this study, simple univariate statistical methods were implemented first, and Tukey's inner-fence criterion was used to delineate statistical outliers. The linear and triangular irregular network (TIN) interpolation was used on the outlier-free Ni data points, which was resampled to a 10*10 km grid. Successive moving average smoothing was applied to generalise the TIN model and to suppress small- and at the same time enhance significant large-scale features of Nickel concentration spatial distribution patterns in European topsoil. The TIN map smoothed with a moving average filter revealed the spatial trends and patterns without losing much detail, and it was used as the input into digital image processing, such as local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction calculation, second derivative profile curvature calculation, edge detection, local variability assessment, lineament density and directional variogram analyses. The detailed image processing analysis revealed several NE-SW, E-W and NW-SE oriented elongated features, which coincide with different spatial parameter classes and alignment with local maxima and minima. The NE-SW oriented linear pattern is the dominant feature to the south of the last glaciation limit. Some of these linear features are parallel to the suture zone of the Iapetus Ocean, while the others follow the Alpine and Carpathian Chains. The highest variability zones of Ni concentration in topsoil are located in the Alps and in the Balkans where mafic and ultramafic rocks outcrop. The predominant NE-SW oriented pattern is also captured by the strong anisotropy in the semi-variograms in this direction. A single major E-W oriented north-facing feature runs along the southern border of the last glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated spatial features are less dominant and are located in the Pyrenees and Scandinavia. This study demonstrates the efficiency of systematic image processing analysis in identifying and characterising spatial geochemical patterns that often remain uncovered by the usual visual map interpretation techniques.

Application of Fourier analysis to multispectral/spatial recognition

NASA Technical Reports Server (NTRS)

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.

Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages

NASA Astrophysics Data System (ADS)

Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça

2017-11-01

Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

NASA Astrophysics Data System (ADS)

Rousta, Iman; Doostkamian, Mehdi; Haghighi, Esmaeil; Ghafarian Malamiri, Hamid Reza; Yarahmadi, Parvane

2017-09-01

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G i statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

Quantitative analysis of residential parking intrusions by passenger vehicles in New York City.

DOT National Transportation Integrated Search

2017-05-01

This paper investigates the spatial patterns of residential parking intrusions in New York City, their determinants, and an : estimated number and spatial patterns of induced excessive vehicle miles traveled (VMT). The paper analyzes parking tickets ...

Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India

NASA Astrophysics Data System (ADS)

Verma, S.; Gupta, R. D.

2014-11-01

In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Physical vs. photolithographic patterning of plasma polymers: an investigation by ToF-SSIMS and multivariate analysis

PubMed Central

Mishra, Gautam; Easton, Christopher D.; McArthur, Sally L.

2009-01-01

Physical and photolithographic techniques are commonly used to create chemical patterns for a range of technologies including cell culture studies, bioarrays and other biomedical applications. In this paper, we describe the fabrication of chemical micropatterns from commonly used plasma polymers. Atomic force microcopy (AFM) imaging, Time-of-Flight Static Secondary Ion Mass Spectrometry (ToF-SSIMS) imaging and multivariate analysis have been employed to visualize the chemical boundaries created by these patterning techniques and assess the spatial and chemical resolution of the patterns. ToF-SSIMS analysis demonstrated that well defined chemical and spatial boundaries were obtained from photolithographic patterning, while the resolution of physical patterning via a transmission electron microscopy (TEM) grid varied depending on the properties of the plasma system including the substrate material. In general, physical masking allowed diffusion of the plasma species below the mask and bleeding of the surface chemistries. Multivariate analysis techniques including Principal Component Analysis (PCA) and Region of Interest (ROI) assessment were used to investigate the ToF-SSIMS images of a range of different plasma polymer patterns. In the most challenging case, where two strongly reacting polymers, allylamine and acrylic acid were deposited, PCA confirmed the fabrication of micropatterns with defined spatial resolution. ROI analysis allowed for the identification of an interface between the two plasma polymers for patterns fabricated using the photolithographic technique which has been previously overlooked. This study clearly demonstrated the versatility of photolithographic patterning for the production of multichemistry plasma polymer arrays and highlighted the need for complimentary characterization and analytical techniques during the fabrication plasma polymer micropatterns. PMID:19950941

[Spatial distribution pattern and fractal analysis of Larix chinensis populations in Qinling Mountain].

PubMed

Guo, Hua; Wang, Xiaoan; Xiao, Yaping

2005-02-01

In this paper, the fractal characters of Larix chinensis populations in Qinling Mountain were studied by contiguous grid quadrate sampling method and by boxing-counting dimension and information dimension. The results showed that the high boxing-counting dimension (1.8087) and information dimension (1.7931) reflected a higher spatial occupational degree of L. chinensis populations. Judged by the dispersal index and Morisita's pattern index, L. chinensis populations clumped at three different age stages (0-25, 25-50 and over 50 years). From Greig-Smiths' mean variance analysis, the figure of pattern scale showed that L. chinensis populations clumped in 128 m2 and 512 m2, and the different age groups clumped in different scales. The pattern intensities decreased with increasing age, and tended to reduce with increasing area when detected by Kershaw's PI index. The spatial pattern characters of L. chinensis populations may be their responses to environmental factors.

Describing spatial pattern in stream networks: A practical approach

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

A geostatistical approach for describing spatial pattern in stream networks

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

Built environment and Property Crime in Seattle, 1998-2000: A Bayesian Analysis.

PubMed

Matthews, Stephen A; Yang, Tse-Chuan; Hayslett-McCall, Karen L; Ruback, R Barry

2010-06-01

The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems (GIS), spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998-2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary.

Built environment and Property Crime in Seattle, 1998–2000: A Bayesian Analysis

PubMed Central

Matthews, Stephen A.; Yang, Tse-chuan; Hayslett-McCall, Karen L.; Ruback, R. Barry

2014-01-01

The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems (GIS), spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998–2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary. PMID:24737924

Spatial organization of bacterial chromosomes

PubMed Central

Wang, Xindan; Rudner, David Z.

2014-01-01

Bacterial chromosomes are organized in stereotypical patterns that are faithfully and robustly regenerated in daughter cells. Two distinct spatial patterns were described almost a decade ago in our most tractable model organisms. In recent years, analysis of chromosome organization in a larger and more diverse set of bacteria and a deeper characterization of chromosome dynamics in the original model systems have provided a broader and more complete picture of both chromosome organization and the activities that generate the observed spatial patterns. Here, we summarize these different patterns highlighting similarities and differences and discuss the protein factors that help establish and maintain them. PMID:25460798

Environmental drivers and spatial dependency in wildfire ignition patterns of northwestern Patagonia.

PubMed

Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas

2013-07-15

Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

USGS Publications Warehouse

Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

2003-01-01

We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

Postural tasks are associated with center of pressure spatial patterns of three-dimensional statokinesigrams in young and elderly healthy subjects.

PubMed

Baracat, Patrícia Junqueira Ferraz; de Sá Ferreira, Arthur

2013-12-01

The present study investigated the association between postural tasks and center of pressure spatial patterns of three-dimensional statokinesigrams. Young (n=35; 27.0±7.7years) and elderly (n=38; 67.3±8.7years) healthy volunteers maintained an undisturbed standing position during postural tasks characterized by combined sensory (vision/no vision) and biomechanical challenges (feet apart/together). A method for the analysis of three-dimensional statokinesigrams based on nonparametric statistics and image-processing analysis was employed. Four patterns of spatial distribution were derived from ankle and hip strategies according to the quantity (single; double; multi) and location (anteroposterior; mediolateral) of high-density regions on three-dimensional statokinesigrams. Significant associations between postural task and spatial pattern were observed (young: gamma=0.548, p<.001; elderly: gamma=0.582, p<.001). Robustness analysis revealed small changes related to parameter choices for histogram processing. MANOVA revealed multivariate main effects for postural task [Wilks' Lambda=0.245, p<.001] and age [Wilks' Lambda=0.308, p<.001], with interaction [Wilks' Lambda=0.732, p<.001]. The quantity of high-density regions was positively correlated to stabilogram and statokinesigram variables (p<.05 or lower). In conclusion, postural tasks are associated with center of pressure spatial patterns and are similar in young and elderly healthy volunteers. Single-centered patterns reflected more stable postural conditions and were more frequent with complete visual input and a wide base of support. Copyright © 2013 Elsevier B.V. All rights reserved.

Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Tempo-spatial analysis of Fennoscandian intraplate seismicity

NASA Astrophysics Data System (ADS)

Roberts, Roland; Lund, Björn

2017-04-01

Coupled spatial-temporal patterns of the occurrence of earthquakes in Fennoscandia are analysed using non-parametric methods. The occurrence of larger events is unambiguously and very strongly temporally clustered, with major implications for the assessment of seismic hazard in areas such as Fennoscandia. In addition, there is a clear pattern of geographical migration of activity. Data from the Swedish National Seismic Network and a collated international catalogue are analysed. Results show consistent patterns on different spatial and temporal scales. We are currently investigating these patterns in order to assess the statistical significance of the tempo-spatial patterns, and to what extent these may be consistent with stress transfer mechanism such as coulomb stress and pore fluid migration. Indications are that some further mechanism is necessary in order to explain the data, perhaps related to post-glacial uplift, which is up to 1cm/year.

Interpreting Intra-site Spatial Patterns in Seasonal Contexts: an Ethnoarchaeological Case Study from the Western Alps.

PubMed

Carrer, Francesco

2017-01-01

This paper deals with the ethnoarchaeological analysis of the spatial pattern of artefacts and ecofacts within two traditional pastoral huts (a dwelling and a seasonal dairy) in the uplands of Val Maudagna (Cuneo province, Italian western Alps). The composition of the ethnoarchaeological assemblages of the two huts was studied and compared; point pattern analysis was applied to identify spatial processes mirrored in the interactions between objects; Moran's I correlogram and empirical variogram were used to investigate the effects of trampling on the displacement of objects on the floor. The results were compared with information provided by the herder who still used the huts. The quantitative and ethnographical data enabled inferences to be made that can help in the interpretation of archaeological seasonal sites. The function of a seasonal site can be recognized, as can the impact of delayed curation on the composition of the assemblage and the importance of the intensity of occupation compared with the frequency of occupation. The spatial organization of activities is reflected in the spatial patterns of objects, with clearer identification of activity areas in intensively occupied sites, and there is evidence for the behaviour behind the spatial segregation of activities. Trampling is a crucial post-depositional factor in the displacement of artefacts and ecofacts, especially in non-intensively exploited sites. From a methodological point of view, this research is another example that highlights the importance of integrating quantitative methods (especially spatial analysis and geostatistical methods) and ethnoarchaeological data in order to improve the interpretation of archaeological sites and assemblages.

Spatial patterns of hydro-social metrics in the Northeastern United States from the Colonial Era through the Industrial Revolution (1600-1920)

NASA Astrophysics Data System (ADS)

Witherell, B. B.; Bain, D. J.; Salant, N.; Aloysius, N. R.

2009-12-01

Humans impact the hydrologic cycle at local, regional and global scales. Understanding how spatial patterns of human water use and hydrologic impact have changed over time is important to future water management in an era of increasing water constraints and globalization of high water-use resources. This study investigates spatial dependence and spatial patterns of hydro-social metrics for the Northeastern United States from 1600 to 1920 through the use of spatial statistical techniques. Several relevant hydro-social metrics, including water residence time, surface water storage (natural and human engineered) and per capita water availability, are analyzed. This study covers a region and period of time that saw significant population growth, landscape change, and industrial growth. These changes had important impacts on water availability. Although some changes such as the elimination of beavers, and the resulting loss of beaver ponds on low-order streams, are felt at a regional scale, preliminary analysis indicates that humans responded to water constraints by acting locally (e.g., mill ponds for water power and water supply reservoirs for public health). This 320-year historical analysis of spatial patterns of hydro-social metrics provides unique insight into long-term changes in coupled human-water systems.

Point pattern analysis applied to flood and landslide damage events in Switzerland (1972-2009)

NASA Astrophysics Data System (ADS)

Barbería, Laura; Schulte, Lothar; Carvalho, Filipe; Peña, Juan Carlos

2017-04-01

Damage caused by meteorological and hydrological extreme events depends on many factors, not only on hazard, but also on exposure and vulnerability. In order to reach a better understanding of the relation of these complex factors, their spatial pattern and underlying processes, the spatial dependency between values of damage recorded at sites of different distances can be investigated by point pattern analysis. For the Swiss flood and landslide damage database (1972-2009) first steps of point pattern analysis have been carried out. The most severe events have been selected (severe, very severe and catastrophic, according to GEES classification, a total number of 784 damage points) and Ripley's K-test and L-test have been performed, amongst others. For this purpose, R's library spatstat has been used. The results confirm that the damage points present a statistically significant clustered pattern, which could be connected to prevalence of damages near watercourses and also to rainfall distribution of each event, together with other factors. On the other hand, bivariate analysis shows there is no segregated pattern depending on process type: flood/debris flow vs landslide. This close relation points to a coupling between slope and fluvial processes, connectivity between small-size and middle-size catchments and the influence of spatial distribution of precipitation, temperature (snow melt and snow line) and other predisposing factors such as soil moisture, land-cover and environmental conditions. Therefore, further studies will investigate the relationship between the spatial pattern and one or more covariates, such as elevation, distance from watercourse or land use. The final goal will be to perform a regression model to the data, so that the adjusted model predicts the intensity of the point process as a function of the above mentioned covariates.

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Processing and statistical analysis of soil-root images

NASA Astrophysics Data System (ADS)

Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov

2016-04-01

Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.

A technique for conducting point pattern analysis of cluster plot stem-maps

Treesearch

C.W. Woodall; J.M. Graham

2004-01-01

Point pattern analysis of forest inventory stem-maps may aid interpretation and inventory estimation of forest attributes. To evaluate the techniques and benefits of conducting point pattern analysis of forest inventory stem-maps, Ripley`s K(t) was calculated for simulated tree spatial distributions and for over 600 USDA Forest Service Forest...

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Atherosclerotic plaque characterization by spatial and temporal speckle pattern analysis

NASA Astrophysics Data System (ADS)

Tearney, Guillermo J.; Bouma, Brett E.

2002-04-01

Improved methods are needed to identify the vulnerable coronary plaques responsible for acute myocardial infraction or sudden cardiac death. We describe a method for characterizing the structure and biomechanical properties of atherosclerotic plaques based on speckle pattern fluctuations. Near-field speckle images were acquired from five human aortic specimens ex vivo. The speckle decorrelation time constant varied significantly for vulnerable aortic plaques (τ = 40 ms) versus stable plaques (τ = 400 ms) and normal aorta (τ = 500 ms). These initial results indicate that different atherosclerotic plaque types may be distinguished by analysis of temporal and spatial speckle pattern fluctuations.

Behavioral states may be associated with distinct spatial patterns in electrocorticogram.

PubMed

Panagiotides, Heracles; Freeman, Walter J; Holmes, Mark D; Pantazis, Dimitrios

2011-03-01

To determine if behavioral states are associated with unique spatial electrocorticographic (ECoG) patterns, we obtained recordings with a microgrid electrode array applied to the cortical surface of a human subject. The array was constructed with the intent of extracting maximal spatial information by optimizing interelectrode distances. A 34-year-old patient with intractable epilepsy underwent intracranial ECoG monitoring after standard methods failed to reveal localization of seizures. During the 8-day period of invasive recording, in addition to standard clinical electrodes a square 1 × 1 cm microgrid array with 64 electrodes (1.25 mm separation) was placed on the right inferior temporal gyrus. Careful review of video recordings identified four extended naturalistic behaviors: reading, conversing on the telephone, looking at photographs, and face-to-face interactions. ECoG activity recorded with the microgrid that corresponded to these behaviors was collected and ECoG spatial patterns were analyzed. During periods of ECoG selected for analysis, no electrographic seizures or epileptiform patterns were present. Moments of maximal spatial variance are shown to cluster by behavior. Comparisons between conditions using a permutation test reveal significantly different spatial patterns for each behavior. We conclude that ECoG recordings obtained on the cortical surface with optimal high spatial frequency resolution reveal distinct local spatial patterns that reflect different behavioral states, and we predict that similar patterns will be found in many if not most cortical areas on which a microgrid is placed.

A GIS-based approach to stand visualization and spatial pattern analysis in a mixed hardwood forest in West Virginia

Treesearch

Benktesh D. Sharma; Jingxin Wang; Gary Miller

2008-01-01

Tree spatial patterns were characterized for a 75-year-old mixed hardwood forest dominated by northern red oak, chestnut oak, red maple and yellow-poplar. All trees ≥5 inches diameter at breast height (d.b.h.) were measured for diameter, total height, crown height, and crown width along with their locations in the field over an area of 8 acres. The spatial...

Analysis of the spatial pattern of strawberry angular leaf spot in California nursery production

USDA-ARS?s Scientific Manuscript database

Xanthomonas fragariae is a bacterium that causes angular leaf spot of strawberry. In California, angular leaf spot (ALS) is a common disease in strawberry nursery production, and a major concern for nurseries wishing to export plants. The spatial pattern of disease is an ecological property whose ch...

The Nexus of Place and Finance in the Analysis of Educational Attainment: A Spatial Econometric Approach

ERIC Educational Resources Information Center

Sutton, Farah

2012-01-01

This study examines the spatial distribution of educational attainment and then builds upon current predictive frameworks for understanding patterns of educational attainment by applying a spatial econometric method of analysis. The research from this study enables a new approach to the policy discussion on how to improve educational attainment…

Remote Sensing-Based Detection and Spatial Pattern Analysis for Geo-Ecological Niche Modeling of Tillandsia SPP. In the Atacama, Chile

NASA Astrophysics Data System (ADS)

Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.

2016-06-01

In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

The Emergence of Regional Immigrant Concentrations in USA and Australia: A Spatial Relatedness Approach

PubMed Central

Novotny, Josef; Hasman, Jiri

2015-01-01

This paper examines the patterns of the US and Australian immigration geography and the process of regional population diversification and the emergence of new immigrant concentrations at the regional level. It presents a new approach in the context of human migration studies, focusing on spatial relatedness between individual foreign-born groups as revealed from the analysis of their joint spatial concentrations. The approach employs a simple assumption that the more frequently the members of two population groups concentrate in the same locations the higher is the probability that these two groups can be related. Based on detailed data on the spatial distribution of foreign-born groups in US counties (2000–2010) and Australian postal areas (2006–2011) we firstly quantify the spatial relatedness between all pairs of foreign-born groups and model the aggregate patterns of US and Australian immigration systems conceptualized as the undirected networks of foreign-born groups linked by their spatial relatedness. Secondly, adopting a more dynamic perspective, we assume that immigrant groups with higher spatial relatedness to those groups already concentrated in a region are also more likely to settle in this region in future. As the ultimate goal of the paper, we examine the power of spatial relatedness measures in projecting the emergence of new immigrant concentrations in the US and Australian regions. The results corroborate that the spatial relatedness measures can serve as useful instruments in the analysis of the patterns of population structure and prediction of regional population change. More generally, this paper demonstrates that information contained in spatial patterns (relatedness in space) of population composition has yet to be fully utilized in population forecasting. PMID:25966371

Dynamics of land change in India: a fine-scale spatial analysis

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.

2015-12-01

Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.

Assessing patterns of spatial behavior in health studies: their socio-demographic determinants and associations with transportation modes (the RECORD Cohort Study).

PubMed

Perchoux, Camille; Kestens, Yan; Thomas, Frédérique; Van Hulst, Andraea; Thierry, Benoit; Chaix, Basile

2014-10-01

Prior epidemiological studies have mainly focused on local residential neighborhoods to assess environmental exposures. However, individual spatial behavior may modify residential neighborhood influences, with weaker health effects expected for mobile populations. By examining individual patterns of daily mobility and associated socio-demographic profiles and transportation modes, this article seeks to develop innovative methods to account for daily mobility in health studies. We used data from the RECORD Cohort Study collected in 2011-2012 in the Paris metropolitan area, France. A sample of 2062 individuals was investigated. Participants' perceived residential neighborhood boundaries and regular activity locations were geocoded using the VERITAS application. Twenty-four indicators were created to qualify individual space-time patterns, using spatial analysis methods and a geographic information system. Three domains of indicators were considered: lifestyle indicators, indicators related to the geometry of the activity space, and indicators related to the importance of the residential neighborhood in the overall activity space. Principal component analysis was used to identify main dimensions of spatial behavior. Multilevel linear regression was used to determine which individual characteristics were associated with each spatial behavior dimension. The factor analysis generated five dimensions of spatial behavior: importance of the residential neighborhood in the activity space, volume of activities, and size, eccentricity, and specialization of the activity space. Age, socioeconomic status, and location of the household in the region were the main predictors of daily mobility patterns. Activity spaces of small sizes centered on the residential neighborhood and implying a large volume of activities were associated with walking and/or biking as a transportation mode. Examination of patterns of spatial behavior by individual socio-demographic characteristics and in relation to transportation modes is useful to identify populations with specific mobility/accessibility needs and has implications for investigating transportation-related physical activity and assessing environmental exposures and their effects on health. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solid perception mechanism by a shading pattern: spatial frequency components in a corrugated wave pattern.

PubMed

Nameda, N

1988-01-01

Illumination allows solid object perception to be obtained and depicted by a shading pattern produced by lighting. The shading cue, as one of solid perception cues (Gibson 1979), was investigated in regard to a white corrugated wave shape, using computer graphic device: Tospix-2. The reason the corrugated wave was chosen, is that an alternately bright and dark pattern, produced by shading, can be conveniently analyzed into contained spatial frequencies. This paper reports spatial frequency properties contained in the shading pattern. The shading patterns, input into the computer graphic device, are analyzed by Fourier Transformation by the same device. After the filtration by various spatial frequency low and high pass filters, Inverse Fourier Transformation is carried out for the residual components. The result of the analysis indicates that the third through higher harmonics components are important in regard to presenting a solid reality feeling in solid perception. Sakata (1983) also reported that an edged pattern, superimposed onto a lower sinusoidal pattern, was important in solid perception. The third through higher harmonics components express the changing position of luminance on the pattern, and a slanted plane relating to the light direction. Detection of a solid shape, constructed with flat planes, is assumed to be on the bottom of the perfect curved solid perception mechanism. Apparent evidence for this assumption, in difficult visual conditions, is that a flat paneled solid is seen before the curved solid. This mechanism is explained by two spatial frequency neural network systems, assumed as having correspondence with higher spatial frequency detection and lower spatial frequency detection.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.

PubMed

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

2011-01-01

Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Spatial Autocorrelation And Autoregressive Models In Ecology

Treesearch

Jeremy W. Lichstein; Theodore R. Simons; Susan A. Shriner; Kathleen E. Franzreb

2003-01-01

Abstract. Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available...

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

PubMed

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

NASA Astrophysics Data System (ADS)

Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

2014-10-01

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

A descriptive analysis of temporal and spatial patterns of variability in Puget Sound oceanographic properties

Treesearch

Stephanie Moore; Nathan J. Mantua; Jan A. Newton; Mitsuhiro Kawase; Mark J. Warner; Jonathan P. Kellogg

2008-01-01

Temporal and spatial patterns of variability in Puget Sound's oceanographic properties are determined using continuous vertical profile data from two long-term monitoring programs; monthly observations at 16 stations from 1993 to 2002, and biannual observations at 40 stations from 1998 to 2003. Climatological monthly means of temperature, salinity, and density...

Spatial pattern of spring phytoplankton community in the coastal waters of northern Zhejiang, East China Sea

NASA Astrophysics Data System (ADS)

Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming

2017-04-01

The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.

Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI.

PubMed

Sengupta, Ayan; Pollmann, Stefan; Hanke, Michael

2018-01-01

Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex that matches a previously conducted study on decoding visual orientation from V1.  The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.; Hines, Glenn D.

2004-01-01

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Spatial and temporal patterns of dengue in Guangdong province of China.

PubMed

Wang, Chenggang; Yang, Weizhong; Fan, Jingchun; Wang, Furong; Jiang, Baofa; Liu, Qiyong

2015-03-01

The aim of the study was to describe the spatial and temporal patterns of dengue in Guangdong for 1978 to 2010. Time series analysis was performed using data on annual dengue incidence in Guangdong province for 1978-2010. Annual average dengue incidences for each city were mapped for 4 periods by using the geographical information system (GIS). Hot spot analysis was used to identify spatial patterns of dengue cases for 2005-2010 by using the CrimeStat III software. The incidence of dengue in Guangdong province had fallen steadily from 1978 to 2010. The time series was a random sequence without regularity and with no fixed cycle. The geographic range of dengue fever had expanded from 1978 to 2010. Cases were mostly concentrated in Zhanjiang and the developed regions of Pearl River Delta and Shantou. © 2013 APJPH.

Urban Spatial Pattern and Interaction based on Analysis of Nighttime Remote Sensing Data and Geo-social Media Information

NASA Astrophysics Data System (ADS)

Ratnasari, Nila; Dwi Candra, Erika; Herdianta Saputra, Defa; Putra Perdana, Aji

2016-11-01

Urban development in Indonesia significantly incerasing in line with rapid development of infrastructure, utility, and transportation network. Recently, people live depend on lights at night and social media and these two aspects can depicted urban spatial pattern and interaction. This research used nighttime remote sensing data with the VIIRS (Visible Infrared Imaging Radiometer Suite) day-night band detects lights, gas flares, auroras, and wildfires. Geo-social media information derived from twitter data gave big picture on spatial interaction from the geospatial footprint. Combined both data produced comprehensive urban spatial pattern and interaction in general for Indonesian territory. The result is shown as a preliminary study of integrating nighttime remote sensing data and geospatial footprint from twitter data.

RipleyGUI: software for analyzing spatial patterns in 3D cell distributions

PubMed Central

Hansson, Kristin; Jafari-Mamaghani, Mehrdad; Krieger, Patrik

2013-01-01

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers. PMID:23658544

Differential spatial activity patterns of acupuncture by a machine learning based analysis

NASA Astrophysics Data System (ADS)

You, Youbo; Bai, Lijun; Xue, Ting; Zhong, Chongguang; Liu, Zhenyu; Tian, Jie

2011-03-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

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

PubMed

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.

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

Texture-dependent motion signals in primate middle temporal area

PubMed Central

Gharaei, Saba; Tailby, Chris; Solomon, Selina S; Solomon, Samuel G

2013-01-01

Neurons in the middle temporal (MT) area of primate cortex provide an important stage in the analysis of visual motion. For simple stimuli such as bars and plaids some neurons in area MT – pattern cells – seem to signal motion independent of contour orientation, but many neurons – component cells – do not. Why area MT supports both types of receptive field is unclear. To address this we made extracellular recordings from single units in area MT of anaesthetised marmoset monkeys and examined responses to two-dimensional images with a large range of orientations and spatial frequencies. Component and pattern cell response remained distinct during presentation of these complex spatial textures. Direction tuning curves were sharpest in component cells when a texture contained a narrow range of orientations, but were similar across all neurons for textures containing all orientations. Response magnitude of pattern cells, but not component cells, increased with the spatial bandwidth of the texture. In addition, response variability in all neurons was reduced when the stimulus was rich in spatial texture. Fisher information analysis showed that component cells provide more informative responses than pattern cells when a texture contains a narrow range of orientations, but pattern cells had more informative responses for broadband textures. Component cells and pattern cells may therefore coexist because they provide complementary and parallel motion signals. PMID:24000175

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics

NASA Astrophysics Data System (ADS)

Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.

Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.

A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

NASA Astrophysics Data System (ADS)

Suryowati, K.; Bekti, R. D.; Faradila, A.

2018-04-01

Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

[Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain].

PubMed

Gómez-Barroso, Diana; Prieto-Flores, María-Eugenia; Mellado San Gabino, Ana; Moreno Jiménez, Antonio

2015-01-01

Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations. An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped. SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases). Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Differences in Looking at Own- and Other-Race Faces Are Subtle and Analysis-Dependent: An Account of Discrepant Reports.

PubMed

Arizpe, Joseph; Kravitz, Dwight J; Walsh, Vincent; Yovel, Galit; Baker, Chris I

2016-01-01

The Other-Race Effect (ORE) is the robust and well-established finding that people are generally poorer at facial recognition of individuals of another race than of their own race. Over the past four decades, much research has focused on the ORE because understanding this phenomenon is expected to elucidate fundamental face processing mechanisms and the influence of experience on such mechanisms. Several recent studies of the ORE in which the eye-movements of participants viewing own- and other-race faces were tracked have, however, reported highly conflicting results regarding the presence or absence of differential patterns of eye-movements to own- versus other-race faces. This discrepancy, of course, leads to conflicting theoretical interpretations of the perceptual basis for the ORE. Here we investigate fixation patterns to own- versus other-race (African and Chinese) faces for Caucasian participants using different analysis methods. While we detect statistically significant, though subtle, differences in fixation pattern using an Area of Interest (AOI) approach, we fail to detect significant differences when applying a spatial density map approach. Though there were no significant differences in the spatial density maps, the qualitative patterns matched the results from the AOI analyses reflecting how, in certain contexts, Area of Interest (AOI) analyses can be more sensitive in detecting the differential fixation patterns than spatial density analyses, due to spatial pooling of data with AOIs. AOI analyses, however, also come with the limitation of requiring a priori specification. These findings provide evidence that the conflicting reports in the prior literature may be at least partially accounted for by the differences in the statistical sensitivity associated with the different analysis methods employed across studies. Overall, our results suggest that detection of differences in eye-movement patterns can be analysis-dependent and rests on the assumptions inherent in the given analysis.

Differences in Looking at Own- and Other-Race Faces Are Subtle and Analysis-Dependent: An Account of Discrepant Reports

PubMed Central

Arizpe, Joseph; Kravitz, Dwight J.; Walsh, Vincent; Yovel, Galit; Baker, Chris I.

2016-01-01

The Other-Race Effect (ORE) is the robust and well-established finding that people are generally poorer at facial recognition of individuals of another race than of their own race. Over the past four decades, much research has focused on the ORE because understanding this phenomenon is expected to elucidate fundamental face processing mechanisms and the influence of experience on such mechanisms. Several recent studies of the ORE in which the eye-movements of participants viewing own- and other-race faces were tracked have, however, reported highly conflicting results regarding the presence or absence of differential patterns of eye-movements to own- versus other-race faces. This discrepancy, of course, leads to conflicting theoretical interpretations of the perceptual basis for the ORE. Here we investigate fixation patterns to own- versus other-race (African and Chinese) faces for Caucasian participants using different analysis methods. While we detect statistically significant, though subtle, differences in fixation pattern using an Area of Interest (AOI) approach, we fail to detect significant differences when applying a spatial density map approach. Though there were no significant differences in the spatial density maps, the qualitative patterns matched the results from the AOI analyses reflecting how, in certain contexts, Area of Interest (AOI) analyses can be more sensitive in detecting the differential fixation patterns than spatial density analyses, due to spatial pooling of data with AOIs. AOI analyses, however, also come with the limitation of requiring a priori specification. These findings provide evidence that the conflicting reports in the prior literature may be at least partially accounted for by the differences in the statistical sensitivity associated with the different analysis methods employed across studies. Overall, our results suggest that detection of differences in eye-movement patterns can be analysis-dependent and rests on the assumptions inherent in the given analysis. PMID:26849447

Definition of spatial patterns of bark beetle Ips typographus (L.) outbreak spreading in Tatra Mountains (Central Europe), using GIS

Treesearch

Rastislav Jakus; Wojciech Grodzki; Marek Jezik; Marcin Jachym

2003-01-01

The spread of bark beetle outbreaks in the Tatra Mountains was explored by using both terrestrial and remote sensing techniques. Both approaches have proven to be useful for studying spatial patterns of bark beetle population dynamics. The terrestrial methods were applied on existing forestry databases. Vegetation change analysis (image differentiation), digital...

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

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

PubMed Central

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

2011-01-01

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

NASA Astrophysics Data System (ADS)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

PubMed

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

[Quantitative analysis of landscape patterns at the juncture of Shaanxi, Shanxi and Inner Mongolia, based on remote sensing data--taking Yulin sheet TM image as an example].

PubMed

Li, Tuansheng

2004-03-01

Based on the TM image of Yulin sheet and with the help of ERDAS, ARC/INFO and ARC/VIEW software, the landscape of Yulin sheet was classified. Using the spatial pattern analysis software FRAGSTATS of the vector version, a set of landscape indices were calculated at three scale levels of patches, classes and landscape. The results showed that landscape pattern indices could be successfully used in characterizing the spatial pattern of the studied area. However, this study should be further extended to the landscape of the same area in other period to analyze its dynamic change. FRAGSTATS was a good software, but should be improved by adding some indices such as PD2 developed by us.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

PubMed

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

Spatial assessment of air quality patterns in Malaysia using multivariate analysis

NASA Astrophysics Data System (ADS)

Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

2012-12-01

This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

Extended generalized recurrence plot quantification of complex circular patterns

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-03-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing patterns, turbulent spatial plankton patterns, and fractals. Determinism is a central measure in this framework quantifying the level of regularity of spatial structures. We show by basic examples of fully regular patterns of different symmetries that this measure underestimates the orderliness of circular patterns resulting from rotational symmetries. We overcome this crucial problem by checking additional structural elements of the generalized recurrence plot which is demonstrated with the examples. Furthermore, we show the potential of the extended quantity of determinism applying it to more irregular circular patterns which are generated by the complex Ginzburg-Landau-equation and which can be often observed in real spatially extended dynamical systems. So, we are able to reconstruct the main separations of the system's parameter space analyzing single snapshots of the real part only, in contrast to the use of the original quantity. This ability of the proposed method promises also an improved description of other systems with complicated spatio-temporal dynamics typically occurring in fluid dynamics, climatology, biology, ecology, social sciences, etc.

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

PubMed Central

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. PMID:27611199

Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese

USGS Publications Warehouse

Reiter, Matthew E.; Andersen, David E.

2013-01-01

Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species’ distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (Branta canadensis interior) has coincided with increasing populations of nesting lesser snow geese (Chen caerulescens caerulescens) and Ross’s geese (Chen rossii). We conducted a spatial analysis of point patterns using Canada goose nest locations and nest fate, and lesser snow goose nest locations at two study areas in northern Manitoba with different densities and temporal durations of sympatric nesting Canada and lesser snow geese. Specifically, we assessed (1) whether Canada geese exhibited territoriality and at what scale and nest density; and (2) whether spatial patterns of Canada goose nest fate were associated with the density of nesting lesser snow geese as predicted by the protective-association hypothesis. Between 2001 and 2007, our data suggest that Canada geese were territorial at the scale of nearest neighbors, but were aggregated when considering overall density of conspecifics at slightly broader spatial scales. The spatial distribution of nest fates indicated that lesser snow goose nest proximity and density likely influence Canada goose nest fate. Our analyses of spatial point patterns suggested that continued changes in the distribution and abundance of breeding lesser snow geese on the Hudson Bay Lowlands may have impacts on the reproductive performance of Canada geese, and subsequently the spatial distribution of Canada goose nests.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Spatial Analysis of “Crazy Quilts”, a Class of Potentially Random Aesthetic Artefacts

PubMed Central

Westphal-Fitch, Gesche; Fitch, W. Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. “Crazy quilts” represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures. PMID:24066095

Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

PubMed

Westphal-Fitch, Gesche; Fitch, W Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data

PubMed Central

Li, Weifeng; Cheng, Xiaoyun; Guo, Gaohua

2014-01-01

The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework. PMID:25435865

Binary Programming Models of Spatial Pattern Recognition: Applications in Remote Sensing Image Analysis

DTIC Science & Technology

1991-12-01

9 2.6.1 Multi-Shape Detection. .. .. .. .. .. .. ...... 9 Page 2.6.2 Line Segment Extraction and Re-Combination.. 9 2.6.3 Planimetric Feature... Extraction ............... 10 2.6.4 Line Segment Extraction From Statistical Texture Analysis .............................. 11 2.6.5 Edge Following as Graph...image after image, could benefit clue to the fact that major spatial characteristics of subregions could be extracted , and minor spatial changes could be

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Spatial Exposure Analysis for Threatened and Endangered Species from Changing Pesticide Use Pattern in Southern Georgia

EPA Science Inventory

In recent decades, pesticide use patterns and crop distributions have changed; however, because there has not been a significant increase in usage disclosures, it is difficult to estimate the changes in potential exposure zones, this analysis focuses on the intersection of agricu...

Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009.

PubMed

Yin, Fei; Feng, Zijian; Li, Xiaosong

2012-07-01

Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.

Net primary production and canopy nitrogen in a temperate forest landscape: an analysis using imaging spectroscopy, modeling and field data

Treesearch

Scott V. Ollinger; Marie-Louise Smith

2005-01-01

Understanding spatial patterns of net primary production (NPP) is central to the study of terrestrial ecosystems, but efforts are frequently hampered by a lack of spatial information regarding factors such as nitrogen availability and site history. Here, we examined the degree to which canopy nitrogen can serve as an indicator of patterns of NPP at the Bartlett...

Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach

DTIC Science & Technology

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

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

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.

Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

PubMed Central

Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

2015-01-01

Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

Spatial analysis of agro-ecological data: Detection of spatial patterns combining three different methodical approaches

NASA Astrophysics Data System (ADS)

Heuer, A.; Casper, M. C.; Vohland, M.

2009-04-01

Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to comprehensive and reasonable results, which will be presented in detail. It can be concluded, that the chosen strategy made it possible to complement preliminary findings, to validate the results of a single approach and to clearly delineate spatial patterns.

Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.

Dynamic Patterns of Modern Epidemics

NASA Astrophysics Data System (ADS)

Brockmann, Dirk; Hufnagel, Lars; Geisel, Theo

2004-03-01

We investigate the effects of scale-free travelling of humans and their inhomogeneous geographic distribution on the dynamic patterns of spreading epidemics. Our approach combines the susceptible/infected/recovered paradigm for the infection dynamics with superdiffusive dispersion of individuals and their inhomogeneous spatial distribution. We show that scale-free motion of individuals and their variable spatial distribution leads to the absence of wavefronts in dynamic epidemic patterns which are typical for the limiting cases of ordinary diffusion and spatially homogeneous populations. Instead, patterns emerge with isolated hotspots on highly populated areas from which regional epidemic outbursts are triggered. Hotspot sizes are independent of the correlation length in the spatial distribution of individuals and occur on all scales. Our theory predicts that highly populated areas are reached by an epidemic in advance and must receive special attention in control measure strategies. Furthermore, our analysis predicts strong fluctuations in the time course of the total infection which cannot be accounted for by ordinary reaction-diffusion models for epidemics.

Applications of Remote Sensing and GIS(Geographic Information System) in Crime Analysis of Gujranwala City.

NASA Astrophysics Data System (ADS)

Munawar, Iqra

2016-07-01

Crime mapping is a dynamic process. It can be used to assist all stages of the problem solving process. Mapping crime can help police protect citizens more effectively. The decision to utilize a certain type of map or design element may change based on the purpose of a map, the audience or the available data. If the purpose of the crime analysis map is to assist in the identification of a particular problem, selected data may be mapped to identify patterns of activity that have been previously undetected. The main objective of this research was to study the spatial distribution patterns of the four common crimes i.e Narcotics, Arms, Burglary and Robbery in Gujranwala City using spatial statistical techniques to identify the hotspots. Hotspots or location of clusters were identified using Getis-Ord Gi* Statistic. Crime analysis mapping can be used to conduct a comprehensive spatial analysis of the problem. Graphic presentations of such findings provide a powerful medium to communicate conditions, patterns and trends thus creating an avenue for analysts to bring about significant policy changes. Moreover Crime mapping also helps in the reduction of crime rate.

Temporal Dynamics and Persistence of Spatial Patterns: from Groundwater to Soil Moisture to Transpiration

NASA Astrophysics Data System (ADS)

Blume, T.; Hassler, S. K.; Weiler, M.

2017-12-01

Hydrological science still struggles with the fact that while we wish for spatially continuous images or movies of state variables and fluxes at the landscape scale, most of our direct measurements are point measurements. To date regional measurements resolving landscape scale patterns can only be obtained by remote sensing methods, with the common drawback that they remain near the earth surface and that temporal resolution is generally low. However, distributed monitoring networks at the landscape scale provide the opportunity for detailed and time-continuous pattern exploration. Even though measurements are spatially discontinuous, the large number of sampling points and experimental setups specifically designed for the purpose of landscape pattern investigation open up new avenues of regional hydrological analyses. The CAOS hydrological observatory in Luxembourg offers a unique setup to investigate questions of temporal stability, pattern evolution and persistence of certain states. The experimental setup consists of 45 sensor clusters. These sensor clusters cover three different geologies, two land use classes, five different landscape positions, and contrasting aspects. At each of these sensor clusters three soil moisture/soil temperature profiles, basic climate variables, sapflow, shallow groundwater, and stream water levels were measured continuously for the past 4 years. We will focus on characteristic landscape patterns of various hydrological state variables and fluxes, studying their temporal stability on the one hand and the dependence of patterns on hydrological states on the other hand (e.g. wet vs dry). This is extended to time-continuous pattern analysis based on time series of spatial rank correlation coefficients. Analyses focus on the absolute values of soil moisture, soil temperature, groundwater levels and sapflow, but also investigate the spatial pattern of the daily changes of these variables. The analysis aims at identifying hydrologic signatures of the processes or landscape characteristics acting as major controls. While groundwater, soil water and transpiration are closely linked by the water cycle, they are controlled by different processes and we expect this to be reflected in interlinked but not necessarily congruent patterns and responses.

Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

PubMed Central

2009-01-01

Background Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns. Methods In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender. Results Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships. Conclusions Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services. PMID:20003460

[Spatial patterns of dominant tree species in sub-alpine Betula-Abies forest in West Sichuan of China].

PubMed

Miao, Ning; Liu, Shi-Rong; Shi, Zuo-Min; Yu, Hong; Liu, Xing-Liang

2009-06-01

Based on the investigation in a 4 hm2 Betula-Abies forest plot in sub-alpine area in West Sichuan of China, and by using point pattern analysis method in terms of O-ring statistics, the spatial patterns of dominant species Betula albo-sinensis and Abies faxoniana in different age classes in study area were analyzed, and the intra- and inter-species associations between these age classes were studied. B. albo-sinensis had a unimodal distribution of its DBH frequency, indicating a declining population, while A. faxoniana had a reverse J-shaped pattern, showing an increasing population. All the big trees of B. albo-sinensis and A. faxoniana were spatially in random at all scales, while the medium age and small trees were spatially clumped at small scales and tended to be randomly or evenly distributed with increasing spatial scale. The maximum aggregation degree decreased with increasing age class. Spatial association mainly occurred at small scales. A. faxoniana generally showed positive intra-specific association, while B. albo-sinensis generally showed negative intra-specific association. For the two populations, big and small trees had no significant spatial association, but middle age trees had negative spatial association. Negative inter-specific associations of the two populations were commonly found in different age classes. The larger the difference of age class, the stronger the negative inter-specific association.

Characterizing forest fragments in boreal, temperate, and tropical ecosystems

Treesearch

Arjan J. H. Meddens; Andrew T. Hudak; Jeffrey S. Evans; William A. Gould; Grizelle Gonzalez

2008-01-01

An increased ability to analyze landscapes in a spatial manner through the use of remote sensing leads to improved capabilities for quantifying human-induced forest fragmentation. Developments of spatially explicit methods in landscape analyses are emerging. In this paper, the image delineation software program eCognition and the spatial pattern analysis program...

Use of Fouler Transforms to define landscape scales of analysis for disturbances: A case study of thinned and unthinned forest stands

Treesearch

J. E. Lundquist; R. A. Sommerfeld

2002-01-01

Various disturbances such as disease and management practices cause canopy gaps that change patterns of forest stand structure. This study examined the usefulness of digital image analysis using aerial photos, Fourier Tranforms, and cluster analysis to investigate how different spatial statistics are affected by spatial scale. The specific aims were to: 1) evaluate how...

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

A morphometric analysis of vegetation patterns in dryland ecosystems

PubMed Central

Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-01-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems. PMID:28386414

A morphometric analysis of vegetation patterns in dryland ecosystems.

PubMed

Mander, Luke; Dekker, Stefan C; Li, Mao; Mio, Washington; Punyasena, Surangi W; Lenton, Timothy M

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

A morphometric analysis of vegetation patterns in dryland ecosystems

NASA Astrophysics Data System (ADS)

Mander, Luke; Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

Relationship Between Landcover Pattern and Surface Net Radiation in AN Coastal City

NASA Astrophysics Data System (ADS)

Zhao, X.; Liu, L.; Liu, X.; Zhao, Y.

2016-06-01

Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marre, O.; El Boustani, S.; Fregnac, Y.

We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

Spatial and temporal analyses of citrus sudden death as a tool to generate hypotheses concerning its etiology.

PubMed

Bassanezi, Renato B; Bergamin Filho, Armando; Amorim, Lilian; Gimenes-Fernandes, Nelson; Gottwald, Tim R; Bové, Joseph M

2003-04-01

ABSTRACT Citrus sudden death (CSD), a new disease of unknown etiology that affects sweet orange grafted on Rangpur lime, was visually monitored for 14 months in 41 groves in Brazil. Ordinary runs analysis of CSD-symptomatic trees indicated a departure from randomness of symptomatic trees status among immediately adjacent trees mainly within rows. The binomial index of dispersion (D) and the intraclass correlation (k) for various quadrat sizes suggested aggregation of CSD-symptomatic trees for almost all plots within the quadrat sizes tested. Estimated parameters of the binary form of Taylor's power law provided an overall measure of aggregation of CSD-symptomatic trees for all quadrat sizes tested. Aggregation in each plot was dependent on disease incidence. Spatial autocorrelation analysis of proximity patterns suggested that aggregation often existed among quadrats of various sizes up to three lag distances; however, significant lag positions discontinuous from main proximity patterns were rare, indicating a lack of spatial association among discrete foci. Some asymmetry was also detected for some spatial autocorrelation proximity patterns, indicating that within-row versus across-row distributions are not necessarily equivalent. These results were interpreted to mean that the cause of the disease was most likely biotic and its dissemination was common within a local area of influence that extended to approximately six trees in all directions, including adjacent trees. Where asymmetry was indicated, this area of influence was somewhat elliptical. Longer-distance patterns were not detected within the confines of the plot sizes tested. Annual rates of CSD progress based on the Gompertz model ranged from 0.37 to 2.02. Numerous similarities were found between the spatial patterns of CSD and Citrus tristeza virus (CTV) described in the literature, both in the presence of the aphid vector, Toxoptera citricida. CSD differs from CTV in that symptoms occur in sweet orange grafted on Rangpur lime. Based on the symptoms of CSD and on its spatial and temporal patterns, our hypothesis is that CSD may be caused by a similar but undescribed pathogen such as a virus and probably vectored by insects such as aphids by similar spatial processes to those affecting CTV.

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

PubMed Central

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-01-01

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

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

NASA Astrophysics Data System (ADS)

Huang, X.; Tan, J.

2014-11-01

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

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Assessment of the spatial pattern of colorectal tumour perfusion estimated at perfusion CT using two-dimensional fractal analysis.

PubMed

Goh, Vicky; Sanghera, Bal; Wellsted, David M; Sundin, Josefin; Halligan, Steve

2009-06-01

The aim was to evaluate the feasibility of fractal analysis for assessing the spatial pattern of colorectal tumour perfusion at dynamic contrast-enhanced CT (perfusion CT). Twenty patients with colorectal adenocarcinoma underwent a 65-s perfusion CT study from which a perfusion parametric map was generated using validated commercial software. The tumour was identified by an experienced radiologist, segmented via thresholding and fractal analysis applied using in-house software: fractal dimension, abundance and lacunarity were assessed for the entire outlined tumour and for selected representative areas within the tumour of low and high perfusion. Comparison was made with ten patients with normal colons, processed in a similar manner, using two-way mixed analysis of variance with statistical significance at the 5% level. Fractal values were higher in cancer than normal colon (p < or = 0.001): mean (SD) 1.71 (0.07) versus 1.61 (0.07) for fractal dimension and 7.82 (0.62) and 6.89 (0.47) for fractal abundance. Fractal values were lower in 'high' than 'low' perfusion areas. Lacunarity curves were shifted to the right for cancer compared with normal colon. In conclusion, colorectal cancer mapped by perfusion CT demonstrates fractal properties. Fractal analysis is feasible, potentially providing a quantitative measure of the spatial pattern of tumour perfusion.

Remote sensing data with the conditional latin hypercube sampling and geostatistical approach to delineate landscape changes induced by large chronological physical disturbances.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh

2009-01-01

This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.

Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity

PubMed Central

2018-01-01

Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. PMID:29465399

Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

NASA Astrophysics Data System (ADS)

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.

Analysis of the spatial and temporal distribution of malaria in an area of Northern Guatemala with seasonal malaria transmission.

PubMed

Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J

2018-06-23

The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.

Complex-ordered patterns in shaken convection.

PubMed

Rogers, Jeffrey L; Pesch, Werner; Brausch, Oliver; Schatz, Michael F

2005-06-01

We report and analyze complex patterns observed in a combination of two standard pattern forming experiments. These exotic states are composed of two distinct spatial scales, each displaying a different temporal dependence. The system is a fluid layer experiencing forcing from both a vertical temperature difference and vertical time-periodic oscillations. Depending on the parameters these forcing mechanisms produce fluid motion with either a harmonic or a subharmonic temporal response. Over a parameter range where these mechanisms have comparable influence the spatial scales associated with both responses are found to coexist, resulting in complex, yet highly ordered patterns. Phase diagrams of this region are reported and criteria to define the patterns as quasiperiodic crystals or superlattices are presented. These complex patterns are found to satisfy four-mode (resonant tetrad) conditions. The qualitative difference between the present formation mechanism and the resonant triads ubiquitously used to explain complex-ordered patterns in other nonequilibrium systems is discussed. The only exception to quantitative agreement between our analysis based on Boussinesq equations and laboratory investigations is found to be the result of breaking spatial symmetry in a small parameter region near onset.

Spatial pattern of reference evapotranspiration change and its temporal evolution over Southwest China

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Wang, Guojie; Huang, Jin; Mu, Mengyuan; Yan, Guixia; Liu, Chunwei; Gao, Chujie; Li, Xing; Yin, Yixing; Zhang, Fangmin; Zhu, Siguang; Hua, Wenjian

2017-11-01

Due to the close relationship of climate change with reference evapotranspiration (ETo), detecting changes in ETo spatial distribution and its temporal evolution at local and regional levels is favorable to comprehensively understand climate change-induced impacts on hydrology and agriculture. In this study, the objective is to identify whether climate change has caused variation of ETo spatial distribution in different analysis periods [i.e., long- (20-year), medium- (10-year), and short-term (5-year)] and to investigate its temporal evolution (namely, when these changes happened) at annual and monthly scales in Southwest China (SWC). First, we estimated ETo values using the United Nations Food and Agriculture Organization (FAO) Penman-Monteith equation, based on historical climate data measured at 269 weather sites during 1973-2012. The analysis of variance (ANOVA) results indicated that the spatial pattern of annual ETo had significantly changed during the past 40 years, particularly in west SWC for the long-term analysis period, and west and southeast SWC in both medium- and short-term periods, which corresponded to the percent area of significant differences which were 21.9, 58.0, and 48.2 %, respectively. For investigating temporal evolution of spatial patterns of annual ETo, Duncan's multiple range test was used, and we found that the most significant changes appeared during 1988-2002 with the significant area of higher than 25.0 %. In addition, for long-, medium-, and short-term analysis periods, the spatial distribution has significantly changed during March, September, November, and December, especially in the corresponding periods of 1988-1997, 1983-1992, 1973-1977, and 1988-2002. All in all, climate change has resulted in significant ETo changes in SWC since the 1970s. Knowledge of climate change-induced spatial distribution of ETo and its temporal evolution would aid in formulating strategies for water resources and agricultural managements.

Phylogenetic congruence of lichenised fungi and algae is affected by spatial scale and taxonomic diversity.

PubMed

Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M

2014-01-01

The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.

The stability and slow dynamics of spot patterns in the 2D Brusselator model: The effect of open systems and heterogeneities

NASA Astrophysics Data System (ADS)

Tzou, J. C.; Ward, M. J.

2018-06-01

Spot patterns, whereby the activator field becomes spatially localized near certain dynamically-evolving discrete spatial locations in a bounded multi-dimensional domain, is a common occurrence for two-component reaction-diffusion (RD) systems in the singular limit of a large diffusivity ratio. In previous studies of 2-D localized spot patterns for various specific well-known RD systems, the domain boundary was assumed to be impermeable to both the activator and inhibitor, and the reaction-kinetics were assumed to be spatially uniform. As an extension of this previous theory, we use formal asymptotic methods to study the existence, stability, and slow dynamics of localized spot patterns for the singularly perturbed 2-D Brusselator RD model when the domain boundary is only partially impermeable, as modeled by an inhomogeneous Robin boundary condition, or when there is an influx of inhibitor across the domain boundary. In our analysis, we will also allow for the effect of a spatially variable bulk feed term in the reaction kinetics. By applying our extended theory to the special case of one-spot patterns and ring patterns of spots inside the unit disk, we provide a detailed analysis of the effect on spot patterns of these three different sources of heterogeneity. In particular, when there is an influx of inhibitor across the boundary of the unit disk, a ring pattern of spots can become pinned to a ring-radius closer to the domain boundary. Under a Robin condition, a quasi-equilibrium ring pattern of spots is shown to exhibit a novel saddle-node bifurcation behavior in terms of either the inhibitor diffusivity, the Robin constant, or the ambient background concentration. A spatially variable bulk feed term, with a concentrated source of "fuel" inside the domain, is shown to yield a saddle-node bifurcation structure of spot equilibria, which leads to qualitatively new spot-pinning behavior. Results from our asymptotic theory are validated from full numerical simulations of the Brusselator model.

Extended quantification of the generalized recurrence plot

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2016-04-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing structures, turbulent spatial plankton patterns, and fractals. But, it is also successfully applied to the description of spatio-temporal dynamics and the detection of regime shifts, such as in the complex Ginzburg-Landau- equation. The recurrence plot based determinism is a central measure in this framework quantifying the level of regularities in temporal and spatial structures. We extend this measure for the generalized recurrence plot considering additional operations of symmetry than the simple translation. It is tested not only on two-dimensional regular patterns and noise but also on complex spatial patterns reconstructing the parameter space of the complex Ginzburg-Landau-equation. The extended version of the determinism resulted in values which are consistent to the original recurrence plot approach. Furthermore, the proposed method allows a split of the determinism into parts which based on laminar and non-laminar regions of the two-dimensional pattern of the complex Ginzburg-Landau-equation. A comparison of these parts with a standard method of image classification, the co-occurrence matrix approach, shows differences especially in the description of patterns associated with turbulence. In that case, it seems that the extended version of the determinism allows a distinction of phase turbulence and defect turbulence by means of their spatial patterns. This ability of the proposed method promise new insights in other systems with turbulent dynamics coming from climatology, biology, ecology, and social sciences, for example.

Characterization of spatial distribution of Tetranychus urticae in peppermint in California and implication for improving sampling plan.

PubMed

Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D

2016-02-01

Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.

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

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

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.

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

USGS Publications Warehouse

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.

A scoping review of spatial cluster analysis techniques for point-event data.

PubMed

Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott

2013-05-01

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

PubMed Central

Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

2016-01-01

Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling. PMID:26507005

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

NASA Astrophysics Data System (ADS)

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.

Landscape pattern of seed banks and anthropogenic impacts in forested wetlands of the northern Mississippi River Alluvial Valley

USGS Publications Warehouse

Middleton, B.; Wu, X.B.

2008-01-01

Agricultural development on floodplains contributes to hydrologic alteration and forest fragmentation, which may alter landscape-level processes. These changes may be related to shifts in the seed bank composition of floodplain wetlands. We examined the patterns of seed bank composition across a floodplain watershed by looking at the number of seeds germinating per m2 by species in 60 farmed and intact forested wetlands along the Cache River watershed in Illinois. The seed bank composition was compared above and below a water diversion (position), which artificially subdivides the watershed. Position of these wetlands represented the most variability of Axis I in a Nonmetric Multidimensional Scaling (NMS) analysis of site environmental variables and their relationship to seed bank composition (coefficient of determination for Axis 1: r2 = 0.376; Pearson correlation of position to Axis 1: r = 0.223). The 3 primary axes were also represented by other site environmental variables, including farming status (farmed or unfarmed), distance from the mouth of the river, latitude, and longitude. Spatial analysis based on Mantel correlograms showed that both water-dispersed and wind/water-dispersed seed assemblages had strong spatial structure in the upper Cache (above the water diversion), bur the spatial structure of water-dispersed seed assemblage was diminished in the lower Cache (below the water diversion), which lost floodpulsing. Bearing analysis also Suggested that water-dispersal process had a stronger influence on the overall spatial pattern of seed assemblage in the upper Cache, while wind/water-dispersal process had a stronger influence in the lower Cache. An analysis of the landscapes along the river showed that the mid-lower Cache (below the water diversion) had undergone greater land cover changes associated with agriculture than did the upper Cache watershed. Thus, the combination of forest fragmentation and hydrologic changes in the surrounding landscape may have had an influence on the seed bank composition and spatial distribution of the seed banks of the Cache River watershed. Our study suggests that the spatial pattern of seed bank composition may be influenced by landscape-level factors and processes.

Spatial distribution pattern of termite in Endau Rompin Plantation

NASA Astrophysics Data System (ADS)

Jalaludin, Nur-Atiqah; Rahim, Faszly

2015-09-01

We censused 18 field blocks approximately 190 ha with total of 28,604 palms in a grid of 2×4 palms from July 2011 to March 2013. The field blocks comprise of rows of palm trees, harvesting paths, field drains and stacking rows with maximum of 30 palms per row, planted about 9 m apart, alternately in maximum of 80 rows. SADIE analysis generating index of aggregation, Ia, local clustering value, Vi and local gap value, Vj is adopted to estimate spatial pattern. The patterns were then presented in contour map using Surfer 12 software. The patterns produced associated with factors i.e. habitat disturbance, habitat fragmentation and resources affecting nesting and foraging activities. Result shows that field blocks with great habitat disturbance recorded highest dead palms and termites hits. Blocks located far from the main access road recorded less than 2% palms with termite hits. This research may provide ecological data on termite spatial pattern in oil palm ecosystem.

OLED emission zone measurement with high accuracy

NASA Astrophysics Data System (ADS)

Danz, N.; MacCiarnain, R.; Michaelis, D.; Wehlus, T.; Rausch, A. F.; Wächter, C. A.; Reusch, T. C. G.

2013-09-01

Highly efficient state of the art organic light-emitting diodes (OLED) comprise thin emitting layers with thicknesses in the order of 10 nm. The spatial distribution of the photon generation rate, i.e. the profile of the emission zone, inside these layers is of interest for both device efficiency analysis and characterization of charge recombination processes. It can be accessed experimentally by reverse simulation of far-field emission pattern measurements. Such a far-field pattern is the sum of individual emission patterns associated with the corresponding positions inside the active layer. Based on rigorous electromagnetic theory the relation between far-field pattern and emission zone is modeled as a linear problem. This enables a mathematical analysis to be applied to the cases of single and double emitting layers in the OLED stack as well as to pattern measurements in air or inside the substrate. From the results, guidelines for optimum emitter - cathode separation and for selecting the best experimental approach are obtained. Limits for the maximum spatial resolution can be derived.

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Exploratory study and application of the angular wavelet analysis for assessing the spatial distribution of breakdown spots in Pt/HfO2/Pt structures

NASA Astrophysics Data System (ADS)

Muñoz-Gorriz, J.; Monaghan, S.; Cherkaoui, K.; Suñé, J.; Hurley, P. K.; Miranda, E.

2017-12-01

The angular wavelet analysis is applied for assessing the spatial distribution of breakdown spots in Pt/HfO2/Pt capacitors with areas ranging from 104 to 105 μm2. The breakdown spot lateral sizes are in the range from 1 to 3 μm, and they appear distributed on the top metal electrode as a point pattern. The spots are generated by ramped and constant voltage stresses and are the consequence of microexplosions caused by the formation of shorts spanning the dielectric film. This kind of pattern was analyzed in the past using the conventional spatial analysis tools such as intensity plots, distance histograms, pair correlation function, and nearest neighbours. Here, we show that the wavelet analysis offers an alternative and complementary method for testing whether or not the failure site distribution departs from a complete spatial randomness process in the angular domain. The effect of using different wavelet functions, such as the Haar, Sine, French top hat, Mexican hat, and Morlet, as well as the roles played by the process intensity, the location of the voltage probe, and the aspect ratio of the device, are all discussed.

Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan.

PubMed

Meliker, Jaymie R; Maio, Ronald F; Zimmerman, Marc A; Kim, Hyungjin Myra; Smith, Sarah C; Wilson, Mark L

2004-11-01

Temporal, behavioral and social risk factors that affect injuries resulting from alcohol-related motor vehicle crashes have been characterized in previous research. Much less is known about spatial patterns and environmental associations of alcohol-related motor vehicle crashes. The aim of this study was to evaluate geographic patterns of alcohol-related motor vehicle crashes and to determine if locations of alcohol outlets are associated with those crashes. In addition, we sought to demonstrate the value of integrating spatial and traditional statistical techniques in the analysis of this preventable public health risk. The study design was a cross-sectional analysis of individual-level blood alcohol content, traffic report information, census block group data, and alcohol distribution outlets. Besag and Newell's spatial analysis and traditional logistic regression both indicated that areas of low population density had more alcohol-related motor vehicle crashes than expected (P < 0.05). There was no significant association between alcohol outlets and alcohol-related motor vehicle crashes using distance analyses, logistic regression, and Chi-square. Differences in environmental or behavioral factors characteristic of areas of low population density may be responsible for the higher proportion of alcohol-related crashes occurring in these areas.

Delineating resource sheds in aquatic ecosystems (presentation)

EPA Science Inventory

Analysis of spatially-explicit ecological phenomena in aquatic ecosystems is impeded by a lack of knowledge of, and tools to delimit, spatial patterns of material supply to point locations. Here we apply the concept of "resource sheds" to coasts and watersheds. Resource sheds ar...

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

Spatial patterns of ecosystem carbon residence time and NPP-driven carbon uptake in the conterminous United States

NASA Astrophysics Data System (ADS)

Zhou, Tao; Luo, Yiqi

2008-09-01

Ecosystem carbon (C) uptake is determined largely by C residence times and increases in net primary production (NPP). Therefore, evaluation of C uptake at a regional scale requires knowledge on spatial patterns of both residence times and NPP increases. In this study, we first applied an inverse modeling method to estimate spatial patterns of C residence times in the conterminous United States. Then we combined the spatial patterns of estimated residence times with a NPP change trend to assess the spatial patterns of regional C uptake in the United States. The inverse analysis was done by using the genetic algorithm and was based on 12 observed data sets of C pools and fluxes. Residence times were estimated by minimizing the total deviation between modeled and observed values. Our results showed that the estimated C residence times were highly heterogeneous over the conterminous United States, with most of the regions having values between 15 and 65 years; and the averaged C residence time was 46 years. The estimated C uptake for the whole conterminous United States was 0.15 P g C a-1. Large portions of the taken C were stored in soil for grassland and cropland (47-70%) but in plant pools for forests and woodlands (73-82%). The proportion of C uptake in soil was found to be determined primarily by C residence times and be independent of the magnitude of NPP increase. Therefore, accurate estimation of spatial patterns of C residence times is crucial for the evaluation of terrestrial ecosystem C uptake.

Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging

NASA Astrophysics Data System (ADS)

Gureyev, T. E.; Paganin, D. M.; Kozlov, A.; Nesterets, Ya. I.; Quiney, H. M.

2018-05-01

A generic computational imaging setup is considered which assumes sequential illumination of a semitransparent object by an arbitrary set of structured coherent illumination patterns. For each incident illumination pattern, all transmitted light is collected by a photon-counting bucket (single-pixel) detector. The transmission coefficients measured in this way are then used to reconstruct the spatial distribution of the object's projected transmission. It is demonstrated that the square of the spatial resolution of such a setup is usually equal to the ratio of the image area to the number of linearly independent illumination patterns. If the noise in the measured transmission coefficients is dominated by photon shot noise, then the ratio of the square of the mean signal to the noise variance is proportional to the ratio of the mean number of registered photons to the number of illumination patterns. The signal-to-noise ratio in a reconstructed transmission distribution is always lower if the illumination patterns are nonorthogonal, because of spatial correlations in the measured data. Examples of imaging methods relevant to the presented analysis include conventional imaging with a pixelated detector, computational ghost imaging, compressive sensing, super-resolution imaging, and computed tomography.

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

PubMed Central

Fan, Yong; Batmanghelich, Nematollah; Clark, Chris M.; Davatzikos, Christos

2010-01-01

Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses. PMID:18053747

Analysis of extent and spatial pattern change of mangrove ecosystem in Mangunharjo Sub-district from 2007 to 2017

NASA Astrophysics Data System (ADS)

Nugraha, S. B.; Sidiq, W. A. B. N.; Setyowati, D. L.; Martuti, N. K. T.

2018-03-01

This study aims to determine changes in the extent and spatial patterns of mangrove ecosystems in Mangunharjo Sub-district from 2007, 2012 and 2017. The main data source of this research is Digital Globe Imagery of Mangunharjo Sub-district and surrounding area. The extent and spatial pattern of the mangrove ecosystem were obtained from visual interpretation result of the time series image and accuracy tested with field survey data, and then the analysis was conducted quantitatively and qualitatively. The result of time series data analysis shows that there is an enhancement of mangrove forest area in Mangunharjo Sub-district from 2007-2017. In the first five years (2007-2012), the area of mangrove ecosystem increased from 9.01 Ha to 19.78 Ha, and then in the next five years (2012-2017), it was increased significantly from 19.78 Ha to 68.47 Ha. If analyzed from the spatial pattern, in 2007-2012 the mangrove ecosystems were distributed extends along the river border ponds, while in 2012-2017 it already clustered to form a certain area located at the estuary. The increasing of mangrove area in Mangunharjo Sub-district is a result of hard work with various parties, from the government institution, individual and company which launched mangrove ecosystem recovery program especially in the coastal area of Semarang City. With the better mangrove ecosystem is expected to help restore and prevent the occurrence of environmental damage in the coastal area of Semarang City due to abrasion, seawater intrusion, and tidal flood.

A spatial emergy model for Alachua County, Florida

NASA Astrophysics Data System (ADS)

Lambert, James David

A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method will be directly comparable with the results of this study. The results and conclusions of this study reinforce the hypothesis that an urban landscape will develop a predictable spatial pattern that can be described in terms of a universal energy transformation hierarchy.

Spatiotemporal distribution patterns of forest fires in northern Mexico

Treesearch

Gustavo Pérez-Verdin; M. A. Márquez-Linares; A. Cortes-Ortiz; M. Salmerón-Macias

2013-01-01

Using the 2000-2011 CONAFOR databases, a spatiotemporal analysis of the occurrence of forest fires in Durango, one of the most affected States in Mexico, was conducted. The Moran's index was used to determine a spatial distribution pattern; also, an analysis of seasonal and temporal autocorrelation of the data collected was completed. The geographically weighted...

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

PubMed

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.

The isolation of spatial patterning modes in a mathematical model of juxtacrine cell signalling.

PubMed

O'Dea, R D; King, J R

2013-06-01

Juxtacrine signalling mechanisms are known to be crucial in tissue and organ development, leading to spatial patterns in gene expression. We investigate the patterning behaviour of a discrete model of juxtacrine cell signalling due to Owen & Sherratt (1998, Mathematical modelling of juxtacrine cell signalling. Math. Biosci., 153, 125-150) in which ligand molecules, unoccupied receptors and bound ligand-receptor complexes are modelled. Feedback between the ligand and receptor production and the level of bound receptors is incorporated. By isolating two parameters associated with the feedback strength and employing numerical simulation, linear stability and bifurcation analysis, the pattern-forming behaviour of the model is analysed under regimes corresponding to lateral inhibition and induction. Linear analysis of this model fails to capture the patterning behaviour exhibited in numerical simulations. Via bifurcation analysis, we show that since the majority of periodic patterns fold subcritically from the homogeneous steady state, a wide variety of stable patterns exists at a given parameter set, providing an explanation for this failure. The dominant pattern is isolated via numerical simulation. Additionally, by sampling patterns of non-integer wavelength on a discrete mesh, we highlight a disparity between the continuous and discrete representations of signalling mechanisms: in the continuous case, patterns of arbitrary wavelength are possible, while sampling such patterns on a discrete mesh leads to longer wavelength harmonics being selected where the wavelength is rational; in the irrational case, the resulting aperiodic patterns exhibit 'local periodicity', being constructed from distorted stable shorter wavelength patterns. This feature is consistent with experimentally observed patterns, which typically display approximate short-range periodicity with defects.

Drive by Soil Moisture Measurement: A Citizen Science Project

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

2017-12-01

Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.

Spatial Analysis of PAHs in Soils along an Urban-Suburban-Rural Gradient: scale effect, distribution patterns, diffusion and influencing factors

NASA Astrophysics Data System (ADS)

Peng, Chi; Wang, Meie; Chen, Weiping

2016-11-01

Spatial statistical methods including Cokriging interpolation, Morans I analysis, and geographically weighted regression (GWR) were used for studying the spatial characteristics of polycyclic aromatic hydrocarbon (PAH) accumulation in urban, suburban, and rural soils of Beijing. The concentrations of PAHs decreased spatially as the level of urbanization decreased. Generally, PAHs in soil showed two spatial patterns on the regional scale: (1) regional baseline depositions with a radius of 16.5 km related to the level of urbanization and (2) isolated pockets of soil contaminated with PAHs were found up to around 3.5 km from industrial point sources. In the urban areas, soil PAHs showed high spatial heterogeneity on the block scale, which was probably related to vegetation cover, land use, and physical soil disturbance. The distribution of total PAHs in urban blocks was unrelated to the indicators of the intensity of anthropogenic activity, namely population density, light intensity at night, and road density, but was significantly related to the same indicators in the suburban and rural areas. The moving averages of molecular ratios suggested that PAHs in the suburban and rural soils were a mix of local emissions and diffusion from urban areas.

Disentangling working memory processes during spatial span assessment: a modeling analysis of preferred eye movement strategies.

PubMed

Patt, Virginie M; Thomas, Michael L; Minassian, Arpi; Geyer, Mark A; Brown, Gregory G; Perry, William

2014-01-01

The neurocognitive processes involved during classic spatial working memory (SWM) assessment were investigated by examining naturally preferred eye movement strategies. Cognitively healthy adult volunteers were tested in a computerized version of the Corsi Block-Tapping Task--a spatial span task requiring the short term maintenance of a series of locations presented in a specific order--coupled with eye tracking. Modeling analysis was developed to characterize eye-tracking patterns across all task phases, including encoding, retention, and recall. Results revealed a natural preference for local gaze maintenance during both encoding and retention, with fewer than 40% fixated targets. These findings contrasted with the stimulus retracing pattern expected during recall as a result of task demands, with 80% fixated targets. Along with participants' self-reported strategies of mentally "making shapes," these results suggest the involvement of covert attention shifts and higher order cognitive Gestalt processes during spatial span tasks, challenging instrument validity as a single measure of SWM storage capacity.

Application of urban neighborhoods in understanding of local level electricity consumption patterns

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Bhaduri, B. L.

2017-12-01

Aggregated national or regional level electricity consumption data fail to capture the spatial variation in consumption, a function of location, climate, topography, and local economics. Spatial monitoring of electricity usage patterns helps to understand derivers of location specific consumption behavior and develop models to cater to the consumer needs, plan efficiency measures, identify settled areas lacking access, and allows for future planning through assessing requirements. Developed countries have started to deploy sensor systems such as smart meters to gather information on local level consumption patterns, but such infrastructure is virtually nonexistent in developing nations, resulting in serious dearth of reliable data for planners and policy makers. Remote sensing of artificial nighttime lights from human settlements have proven useful to study electricity consumptions from global to regional scales, however, local level studies remain scarce. Using the differences in spatial characteristics among different urban neighborhoods such as industrial, commercial and residential, observable through very high resolution day time satellite images (<0.5 meter), formal urban neighborhoods have been generated through texture analysis. In this study, we explore the applicability of these urban neighborhoods in understanding local level electricity consumption patterns through exploring possible correlations between the spatial characteristics of these neighborhoods, associated general economic activities, and corresponding VIIRS day-night band (DNB) nighttime lights observations, which we use as a proxy for electricity consumption in the absence of ground level consumption data. The overall trends observed through this analysis provides useful explanations helping in understanding of broad electricity consumption patterns in urban areas lacking ground level observations. This study thus highlights possible application of remote sensing data driven methods in providing novel insights into local level socio-economic patterns that were hitherto undetected due to lack of ground data.

A MULTI-LOCUS, MULTI-TAXA PHYLOGEOGRAPHICAL ANALYSIS OF GENETIC DIVERSITY

EPA Science Inventory

In addition to measuring spatial patterns of genetic diversity, population genetic measures of biological resources should include temporal data that indicate whether the observed patterns are the result of historical or contemporary processes. In general, genetic measures focus...

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

Accounting for biotic spatial variability in fields: Case of resistance screening against sunflower Verticillium wilt

PubMed Central

Missonnier, Hélène; Jacques, Alban; Bang, JiSu; Daydé, Jean; Mirleau-Thebaud, Virginie

2017-01-01

In breeding for disease resistance, the magnitude of the genetic response is difficult to appreciate because of environmental stresses that interact with the plant genotype. We discuss herein the fundamental problems in breeding for disease resistance with the aim being to better understand the interactions between plant, pathogen, and spatial patterns. The goal of this study is to fine tune breeding decisions by incorporating spatial patterns of such biotic factors into the definition of disease-occurrence probability. We use a preexisting statistics method based on geostatistics for a descriptive analysis of biotic factors for trial quality control. The plant-population structure used for spatial-pattern analysis consists of two F1-hybrid cultivars, defined as symptomatic and asymptomatic controls with respect to the studied pathogen. The controls are inserted at specific locations to establish a grid arrangement over the field that include the F1-hybrid cultivars under evaluation. We characterize the spatial structure of the pathogen population and of the general plant environment—with undetermined but present abiotic constraints—not by using direct notation such as flower time or rainfall but by using plant behavior (i.e., leaf symptom severity, indirect notation). The analysis indicates areas with higher or lower risk of disease and reveals a correlation between the symptomatic control and the effective level of disease for sunflowers. This result suggests that the pathogen and/or abiotic components are major factors in determining the probability that a plant develops the disease, which could lead to a misinterpretation of plant resistance. PMID:28817567

Accounting for biotic spatial variability in fields: Case of resistance screening against sunflower Verticillium wilt.

PubMed

Missonnier, Hélène; Jacques, Alban; Bang, JiSu; Daydé, Jean; Mirleau-Thebaud, Virginie

2017-01-01

In breeding for disease resistance, the magnitude of the genetic response is difficult to appreciate because of environmental stresses that interact with the plant genotype. We discuss herein the fundamental problems in breeding for disease resistance with the aim being to better understand the interactions between plant, pathogen, and spatial patterns. The goal of this study is to fine tune breeding decisions by incorporating spatial patterns of such biotic factors into the definition of disease-occurrence probability. We use a preexisting statistics method based on geostatistics for a descriptive analysis of biotic factors for trial quality control. The plant-population structure used for spatial-pattern analysis consists of two F1-hybrid cultivars, defined as symptomatic and asymptomatic controls with respect to the studied pathogen. The controls are inserted at specific locations to establish a grid arrangement over the field that include the F1-hybrid cultivars under evaluation. We characterize the spatial structure of the pathogen population and of the general plant environment-with undetermined but present abiotic constraints-not by using direct notation such as flower time or rainfall but by using plant behavior (i.e., leaf symptom severity, indirect notation). The analysis indicates areas with higher or lower risk of disease and reveals a correlation between the symptomatic control and the effective level of disease for sunflowers. This result suggests that the pathogen and/or abiotic components are major factors in determining the probability that a plant develops the disease, which could lead to a misinterpretation of plant resistance.

Testing aggregation hypotheses among Neotropical trees and shrubs: results from a 50-ha plot over 20 years of sampling.

PubMed

Myster, Randall W; Malahy, Michael P

2012-09-01

Spatial patterns of tropical trees and shrubs are important to understanding their interaction and the resultant structure of tropical rainforests. To assess this issue, we took advantage of previously collected data, on Neotropical tree and shrub stem identified to species and mapped for spatial coordinates in a 50ha plot, with a frequency of every five years and over a 20 year period. These stems data were first placed into four groups, regardless of species, depending on their location in the vertical strata of the rainforest (shrubs, understory trees, mid-sized trees, tall trees) and then used to generate aggregation patterns for each sampling year. We found shrubs and understory trees clumped at small spatial scales of a few meters for several of the years sampled. Alternatively, mid-sized trees and tall trees did not clump, nor did they show uniform (regular) patterns, during any sampling period. In general (1) groups found higher in the canopy did not show aggregation on the ground and (2) the spatial patterns of all four groups showed similarity among different sampling years, thereby supporting a "shifting mosaic" view of plant communities over large areas. Spatial analysis, such as this one, are critical to understanding and predicting tree spaces, tree-tree replacements and the Neotropical forest patterns, such as biodiversity and those needed for sustainability efforts, they produce.

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

Meteorology-induced variations in the spatial behavior of summer ozone pollution in Central California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ling; Harley, Robert A.; Brown, Nancy J.

Cluster analysis was applied to daily 8 h ozone maxima modeled for a summer season to characterize meteorology-induced variations in the spatial distribution of ozone. Principal component analysis is employed to form a reduced dimension set to describe and interpret ozone spatial patterns. The first three principal components (PCs) capture {approx}85% of total variance, with PC1 describing a general spatial trend, and PC2 and PC3 each describing a spatial contrast. Six clusters were identified for California's San Joaquin Valley (SJV) with two low, three moderate, and one high-ozone cluster. The moderate ozone clusters are distinguished by elevated ozone levels inmore » different parts of the valley: northern, western, and eastern, respectively. The SJV ozone clusters have stronger coupling with the San Francisco Bay area (SFB) than with the Sacramento Valley (SV). Variations in ozone spatial distributions induced by anthropogenic emission changes are small relative to the overall variations in ozone amomalies observed for the whole summer. Ozone regimes identified here are mostly determined by the direct and indirect meteorological effects. Existing measurement sites are sufficiently representative to capture ozone spatial patterns in the SFB and SV, but the western side of the SJV is under-sampled.« less

Spatial distribution of vehicle emission inventories in the Federal District, Brazil

NASA Astrophysics Data System (ADS)

Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer

2015-07-01

Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.

Spatial Analysis of Large Woody Debris Arrangement in a Midwestern U.S. River System: Geomorphic Implications and Influences

NASA Astrophysics Data System (ADS)

Martin, D. J.

2013-12-01

Large woody debris (LWD) is universally recognized as a key component of the geomorphological and ecological function of fluvial systems and has been increasingly incorporated into stream restoration and watershed management projects. However, 'natural' processes of recruitment and the subsequent arrangement of LWD within the river network are poorly understood and are thus, rarely a management consideration. Additionally, LWD research tends to be regionally biased toward mountainous regions, and scale biased toward the micro-scale. In many locations, the lack of understanding has led to the failure of restoration/rehabilitation projects that involved the use of LWD. This research uses geographic information systems and spatial analysis techniques to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. A large-scale GPS inventory of LWD was performed on the Big River, located in the eastern Missouri Ozarks resulting in over 5,000 logged positions of LWD along seven river segments covering nearly 100 km of the 237 km river system. A time series analysis framework was used to statistically identify longitudinal spatial patterns of LWD arrangement along the main stem of the river, and correlation analyses were performed to help identify physical controls of those patterns. Results indicate that upstream segments have slightly lower densities than downstream segments, with the exception of the farthest upstream segment. Results also show lack of an overall longitudinal trend in LWD density; however, periodogram analysis revealed an inherent periodicity in LWD arrangement. Periodicities were most evident in the downstream segments with frequencies ranging from 3 km to 7 km. Additionally, Pearson correlation analysis, performed within the segment displaying the strongest periodic behavior, show that LWD densities are correlated with channel sinuosity (r=0.25). Ongoing research is investigating further relationships between arrangement patterns and geomorphic and riparian variables. Understanding these spatial patterns and relationships will provide valuable insight into the application of LWD-related stream and watershed management practices, and fill a necessary regional knowledge gap in our understanding of LWD's role in fluvial processes.

Genetic analysis across differential spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes

EPA Science Inventory

Understanding patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. Here we explore genetic ...

CROSS-SCALE CORRELATIONS AND THE DESIGN AND ANALYSIS OF AVIAN HABITAT SELECTION STUDIES

EPA Science Inventory

It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large ...

[Spatial regimes: dynamics of intentional homicides in the city of São Paulo between 2000 and 2008].

PubMed

Nery, Marcelo Batista; Peres, Maria Fernanda Tourinho; Cardia, Nancy; Vicentin, Diego; Adorno, Sérgio

2012-12-01

To identify the existence of spatial and temporal patterns in the occurrence of intentional homicides in the municipality of São Paulo (MSP), Brazil, and to discuss the analytical value of taking such patterns into account when designing studies that address the dynamics and factors associated with the incidence of homicides. A longitudinal ecological study was conducted, having as units of analysis 13 205 census tracts and the 96 census districts that congregate these sectors in São Paulo. All intentional homicides reported in the city between 2000 and 2008 were analyzed. The gross homicide rates per 100 000 population was calculated as well as the global and local Bayesian estimates for each census tract during the study period. To verify the possibility of identifying different patterns of the spatial distribution of homicides, we used BoxMap and Moran's I index. The homicide trends in the city of São Paulo in the last decade were not homogeneous and systematic. Instead, seven patterns of spatial distribution were identified; that is, seven spatial regimes for the occurrence of intentional homicides, considering the homicide rates within each census tract as well as the rates in adjacent tracts. These spatial distribution regimes were not contained within the limits of the census tracts and districts. The results show the importance of analyzing the spatial distribution of social phenomena without restriction of political and administrative boundaries.

Exhaled Aerosol Pattern Discloses Lung Structural Abnormality: A Sensitivity Study Using Computational Modeling and Fractal Analysis

PubMed Central

Xi, Jinxiang; Si, Xiuhua A.; Kim, JongWon; Mckee, Edward; Lin, En-Bing

2014-01-01

Background Exhaled aerosol patterns, also called aerosol fingerprints, provide clues to the health of the lung and can be used to detect disease-modified airway structures. The key is how to decode the exhaled aerosol fingerprints and retrieve the lung structural information for a non-invasive identification of respiratory diseases. Objective and Methods In this study, a CFD-fractal analysis method was developed to quantify exhaled aerosol fingerprints and applied it to one benign and three malign conditions: a tracheal carina tumor, a bronchial tumor, and asthma. Respirations of tracer aerosols of 1 µm at a flow rate of 30 L/min were simulated, with exhaled distributions recorded at the mouth. Large eddy simulations and a Lagrangian tracking approach were used to simulate respiratory airflows and aerosol dynamics. Aerosol morphometric measures such as concentration disparity, spatial distributions, and fractal analysis were applied to distinguish various exhaled aerosol patterns. Findings Utilizing physiology-based modeling, we demonstrated substantial differences in exhaled aerosol distributions among normal and pathological airways, which were suggestive of the disease location and extent. With fractal analysis, we also demonstrated that exhaled aerosol patterns exhibited fractal behavior in both the entire image and selected regions of interest. Each exhaled aerosol fingerprint exhibited distinct pattern parameters such as spatial probability, fractal dimension, lacunarity, and multifractal spectrum. Furthermore, a correlation of the diseased location and exhaled aerosol spatial distribution was established for asthma. Conclusion Aerosol-fingerprint-based breath tests disclose clues about the site and severity of lung diseases and appear to be sensitive enough to be a practical tool for diagnosis and prognosis of respiratory diseases with structural abnormalities. PMID:25105680

Analysis of sea use landscape pattern based on GIS: a case study in Huludao, China.

PubMed

Suo, Anning; Wang, Chen; Zhang, Minghui

2016-01-01

This study aims to analyse sea use landscape patterns on a regional scale based on methods of landscape ecology integrated with sea use spatial characteristics. Several landscape-level analysis indices, such as the dominance index, complex index, intensivity index, diversity index and sea congruency index, were established using Geographic Information System (GIS) and applied in Huludao, China. The results indicated that sea use landscape analysis indices, which were created based on the characteristics of sea use spatial patterns using GIS, are suitable to quantitatively describe the landscape patterns of sea use. They are operable tools for the landscape analysis of sea use. The sea use landscape in Huludao was dominated by fishing use with a landscape dominance index of 0.724. The sea use landscape is a complex mosaic with high diversity and plenty of fishing areas, as shown by the landscape complex index of 27.21 and the landscape diversity index of 1.25. Most sea use patches correspond to the marine functional zonation plan and the sea use congruency index is 0.89 in the fishing zone and 0.92 in the transportation zone.

Urban area thermal monitoring: Liepaja case study using satellite and aerial thermal data

NASA Astrophysics Data System (ADS)

Gulbe, Linda; Caune, Vairis; Korats, Gundars

2017-12-01

The aim of this study is to explore large (60 m/pixel) and small scale (individual building level) temperature distribution patterns from thermal remote sensing data and to conclude what kind of information could be extracted from thermal remote sensing on regular basis. Landsat program provides frequent large scale thermal images useful for analysis of city temperature patterns. During the study correlation between temperature patterns and vegetation content based on NDVI and building coverage based on OpenStreetMap data was studied. Landsat based temperature patterns were independent from the season, negatively correlated with vegetation content and positively correlated with building coverage. Small scale analysis included spatial and raster descriptor analysis for polygons corresponding to roofs of individual buildings for evaluating insulation of roofs. Remote sensing and spatial descriptors are poorly related to heat consumption data, however, thermal aerial data median and entropy can help to identify poorly insulated roofs. Automated quantitative roof analysis has high potential for acquiring city wide information about roof insulation, but quality is limited by reference data quality and information on building types, and roof materials would be crucial for further studies.

Mitochondrial phylogeography of a Beringian relict: the endemic freshwater genus of blackfish Dallia (Esociformes).

PubMed

Campbell, M A; Lopéz, J A

2014-02-01

Mitochondrial genetic variability among populations of the blackfish genus Dallia (Esociformes) across Beringia was examined. Levels of divergence and patterns of geographic distribution of mitochondrial DNA lineages were characterized using phylogenetic inference, median-joining haplotype networks, Bayesian skyline plots, mismatch analysis and spatial analysis of molecular variance (SAMOVA) to infer genealogical relationships and to assess patterns of phylogeography among extant mitochondrial lineages in populations of species of Dallia. The observed variation includes extensive standing mitochondrial genetic diversity and patterns of distinct spatial segregation corresponding to historical and contemporary barriers with minimal or no mixing of mitochondrial haplotypes between geographic areas. Mitochondrial diversity is highest in the common delta formed by the Yukon and Kuskokwim Rivers where they meet the Bering Sea. Other regions sampled in this study host comparatively low levels of mitochondrial diversity. The observed levels of mitochondrial diversity and the spatial distribution of that diversity are consistent with persistence of mitochondrial lineages in multiple refugia through the last glacial maximum. © 2014 The Fisheries Society of the British Isles.

Abnormal functional specialization within medial prefrontal cortex in high-functioning autism: a multi-voxel similarity analysis

PubMed Central

Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.

2009-01-01

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

Spatial analysis of muscular activations in stroke survivors.

PubMed

Rasool, Ghulam; Afsharipour, Babak; Suresh, Nina L; Xiaogang Hu; Rymer, William Zev

2015-01-01

We investigated the spatial patterns of electrical activity in stroke-affected muscles using the high density surface electromyogram (sEMG) grids. We acquired 128-channel sEMG signals from the impaired as well as contralateral Biceps Brachii (BB) muscles of stroke survivors and from healthy participants at various force levels from 20 to 60% of maximum voluntary contraction in an isometric non-fatiguing recording protocol. We found the spatial sEMG pattern to be consistent across force levels in healthy and stroke subjects. However, once compared across sides (left vs right in healthy and impaired vs. contralateral in stroke) we found stroke-affected sides to be significantly different in distribution pattern of sEMG from the contralateral side. The sEMG activity areas were significantly shrunk on the affected sides indicating muscle atrophy due to stroke.

Environmental characteristics associated with pedestrian-motor vehicle collisions in Denver, Colorado.

PubMed

Sebert Kuhlmann, Anne K; Brett, John; Thomas, Deborah; Sain, Stephan R

2009-09-01

We examined patterns of pedestrian-motor vehicle collisions and associated environmental characteristics in Denver, Colorado. We integrated publicly available data on motor vehicle collisions, liquor licenses, land use, and sociodemographic characteristics to analyze spatial patterns and other characteristics of collisions involving pedestrians. We developed both linear and spatially weighted regression models of these collisions. Spatial analysis revealed global clustering of pedestrian-motor vehicle collisions with concentrations in downtown, in a contiguous neighborhood, and along major arterial streets. Walking to work, population density, and liquor license outlet density all contributed significantly to both linear and spatial models of collisions involving pedestrians and were each significantly associated with these collisions. These models, constructed with data from Denver, identified conditions that likely contribute to patterns of pedestrian-motor vehicle collisions. Should these models be verified elsewhere, they will have implications for future research directions, public policy to enhance pedestrian safety, and public health programs aimed at decreasing unintentional injury from pedestrian-motor vehicle collisions and promoting walking as a routine physical activity.

Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data.

PubMed

Hoffman, Kate; Aschengrau, Ann; Webster, Thomas F; Bartell, Scott M; Vieira, Verónica M

2015-07-21

Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location. We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk. We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82). Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

Multifractality of laser beam spatial intensity in a turbulent medium

NASA Astrophysics Data System (ADS)

Barille, Régis; Lapenna, Paolo

2006-05-01

We present the results of a laser beam passing through a turbulent medium. First we measure the geometric parameters and the spatial coherence of the beam as a function of wind velocities. A multifractal detrended fluctuation analysis algorithm is applied to determine the multifractal scaling behavior of the intensity patterns. The measurements are fitted with models used in the analysis of river runoff records. We show the surprising result that the multifractality decreases when the spatial coherence of the laser is decreased. Universal scaling properties could be applied to the spatial characterization of a laser propagating in a turbulent medium or random medium.

Submillimeter-scale heterogeneity of labile phosphorus in sediments characterized by diffusive gradients in thin films and spatial analysis.

PubMed

Meng, Yuting; Ding, Shiming; Gong, Mengdan; Chen, Musong; Wang, Yan; Fan, Xianfang; Shi, Lei; Zhang, Chaosheng

2018-03-01

Sediments have a heterogeneous distribution of labile redox-sensitive elements due to a drastic downward transition from oxic to anoxic condition as a result of organic matter degradation. Characterization of the heterogeneous nature of sediments is vital for understanding of small-scale biogeochemical processes. However, there are limited reports on the related specialized methodology. In this study, the monthly distributions of labile phosphorus (P), a redox-sensitive limiting nutrient, were measured in the eutrophic Lake Taihu by Zr-oxide diffusive gradients in thin films (Zr-oxide DGT) on a two-dimensional (2D) submillimeter level. Geographical information system (GIS) techniques were used to visualize the labile P distribution at such a micro-scale, showing that the DGT-labile P was low in winter and high in summer. Spatial analysis methods, including semivariogram and Moran's I, were used to quantify the spatial variation of DGT-labile P. The distribution of DGT-labile P had clear submillimeter-scale spatial patterns with significant spatial autocorrelation during the whole year and displayed seasonal changes. High values of labile P with strong spatial variation were observed in summer, while low values of labile P with relatively uniform spatial patterns were detected in winter, demonstrating the strong influences of temperature on the mobility and spatial distribution of P in sediment profiles. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring spatial patterns of farmland transactions and farmland use changes.

PubMed

Chang, Hsueh-Sheng; Chen, Tzu-Ling

2015-09-01

Strong economic incentives stimulate the conversion of farmland to non-farm uses possessing higher economic benefits, and rising land values can result in further conversions in the surrounding areas. However, previous studies focused exclusively on the analysis of attribute data, without concern for location or geographic information. Our study focuses on the application of spatial analysis method by exploring the magnitude and patterns of farmland use changes and farmland transactions in Tainan County in southwestern Taiwan. The results show that farmland use changes and transactions appear to cluster in specific locations-near urban planning areas, industrial parks, and science parks. Clustered farmland use changes indicate both excessive development of some farmland and possible protection of other farmland, while clustered farmland transactions indicate potential pressure for future conversion to non-farming uses. Overall, the spatial analyses indicate (without necessarily implying a cause-and-effect relationship) that the greater the farmland use change, the greater the number of farmland transactions. This approach to exploring the spatial patterns in and the interaction between farmland use change and farmland transactions can be applied to other regions facing increasing competition for farmland conversions and may be a useful tool for monitoring both urban expansion and increased farmland transactions. These occurrences should be closely monitored by governments to avoid excessive loss of farmland.

Triatomine Infestation in Guatemala: Spatial Assessment after Two Rounds of Vector Control

PubMed Central

Manne, Jennifer; Nakagawa, Jun; Yamagata, Yoichi; Goehler, Alexander; Brownstein, John S.; Castro, Marcia C.

2012-01-01

In 2000, the Guatemalan Ministry of Health initiated a Chagas disease program to control Rhodnius prolixus and Triatoma dimidiata by periodic house spraying with pyrethroid insecticides to characterize infestation patterns and analyze the contribution of programmatic practices to these patterns. Spatial infestation patterns at three time points were identified using the Getis-Ord Gi*(d) test. Logistic regression was used to assess predictors of reinfestation after pyrethroid insecticide administration. Spatial analysis showed high and low clusters of infestation at three time points. After two rounds of spray, 178 communities persistently fell in high infestation clusters. A time lapse between rounds of vector control greater than 6 months was associated with 1.54 (95% confidence interval = 1.07–2.23) times increased odds of reinfestation after first spray, whereas a time lapse of greater than 1 year was associated with 2.66 (95% confidence interval = 1.85–3.83) times increased odds of reinfestation after first spray compared with localities where the time lapse was less than 180 days. The time lapse between rounds of vector control should remain under 1 year. Spatial analysis can guide targeted vector control efforts by enabling tracking of reinfestation hotspots and improved targeting of resources. PMID:22403315

Advanced brain aging: relationship with epidemiologic and genetic risk factors, and overlap with Alzheimer disease atrophy patterns.

PubMed

Habes, M; Janowitz, D; Erus, G; Toledo, J B; Resnick, S M; Doshi, J; Van der Auwera, S; Wittfeld, K; Hegenscheid, K; Hosten, N; Biffar, R; Homuth, G; Völzke, H; Grabe, H J; Hoffmann, W; Davatzikos, C

2016-04-05

We systematically compared structural imaging patterns of advanced brain aging (ABA) in the general-population, herein defined as significant deviation from typical BA to those found in Alzheimer disease (AD). The hypothesis that ABA would show different patterns of structural change compared with those found in AD was tested via advanced pattern analysis methods. In particular, magnetic resonance images of 2705 participants from the Study of Health in Pomerania (aged 20-90 years) were analyzed using an index that captures aging atrophy patterns (Spatial Pattern of Atrophy for Recognition of BA (SPARE-BA)), and an index previously shown to capture atrophy patterns found in clinical AD (Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease (SPARE-AD)). We studied the association between these indices and risk factors, including an AD polygenic risk score. Finally, we compared the ABA-associated atrophy with typical AD-like patterns. We observed that SPARE-BA had significant association with: smoking (P<0.05), anti-hypertensive (P<0.05), anti-diabetic drug use (men P<0.05, women P=0.06) and waist circumference for the male cohort (P<0.05), after adjusting for age. Subjects with ABA had spatially extensive gray matter loss in the frontal, parietal and temporal lobes (false-discovery-rate-corrected q<0.001). ABA patterns of atrophy were partially overlapping with, but notably deviating from those typically found in AD. Subjects with ABA had higher SPARE-AD values; largely due to the partial spatial overlap of associated patterns in temporal regions. The AD polygenic risk score was significantly associated with SPARE-AD but not with SPARE-BA. Our findings suggest that ABA is likely characterized by pathophysiologic mechanisms that are distinct from, or only partially overlapping with those of AD.

Spatial patterns of giant sequoia (Sequoiadendron giganteum) in two sequoia groves in Sequoia National Park, California

USGS Publications Warehouse

Stohlgren, Thomas J.

1993-01-01

Although Muir Grove and Castle Creek Grove are similar in area, elevation, and number of giant sequoias, various spatial pattern analysis techniques showed that they had dissimilar spatial patterns for similar-sized trees. Two-dimensional and transect two-term local quadrat variance techniques detected general trends in the spatial patterns of different-sized trees, detected multiple-scale patterns within individual size classes, and provided information on the scale and intensity of patches of individual size classes of trees in Muir and Castle Creek groves. In Muir Grove, midsized sequoias (1.5 to 2.4 m DBH classes) had major pattern scales 350–450 m in diameter, whereas the same-sized trees in Castle Creek Grove had pattern scales >1000 m in diameter. Many size classes of trees had minor patches superimposed on larger scale patterns in both groves. There may be different recruitment patterns in core (i.e., central) areas compared with peripheral areas of sequoia groves; core areas of both groves had more small live sequoias and dead sequoias than peripheral areas of the groves. Higher densities of sequoias and, perhaps, more rapid turnover of individuals in core areas may indicate (i) differences in disturbance histories and favorability of microsites in the core and peripheral areas of groves; (ii) different responses to disturbance due to shifts in the species composition of the stand and thus, the relative influences of intra- to inter-specific competition; or (iii) slower growth or lower survivorship rates in marginal habitat (i.e., peripheral areas).

Spatial point pattern analysis of human settlements and geographical associations in eastern coastal China - a case study.

PubMed

Zhang, Zhonghao; Xiao, Rui; Shortridge, Ashton; Wu, Jiaping

2014-03-10

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley's K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning.

On the role of spatial phase and phase correlation in vision, illusion, and cognition

PubMed Central

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.” PMID:25954190

On the role of spatial phase and phase correlation in vision, illusion, and cognition.

PubMed

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of "cognition by phase correlation."

Cross-scale analysis of fire regimes

Treesearch

Donald A. Falk; Carol Miller; Donald McKenzie; Anne E. Black

2007-01-01

Cross-scale spatial and temporal perspectives are important for studying contagious landscape disturbances such as fire, which are controlled by myriad processes operating at different scales. We examine fire regimes in forests of western North America, focusing on how observed patterns of fire frequency change across spatial scales. To quantify changes in fire...

Spatial and Temporal Emergence Pattern of Lyme Disease in Virginia

PubMed Central

Li, Jie; Kolivras, Korine N.; Hong, Yili; Duan, Yuanyuan; Seukep, Sara E.; Prisley, Stephen P.; Campbell, James B.; Gaines, David N.

2014-01-01

The emergence of infectious diseases over the past several decades has highlighted the need to better understand epidemics and prepare for the spread of diseases into new areas. As these diseases expand their geographic range, cases are recorded at different geographic locations over time, making the analysis and prediction of this expansion complicated. In this study, we analyze spatial patterns of the disease using a statistical smoothing analysis based on areal (census tract level) count data of Lyme disease cases in Virginia from 1998 to 2011. We also use space and space–time scan statistics to reveal the presence of clusters in the spatial and spatiotemporal distribution of Lyme disease. Our results confirm and quantify the continued emergence of Lyme disease to the south and west in states along the eastern coast of the United States. The results also highlight areas where education and surveillance needs are highest. PMID:25331806

Genetic analysis across different spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes.

PubMed

Darling, John A; Folino-Rorem, Nadine C

2009-12-01

Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.

Geographical Network Analysis and Spatial Econometrics as Tools to Enhance Our Understanding of Student Migration Patterns and Benefits in the U.S. Higher Education Network

ERIC Educational Resources Information Center

González Canché, Manuel S.

2018-01-01

This study measures the extent to which student outmigration outside the 4-year sector takes place and posits that the benefits from attracting non-resident students exist regardless of sector of enrollment. The study also provides empirical evidence about the relevance of employing geographical network analysis (GNA) and spatial econometrics in…

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

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

PubMed Central

2011-01-01

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 < 13) among the adult population (age ≥15) was prevalent in all slum settlements. We detected spatially autocorrelated WHO-5 scores (i.e., spatial clusters of poor and good mental health among different population groups). Further, we detected spatial associations between mental health and housing quality, sanitation, income generation, environmental health knowledge, education, age, gender, flood non-affectedness, and selected properties of the natural environment. 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. PMID:21599932

How memory of direct animal interactions can lead to territorial pattern formation.

PubMed

Potts, Jonathan R; Lewis, Mark A

2016-05-01

Mechanistic home range analysis (MHRA) is a highly effective tool for understanding spacing patterns of animal populations. It has hitherto focused on populations where animals defend their territories by communicating indirectly, e.g. via scent marks. However, many animal populations defend their territories using direct interactions, such as ritualized aggression. To enable application of MHRA to such populations, we construct a model of direct territorial interactions, using linear stability analysis and energy methods to understand when territorial patterns may form. We show that spatial memory of past interactions is vital for pattern formation, as is memory of 'safe' places, where the animal has visited but not suffered recent territorial encounters. Additionally, the spatial range over which animals make decisions to move is key to understanding the size and shape of their resulting territories. Analysis using energy methods, on a simplified version of our system, shows that stability in the nonlinear system corresponds well to predictions of linear analysis. We also uncover a hysteresis in the process of territory formation, so that formation may depend crucially on initial space-use. Our analysis, in one dimension and two dimensions, provides mathematical groundwork required for extending MHRA to situations where territories are defended by direct encounters. © 2016 The Author(s).

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Direct nano-patterning of graphene with helium ion beams

NASA Astrophysics Data System (ADS)

Naitou, Y.; Iijima, T.; Ogawa, S.

2015-01-01

Helium ion microscopy (HIM) was used for direct nano-patterning of single-layer graphene (SLG) on SiO2/Si substrates. This technique involves irradiation of the sample with accelerated helium ions (He+). Doses of 2.0 × 1016 He+ cm-2 from a 30 kV beam induced a metal-insulator transition in the SLG. The resolution of HIM patterning on SLG was investigated by fabricating nanoribbons and nanostructures. Analysis of scanning capacitance microscopy measurements revealed that the spatial resolution of HIM patterning depended on the dosage of He+ in a non-monotonic fashion. Increasing the dose from 2.0 × 1016 to 5.0 × 1016 He+ cm-2 improved the spatial resolution to several tens of nanometers. However, doses greater than 1.0 × 1017 He+ cm-2 degraded the patterning characteristics. Direct patterning using HIM is a versatile approach to graphene fabrication and can be applied to graphene-based devices.

Spatial and seasonal patterns in water quality in an embayment-mainstem reach of the tidal freshwater Potomac River, USA: a multiyear study.

PubMed

Jones, R Christian; Kelso, Donald P; Schaeffer, Elaine

2008-12-01

Spatial and temporal patterns in water quality were studied for seven years within an embayment-river mainstem area of the tidal freshwater Potomac River. The purpose of this paper is to determine the important components of spatial and temporal variation in water quality in this study area to facilitate an understanding of management impacts and allow the most effective use of future monitoring resources. The study area received treated sewage effluent and freshwater inflow from direct tributary inputs into the shallow embayment as well as upriver sources in the mainstem. Depth variations were determined to be detectable, but minimal due mainly to the influence of tidal mixing. Results of principal component analysis of two independent water quality datasets revealed clear spatial and seasonal patterns. Interannual variation was generally minimal despite substantial variations in tributary and mainstem discharge among years. Since both spatial and seasonal components were important, data were segmented by season to best determine the spatial pattern. A clear difference was found between a set of stations located within one embayment (Gunston Cove) and a second set in the nearby Potomac mainstem. Parameters most highly correlated with differences were those typically associated with higher densities of phytoplankton: chlorophyll a, photosynthetic rate, pH, dissolved oxygen, BOD, total phosphorus and Secchi depth. These differences and their consistency indicated two distinct water masses: one in the cove harboring higher algal density and activity and a second in the river with lower phytoplankton activity. A second embayment not receiving sewage effluent generally had an intermediate position. While this was the most consistent spatial pattern, there were two others of a secondary nature. Stations closer to the effluent inputs in the embayment sometimes grouped separately due to elevated ammonia and chloride. Stations closer to tributary inflows into the embayment sometimes grouped separately due to dilution with freshwater runoff. Segmenting the datasets by spatial region resulted in a clarification of seasonal patterns with similar factors relating to algal activity being the major correlates of the seasonal pattern. A basic seasonal pattern of lower scores in the spring increasing steadily to a peak in July and August followed by a steady decline through the fall was observed in the cove. In the river, the pattern of increases tended to be delayed slightly in the spring. Results indicate that the study area can be effectively monitored with fewer study sites provided that at least one is located in each of the spatial regions.

Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises

PubMed Central

Latch, Emily K.; Boarman, William I.; Walde, Andrew; Fleischer, Robert C.

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately. PMID:22132143

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises.

PubMed

Latch, Emily K; Boarman, William I; Walde, Andrew; Fleischer, Robert C

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.

Techniques for spatio-temporal analysis of vegetation fires in the topical belt of Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brivio, P.A.; Ober, G.; Koffi, B.

1995-12-31

Biomass burning of forests and savannas is a phenomenon of continental or even global proportions, capable of causing large scale environmental changes. Satellite space observations, in particular from NOAA-AVHRR GAC data, are the only source of information allowing one to document burning patterns at regional and continental scale and over long periods of time. This paper presents some techniques, such as clustering and rose-diagram, useful in the spatial-temporal analysis of satellite derived fires maps to characterize the evolution of spatial patterns of vegetation fires at regional scale. An automatic clustering approach is presented which enables one to describe and parameterizemore » spatial distribution of fire patterns at different scales. The problem of geographical distribution of vegetation fires with respect to some location of interest, point or line, is also considered and presented. In particular rose-diagrams are used to relate fires patterns to some reference point, as experimental sites of tropospheric chemistry measurements. Different temporal data-sets in the tropical belt of Africa, covering both Northern and Southern Hemisphere dry seasons, using these techniques were analyzed and showed very promising results when compared with data from rain chemistry studies at different sampling sites in the equatorial forest.« less

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.

Anthropometric geography applied to the analysis of socioeconomic disparities: cohort trends and spatial patterns of height and robustness in 20th-century Spain.

PubMed

Camara, Antonio D; Roman, Joan Garcia

2015-11-01

Anthropometrics have been widely used to study the influence of environmental factors on health and nutritional status. In contrast, anthropometric geography has not often been employed to approximate the dynamics of spatial disparities associated with socioeconomic and demographic changes. Spain exhibited intense disparity and change during the middle decades of the 20 th century, with the result that the life courses of the corresponding cohorts were associated with diverse environmental conditions. This was also true of the Spanish territories. This paper presents insights concerning the relationship between socioeconomic changes and living conditions by combining the analysis of cohort trends and the anthropometric cartography of height and physical build. This analysis is conducted for Spanish male cohorts born 1934-1973 that were recorded in the Spanish military statistics. This information is interpreted in light of region-level data on GDP and infant mortality. Our results show an anthropometric convergence across regions that, nevertheless, did not substantially modify the spatial patterns of robustness, featuring primarily robust northeastern regions and weak Central-Southern regions. These patterns persisted until the 1990s (cohorts born during the 1970s). For the most part, anthropometric disparities were associated with socioeconomic disparities, although the former lessened over time to a greater extent than the latter. Interestingly, the various anthropometric indicators utilized here do not point to the same conclusions. Some discrepancies between height and robustness patterns have been found that moderate the statements from the analysis of cohort height alone regarding the level and evolution of living conditions across Spanish regions.

Spatiotemporal Analysis of the Ebola Hemorrhagic Fever in West Africa in 2014

NASA Astrophysics Data System (ADS)

Xu, M.; Cao, C. X.; Guo, H. F.

2017-09-01

Ebola hemorrhagic fever (EHF) is an acute hemorrhagic diseases caused by the Ebola virus, which is highly contagious. This paper aimed to explore the possible gathering area of EHF cases in West Africa in 2014, and identify endemic areas and their tendency by means of time-space analysis. We mapped distribution of EHF incidences and explored statistically significant space, time and space-time disease clusters. We utilized hotspot analysis to find the spatial clustering pattern on the basis of the actual outbreak cases. spatial-temporal cluster analysis is used to analyze the spatial or temporal distribution of agglomeration disease, examine whether its distribution is statistically significant. Local clusters were investigated using Kulldorff's scan statistic approach. The result reveals that the epidemic mainly gathered in the western part of Africa near north Atlantic with obvious regional distribution. For the current epidemic, we have found areas in high incidence of EVD by means of spatial cluster analysis.

Patterns of fish community composition along a river affected by agricultural and urban disturbance in south-central Chile

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orrego, Rodrigo; Barra, Ricardo; Chiang, Gustavo

2008-03-01

Patterns of fish community composition in a south-central Chile river were investigated along the altitudinal-spatial and environmental gradient and as a function of anthropogenic factors. The spatial pattern of fish communities in different biocoenotic zones of the Chillan River is influenced by both natural factors such a hydrologic features, habitat, and feeding types, and also by water quality variables which can reduce the diversity and abundance of sensitive species. A principal component analysis incorporating both water quality parameters and biomarker responses of representative fish species was used to evaluate the status of fish communities along the spatial gradient of themore » stream. The abundance and diversity of the fish community changed from a low in the upper reaches where the low pollution-tolerant species such as salmonid dominated, to a reduced diversity in the lower reaches of the river where tolerant browser species such as cypriniformes dominated. Even though the spatial pattern of fish community structure is similar to that found for the Chilean Rivers, the structure of these communities is highly influenced by human disturbance, particularly along the lower reaches of the river.« less

Spatial analysis of electricity demand patterns in Greece: Application of a GIS-based methodological framework

NASA Astrophysics Data System (ADS)

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

2016-04-01

We investigate various uses of electricity demand in Greece (agricultural, commercial, domestic, industrial use as well as use for public and municipal authorities and street lightning) and we examine their relation with variables such as population, total area, population density and the Gross Domestic Product. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the level of prefecture. We both visualize the results of the analysis and we perform cluster and outlier analysis using the Anselin local Moran's I statistic as well as hot spot analysis using the Getis-Ord Gi* statistic. The definition of the spatial patterns and relationships of the aforementioned variables in a GIS environment provides meaningful insight and better understanding of the regional development model in Greece and justifies the basis for an energy demand forecasting methodology. Acknowledgement: This research has been partly financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II: Reinforcement of the interdisciplinary and/ or inter-institutional research and innovation (CRESSENDO project; grant number 5145).

[Geostatistics analyzing to cause of formation of circle distribution of plant communities in Horqin Sandy Land].

PubMed

He, Xingdong; Gao, Yubao; Zhao, Wenzhi; Cong, Zili

2004-09-01

Investigation results in the present study showed that plant communities took typical concentric circles distribution patterns along habitat gradient from top, slope to interdune on a few large fixed dunes in middle part of Korqin Sandy Land. In order to explain this phenomenon, analysis of water content and its spatial heterogeneity in sand layers on different locations of dunes was conducted. In these dunes, water contents in sand layers of the tops were lower than those of the slopes; both of them were lower than those of the interdunes. According to the results of geostatistics analysis, whether shifting dune or fixed dune, spatial heterogeneity of water contents in sand layers took on regular changes, such as ratios between nugget and sill and ranges reduced gradually, fractal dimension increased gradually, the regular changes of these parameters indicated that random spatial heterogeneity reduced gradually, and autocorrelation spatial heterogeneity increased gradually from the top, the slope to the interdune. The regular changes of water contents in sand layers and their spatial heterogeneity of different locations of the dunes, thus, might be an important cause resulted in the formation of the concentric circles patterns of the plant communities on these fixed dunes.

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Spatial distribution and implications to sources of halogenated flame retardants in riverine sediments of Taizhou, an intense e-waste recycling area in eastern China.

PubMed

Zhou, Shanshan; Fu, Jie; He, Huan; Fu, Jianjie; Tang, Qiaozhi; Dong, Minfeng; Pan, Yongqiang; Li, An; Liu, Weiping; Zhang, Limin

2017-10-01

Concentrations and spatial distribution pattern of organohalogen flame retardants were investigated in the riverine surface sediments from Taizhou, an intensive e-waste recycling region in China. The analytes were syn- and anti- Dechlorane Plus (DP), Dechloranes 602, 603, and 604, a DP monoadduct, two dechlorinated DPs and 8 congeners of polybrominated diphenyl ethers (PBDEs). The concentrations of Σ 8 PBDEs, ΣDP, ΣDec600s, and ΣDP-degradates ranged from <100 to 172,000, 100 to 55,000, not detectable (nd) to 1600, and nd to 2800 pg/g dry weight, respectively. BDE-209 and DP, both have been manufactured in China, had similar spatial distribution patterns in the study area, featured by distinctly recognizable hotspots some of which are in proximity to known e-waste dumping or metal recycling facilities. Such patterns were largely shared by Dec602 and dechlorinated DP, although their concentration levels were much lower. These major flame retardants significantly correlate with each other, and cluster together in the loading plot of principle component analysis. In contrast, most non-deca PBDE congeners do not correlate with DPs. Dec604 stood out having distinctly different spatial distribution pattern, which could be linked to historical use of mirex. Organic matter content of the sediment was not the dominant factor in determining the spatial pattern of pollution by halogenated flame retardants in the rivers of this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks.

PubMed

Wu, Siqi; Joseph, Antony; Hammonds, Ann S; Celniker, Susan E; Yu, Bin; Frise, Erwin

2016-04-19

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

[Explore the spatial and temporal patterns of water pollution in the Yincungang canal of the Lake Taihu basin, China].

PubMed

Yang, Xiao-Ying; Luo, Xing-Zhang; Zheng, Zheng; Fang, Shu-Bo

2012-09-01

Two high-density snap-shot samplings were conducted along the Yincungang canal, one important tributary of the Lake Tai, in April (low flow period) and June (high flow period) of 2010. Geostatistical analysis based on the river network distance was used to analyze the spatial and temporal patterns of the pollutant concentrations along the canal with an emphasis on chemical oxygen demand (COD) and total nitrogen (TN). Study results have indicated: (1) COD and TN concentrations display distinctly different spatial and temporal patterns between the low and high flow periods. COD concentration in June is lower than that in April, while TN concentration has the contrary trend. (2) COD load is relatively constant during the period between the two monitoring periods. The spatial correlation structure of COD is exponential for both April and June, and the change of COD concentration is mainly influenced by hydrological conditions. (3) Nitrogen load from agriculture increased significantly during the period between the two monitoring periods. Large amount of chaotic fertilizing by individual farmers has led to the loss of the spatial correlation among the observed TN concentrations. Hence, changes of TN concentration in June are under the dual influence of agricultural fertilizing and hydrological conditions. In the view of the complex hydrological conditions and serious water pollution in the Lake Taihu region, geostatistical analysis is potentially a useful tool for studying the characteristics of pollutant distribution and making predictions in the region.

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

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

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

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.

Interaction of Soil Heavy Metal Pollution with Industrialisation and the Landscape Pattern in Taiyuan City, China

PubMed Central

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning. PMID:25251460

Interaction of soil heavy metal pollution with industrialisation and the landscape pattern in Taiyuan city, China.

PubMed

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning.

Spatial Point Pattern Analysis of Neurons Using Ripley's K-Function in 3D

PubMed Central

Jafari-Mamaghani, Mehrdad; Andersson, Mikael; Krieger, Patrik

2010-01-01

The aim of this paper is to apply a non-parametric statistical tool, Ripley's K-function, to analyze the 3-dimensional distribution of pyramidal neurons. Ripley's K-function is a widely used tool in spatial point pattern analysis. There are several approaches in 2D domains in which this function is executed and analyzed. Drawing consistent inferences on the underlying 3D point pattern distributions in various applications is of great importance as the acquisition of 3D biological data now poses lesser of a challenge due to technological progress. As of now, most of the applications of Ripley's K-function in 3D domains do not focus on the phenomenon of edge correction, which is discussed thoroughly in this paper. The main goal is to extend the theoretical and practical utilization of Ripley's K-function and corresponding tests based on bootstrap resampling from 2D to 3D domains. PMID:20577588

Influence of orographically steered winds on Mutsu Bay surface currents

NASA Astrophysics Data System (ADS)

Yamaguchi, Satoshi; Kawamura, Hiroshi

2005-09-01

Effects of spatially dependent sea surface wind field on currents in Mutsu Bay, which is located at the northern end of Japanese Honshu Island, are investigated using winds derived from synthetic aperture radar (SAR) images and a numerical model. A characteristic wind pattern over the bay was evidenced from analysis of 118 SAR images and coincided with in situ observations. Wind is topographically steered with easterly winds entering the bay through the terrestrial gap and stronger wind blowing over the central water toward its mouth. Nearshore winds are weaker due to terrestrial blockages. Using the Princeton Ocean Model, we investigated currents forced by the observed spatially dependent wind field. The predicted current pattern agrees well with available observations. For a uniform wind field of equal magnitude and average direction, the circulation pattern departs from observations demonstrating that vorticity input due to spatially dependent wind stress is essential in generation of the wind-driven current in Mutsu Bay.

Assessing the spatial distribution of Tuta absoluta (Lepidoptera: Gelechiidae) eggs in open-field tomato cultivation through geostatistical analysis.

PubMed

Martins, Júlio C; Picanço, Marcelo C; Silva, Ricardo S; Gonring, Alfredo Hr; Galdino, Tarcísio Vs; Guedes, Raul Nc

2018-01-01

The spatial distribution of insects is due to the interaction between individuals and the environment. Knowledge about the within-field pattern of spatial distribution of a pest is critical to planning control tactics, developing efficient sampling plans, and predicting pest damage. The leaf miner Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato crops in several regions of the world. Despite the importance of this pest, the pattern of spatial distribution of T. absoluta on open-field tomato cultivation remains unknown. Therefore, this study aimed to characterize the spatial distribution of T. absoluta in 22 commercial open-field tomato cultivations with plants at the three phenological development stages by using geostatistical analysis. Geostatistical analysis revealed that there was strong evidence for spatially dependent (aggregated) T. absoluta eggs in 19 of the 22 sample tomato cultivations. The maps that were obtained demonstrated the aggregated structure of egg densities at the edges of the crops. Further, T. absoluta was found to accomplish egg dispersal along the rows more frequently than it does between rows. Our results indicate that the greatest egg densities of T. absoluta occur at the edges of tomato crops. These results are discussed in relation to the behavior of T. absoluta distribution within fields and in terms of their implications for improved sampling guidelines and precision targeting control methods that are essential for effective pest monitoring and management. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis.

PubMed

Siemann, Julia; Herrmann, Manfred; Galashan, Daniela

2018-01-25

The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants' attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

EPA Science Inventory

This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

Space-variant polarization patterns of non-collinear Poincaré superpositions

NASA Astrophysics Data System (ADS)

Galvez, E. J.; Beach, K.; Zeosky, J. J.; Khajavi, B.

2015-03-01

We present analysis and measurements of the polarization patterns produced by non-collinear superpositions of Laguerre-Gauss spatial modes in orthogonal polarization states, which are known as Poincaré modes. Our findings agree with predictions (I. Freund Opt. Lett. 35, 148-150 (2010)), that superpositions containing a C-point lead to a rotation of the polarization ellipse in 3-dimensions. Here we do imaging polarimetry of superpositions of first- and zero-order spatial modes at relative beam angles of 0-4 arcmin. We find Poincaré-type polarization patterns showing fringes in polarization orientation, but which preserve the polarization-singularity index for all three cases of C-points: lemons, stars and monstars.

Effects of speckle/pixel size ratio on temporal and spatial speckle-contrast analysis of dynamic scattering systems: Implications for measurements of blood-flow dynamics.

PubMed

Ramirez-San-Juan, J C; Mendez-Aguilar, E; Salazar-Hermenegildo, N; Fuentes-Garcia, A; Ramos-Garcia, R; Choi, B

2013-01-01

Laser Speckle Contrast Imaging (LSCI) is an optical technique used to generate blood flow maps with high spatial and temporal resolution. It is well known that in LSCI, the speckle size must exceed the Nyquist criterion to maximize the speckle's pattern contrast. In this work, we study experimentally the effect of speckle-pixel size ratio not only in dynamic speckle contrast, but also on the calculation of the relative flow speed for temporal and spatial analysis. Our data suggest that the temporal LSCI algorithm is more accurate at assessing the relative changes in flow speed than the spatial algorithm.

Statistical Analysis of Sport Movement Observations: the Case of Orienteering

NASA Astrophysics Data System (ADS)

Amouzandeh, K.; Karimipour, F.

2017-09-01

Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope) and non-spatial movement attributes (e.g. speed and heart rate) of athletes. As the case study, an example dataset of movement observations acquired during the "orienteering" sport is presented and statistically analyzed.

New spatially continuous indices of redlining and racial bias in mortgage lending: links to survival after breast cancer diagnosis and implications for health disparities research.

PubMed

Beyer, Kirsten M M; Zhou, Yuhong; Matthews, Kevin; Bemanian, Amin; Laud, Purushottam W; Nattinger, Ann B

2016-07-01

Racial health disparities continue to be a serious problem in the United States and have been linked to contextual factors, including racial segregation. In some cases, including breast cancer survival, racial disparities appear to be worsening. Using the Home Mortgage Disclosure Act (HMDA) database, we extend current spatial analysis methodology to derive new, spatially continuous indices of (1) racial bias in mortgage lending and (2) redlining. We then examine spatial patterns of these indices and the association between these new measures and breast cancer survival among Black/African American women in the Milwaukee, Wisconsin metropolitan area. These new measures can be used to examine relationships between mortgage discrimination and patterns of disease throughout the United States. Copyright © 2016 Elsevier Ltd. All rights reserved.

Violent crime in San Antonio, Texas: an application of spatial epidemiological methods.

PubMed

Sparks, Corey S

2011-12-01

Violent crimes are rarely considered a public health problem or investigated using epidemiological methods. But patterns of violent crime and other health conditions are often affected by similar characteristics of the built environment. In this paper, methods and perspectives from spatial epidemiology are used in an analysis of violent crimes in San Antonio, TX. Bayesian statistical methods are used to examine the contextual influence of several aspects of the built environment. Additionally, spatial regression models using Bayesian model specifications are used to examine spatial patterns of violent crime risk. Results indicate that the determinants of violent crime depend on the model specification, but are primarily related to the built environment and neighborhood socioeconomic conditions. Results are discussed within the context of a rapidly growing urban area with a diverse population. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

One indication of model performance is the comparison of spatial patterns of pollutants, either as concentration or deposition, predicted by the model with spatial patterns derived from measurements. If the spatial patterns produced by the model are similar to the observations i...

Application of spatially modulated near-infrared structured light to study changes in optical properties of mouse brain tissue during heatstress.

PubMed

Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A; Abookasis, David

2017-11-10

Heat stress (HS) is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological, and hematological changes. The goal of the present research was to detect variations in optical properties (absorption, reduced scattering, and refractive index coefficients) of mouse brain tissue during HS by using near-infrared (NIR) spatial light modulation. NIR spatial patterns with different spatial phases were used to differentiate the effects of tissue scattering from those of absorption. Decoupling optical scattering from absorption enabled the quantification of a tissue's chemical constituents (related to light absorption) and structural properties (related to light scattering). Technically, structured light patterns at low and high spatial frequencies of six wavelengths ranging between 690 and 970 nm were projected onto the mouse scalp surface while diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse scalp. Concurrently to pattern projection, brain temperature was measured with a thermal camera positioned slightly off angle from the mouse head while core body temperature was monitored by thermocouple probe. Data analysis demonstrated variations from baseline measurements in a battery of intrinsic brain properties following HS.

Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

USDA-ARS?s Scientific Manuscript database

Soil water patterns vary significantly due to precipitation, soil properties, topographic features, and land use. We used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water across a 37-ha field of the Washington State University Cook Agronomy Farm near...

Spatial Point Pattern Analysis of Human Settlements and Geographical Associations in Eastern Coastal China — A Case Study

PubMed Central

Zhang, Zhonghao; Xiao, Rui; Shortridge, Ashton; Wu, Jiaping

2014-01-01

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley’s K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning. PMID:24619117

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach.

PubMed

Domnich, Alexander; Arata, Lucia; Amicizia, Daniela; Signori, Alessio; Gasparini, Roberto; Panatto, Donatella

2016-11-16

Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (I=0.082) and per km2 (I=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms population, mean altitude and rural status and the global term income functioned as independent variables predicting pharmacies per km2. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.

Związek rozmieszczenia powierzchniowych form krasowych międzyrzecza środkowego Wieprza i Bugu z tektoniką dysjunktywną w świetle analizy statystycznej

NASA Astrophysics Data System (ADS)

Kamińska, Anna

2010-01-01

The relationship between karst of chalk and tectonics in the interfluve of the middle Wieprz and Bug Rivers has been already examined by Maruszczak (1966), Harasimiuk (1980) and Dobrowolski (1998). Investigating the connection of the karst formation course and the substratum structure, the direction of the landforms and their spatial pattern were analysed and compared later to the structural pattern. The obvious completion of the collected data is a quantity analysis using statistical methods. This paper deals with the characteristics of such quantity analysis. By using the tools of the directional statistics, the following indexes have been calculated: the mean vector orientation, the length of the vector mean, strength of the vector mean, the Batschelet variance, as well as determined confidence intervals for the mean vector. In order to examine the distribution structure of these forms, the selected methods of the spatial statistics have been used-angular wavelet analysis (Rosenberg 2004) and the semivariogram analysis (Namysłowska-Wilczyńska 2006). On the basis of conducted analyses, it is possible to describe in detail the regularities in spatial distribution of the surface karst forms in the interfluve of the middle Wieprz and Bug Rivers. The orientation analysis reveals an important feature of their direction-along with a rise in the size of surface karst forms, the level of concentration around the mean vector orientation increases. Primary karst forms point out poor concentration along the longitudinal direction whereas complex forms are clearly concentrated along the WNW-ESE direction. Hence, only after clumping of the primary forms into the complex ones, the convergence of the surface karst forms direction with the direction of the main faults in the Meso-Cenozoic complex is visible (after A. Henkiel 1984). The results of the wavelet analysis modified by Rosenberg (2004) have indicated significant directions of the clumping of the surface karst forms. A clear difference in the distribution of these forms in west and east areas is noticed. Whereas the west area is dominated by the W-E, NW-SE, N-S directions, the karst forms in the east are concentrated along the NE-SW direction. The semivariogram analysis has confirmed the importance of the W-E and NE-SW directions. Moreover, this analysis has indicated which areas are characterized by the poor karst forms direction. It is a region where the Kock-Wasylów dislocation zone crosses the Święcica dislocation zone in the north-east part of the analysed area. The south-east region is the second such area. The picture of the spatial pattern one confirms the previous results (Dobrowolski 1998) and refers clearly to the structural pattern of this area. Nevertheless, the analyses mentioned above have shown the dominance of the W-E direction over the NW-SE one. The obtained results of the spatial and direction analyses expand and confirm hitherto information about the relation between the spatial pattern of the karst landforms and the tectonics in the interfluve of the middle Wieprz and Bug Rivers.

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.

PubMed

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.

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

PubMed Central

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

Wavelet Analysis for RADARSAT Exploitation: Demonstration of Algorithms for Maritime Surveillance

DTIC Science & Technology

2007-02-01

this study , we demonstrate wavelet analysis for exploitation of RADARSAT ocean imagery, including wind direction estimation, oceanic and atmospheric ...of image striations that can arise as a texture pattern caused by turbulent coherent structures in the marine atmospheric boundary layer. The image...associated change in the pattern texture (i.e., the nature of the turbulent atmospheric structures) across the front. Due to the large spatial scale of

Spatial and Temporal Patterns of Impervious Cover Relative to Watershed Stream Location

EPA Science Inventory

The influence of spatial pattern on ecological processes is a guiding principle of landscape ecology. The guiding principle of spatial pattern was used for a U.S. nationwide assessment of impervious cover (IC). Spatial pattern was measured by comparing IC concentration near strea...

Spatial vegetation patterns and neighborhood competition among woody plants in an East African savanna.

PubMed

Dohn, Justin; Augustine, David J; Hanan, Niall P; Ratnam, Jayashree; Sankaran, Mahesh

2017-02-01

The majority of research on savanna vegetation dynamics has focused on the coexistence of woody and herbaceous vegetation. Interactions among woody plants in savannas are relatively poorly understood. We present data from a 10-yr longitudinal study of spatially explicit growth patterns of woody vegetation in an East African savanna following exclusion of large herbivores and in the absence of fire. We examined plant spatial patterns and quantified the degree of competition among woody individuals. Woody plants in this semiarid savanna exhibit strongly clumped spatial distributions at scales of 1-5 m. However, analysis of woody plant growth rates relative to their conspecific and heterospecific neighbors revealed evidence for strong competitive interactions at neighborhood scales of up to 5 m for most woody plant species. Thus, woody plants were aggregated in clumps despite significantly decreased growth rates in close proximity to neighbors, indicating that the spatial distribution of woody plants in this region depends on dispersal and establishment processes rather than on competitive, density-dependent mortality. However, our documentation of suppressive effects of woody plants on neighbors also suggests a potentially important role for tree-tree competition in controlling vegetation structure and indicates that the balanced-competition hypothesis may contribute to well-known patterns in maximum tree cover across rainfall gradients in Africa. © 2016 by the Ecological Society of America.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

The spatial impact of neighbouring on the exports activities of COMESA countries by using spatial panel models

NASA Astrophysics Data System (ADS)

Hamzalouh, L.; Ismail, M. T.; Rahman, R. A.

2017-09-01

In this paper, spatial panel models were used and the method for selecting the best model amongst the spatial fixed effects model and the spatial random effects model to estimate the fitting model by using the robust Hausman test for analysis of the exports pattern of the Common Market for Eastern and Southern African (COMESA) countries. And examine the effects of the interactions of the economic statistic of explanatory variables on the exports of the COMESA. Results indicated that the spatial Durbin model with fixed effects specification should be tested and considered in most cases of this study. After that, the direct and indirect effects among COMESA regions were assessed, and the role of indirect spatial effects in estimating exports was empirically demonstrated. Regarding originality and research value, and to the best of the authors’ knowledge, this is the first attempt to examine exports between COMESA and its member countries through spatial panel models using XSMLE, which is a new command for spatial analysis using STATA.

Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

PubMed

Hassan, M Manzurul; Atkins, Peter J

2011-01-01

This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.

Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model

PubMed Central

Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.

2015-01-01

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

2010-01-01

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Detecting trends in landscape pattern metrics over a 20-year period using a sampling-based monitoring programme

USGS Publications Warehouse

Griffith, J.A.; Stehman, S.V.; Sohl, Terry L.; Loveland, Thomas R.

2003-01-01

Temporal trends in landscape pattern metrics describing texture, patch shape and patch size were evaluated in the US Middle Atlantic Coastal Plain Ecoregion. The landscape pattern metrics were calculated for a sample of land use/cover data obtained for four points in time from 1973-1992. The multiple sampling dates permit evaluation of trend, whereas availability of only two sampling dates allows only evaluation of change. Observed statistically significant trends in the landscape pattern metrics demonstrated that the sampling-based monitoring protocol was able to detect a trend toward a more fine-grained landscape in this ecoregion. This sampling and analysis protocol is being extended spatially to the remaining 83 ecoregions in the US and temporally to the year 2000 to provide a national and regional synthesis of the temporal and spatial dynamics of landscape pattern covering the period 1973-2000.

Antiferromagnetic order in the Hubbard model on the Penrose lattice

NASA Astrophysics Data System (ADS)

Koga, Akihisa; Tsunetsugu, Hirokazu

2017-12-01

We study an antiferromagnetic order in the ground state of the half-filled Hubbard model on the Penrose lattice and investigate the effects of quasiperiodic lattice structure. In the limit of infinitesimal Coulomb repulsion U →+0 , the staggered magnetizations persist to be finite, and their values are determined by confined states, which are strictly localized with thermodynamics degeneracy. The magnetizations exhibit an exotic spatial pattern, and have the same sign in each of cluster regions, the size of which ranges from 31 sites to infinity. With increasing U , they continuously evolve to those of the corresponding spin model in the U =∞ limit. In both limits of U , local magnetizations exhibit a fairly intricate spatial pattern that reflects the quasiperiodic structure, but the pattern differs between the two limits. We have analyzed this pattern change by a mode analysis by the singular value decomposition method for the fractal-like magnetization pattern projected into the perpendicular space.

Analysis of Alaskan burn severity patterns using remotely sensed data

USGS Publications Warehouse

Duffy, P.A.; Epting, J.; Graham, J.M.; Rupp, T.S.; McGuire, A.D.

2007-01-01

Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.

Influence of Different Factors on Relative Air Humidity in Zaragoza, Spain

NASA Astrophysics Data System (ADS)

Cuadrat, José M.

2015-03-01

In this study, the spatial patterns of relative air humidity and its relation to urban, geographical and meteorological factors in the city of Zaragoza (Spain) is discussed. We created a relative humidity database by means of 32 urban transects. Data were taken on different days and with different weather types. This data set was used to map the mean spatial distribution of urban dry island (UDI). Using stepwise multiple regression analysis and Landsat ETM+ images the relationships between mean UDI and the main geographic-urban factors: topography, land cover and surface reflectivity, have been analyzed. Different spatial patterns of UDI were determined using Principal Component Analysis (Varimax rotation). The three components extracted accounted for 91% of the total variance. PC1 accounted for the most general patterns (similar to mean UDI); PC2 showed a shift of dry areas to the SE and PC3 a shift to NW. Using data on wind direction in Zaragoza, we have found that the displacement of dry areas to the SE (PC 2) was greater during NW winds while the shift to the NW (PC 3) was produced mainly by SE winds.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Environmental Characteristics Associated With Pedestrian–Motor Vehicle Collisions in Denver, Colorado

PubMed Central

Sebert Kuhlmann, Anne K.; Thomas, Deborah; R. Sain, Stephan

2009-01-01

Objectives. We examined patterns of pedestrian–motor vehicle collisions and associated environmental characteristics in Denver, Colorado. Methods. We integrated publicly available data on motor vehicle collisions, liquor licenses, land use, and sociodemographic characteristics to analyze spatial patterns and other characteristics of collisions involving pedestrians. We developed both linear and spatially weighted regression models of these collisions. Results. Spatial analysis revealed global clustering of pedestrian–motor vehicle collisions with concentrations in downtown, in a contiguous neighborhood, and along major arterial streets. Walking to work, population density, and liquor license outlet density all contributed significantly to both linear and spatial models of collisions involving pedestrians and were each significantly associated with these collisions. Conclusions. These models, constructed with data from Denver, identified conditions that likely contribute to patterns of pedestrian–motor vehicle collisions. Should these models be verified elsewhere, they will have implications for future research directions, public policy to enhance pedestrian safety, and public health programs aimed at decreasing unintentional injury from pedestrian–motor vehicle collisions and promoting walking as a routine physical activity. PMID:19608966

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Summer spatial patterning of chukars in relation to free water in Western Utah

USGS Publications Warehouse

Larsen, R.T.; Bissonette, J.A.; Flinders, J.T.; Hooten, M.B.; Wilson, T.L.

2010-01-01

Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research. ?? Springer Science+Business Media B.V. 2009.

High cell density suppresses BMP4-induced differentiation of human pluripotent stem cells to produce macroscopic spatial patterning in a unidirectional perfusion culture chamber.

PubMed

Tashiro, Shota; Le, Minh Nguyen Tuyet; Kusama, Yuta; Nakatani, Eri; Suga, Mika; Furue, Miho K; Satoh, Taku; Sugiura, Shinji; Kanamori, Toshiyuki; Ohnuma, Kiyoshi

2018-04-19

Spatial pattern formation is a critical step in embryogenesis. Bone morphogenetic protein 4 (BMP4) and its inhibitors are major factors for the formation of spatial patterns during embryogenesis. However, spatial patterning of the human embryo is unclear because of ethical issues and isotropic culture environments resulting from conventional culture dishes. Here, we utilized human pluripotent stem cells (hiPSCs) and a simple anisotropic (unidirectional perfusion) culture chamber, which creates unidirectional conditions, to measure the cell community effect. The influence of cell density on BMP4-induced differentiation was explored during static culture using a conventional culture dish. Immunostaining of the early differentiation marker SSEA-1 and the mesendoderm marker BRACHYURY revealed that high cell density suppressed differentiation, with small clusters of differentiated and undifferentiated cells formed. Addition of five-fold higher concentration of BMP4 showed similar results, suggesting that suppression was not caused by depletion of BMP4 but rather by high cell density. Quantitative RT-PCR array analysis showed that BMP4 induced multi-lineage differentiation, which was also suppressed under high-density conditions. We fabricated an elongated perfusion culture chamber, in which proteins were transported unidirectionally, and hiPSCs were cultured with BMP4. At low density, the expression was the same throughout the chamber. However, at high density, SSEA-1 and BRACHYURY were expressed only in upstream cells, suggesting that some autocrine/paracrine factors inhibited the action of BMP4 in downstream cells to form the spatial pattern. Human iPSCs cultured in a perfusion culture chamber might be useful for studying in vitro macroscopic pattern formation in human embryogenesis. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Social stressors and air pollution across New York City communities: a spatial approach for assessing correlations among multiple exposures.

PubMed

Shmool, Jessie L C; Kubzansky, Laura D; Newman, Ogonnaya Dotson; Spengler, John; Shepard, Peggy; Clougherty, Jane E

2014-11-06

Recent toxicological and epidemiological evidence suggests that chronic psychosocial stress may modify pollution effects on health. Thus, there is increasing interest in refined methods for assessing and incorporating non-chemical exposures, including social stressors, into environmental health research, towards identifying whether and how psychosocial stress interacts with chemical exposures to influence health and health disparities. We present a flexible, GIS-based approach for examining spatial patterns within and among a range of social stressors, and their spatial relationships with air pollution, across New York City, towards understanding their combined effects on health. We identified a wide suite of administrative indicators of community-level social stressors (2008-2010), and applied simultaneous autoregressive models and factor analysis to characterize spatial correlations among social stressors, and between social stressors and air pollutants, using New York City Community Air Survey (NYCCAS) data (2008-2009). Finally, we provide an exploratory ecologic analysis evaluating possible modification of the relationship between nitrogen dioxide (NO2) and childhood asthma Emergency Department (ED) visit rates by social stressors, to demonstrate how the methods used to assess stressor exposure (and/or consequent psychosocial stress) may alter model results. Administrative indicators of a range of social stressors (e.g., high crime rate, residential crowding rate) were not consistently correlated (rho = - 0.44 to 0.89), nor were they consistently correlated with indicators of socioeconomic position (rho = - 0.54 to 0.89). Factor analysis using 26 stressor indicators suggested geographically distinct patterns of social stressors, characterized by three factors: violent crime and physical disorder, crowding and poor access to resources, and noise disruption and property crimes. In an exploratory ecologic analysis, these factors were differentially associated with area-average NO2 and childhood asthma ED visits. For example, only the 'violent crime and disorder' factor was significantly associated with asthma ED visits, and only the 'crowding and resource access' factor modified the association between area-level NO2 and asthma ED visits. This spatial approach enabled quantification of complex spatial patterning and confounding between chemical and non-chemical exposures, and can inform study design for epidemiological studies of separate and combined effects of multiple urban exposures.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

[Prevalence and spatial distribution of trachoma among schoolchildren in Botucatu, São Paulo - Brazil].

PubMed

Schellini, Silvana Artioli; Lavezzo, Marcelo Mendes; Ferraz, Lucieni Barbarini; Olbrich Neto, Jaime; Medina, Norma Hellen; Padovani, Carlos Roberto

2010-01-01

To assess the prevalence of trachoma in schoolchildren of Botucatu/ SP-Brazil and its spatial distribution. Cross-sectional study in children aged from 7 to 14 years, who attended elementary schools in Botucatu/SP in November/2005. The sample size was estimated in 2,092 children, considering the 11.2% historic prevalence of trachoma, accepting an estimation error of 10% and confidence level of 95%. The sample was random, weighted and increased by 20%, because of the possible occurrence of losses. The total number of children examined was 2,692. The diagnosis was clinical, based on WHO guidelines. For the evaluation of spatial data, the CartaLinx program (v1.2) was used, and the school demand sectors digitized according to the planning divisions of the Department of Education. The data were statistically analyzed, and the analysis of the spatial structure of events calculated using the Geode program. The prevalence of trachoma in schoolchildren of Botucatu was 2.9% and there were cases of follicular trachoma. The exploratory spatial analysis failed to reject the null hypothesis of randomness (R= -0.45, p>0.05), with no significant demand sectors. The analysis for the Thiessen polygons also showed that the overall pattern was random (I= -0.07, p=0.49). However, local indicators pointed to a group of low-low type for a polygon to the north of the urban area. The prevalence of trachoma in schoolchildren in Botucatu was 2.9%. The analysis of the spatial distribution did not reveal areas of greater clustering of cases. Although the overall pattern of the disease does not reproduce the socio-economic conditions of the population, the lower prevalence of trachoma was found in areas of lower social vulnerability.

Anthropometric geography applied to the analysis of socioeconomic disparities: cohort trends and spatial patterns of height and robustness in 20th-century Spain

PubMed Central

Camara, Antonio D.; Roman, Joan Garcia

2014-01-01

Anthropometrics have been widely used to study the influence of environmental factors on health and nutritional status. In contrast, anthropometric geography has not often been employed to approximate the dynamics of spatial disparities associated with socioeconomic and demographic changes. Spain exhibited intense disparity and change during the middle decades of the 20th century, with the result that the life courses of the corresponding cohorts were associated with diverse environmental conditions. This was also true of the Spanish territories. This paper presents insights concerning the relationship between socioeconomic changes and living conditions by combining the analysis of cohort trends and the anthropometric cartography of height and physical build. This analysis is conducted for Spanish male cohorts born 1934–1973 that were recorded in the Spanish military statistics. This information is interpreted in light of region-level data on GDP and infant mortality. Our results show an anthropometric convergence across regions that, nevertheless, did not substantially modify the spatial patterns of robustness, featuring primarily robust northeastern regions and weak Central-Southern regions. These patterns persisted until the 1990s (cohorts born during the 1970s). For the most part, anthropometric disparities were associated with socioeconomic disparities, although the former lessened over time to a greater extent than the latter. Interestingly, the various anthropometric indicators utilized here do not point to the same conclusions. Some discrepancies between height and robustness patterns have been found that moderate the statements from the analysis of cohort height alone regarding the level and evolution of living conditions across Spanish regions. PMID:26640422

A geomorphic perspective on terrain-modulated organization of vegetation productivity: Analysis in two semiarid grassland ecosystems in Southwestern United States

USDA-ARS?s Scientific Manuscript database

Spatial patterns of ecosystem productivity arise from the terrain-modulated wetting and drying of the landscape. Using a daily relative greenness (rG) index we explore the relations between spatial variability of plant productivity and landscape morphology, and how these relations change over time...

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

[Development of spatial orientation during pilot training].

PubMed

Ivanov, V V; Vorob'ev, O A; Snipkov, Iu Iu

1988-01-01

The problem of spatial orientation of pilots flying high-altitude aircraft is in the focus of present-day aviation medicine because of a growing number of accidents in the air. One of the productive lines of research is to study spatial orientation in terms of active formation and maintenance of its imagery in a complex environment. However investigators usually emphasize the role of visual (instrumental) information in the image construction, almost ignoring the sensorimotor component of spatial orientation. The theoretical analysis of the process of spatial orientation has facilitated the development of the concept assuming that the pattern of space perception changes with growing professional experience. The concept is based on an active approach to the essence, emergence, formation and variation in the pattern of sensory perception of space in man's consciousness. This concept asserts that as pilot's professional expertise increases, the pattern of spatial orientation becomes geocentric because a new system of spatial perception evolves which is a result of the development of a new (instrumental) type of motor activity in space. This finds expression in the fact that perception of spatial position inflight occurs when man has to resolve a new motor task--movement along a complex trajectory in the three-dimensional space onboard a flying vehicle. The meaningful structure of this problem which is to be implemented through controlling movements of the pilot acts as a factor that forms this new system of perception. All this underlies the arrangement of meaningful collection of instrumental data and detection of noninstrumental signals in the comprehensive perception of changes in the spatial position of a flying vehicle.

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane

PubMed Central

Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian

2016-01-01

Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951

Spatial Analysis of Phytophthora infestans Genotypes and Late Blight Severity on Tomato and Potato in the Del Fuerte Valley Using Geostatistics and Geographic Information Systems.

PubMed

Jaime-Garcia, R; Orum, T V; Felix-Gastelum, R; Trinidad-Correa, R; Vanetten, H D; Nelson, M R

2001-12-01

ABSTRACT Genetic structure of Phytophthora infestans, the causal agent of potato and tomato late blight, was analyzed spatially in a mixed potato and tomato production area in the Del Fuerte Valley, Sinaloa, Mexico. Isolates of P. infestans were characterized by mating type, allozyme analysis at the glucose-6-phosphate isomerase and peptidase loci, restriction fragment length polymorphism with probe RG57, metalaxyl sensitivity, and aggressiveness to tomato and potato. Spatial patterns of P. infestans genotypes were analyzed by geographical information systems and geo-statistics during the seasons of 1994-95, 1995-96, and 1996-97. Spatial analysis of the genetic structure of P. infestans indicates that geographic substructuring of this pathogen occurs in this area. Maps displaying the probabilities of occurrence of mating types and genotypes of P. infestans, and of disease severity at a regional scale, were presented. Some genotypes that exhibited differences in epidemiologically important features such as metalaxyl sensitivity and aggressiveness to tomato and potato had a restricted spread and were localized in isolated areas. Analysis of late blight severity showed recurring patterns, such as the earliest onset of the disease in the area where both potato and tomato were growing, strengthening the hypothesis that infected potato tubers are the main source of primary inoculum. The information that geostatistical analysis provides might help improve management programs for late blight in the Del Fuerte Valley.

Collective behavior in the spatial spreading of obesity

PubMed Central

Gallos, Lazaros K.; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernán A.

2012-01-01

Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies. PMID:22822425

Collective behavior in the spatial spreading of obesity

NASA Astrophysics Data System (ADS)

Gallos, Lazaros K.; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernán A.

2012-06-01

Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies.

Magnetic field pattern synthesis and its application in targeted drug delivery: Design and implementation.

PubMed

Hajiaghajani, Amirhossein; Abdolali, Ali

2018-05-01

In cancer therapy, magnetic drug targeting is considered as an effective treatment to reduce chemotherapy's side effects. The accurate design and shaping of magnetic fields are crucial for healthy cells to be immune from chemotherapeutics. In this paper, arbitrary 2-dimensional spatial patterns of magnetic fields from DC to megahertz are represented in terms of spatial Fourier spectra with sinusoidal eigenfunctions. Realization of each spatial frequency was investigated by a set of elliptical coils. Therefore, it is shown that the desired pattern was synthesized by simultaneous use of coil sets. Currents running on each set were obtained via fast and straightforward analytical Fourier series calculation. Experimentally scanned sample patterns were in close agreement with full wave analysis. Discussions include the evaluation of the Fourier series approximation error and cross-polarization of produced magnetic fields. It was observed that by employing the controlled magnetic field produced by the proposed setup, we were able to steer therapeutic particles toward the right or left half-spheres of the breast, with an efficiency of 90%. Such a pattern synthesizer may be employed in numerous human arteries as well as other bioelectromagnetic patterning applications, e.g., wireless power transfer, magnetic innervation, and tomography. Bioelectromagnetics. 39:325-338, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

Spatial and Temporal Patterns of Throughfall Amounts and Solutes in a Tropical Montane Forest - Comparisons with Findings From Lowland Rain Forests

NASA Astrophysics Data System (ADS)

Zimmermann, A.

2007-05-01

The diverse tree species composition, irregular shaped tree crowns and a multi-layered forest structure affect the redistribution of rainfall in lower montane rain forests. In addition, abundant epiphyte biomass and associated canopy humus influence spatial patterns of throughfall. The spatial variability of throughfall amounts controls spatial patterns of solute concentrations and deposition. Moreover, the living and dead biomass interacts with the rainwater during the passage through the canopy and creates a chemical variability of its own. Since spatial and temporal patterns are intimately linked, the analysis of temporal solute concentration dynamics is an important step to understand the emerging spatial patterns. I hypothesized that: (1) the spatial variability of volumes and chemical composition of throughfall is particularly high compared with other forests because of the high biodiversity and epiphytism, (2) the temporal stability of the spatial pattern is high because of stable structures in the canopy (e.g. large epiphytes) that show only minor changes during the short term observation period, and (3) the element concentrations decrease with increasing rainfall because of exhausting element pools in the canopy. The study area at 1950 m above sea level is located in the south Ecuadorian Andes far away from anthropogenic emission sources and marine influences. Rain and throughfall were collected from August to October 2005 on an event and within-event basis for five precipitation periods and analyzed for pH, K, Na, Ca, Mg, NH4+, Cl-, NO3-, PO43-, TN, TP and TOC. Throughfall amounts and most of the solutes showed a high spatial variability, thereby the variability of H+, K, Ca, Mg, Cl- and NO3- exceeded those from a Brazilian tropical rain forest. The temporal persistence of the spatial patterns was high for throughfall amounts and varied depending on the solute. Highly persistent time stability patterns were detected for K, Mg and TOC concentrations. Time stability patterns of solute deposition were somewhat weaker than for concentrations for most of the solutes. Epiphytes strongly affected time stability patterns in that collectors situated below thick moss mats or arboreal bromeliads were in large part responsible for the extreme persistence with low throughfall amounts and high ion concentrations (H+ showed low concentrations). Rainfall solute concentrations were low compared with a variety of other tropical lowland and montane forest sites and showed a small temporal variability during the study period for both between and within-event dynamics, respectively. Throughfall solute concentrations were more within the range when compared with other sites and showed highly variable within-event dynamics. For most of the solutes, within-event concentrations did not reach low, constant concentrations in later event stages, rather concentrations fluctuated (e.g. Cl-) or increased (e.g. K and TOC). The within-event throughfall solute concentration dynamics in this lower montane rain forest contrast to recent observations from lowland tropical rain forests in Panama and Brazil. The observed within-event patterns are attributed (1) to the influence of epiphytes and associated canopy humus, and (2) to low rainfall intensities.

Scale dependent inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

Forest fragmentation in Massachusetts, USA: a town-level assessment using Morphological Spatial Pattern Analysis and affinity propagation

Treesearch

J. Rogan; T.M. Wright; J. Cardille; H. Pearsall; Y. Ogneva-Himmelberger; Rachel Riemann; Kurt Riitters; K. Partington

2016-01-01

Forest fragmentation has been studied extensively with respect to biodiversity loss, disruption of ecosystem services, and edge effects although the relationship between forest fragmentation and human activities is still not well understood. We classified the pattern of forests in Massachusetts using fragmentation indicators to address...

Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

PubMed

Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

2015-06-01

Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. © 2015 International Society for Advancement of Cytometry.

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

DOE PAGES

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.; ...

2016-04-06

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. D.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth.

A method for studying the development pattern of urban commercial service facilities based on customer reviews from social media

NASA Astrophysics Data System (ADS)

Wang, Y. D.; Jiang, B. T.; Ye, X. Y.

2016-06-01

Urbanization is one of the most important human social activities in the 21st century (Chaolin et al., 2012). With an increasing number of people visiting cities, the provision of adequate urban service facilities, including public and commercial service facilities, in locations where people live has become an important guarantee of the success of urbanization. Exploring the commercial service facilities in a specific area of a city can help us understand the progress and trends of urban renewal in the area, provide a quantitative basis for evaluating the rationality of planning implementation, and facilitate an analysis of the effects of different factors on the regional development of a city (Schor et al. 2003). In this paper, we proposed a data processing and analysis method for studying the distribution and development pattern of urban commercial facilities based on customer reviews. In addition, based on road network constraints, we explored the patterns contained in customer reviews data, including patterns for the spatial distribution and spatial-temporal evolution of facilities as well as the number of facilities and degree of satisfaction.

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

NASA Astrophysics Data System (ADS)

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.

Changing the spatial pattern of TFL1 expression reveals its key role in the shoot meristem in controlling Arabidopsis flowering architecture

PubMed Central

Baumann, Kim; Venail, Julien; Berbel, Ana; Domenech, Maria Jose; Money, Tracy; Conti, Lucio; Hanzawa, Yoshie; Madueno, Francisco; Bradley, Desmond

2015-01-01

Models for the control of above-ground plant architectures show how meristems can be programmed to be either shoots or flowers. Molecular, genetic, transgenic, and mathematical studies have greatly refined these models, suggesting that the phase of the shoot reflects different genes contributing to its repression of flowering, its vegetativeness (‘veg’), before activators promote flower development. Key elements of how the repressor of flowering and shoot meristem gene TFL1 acts have now been tested, by changing its spatiotemporal pattern. It is shown that TFL1 can act outside of its normal expression domain in leaf primordia or floral meristems to repress flower identity. These data show how the timing and spatial pattern of TFL1 expression affect overall plant architecture. This reveals that the underlying pattern of TFL1 interactors is complex and that they may be spatially more widespread than TFL1 itself, which is confined to shoots. However, the data show that while TFL1 and floral genes can both act and compete in the same meristem, it appears that the main shoot meristem is more sensitive to TFL1 rather than floral genes. This spatial analysis therefore reveals how a difference in response helps maintain the ‘veg’ state of the shoot meristem. PMID:26019254

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Bioconvection in spatially extended domains

NASA Astrophysics Data System (ADS)

Karimi, A.; Paul, M. R.

2013-05-01

We numerically explore gyrotactic bioconvection in large spatially extended domains of finite depth using parameter values from available experiments with the unicellular alga Chlamydomonas nivalis. We numerically integrate the three-dimensional, time-dependent continuum model of Pedley [J. Fluid Mech.10.1017/S0022112088002393 195, 223 (1988)] using a high-order, parallel, spectral-element approach. We explore the long-time nonlinear patterns and dynamics found for layers with an aspect ratio of 10 over a range of Rayleigh numbers. Our results yield the pattern wavelength and pattern dynamics which we compare with available theory and experimental measurement. There is good agreement for the pattern wavelength at short times between numerics, experiment, and a linear stability analysis. At long times we find that the general sequence of patterns given by the nonlinear evolution of the governing equations correspond qualitatively to what has been described experimentally. However, at long times the patterns in numerics grow to larger wavelengths, in contrast to what is observed in experiment where the wavelength is found to decrease with time.

A Spatial Analysis of the Potato Cyst Nematode Globodera pallida in Idaho.

PubMed

Dandurand, Louise-Marie; Contina, Jean Bertrand; Knudsen, Guy R

2018-03-13

The potato cyst nematode (PCN), Globodera pallida, is a globally regulated and quarantine potato pest. It was detected for the first time in the U.S. in the state of Idaho in 2006. A spatial analysis was performed to: (i) understand the spatial arrangement of PCN infested fields in southern Idaho using spatial point pattern analysis; and (ii) evaluate the potential threat of PCN for entry to new areas using spatial interpolation techniques. Data point locations, cyst numbers and egg viability values for each infested field were collected by USDA-APHIS during 2006-2014. Results showed the presence of spatially clustered PCN infested fields (P = 0.003). We determined that the spread of PCN grew in diameter from the original center of infestation toward the southwest as an ellipsoidal-shaped cluster. Based on the aggregated spatial pattern of distribution and the low extent level of PCN infested fields in southern Idaho, we determined that PCN spread followed a contagion effect scenario, where nearby infested fields contributed to the infestation of new fields, probably through soil contaminated agricultural equipment or tubers. We determined that the recent PCN presence in southern Idaho is unlikely to be associated with new PCN entry from outside the state of Idaho. The relative aggregation of PCN infested fields, the low number of cysts recovered, and the low values in egg viability facilitate quarantine activities and confine this pest to a small area, which, in 2017, is estimated to be 1,233 hectares. The tools and methods provided in this study should facilitate comprehensive approaches to improve PCN control and eradication programs as well as to raise public awareness about this economically important potato pest.

A spatial and genetic analysis of Cowbird host selection

USGS Publications Warehouse

Hahn, D.C.; Sedgwick, J.A.; Painter, I.S.; Casna, N.J.; Morrison, Michael L.; Hall, Linnea S.; Robinson, Scott K.; Rothstein, Stephen I.; Hahn, D. Caldwell; Rich, Terrell D.

1999-01-01

Our study of brood parasitism patterns in forest communities revealed the egg-laying frequency and host selection patterns of female cowbirds. By integrating molecular genetics and spatial data, we have the first published estimate on cowbird laying rates in field studies. The 29 females in the study laid only 1-5 eggs each, much lower than previous estimates from captive cowbirds and extrapolations from ovarian development in capture/recapture studies that had suggested that as many as 40 eggs could be laid per individual cowbird. Cowbird females also were shown for the first time to lay significantly more eggs within the home range areas they established rather than outside the home range. No patterns were uncovered for individual females preferentially parasitizing particular host species

Exploring the relation between spatial configuration of buildings and remotely sensed temperatures

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Kaplan, S.; Huang, H.

2013-12-01

While the relationship between fractional cover of buildings and the UHI has been well studied, relationships of how spatial arrangements (e.g., clustered, dispersed) of buildings influence urban warming are not well understood. Since a diversity of spatial patterns can be observed under the same percentage of buildings cover, it is of great interest and importance to investigate the amount of variation in certain urban thermal feature such as surface temperature that is accounted for by the inclusion of spatial arrangement component. The various spatial arrangements of buildings cover can give rise to different urban thermal behaviors that may not be uncovered with the information of buildings fraction only, but can be captured to some extent using spatial analysis. The goal of this study is to examine how spatial arrangements of buildings influence and shape surface temperature in different urban settings. The study area selected is the Las-Vegas metropolitan area in Nevada, located in the Mojave Desert. An object-oriented approach was used to identify buildings using a Geoeye-1 image acquired on October 12, 2011. A spatial autocorrelation technique (i.e., Moran's I) that can measure spatial pattern (clustered, dispersed) was used to determine spatial configuration of buildings. A daytime temperature layer in degree Celsius, generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image, was integrated with Moran's I values of building cover and building fractions to achieve the goals set in the study. To avoid uncertainty and properly evaluate if spatial pattern of buildings has an impact on urban warming, the relation between Moran's I values and surface temperatures was observed at different levels according to their fractions (e.g., 0-0.1, 0.5-0.6, 0.9-1). There is a negative correlation exists between spatial pattern of buildings and surface temperatures implying that dispersed building arrangements elevate surface temperatures more severely than clustered buildings. This suggests that more clustered buildings have less impact on the urban heat island (UHI) effect. We conclude that having buildings as clustered as possible can be expected to protect the settlements from increased heat island effects, reduce pollution, and preserve the hydrological systems.

Evaluating influence of active tectonics on spatial distribution pattern of floods along eastern Tamil Nadu, India

NASA Astrophysics Data System (ADS)

Selvakumar, R.; Ramasamy, SM.

2014-12-01

Flooding is a naturally recurrent phenomenon that causes severe damage to lives and property. Predictions on flood-prone zones are made based on intensity-duration of rainfall, carrying capacity of drainage, and natural or man-made obstructions. Particularly, the lower part of the drainage system and its adjacent geomorphic landforms like floodplains and deltaic plains are considered for analysis, but stagnation in parts of basins that are far away from major riverine systems is less unveiled. Similarly, uncharacteristic flooding in the upper and middle parts of drainage, especially in zones of an anomalous drainage pattern, is also least understood. Even though topographic differences are attributed for such anomalous spatial occurrence of floods, its genetic cause has to be identified for effective management practice. Added to structural and lithological variations, tectonic movements too impart micro-scale terrain undulations. Because active tectonic movements are slow-occurring, long-term geological processes, its resultant topographical variations and drainage anomalies are least correlated with floods. The recent floods of Tamil Nadu also exhibit a unique distribution pattern emphasizing the role of tectonics over it. Hence a detailed geoinformatics-based analysis was carried out to envisage the relationship between spatial distribution of flood and active tectonic elements such as regional arches and deeps, block faults, and graben and drainage anomalies such as deflected drainage, compressed meander, and eyed drainages. The analysis reveals that micro-scale topographic highs and lows imparted by active tectonic movements and its further induced drainage anomalies have substantially controlled the distribution pattern of flood.

Spatial Analysis of Rice Blast in China at Three Different Scales.

PubMed

Guo, Fangfang; Chen, Xinglong; Lu, Minghong; Yang, Li; Wang, Shi Wei; Wu, Bo Ming

2018-05-22

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from June 10 th to Sep. 10 th during 2009-2014, and surveyed in 143 fields in September, 2016; at county scale, 3 surveys were done covering 1-5 counties in 2015-2016; and at field scale, blast was evaluated in 6 fields in 2015-2016. Spatial cluster and hot spot analyses were conducted in GIS on the geographical pattern of the disease at regional scale, and geostatistical analysis performed at all the three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1080 km at regional scale, and 5 to 10 m at field scale, but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Spatially characterizing visitor use and its association with informal trails in Yosemite Valley meadows.

PubMed

Walden-Schreiner, Chelsey; Leung, Yu-Fai

2013-07-01

Ecological impacts associated with nature-based recreation and tourism can compromise park and protected area goals if left unrestricted. Protected area agencies are increasingly incorporating indicator-based management frameworks into their management plans to address visitor impacts. Development of indicators requires empirical evaluation of indicator measures and examining their ecological and social relevance. This study addresses the development of the informal trail indicator in Yosemite National Park by spatially characterizing visitor use in open landscapes and integrating use patterns with informal trail condition data to examine their spatial association. Informal trail and visitor use data were collected concurrently during July and August of 2011 in three, high-use meadows of Yosemite Valley. Visitor use was clustered at statistically significant levels in all three study meadows. Spatial data integration found no statistically significant differences between use patterns and trail condition class. However, statistically significant differences were found between the distance visitors were observed from informal trails and visitor activity type with active activities occurring closer to trail corridors. Gender was also found to be significant with male visitors observed further from trail corridors. Results highlight the utility of integrated spatial analysis in supporting indicator-based monitoring and informing management of open landscapes. Additional variables for future analysis and methodological improvements are discussed.

Spatially Characterizing Visitor Use and Its Association with Informal Trails in Yosemite Valley Meadows

NASA Astrophysics Data System (ADS)

Walden-Schreiner, Chelsey; Leung, Yu-Fai

2013-07-01

Ecological impacts associated with nature-based recreation and tourism can compromise park and protected area goals if left unrestricted. Protected area agencies are increasingly incorporating indicator-based management frameworks into their management plans to address visitor impacts. Development of indicators requires empirical evaluation of indicator measures and examining their ecological and social relevance. This study addresses the development of the informal trail indicator in Yosemite National Park by spatially characterizing visitor use in open landscapes and integrating use patterns with informal trail condition data to examine their spatial association. Informal trail and visitor use data were collected concurrently during July and August of 2011 in three, high-use meadows of Yosemite Valley. Visitor use was clustered at statistically significant levels in all three study meadows. Spatial data integration found no statistically significant differences between use patterns and trail condition class. However, statistically significant differences were found between the distance visitors were observed from informal trails and visitor activity type with active activities occurring closer to trail corridors. Gender was also found to be significant with male visitors observed further from trail corridors. Results highlight the utility of integrated spatial analysis in supporting indicator-based monitoring and informing management of open landscapes. Additional variables for future analysis and methodological improvements are discussed.

Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems.

PubMed

Wu, B M; van Bruggen, A H; Subbarao, K V; Pennings, G G

2001-02-01

ABSTRACT The epidemiology of lettuce downy mildew has been investigated extensively in coastal California. However, the spatial patterns of the disease and the distance that Bremia lactucae spores can be transported have not been determined. During 1995 to 1998, we conducted several field- and valley-scale surveys to determine spatial patterns of this disease in the Salinas valley. Geostatistical analyses of the survey data at both scales showed that the influence range of downy mildew incidence at one location on incidence at other locations was between 80 and 3,000 m. A linear relationship was detected between semivariance and lag distance at the field scale, although no single statistical model could fit the semi-variograms at the valley scale. Spatial interpolation by the inverse distance weighting method with a power of 2 resulted in plausible estimates of incidence throughout the valley. Cluster analysis in geographic information systems on the interpolated disease incidence from different dates demonstrated that the Salinas valley could be divided into two areas, north and south of Salinas City, with high and low disease pressure, respectively. Seasonal and spatial trends along the valley suggested that the distinction between the downy mildew conducive and nonconducive areas might be determined by environmental factors.

Detection of forest stand-level spatial structure in ectomycorrhizal fungal communities.

PubMed

Lilleskov, Erik A; Bruns, Thomas D; Horton, Thomas R; Taylor, D; Grogan, Paul

2004-08-01

Ectomycorrhizal fungal (EMF) communities are highly diverse at the stand level. To begin to understand what might lead to such diversity, and to improve sampling designs, we investigated the spatial structure of these communities. We used EMF community data from a number of studies carried out in seven mature and one recently fire-initiated forest stand. We applied various measures of spatial pattern to characterize distributions at EMF community and species levels: Mantel tests, Mantel correlograms, variance/mean and standardized variograms. Mantel tests indicated that in four of eight sites community similarity decreased with distance, whereas Mantel correlograms also found spatial autocorrelation in those four plus two additional sites. In all but one of these sites elevated similarity was evident only at relatively small spatial scales (< 2.6 m), whereas one exhibited a larger scale pattern ( approximately 25 m). Evenness of biomass distribution among cores varied widely among taxa. Standardized variograms indicated that most of the dominant taxa showed patchiness at a scale of less than 3 m, with a range from 0 to < or =17 m. These results have implications for both sampling scale and intensity to achieve maximum efficiency of community sampling. In the systems we examined, cores should be at least 3 m apart to achieve the greatest sampling efficiency for stand-level community analysis. In some cases even this spacing may result in reduced sampling efficiency arising from patterns of spatial autocorrelation. Interpretation of the causes and significance of these patterns requires information on the genetic identity of individuals in the communities.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

PubMed

Freeman, Mary Pyott; Stow, Douglas A; An, Li

2017-10-01

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Mean mortality remained static from 1997 to 2002 (4, 2.2, and 4.2 trees/ha for Palomar, Volcan, and Laguna) and then increased by 2005 to 10.3, 9.7, and 5.2 trees/ha, respectively. The increase in mortality between 2002 and 2005 represents the temporal pattern of a discrete disturbance event, attributable to the 2002-2003 drought. Dead trees are significantly clustered for all dates, based on spatial cluster analysis, indicating that they form distinct groups, as opposed to spatially random single dead trees. Other tests indicate no directional shift or spread of mortality over time, but rather an increase in density. While general temporal and spatial mortality processes are uniform across all study areas, the plot-based species and quantity distribution of mortality, and diameter distributions of dead vs. living trees, vary by study area. The results of this study improve our understanding of stand- to landscape-level forest structure and dynamics, particularly by examining them from the multiple perspectives of field and remotely sensed data. © 2017 by the Ecological Society of America.

Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease.

PubMed

Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar

2018-05-15

The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

NASA Astrophysics Data System (ADS)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

Antarctic Sea Ice-Atmosphere Interactions: A Self-organizing Map-based Perspective

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2005-12-01

Interactions between the ocean, sea ice and the atmosphere are a significant component of the dynamic nature of the Earth's climate system. Self-organizing maps (SOMs), an analysis tool from the field of artificial neural networks, have been used to study variability in Antarctic sea ice extent and the West Antarctic atmospheric circulation, plus the relationship and interactions between these two systems. Self-organizing maps enable unsupervised classification of large, multivariate/multidimensional data sets, e.g., time series of the atmospheric circulation or sea-ice extent, into a fixed number of distinct generalized states or modes, organized spatially as a two-dimensional grid, that are representative of the input data. When applied to atmospheric data, the analysis yields a nonlinear classification of the continuum of atmospheric conditions. In contrast to principal component analysis, SOMs do not force orthogonality or require subjective rotations to produce interpretable patterns. Twenty four years (1973-96) of monthly sea ice extent data (10 deg longitude bands; Simmonds and Jacka, 1995) were analyzed with a 30-node SOM. The resulting set of generalized patterns concisely captures the spatial and temporal variability in this data. An example of the former is variability in the longitudinal region of greatest extent. The SOM patterns readily show that there are multiple spatial patterns corresponding to "greatest extent conditions". Temporal variability is examined by creating frequency maps (i.e., which patterns occur most often) by month. With the annual cycle still in the data, the monthly frequency maps show a cycle moving from least extent, through expansion to greatest extent and back through retreat. When plotted in "SOM space", month-to-month transitions occur at different rates of change, suggesting that there is variability in the rate of change in extent at different times of the year, e.g., retreat in January is faster than November. Twenty five years (1977-2001) of monthly 500 mb temperature and pressure data (from the ECMWF 40-year reanalysis, ERA-40) from a region centered on the Antarctic Peninsula were analyzed independently for a separate SOMs-based study. Dominant SOM temperature patterns include the expected summer warmth and winter cold, plus "dipoles" of warm Atlantic (Pacific) and cold Pacific (Atlantic) sectors (with corresponding pressure patterns). Temporally, there is the expected annual progression from warmth, through cooling and back to warmth, with no particularly predominant patterns in many of the monthly frequency maps when the full record is used. Stratifying by high/low values of the Southern Oscillation Index (SOI) suggests that the spatial patterns of cooling and warming may be related to conditions in the tropical Pacific: in a low SOI year (1987), cooling and warming both begin in the Atlantic sector, with the opposite true in a high SOI year (1989). Further study of this aspect is planned. In addition to direct comparisons of the SOM analysis results from each study, a joint SOM analysis will be done on the combined data sets, exploiting the flexibility and power of this technique. We anticipate additional useful insights into the joint variability and relationships between Antarctic sea ice and the overlying atmosphere through this expanded analysis.

Fish assemblage in a semi-arid Neotropical reservoir: composition, structure and patterns of diversity and abundance.

PubMed

Novaes, J L C; Moreira, S I L; Freire, C E C; Sousa, M M O; Costa, R S

2014-05-01

The aim of this study was to analyse the composition, structure and spatial and temporal patterns of diversity and abundance of the ichthyofauna of the Santa Cruz Reservoir in semi-arid Brazil. Data were collected quarterly at eight sampling locations on the reservoir between February 2010 and November 2011 using gillnets from 12- to 70-mm mesh that were left in the water for 12h00min during the night. We evaluated the composition, structure and assemblage descriptors (Shannon-Wiener diversity index and equitability, respectively) and catch per unit effort by the number (CPUEn) and biomass (CPUEb) of the ichthyofauna. The 6,047 individuals (399,211.6 g) captured represented three orders, ten families and 20 species, of which four belonged to introduced species. The family Characidae was the most abundant with a total of 2,772 (45.8%) individuals captured. The species-abundance curve fit the log-normal model. In the spatial analysis of diversity, there were significant differences between sampling sites in the lacustrine and fluvial regions, and the highest values were found in the lacustrine region. In the temporal analysis of diversity, significant differences were also observed between the rainy and dry seasons, and the higher values were found during the dry season. Equitability followed the same spatiotemporal pattern as diversity. The Spearman correlation was significantly negative between diversity and rainfall. A cluster analysis spatially separated the ichthyofauna into two groups: one group formed by sampling sites in the fluvial region and another group formed by the remainder of the points in the lacustrine region. Both the CPUEn and CPUEb values were higher at point 8 (fluvial region) and during the rainy season. A two-way ANOVA showed that the CPUEn and CPUEb values were spatially and temporally significant. We conclude that the spatial and temporal trends of diversity in the Santa Cruz reservoir differ from those of other Brazilian reservoirs but that the fish community composition and spatiotemporal patterns of abundance were similar.

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

Decoding auditory spatial and emotional information encoding using multivariate versus univariate techniques.

PubMed

Kryklywy, James H; Macpherson, Ewan A; Mitchell, Derek G V

2018-04-01

Emotion can have diverse effects on behaviour and perception, modulating function in some circumstances, and sometimes having little effect. Recently, it was identified that part of the heterogeneity of emotional effects could be due to a dissociable representation of emotion in dual pathway models of sensory processing. Our previous fMRI experiment using traditional univariate analyses showed that emotion modulated processing in the auditory 'what' but not 'where' processing pathway. The current study aims to further investigate this dissociation using a more recently emerging multi-voxel pattern analysis searchlight approach. While undergoing fMRI, participants localized sounds of varying emotional content. A searchlight multi-voxel pattern analysis was conducted to identify activity patterns predictive of sound location and/or emotion. Relative to the prior univariate analysis, MVPA indicated larger overlapping spatial and emotional representations of sound within early secondary regions associated with auditory localization. However, consistent with the univariate analysis, these two dimensions were increasingly segregated in late secondary and tertiary regions of the auditory processing streams. These results, while complimentary to our original univariate analyses, highlight the utility of multiple analytic approaches for neuroimaging, particularly for neural processes with known representations dependent on population coding.

Spatial correlations, clustering and percolation-like transitions in homicide crimes

NASA Astrophysics Data System (ADS)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Striking the balance: Privacy and spatial pattern preservation in masked GPS data

NASA Astrophysics Data System (ADS)

Seidl, Dara E.

Volunteered location and trajectory data are increasingly collected and applied in analysis for a variety of academic fields and recreational pursuits. As access to personal location data increases, issues of privacy arise as individuals become identifiable and linked to other repositories of information. While the quality and precision of data are essential to accurate analysis, there is a tradeoff between privacy and access to data. Obfuscation of point data is a solution that aims to protect privacy and maximize preservation of spatial pattern. This study explores two methods of location obfuscation for volunteered GPS data: grid masking and random perturbation. These methods are applied to travel survey GPS data in the greater metropolitan regions of Chicago and Atlanta in the first large-scale GPS masking study of its kind.

Methods for Monitoring the Detection of Multi-Temporal Land Use Change Through the Classification of Urban Areas

NASA Astrophysics Data System (ADS)

Alhaddad, B. I.; Burns, M. C.; Roca, J.

2011-08-01

Urban areas are complicated due to the mix of man-made features and natural features. A higher level of structural information plays an important role in land cover/use classification of urban areas. Additional spatial indicators have to be extracted based on structural analysis in order to understand and identify spatial patterns or the spatial organization of features, especially for man-made feature. It's very difficult to extract such spatial patterns by using only classification approaches. Clusters of urban patterns which are integral parts of other uses may be difficult to identify. A lot of public resources have been directed towards seeking to develop a standardized classification system and to provide as much compatibility as possible to ensure the widespread use of such categorized data obtained from remote sensor sources. In this paper different methods applied to understand the change in the land use areas by understanding and monitoring the change in urban areas and as its hard to apply those methods to classification results for high elements quantities, dusts and scratches (Roca and Alhaddad, 2005). This paper focuses on a methodology developed based relation between urban elements and how to join this elements in zones or clusters have commune behaviours such as form, pattern, size. The main objective is to convert urban class category in to various structure densities depend on conjunction of pixel and shortest distance between them, Delaunay triangulation has been widely used in spatial analysis and spatial modelling. To identify these different zones, a spatial density-based clustering technique was adopted. In highly urban zones, the spatial density of the pixels is high, while in sparsely areas the density of points is much lower. Once the groups of pixels are identified, the calculation of the boundaries of the areas containing each group of pixels defines the new regions indicate the different contains inside such as high or low urban areas. Multi-temporal datasets from 1986, 1995 and 2004 used to urban region centroid to be our reference in this study which allow us to follow the urban movement, increase and decrease by the time. Kernel Density function used to Calculates urban magnitude, Voronoi algorithm is proposed for deriving explicit boundaries between objects units. To test the approach, we selected a site in a suburban area in Barcelona Municipality, the Spain.

Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan

2017-07-01

Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

[Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

PubMed

Liang, Jia Xin; Li, Xin Ju

2018-02-01

With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas.

PubMed

Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun

2016-09-02

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas

PubMed Central

Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun

2016-01-01

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST. PMID:27598186

Analysis of suicide mortality in Brazil: spatial distribution and socioeconomic context.

PubMed

Dantas, Ana P; Azevedo, Ulicélia N de; Nunes, Aryelly D; Amador, Ana E; Marques, Marilane V; Barbosa, Isabelle R

2018-01-01

To perform a spatial analysis of suicide mortality and its correlation with socioeconomic indicators in Brazilian municipalities. This is an ecological study with Brazilian municipalities as a unit of analysis. Data on deaths from suicide and contextual variables were analyzed. The spatial distribution, intensity and significance of the clusters were analyzed with the global Moran index, MoranMap and local indicators of spatial association (LISA), seeking to identify patterns through geostatistical analysis. A total of 50,664 deaths from suicide were registered in Brazil between 2010 and 2014. The average suicide mortality rate in Brazil was 5.23/100,000 population. The Brazilian municipalities presenting the highest rates were Taipas do Tocantins, state of Tocantins (79.68 deaths per 100,000 population), Itaporã, state of Mato Grosso do Sul (75.15 deaths per 100,000 population), Mampituba, state of Rio Grande do Sul (52.98 deaths per 100,000 population), Paranhos, state of Mato Grosso do Sul (52.41 deaths per 100,000 population), and Monjolos, state of Minas Gerais (52.08 deaths per 100,000 population). Although weak spatial autocorrelation was observed for suicide mortality (I = 0.2608), there was a formation of clusters in the South. In the bivariate spatial and classical analysis, no correlation was observed between suicide mortality and contextual variables. Suicide mortality in Brazil presents a weak spatial correlation and low or no spatial relationship with socioeconomic factors.

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

NASA Technical Reports Server (NTRS)

Ripple, William J.; Bradshaw, G. A.; Spies, Thomas A.

1995-01-01

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Space-based constraints on spatial and temporal patterns of NO(x) emissions in California, 2005-2008.

PubMed

Russell, Ashley R; Valin, Lukas C; Bucsela, Eric J; Wenig, Mark O; Cohen, Ronald C

2010-05-01

We describe ground and space-based measurements of spatial and temporal variation of NO(2) in four California metropolitan regions. The measurements of weekly cycles and trends over the years 2005-2008 observed both from the surface and from space are nearly identical to each other. Observed decreases in Los Angeles and the surrounding cities are 46% on weekends and 9%/year from 2005-2008. Similar decreases are observed in the San Francisco Bay area and in Sacramento. In the San Joaquin Valley cities of Fresno and Bakersfield weekend decreases are much smaller, only 27%, and the decreasing trend is only 4%/year. We describe evidence that the satellite observations provide a uniquely complete view of changes in spatial patterns over time. For example, we observe variations in the spatial pattern of weekday-weekend concentrations in the Los Angeles basin with much steeper weekend decreases at the eastern edge of the basin. We also observe that the spatial extent of high NO(2) in the San Joaquin Valley has not receded as much as it has for other regions in the state. Analysis of these measurements is used to describe observational constraints on temporal trends in emission sources in the different regions.

Surface plasmon enhanced cell microscopy with blocked random spatial activation

NASA Astrophysics Data System (ADS)

Son, Taehwang; Oh, Youngjin; Lee, Wonju; Yang, Heejin; Kim, Donghyun

2016-03-01

We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

NASA Astrophysics Data System (ADS)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

Spatial Analysis after Perinatal Stroke: Patterns of Neglect and Exploration in Extra-Personal Space

ERIC Educational Resources Information Center

Thareja, Tarika; Ballantyne, Angela O.; Trauner, Doris A.

2012-01-01

This study was conducted to determine whether school-aged children who had experienced a perinatal stroke demonstrate evidence of persistent spatial neglect, and if such neglect was specific to the visual domain or was more generalized. Two studies were carried out. In the first, 38 children with either left hemisphere (LH) or right hemisphere…

Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis [chapter 7

Treesearch

Samuel A. Cushman

2010-01-01

In the previous chapter we presented the idea of a multi-layer, multi-scale, spatially referenced data-cube as the foundation for monitoring and for implementing flexible modeling of ecological pattern-process relationships in particulate, in context and to integrate these across large spatial extents at the grain of the strongest linkage between response and driving...

Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003-2015): Implications for Prevention and Control Policies.

PubMed

Zhu, Bin; Liu, Jinlin; Fu, Yang; Zhang, Bo; Mao, Ying

2018-04-02

Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran's I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit.

Membrane Driven Spatial Organization of GPCRs

NASA Astrophysics Data System (ADS)

Mondal, Sayan; Johnston, Jennifer M.; Wang, Hao; Khelashvili, George; Filizola, Marta; Weinstein, Harel

2013-10-01

Spatial organization of G-protein coupled receptors (GPCRs) into dimers and higher order oligomers has been demonstrated in vitro and in vivo. The pharmacological readout was shown to depend on the specific interfaces, but why particular regions of the GPCR structure are involved, and how ligand-determined states change them remains unknown. Here we show why protein-membrane hydrophobic matching is attained upon oligomerization at specific interfaces from an analysis of coarse-grained molecular dynamics simulations of the spontaneous diffusion-interaction of the prototypical beta2-adrenergic (β2AR) receptors in a POPC lipid bilayer. The energy penalty from mismatch is significantly reduced in the spontaneously emerging oligomeric arrays, making the spatial organization of the GPCRs dependent on the pattern of mismatch in the monomer. This mismatch pattern is very different for β2AR compared to the highly homologous and structurally similar β1AR, consonant with experimentally observed oligomerization patterns of β2AR and β1AR. The results provide a mechanistic understanding of the structural context of oligomerization.

Structure preserving clustering-object tracking via subgroup motion pattern segmentation

NASA Astrophysics Data System (ADS)

Fan, Zheyi; Zhu, Yixuan; Jiang, Jiao; Weng, Shuqin; Liu, Zhiwen

2018-01-01

Tracking clustering objects with similar appearances simultaneously in collective scenes is a challenging task in the field of collective motion analysis. Recent work on clustering-object tracking often suffers from poor tracking accuracy and terrible real-time performance due to the neglect or the misjudgment of the motion differences among objects. To address this problem, we propose a subgroup motion pattern segmentation framework based on a multilayer clustering structure and establish spatial constraints only among objects in the same subgroup, which entails having consistent motion direction and close spatial position. In addition, the subgroup segmentation results are updated dynamically because crowd motion patterns are changeable and affected by objects' destinations and scene structures. The spatial structure information combined with the appearance similarity information is used in the structure preserving object tracking framework to track objects. Extensive experiments conducted on several datasets containing multiple real-world crowd scenes validate the accuracy and the robustness of the presented algorithm for tracking objects in collective scenes.

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

Networks, narratives and territory in anthropological race classification: towards a more comprehensive historical geography of Europe's culture.

PubMed

McMahon, Richard

2011-01-01

This article aims to integrate discourse analysis of politically instrumental imagined identity geographies with the relational and territorial geography of the communities of praxis and interpretation that produce them. My case study is the international community of nationalist scientists who classified Europe's biological races in the 1820s-1940s. I draw on network analysis, relational geography, historical sociology and the historical turn to problematize empirically how spatial patterns of this community's shifting disciplinary and political coalitions, communication networks and power relations emerged, were structured, persisted, changed, interacted and disappeared. I focus especially on core-periphery relations. I argue that if local historical spatial patterns affect those of later phenomena, geographies like that of European integration should be understood in the context of Europe's complex historical cultural geography. Unlike discourse deconstruction alone, this complementary relational de-essentialization of geography can identify large-scale, enduring associations of cultural patterns as well as cultural flux and ambiguity.

Spatial Patterns of NLCD Land Cover Change Thematic Accuracy (2001 - 2011)

EPA Science Inventory

Research on spatial non-stationarity of land cover classification accuracy has been ongoing for over two decades. We extend the understanding of thematic map accuracy spatial patterns by: 1) quantifying spatial patterns of map-reference agreement for class-specific land cover c...

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile.

PubMed

Inostroza, Luis; Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

PubMed Central

Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making. PMID:27606592

Separate channels for the analysis of the shape and the movement of moving visual stimulus.

PubMed

Tolhurst, D J

1973-06-01

1. The effects of temporal modulation on the properties of spatial frequency channels have been investigated using adaptation.2. Adapting to drifting sinusoidal gratings caused threshold elevation that was both spatial frequency and direction specific. Little systematic difference was found between the band widths of the elevation curves for drifting and stationary gratings.3. It was confirmed that adaptation fails to reveal channels at low spatial frequencies when stationary gratings are used. However, channels were revealed at frequencies at least as low as 0.66 c/deg when the test gratings were made to move. These channels are adapted only a little by stationary gratings, confirming their dependence on movement.4. The existence of movement-sensitive channels at low spatial frequencies explains the well known observation that temporal modulation greatly increases the sensitivity of the visual system to low spatial frequencies.5. Temporal modulation was effective at revealing these channels only when the flicker or movement of the test patterns was apparent to the observer; only at low spatial frequencies did patterns, modulated at low rates, actually appear to be temporarily modulated at threshold. At higher spatial frequencies, they were indistinguishable from stationary patterns until the contrast was some way above the detection threshold.6. It is suggested, therefore, that the movement-sensitive channels are responsible for signalling the occurrence of movement; the channels at higher spatial frequencies give no information about temporal changes. These two systems of channels are compared to the Y- and X-cells respectively of the cat.

Actionable Cultural Understanding for Support to Tactical Operations (ACUSTO): Toward a New Methodological Template for Spatial Decision Support System

DTIC Science & Technology

2009-05-01

gangs. Important aspects of these are the concept of micro locations, or “set space” where gangs tend to locate ( Tita et al. 2005) and patterns of...spatial diffusion of gang activity (Cohen and Tita 1999, Tita and Cohen 2004). A particularly promising approach is the combination of concepts from...matches their social interaction ( Tita 2007, Tita and Ridgeway 2007). An illustration of the incorporation of insights from a spatial analysis into

A MS-lesion pattern discrimination plot based on geostatistics.

PubMed

Marschallinger, Robert; Schmidt, Paul; Hofmann, Peter; Zimmer, Claus; Atkinson, Peter M; Sellner, Johann; Trinka, Eugen; Mühlau, Mark

2016-03-01

A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.

[Assessment on ecological security spatial differences of west areas of Liaohe River based on GIS].

PubMed

Wang, Geng; Wu, Wei

2005-09-01

Ecological security assessment and early warning research have spatiality; non-linearity; randomicity, it is needed to deal with much spatial information. Spatial analysis and data management are advantages of GIS, it can define distribution trend and spatial relations of environmental factors, and show ecological security pattern graphically. The paper discusses the method of ecological security spatial differences of west areas of Liaohe River based on GIS and ecosystem non-health. First, studying on pressure-state-response (P-S-R) assessment indicators system, investigating in person and gathering information; Second, digitizing the river, applying fuzzy AHP to put weight, quantizing and calculating by fuzzy comparing; Last, establishing grid data-base; expounding spatial differences of ecological security by GIS Interpolate and Assembly.

Spatial patterns of development drive water use

USGS Publications Warehouse

Sanchez, G.M.; Smith, J.W.; Terando, Adam J.; Sun, G.; Meentemeyer, R.K.

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.

Spatial Patterns of Development Drive Water Use

NASA Astrophysics Data System (ADS)

Sanchez, G. M.; Smith, J. W.; Terando, A.; Sun, G.; Meentemeyer, R. K.

2018-03-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non-spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio-economic and environmental variables and two water use variables: a) domestic water use, and b) total development-related water use (a combination of public supply, domestic self-supply and industrial self-supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio-economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water-efficient land use planning.

Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

NASA Astrophysics Data System (ADS)

Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

2017-04-01

The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool for the analysis of global water security issues.

Dynamic Analysis and Research on Environmental Pollution in China from 1992 to 2014

NASA Astrophysics Data System (ADS)

Sun, Fei; Yuan, Peng; Li, Huiting; Zhang, Moli

2018-01-01

The regular pattern of development of the environmental pollution events was analyzed from the perspective of statistical analysis of pollution events in recent years. The Moran, s I and spatial center-of-gravity shift curve of China, s environmental emergencies were calculated by ARCGIS software. And the method is global spatial analysis and spatial center of gravity shift. The results showed that the trend of China, s environmental pollution events from 1992 to 2014 was the first dynamic growth and then gradually reduced. Environmental pollution events showed spatial aggregation distribution in 1992-1994, 2001-2006, 2008-2014, and the rest of year was a random distribution of space. There were two stages in China, s environmental pollution events: The transition to the southwest from 1992 to 2006 and the transition to the northeast from the year of 2006 to 2014.

Regional gradient analysis and spatial pattern of woody plant communities in Oregon forests.

Treesearch

J.L. Ohmann; T.A. Spies

1998-01-01

Knowledge of regional-scale patterns of ecological community structure, and of factors that control them, is largely conceptual. Regional- and local-scale factors associated with regional variation in community composition have not been quantified. We analyzed data on woody plant species abundance from 2443 field plots across natural and seminatural forests and...

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Mortality atlas of the main causes of death in Switzerland, 2008-2012.

PubMed

Chammartin, Frédérique; Probst-Hensch, Nicole; Utzinger, Jürg; Vounatsou, Penelope

2016-01-01

Analysis of the spatial distribution of mortality data is important for identification of high-risk areas, which in turn might guide prevention, and modify behaviour and health resources allocation. This study aimed to update the Swiss mortality atlas by analysing recent data using Bayesian statistical methods. We present average pattern for the major causes of death in Switzerland. We analysed Swiss mortality data from death certificates for the period 2008-2012. Bayesian conditional autoregressive models were employed to smooth the standardised mortality rates and assess average patterns. Additionally, we developed models for age- and gender-specific sub-groups that account for urbanisation and linguistic areas in order to assess their effects on the different sub-groups. We describe the spatial pattern of the major causes of death that occurred in Switzerland between 2008 and 2012, namely 4 cardiovascular diseases, 10 different kinds of cancer, 2 external causes of death, as well as chronic respiratory diseases, Alzheimer's disease, diabetes, influenza and pneumonia, and liver diseases. In-depth analysis of age- and gender-specific mortality rates revealed significant disparities between urbanisation and linguistic areas. We provide a contemporary overview of the spatial distribution of the main causes of death in Switzerland. Our estimates and maps can help future research to deepen our understanding of the spatial variation of major causes of death in Switzerland, which in turn is crucial for targeting preventive measures, changing behaviours and a more cost-effective allocation of health resources.

Fringe pattern demodulation with a two-frame digital phase-locked loop algorithm.

PubMed

Gdeisat, Munther A; Burton, David R; Lalor, Michael J

2002-09-10

A novel technique called a two-frame digital phase-locked loop for fringe pattern demodulation is presented. In this scheme, two fringe patterns with different spatial carrier frequencies are grabbed for an object. A digital phase-locked loop algorithm tracks and demodulates the phase difference between both fringe patterns by employing the wrapped phase components of one of the fringe patterns as a reference to demodulate the second fringe pattern. The desired phase information can be extracted from the demodulated phase difference. We tested the algorithm experimentally using real fringe patterns. The technique is shown to be suitable for noncontact measurement of objects with rapid surface variations, and it outperforms the Fourier fringe analysis technique in this aspect. Phase maps produced withthis algorithm are noisy in comparison with phase maps generated with the Fourier fringe analysis technique.

Sex and strategy use matters for pattern separation, adult neurogenesis, and immediate early gene expression in the hippocampus.

PubMed

Yagi, Shunya; Chow, Carmen; Lieblich, Stephanie E; Galea, Liisa A M

2016-01-01

Adult neurogenesis in the dentate gyrus (DG) plays a crucial role for pattern separation, and there are sex differences in the regulation of neurogenesis. Although sex differences, favoring males, in spatial navigation have been reported, it is not known whether there are sex differences in pattern separation. The current study was designed to determine whether there are sex differences in the ability for separating similar or distinct patterns, learning strategy choice, adult neurogenesis, and immediate early gene (IEG) expression in the DG in response to pattern separation training. Male and female Sprague-Dawley rats received a single injection of the DNA synthesis marker, bromodeoxyuridine (BrdU), and were tested for the ability of separating spatial patterns in a spatial pattern separation version of delayed nonmatching to place task using the eight-arm radial arm maze. Twenty-seven days following BrdU injection, rats received a probe trial to determine whether they were idiothetic or spatial strategy users. We found that male spatial strategy users outperformed female spatial strategy users only when separating similar, but not distinct, patterns. Furthermore, male spatial strategy users had greater neurogenesis in response to pattern separation training than all other groups. Interestingly, neurogenesis was positively correlated with performance on similar pattern trials during pattern separation in female spatial strategy users but negatively correlated with performance in male idiothetic strategy users. These results suggest that the survival of new neurons may play an important positive role for pattern separation of similar patterns in females. Furthermore, we found sex and strategy differences in IEG expression in the CA1 and CA3 regions in response to pattern separation. These findings emphasize the importance of studying biological sex on hippocampal function and neural plasticity. © 2015 Wiley Periodicals, Inc.

Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System.

PubMed

Roth, Zvi N

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream.

Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System

PubMed Central

Roth, Zvi N.

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream. PMID:27242455

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments.

PubMed

Krami, Loghman Khoda; Amiri, Fazel; Sefiyanian, Alireza; Shariff, Abdul Rashid B Mohamed; Tabatabaie, Tayebeh; Pradhan, Biswajeet

2013-12-01

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF(G)) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF(G) techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF(G) technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.

Spatial analysis improves the detection of early corneal nerve fiber loss in patients with recently diagnosed type 2 diabetes

PubMed Central

Winter, Karsten; Strom, Alexander; Zhivov, Andrey; Allgeier, Stephan; Papanas, Nikolaos; Ziegler, Iris; Brüggemann, Jutta; Ringel, Bernd; Peschel, Sabine; Köhler, Bernd; Stachs, Oliver; Guthoff, Rudolf F.; Roden, Michael

2017-01-01

Corneal confocal microscopy (CCM) has revealed reduced corneal nerve fiber (CNF) length and density (CNFL, CNFD) in patients with diabetes, but the spatial pattern of CNF loss has not been studied. We aimed to determine whether spatial analysis of the distribution of corneal nerve branching points (CNBPs) may contribute to improving the detection of early CNF loss. We hypothesized that early CNF decline follows a clustered rather than random distribution pattern of CNBPs. CCM, nerve conduction studies (NCS), and quantitative sensory testing (QST) were performed in a cross-sectional study including 86 patients recently diagnosed with type 2 diabetes and 47 control subjects. In addition to CNFL, CNFD, and branch density (CNBD), CNBPs were analyzed using spatial point pattern analysis (SPPA) including 10 indices and functional statistics. Compared to controls, patients with diabetes showed lower CNBP density and higher nearest neighbor distances, and all SPPA parameters indicated increased clustering of CNBPs (all P<0.05). SPPA parameters were abnormally increased >97.5th percentile of controls in up to 23.5% of patients. When combining an individual SPPA parameter with CNFL, ≥1 of 2 indices were >99th or <1st percentile of controls in 28.6% of patients compared to 2.1% of controls, while for the conventional CNFL/CNFD/CNBD combination the corresponding rates were 16.3% vs 2.1%. SPPA parameters correlated with CNFL and several NCS and QST indices in the controls (all P<0.001), whereas in patients with diabetes these correlations were markedly weaker or lost. In conclusion, SPPA reveals increased clustering of early CNF loss and substantially improves its detection when combined with a conventional CCM measure in patients with recently diagnosed type 2 diabetes. PMID:28296936

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

NASA Astrophysics Data System (ADS)

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.

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

Aquifer configuration and geostructural links control the groundwater quality in thin-bedded carbonate-siliciclastic alternations of the Hainich CZE, central Germany

NASA Astrophysics Data System (ADS)

Kohlhepp, Bernd; Lehmann, Robert; Seeber, Paul; Küsel, Kirsten; Trumbore, Susan E.; Totsche, Kai U.

2017-12-01

The quality of near-surface groundwater reservoirs is controlled, but also threatened, by manifold surface-subsurface interactions. Vulnerability studies typically evaluate the variable interplay of surface factors (land management, infiltration patterns) and subsurface factors (hydrostratigraphy, flow properties) in a thorough way, but disregard the resulting groundwater quality. Conversely, hydrogeochemical case studies that address the chemical evolution of groundwater often lack a comprehensive analysis of the structural buildup. In this study, we aim to reconstruct the actual spatial groundwater quality pattern from a synoptic analysis of the hydrostratigraphy, lithostratigraphy, pedology and land use in the Hainich Critical Zone Exploratory (Hainich CZE). This CZE represents a widely distributed yet scarcely described setting of thin-bedded mixed carbonate-siliciclastic strata in hillslope terrains. At the eastern Hainich low-mountain hillslope, bedrock is mainly formed by alternated marine sedimentary rocks of the Upper Muschelkalk (Middle Triassic) that partly host productive groundwater resources. Spatial patterns of the groundwater quality of a 5.4 km long well transect are derived by principal component analysis and hierarchical cluster analysis. Aquifer stratigraphy and geostructural links were deduced from lithological drill core analysis, mineralogical analysis, geophysical borehole logs and mapping data. Maps of preferential recharge zones and recharge potential were deduced from digital (soil) mapping, soil survey data and field measurements of soil hydraulic conductivities (Ks). By attributing spatially variable surface and subsurface conditions, we were able to reconstruct groundwater quality clusters that reflect the type of land management in their preferential recharge areas, aquifer hydraulic conditions and cross-formational exchange via caprock sinkholes or ascending flow. Generally, the aquifer configuration (spatial arrangement of strata, valley incision/outcrops) and related geostructural links (enhanced recharge areas, karst phenomena) control the role of surface factors (input quality and locations) vs. subsurface factors (water-rock interaction, cross-formational flow) for groundwater quality in the multi-layered aquifer system. Our investigation reveals general properties of alternating sequences in hillslope terrains that are prone to forming multi-layered aquifer systems. This synoptic analysis is fundamental and indispensable for a mechanistic understanding of ecological functioning, sustainable resource management and protection.

Virtual Human Analogs to Rodent Spatial Pattern Separation and Completion Memory Tasks

ERIC Educational Resources Information Center

Paleja, Meera; Girard, Todd A.; Christensen, Bruce K.

2011-01-01

Spatial pattern separation (SPS) and spatial pattern completion (SPC) have played an increasingly important role in computational and rodent literatures as processes underlying associative memory. SPS and SPC are complementary processes, allowing the formation of unique representations and the reconstruction of complete spatial environments based…

Formalized description and construction of semantic dictionary of graphic-text spatial relationship

NASA Astrophysics Data System (ADS)

Sun, Yizhong; Xue, Xiaolei; Zhao, Xiaoqin

2008-10-01

Graphic and text are two major elements in exhibiting of the results of urban planning and land administration. In combination, they convey the complex relationship resulting from spatial analysis and decision-making. Accurately interpreting and representing these relationships are important steps towards an intelligent GIS for urban planning. This paper employs concept-hierarchy-tree to formalize graphic-text relationships through a framework of spatial object lexicon, spatial relationship lexicon, restriction lexicon, applied pattern base, and word segmentation rule base. The methodology is further verified and shown effective on several urban planning archives.

Spatial Patterns of Forest Cover Loss in the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M.; Potapov, P.; Justice, C. O.

2013-12-01

Three groups of metrics of spatial patterns of forest cover loss were calculated for the Democratic Republic of Congo (DRC). While other studies had previously assessed landscape patterns in the Congo Basin, they had done so for small areas due to data limitations. The input data for this study, the Forets d;Afrique Central Evaluee par Teledetection(FACET), allowed the analysis to be performed at the national level. FACET is a landsat-scale dataset giving an unprecedented synoptic view of forest cover and forest cover loss for the DRC for three time periods: 2000, 2005 and 2010. The three groups of metrics evaluated the following spatial characteristics of forest cover loss for the same standard 1.5km unit of area: proportions of typologies of forest lost, forest fragmentation and proximity of forest loss patches from other land cover types. Results indicate that there are several different typologies of forest cover loss in the DRC, and offer quantitative explanations of these differences, providing a valuable locally-relevant tool for land use planning, available at the national level. Spatial patterns of forest cover loss highlight differences between areas of high primary forest loss due to agriculture conversion in frontier deforestation, such as in the east of the country, areas of equivalent primary and secondary forest loss emanating from the rural complex and areas of variable proportions of primary and secondary forest loss but important ecological repercussions of forest fragmentation due to isolated, but systematic forest perforations. Typologies of spatial patterns of forest cover loss are presented as well as their correlated drivers, and ecological, conservation and land use planning considerations are discussed.

City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France.

PubMed

Padilla, Cindy M; Kihal-Talantikit, Wahida; Vieira, Verónica M; Deguen, Séverine

2016-06-22

Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease-a leading cause of infant mortality.

City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France

PubMed Central

Padilla, Cindy M.; Kihal-Talantikit, Wahida; Vieira, Verónica M.; Deguen, Séverine

2016-01-01

Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease—a leading cause of infant mortality. PMID:27338439

Integrating Remote Sensing Data with Directional Two- Dimensional Wavelet Analysis and Open Geospatial Techniques for Efficient Disaster Monitoring and Management.

PubMed

Lin, Yun-Bin; Lin, Yu-Pin; Deng, Dong-Po; Chen, Kuan-Wei

2008-02-19

In Taiwan, earthquakes have long been recognized as a major cause oflandslides that are wide spread by floods brought by typhoons followed. Distinguishingbetween landslide spatial patterns in different disturbance regimes is fundamental fordisaster monitoring, management, and land-cover restoration. To circumscribe landslides,this study adopts the normalized difference vegetation index (NDVI), which can bedetermined by simply applying mathematical operations of near-infrared and visible-redspectral data immediately after remotely sensed data is acquired. In real-time disastermonitoring, the NDVI is more effective than using land-cover classifications generatedfrom remotely sensed data as land-cover classification tasks are extremely time consuming.Directional two-dimensional (2D) wavelet analysis has an advantage over traditionalspectrum analysis in that it determines localized variations along a specific direction whenidentifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series ofsolutions developed based on Open Geospatial Consortium specifications that can beapplied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2Dwavelet analysis of real-time NDVI images to effectively identify landslide patterns andshare resulting patterns via open geospatial techniques. As a case study, this study analyzedNDVI images derived from SPOT HRV images before and after the ChiChi earthquake(7.3 on the Richter scale) that hit the Chenyulan basin in Taiwan, as well as images aftertwo large typhoons (Xangsane and Toraji) to delineate the spatial patterns of landslidescaused by major disturbances. Disturbed spatial patterns of landslides that followed theseevents were successfully delineated using 2D wavelet analysis, and results of patternrecognitions of landslides were distributed simultaneously to other agents using geographymarkup language. Real-time information allows successive platforms (agents) to work withlocal geospatial data for disaster management. Furthermore, the proposed is suitable fordetecting landslides in various regions on continental, regional, and local scales usingremotely sensed data in various resolutions derived from SPOT HRV, IKONOS, andQuickBird multispectral images.

Exploratory Temporal and Spatial Analysis of Myocardial Infarction Hospitalizations in Calgary, Canada

PubMed Central

Liu, Xiaoxiao; Bertazzon, Stefania

2017-01-01

Spatial and temporal analyses are critical to understand the pattern of myocardial infarction (MI) hospitalizations over space and time, and to identify their underlying determinants. In this paper, we analyze MI hospitalizations in Calgary from 2004 to 2013, stratified by age and gender. First, a seasonal trend decomposition analyzes the seasonality; then a linear regression models the trend component. Moran’s I and hot spot analyses explore the spatial pattern. Though exploratory, results show that most age and gender groups feature a statistically significant decline over the 10 years, consistent with previous studies in Canada. Decline rates vary across ages and genders, with the slowest decline observed for younger males. Each gender exhibits a seasonal pattern with peaks in both winter and summer. Spatially, MI hot spots are identified in older communities, and in socioeconomically and environmentally disadvantaged communities. In the older communities, higher MI rates appear to be more highly associated with demographics. Conversely, worse air quality appears to be locally associated with higher MI incidence in younger age groups. The study helps identify areas of concern, where MI hot spots are identified for younger age groups, suggesting the need for localized public health policies to target local risk factors. PMID:29232910

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

Climatic Redistribution of Canada's Water Resources (CROCWR): An analysis of spatial and temporal hydrological trends and patterns in western Canada

NASA Astrophysics Data System (ADS)

Bawden, A. J.; Burn, D. H.; Prowse, T. D.

2012-12-01

Climate variability and change can have profound impacts on the hydrologic regime of a watershed. These effects are likely to be especially severe in regions particularly sensitive to changes in climate, such as the Canadian north, or when there are other stresses on the hydrologic regime, such as may occur when there are large withdrawals from, or land-use changes within, a watershed. A recent report of the Intergovernmental Panel on Climate Change (IPCC) stressed that future climate is likely to accelerate the hydrologic cycle and hence may affect water security in certain locations. For some regions, this will mean enhanced access to water resources, but because the effects will not be spatially uniform, other regions will experience reduced access. Understanding these patterns is critical for water managers and government agencies in western Canada - an area of highly contrasting hydroclimatic regimes and overlapping water-use and jurisdictional borders - as adapting to climate change may require reconsideration of inter-regional transfers and revised allocation of water resources to competing industrial sectors, including agriculture, hydroelectric production, and oil and gas. This research involves the detection and examination of spatial and temporal streamflow trends in western Canadian rivers as a response to changing climatic factors, including temperature, precipitation, snowmelt, and the synoptic patterns controlling these drivers. The study area, known as the CROCWR region, extends from the Pacific coast of British Columbia as far east as the Saskatchewan-Manitoba border and from the Canada-United States international border through a large portion of the Northwest Territories. This analysis examines hydrologic trends in monthly and annual streamflow for a collection of 34 hydrometric gauging stations believed to adequately represent the overall effects of climate variability and change on flows in western Canada by means of the Mann-Kendall non-parametric trend test. Large-scale spatial patterns are determined through examination of trends and contrasts between upper and lower reaches of individual sub-basins, as well as via analysis of streamflow redistributions within the CROCWR region as an entirety (i.e. north, south, east and/or west-moving patterns). Results are used to predict future implications of hydroclimatic variability and change on western Canada's water resources and recommend measures to be taken by water managers in response to these changes. This research is part of a larger hydroclimatic study that includes an analysis of the climatic drivers contributing to shifting flow regimes in western Canada as well as a study of the controlling synoptic patterns and teleconnections associated with changes in these driving forces.

The combined effects of exogenous and endogenous variability on the spatial distribution of ant communities in a forested ecosystem (Hymenoptera: Formicidae).

PubMed

Yitbarek, Senay; Vandermeer, John H; Allen, David

2011-10-01

Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Quantifying spatial and temporal trends in beach-dune volumetric changes using spatial statistics

NASA Astrophysics Data System (ADS)

Eamer, Jordan B. R.; Walker, Ian J.

2013-06-01

Spatial statistics are generally underutilized in coastal geomorphology, despite offering great potential for identifying and quantifying spatial-temporal trends in landscape morphodynamics. In particular, local Moran's Ii provides a statistical framework for detecting clusters of significant change in an attribute (e.g., surface erosion or deposition) and quantifying how this changes over space and time. This study analyzes and interprets spatial-temporal patterns in sediment volume changes in a beach-foredune-transgressive dune complex following removal of invasive marram grass (Ammophila spp.). Results are derived by detecting significant changes in post-removal repeat DEMs derived from topographic surveys and airborne LiDAR. The study site was separated into discrete, linked geomorphic units (beach, foredune, transgressive dune complex) to facilitate sub-landscape scale analysis of volumetric change and sediment budget responses. Difference surfaces derived from a pixel-subtraction algorithm between interval DEMs and the LiDAR baseline DEM were filtered using the local Moran's Ii method and two different spatial weights (1.5 and 5 m) to detect statistically significant change. Moran's Ii results were compared with those derived from a more spatially uniform statistical method that uses a simpler student's t distribution threshold for change detection. Morphodynamic patterns and volumetric estimates were similar between the uniform geostatistical method and Moran's Ii at a spatial weight of 5 m while the smaller spatial weight (1.5 m) consistently indicated volumetric changes of less magnitude. The larger 5 m spatial weight was most representative of broader site morphodynamics and spatial patterns while the smaller spatial weight provided volumetric changes consistent with field observations. All methods showed foredune deflation immediately following removal with increased sediment volumes into the spring via deposition at the crest and on lobes in the lee, despite erosion on the stoss slope and dune toe. Generally, the foredune became wider by landward extension and the seaward slope recovered from erosion to a similar height and form to that of pre-restoration despite remaining essentially free of vegetation.

EVOLUTION OF NEAR-SURFACE FLOWS INFERRED FROM HIGH-RESOLUTION RING-DIAGRAM ANALYSIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bogart, Richard S.; Baldner, Charles S.; Basu, Sarbani

2015-07-10

Ring-diagram analysis of acoustic waves observed at the photosphere can provide a relatively robust determination of the sub-surface flows at a particular time under a particular region. The depth of penetration of the waves is related to the size of the region, hence the depth extent of the measured flows is inversely proportional to the spatial resolution. Most ring-diagram analysis has focused on regions of extent ∼15° (180 Mm) or more in order to provide reasonable mode sets for inversions. Helioseismic and Magnetic Imager (HMI) data analysis also provides a set of ring fit parameters on a scale three timesmore » smaller. These provide flow estimates for the outer 1% (7 Mm) of the Sun only, with very limited depth resolution, but with spatial resolution adequate to map structures potentially associated with the belts and regions of magnetic activity. There are a number of systematic effects affecting the determination of flows from a local helioseismic analysis of regions over different parts of the observable disk, and not all of them are well understood. In this study we characterize those systematic effects with higher spatial resolution so that they may be accounted for more effectively in mapping the temporal and spatial evolution of the flows. Leaving open the question of the mean structure of the global meridional circulation and the differential rotation, we describe the near-surface flow anomalies in time and latitude corresponding to the torsional oscillation pattern in differential rotation and analogous patterns in the meridional cell structure as observed by the Solar Dynamics Observatory/HMI.« less

What are we ‘tweeting’ about obesity? Mapping tweets with Topic Modeling and Geographic Information System

PubMed Central

Ghosh, Debarchana (Debs); Guha, Rajarshi

2014-01-01

Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are ‘food deserts’, ‘fast food’, and ‘childhood obesity’. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as ‘childhood obesity and schools’, ‘obesity prevention’, and ‘obesity and food habits’ are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets. PMID:25126022

What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System.

PubMed

Ghosh, Debarchana Debs; Guha, Rajarshi

2013-01-01

Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are 'food deserts', 'fast food', and 'childhood obesity'. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as 'childhood obesity and schools', 'obesity prevention', and 'obesity and food habits' are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets.

A Secondary Spatial Analysis of Gun Violence near Boston Schools: a Public Health Approach.

PubMed

Barboza, Gia

2018-06-01

School neighborhood violence continues to be a major public health problem among urban students. A large body of research addresses violence at school; however, fewer studies have explored concentrations of violence in areas proximal to schools. This study aimed to quantify the concentration of shootings near schools to elucidate the place-based dynamics that may be focal points for violence prevention. Geocoded databases of shooting and school locations were used to examine locational patterns of firearm shootings and elementary, middle, and high schools in Boston, Massachusetts. Analyses utilized spatial statistics for point pattern data including distance matrix and K function methodology to quantify the degree of spatial dependence of shootings around schools. Results suggested that between 2012 and 2015, there were 678 shooting incidents in Boston; the average density was 5.1 per square kilometer. The nearest neighbor index (NNI = 0.335 km, p < .001, O = 0.95 km, E = 0.28 km) and G function analysis revealed a clustered pattern of gun shooting incidents indicative of a spatially non-random process. The mean and median distance from any school to the nearest shooting location was 0.35 and 0.33 km, respectively. A majority (56%, 74/133) of schools in Boston had at least one shooting incident within 400 m, a distance that would take about 5 min to walk if traveling by foot. The bivariate K function indicated that a significantly greater number of shootings were clustered within short distances from schools than would be expected under a null hypothesis of no spatial dependence. Implications for students attending schools in racially homogenous neighborhoods across all income levels are discussed.

Satellite observations for describing fire patterns and climate-related fire drivers in the Brazilian savannas

NASA Astrophysics Data System (ADS)

Verola Mataveli, Guilherme Augusto; Siqueira Silva, Maria Elisa; Pereira, Gabriel; da Silva Cardozo, Francielle; Shinji Kawakubo, Fernando; Bertani, Gabriel; Cezar Costa, Julio; de Cássia Ramos, Raquel; Valéria da Silva, Viviane

2018-01-01

In the Brazilian savannas (Cerrado biome) fires are natural and a tool for shifting land use; therefore, temporal and spatial patterns result from the interaction of climate, vegetation condition and human activities. Moreover, orbital sensors are the most effective approach to establish patterns in the biome. We aimed to characterize fire, precipitation and vegetation condition regimes and to establish spatial patterns of fire occurrence and their correlation with precipitation and vegetation condition in the Cerrado. The Cerrado was first and second biome for the occurrence of burned areas (BA) and hotspots, respectively. Occurrences are higher during the dry season and in the savanna land use. Hotspots and BA tend to decrease, and concentrate in the north, but more intense hotspots are not necessarily located where concentration is higher. Spatial analysis showed that averaged and summed values can hide patterns, such as for precipitation, which has the lowest average in August, but minimum precipitation in August was found in 7 % of the Cerrado. Usually, there is a 2-3-month lag between minimum precipitation and maximum hotspots and BA, while minimum VCI and maximum hotspots and BA occur in the same month. Hotspots and BA are better correlated with VCI than precipitation, qualifying VCI as an indicator of the susceptibility of vegetation to ignition.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

PubMed

Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide

2017-07-01

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Brazilian spatial dynamics in the long term (1872-2000): ``path dependency'' or ``reversal of fortune''?

NASA Astrophysics Data System (ADS)

Monasterio, Leonardo Monteiro

2010-03-01

This paper analyzes the spatial dynamics of Brazilian regional inequalities between 1872 and 2000 using contemporary tools. The first part of the paper provides new estimates of income per capita in 1872 by municipality using census and electoral information on income by occupation. The level of analysis is the Minimum Comparable Areas 1872-2000 developed by Reis et al. (Áreas mínimas comparáveis para os períodos intercensitários de 1872 a 2000, 2007). These areas are the least aggregation of adjacent municipalities required to allow consistent geographic area comparisons between census years. In the second section of the paper, Exploratory Spatial Data Analysis, Markov chains and stochastic kernel techniques (spatially conditioned) are applied to the dataset. The results suggest that, in broad terms, the spatial pattern of income distribution in Brazil during that period of time has remained stable.

Basic Characteristics and Spatial Patterns of Pseudo-Settlements--Taking Dalian as An Example.

PubMed

Gao, Jiaji; Zhang, Yingjia; Li, Xueming

2016-01-20

A person's living behavior patterns are closely related to three types of settlements: real-life settlements, imagined settlements, and pseudo-settlements. The term "pseudo-settlement" (PS) refers to the places that are selectively recorded and represented after the mass media chose and restructure the residence information. As the mass media rapidly develops and people's way of obtaining information gradually change, PS has already become one of the main ways for people to recognize and understand real-life settlements, as well as describe their impressions of imagined settlements. PS also has a profound impact on tourism, employment, investment, migration, real estate development, etc. Thus, the study of PSs has important theoretical and practical significance. This paper proposes to put forward residential quarters where the mass media is displayed as the object of study and establishes the pseudo-settlement index system of Dalian in and elaborate analysis of the concept of PSs. From three aspects, including pseudo-buildings, pseudo-districts and pseudo-culture, this paper uses the ArcGIS 10.0 kernel density (spacial analyst) to analyze and interpret the basic characteristics and spatial patterns of 14 elements of the PS in Dalian. Through systemic clustering analysis, it identifies eight major types of PSs in Dalian. Then it systematically elaborates current situations and characteristics of the spatial pattern of PSs in Dalian, namely: regionally concentrated, widely scattered and blank spaces without pseudo-settlements. Finally, this paper discusses the mechanism of formation of PSs in Dalian.

a Multidisciplinary Analytical Framework for Studying Active Mobility Patterns

NASA Astrophysics Data System (ADS)

Orellana, D.; Hermida, C.; Osorio, P.

2016-06-01

Intermediate cities are urged to change and adapt their mobility systems from a high energy-demanding motorized model to a sustainable low-motorized model. In order to accomplish such a model, city administrations need to better understand active mobility patterns and their links to socio-demographic and cultural aspects of the population. During the last decade, researchers have demonstrated the potential of geo-location technologies and mobile devices to gather massive amounts of data for mobility studies. However, the analysis and interpretation of this data has been carried out by specialized research groups with relatively narrow approaches from different disciplines. Consequently, broader questions remain less explored, mainly those relating to spatial behaviour of individuals and populations with their geographic environment and the motivations and perceptions shaping such behaviour. Understanding sustainable mobility and exploring new research paths require an interdisciplinary approach given the complex nature of mobility systems and their social, economic and environmental impacts. Here, we introduce the elements for a multidisciplinary analytical framework for studying active mobility patterns comprised of three components: a) Methodological, b) Behavioural, and c) Perceptual. We demonstrate the applicability of the framework by analysing mobility patterns of cyclists and pedestrians in an intermediate city integrating a range of techniques, including: GPS tracking, spatial analysis, auto-ethnography, and perceptual mapping. The results demonstrated the existence of non-evident spatial behaviours and how perceptual features affect mobility. This knowledge is useful for developing policies and practices for sustainable mobility planning.

Basic Characteristics and Spatial Patterns of Pseudo-Settlements—Taking Dalian as An Example

PubMed Central

Gao, Jiaji; Zhang, Yingjia; Li, Xueming

2016-01-01

A person’s living behavior patterns are closely related to three types of settlements: real-life settlements, imagined settlements, and pseudo-settlements. The term “pseudo-settlement” (PS) refers to the places that are selectively recorded and represented after the mass media chose and restructure the residence information. As the mass media rapidly develops and people’s way of obtaining information gradually change, PS has already become one of the main ways for people to recognize and understand real-life settlements, as well as describe their impressions of imagined settlements. PS also has a profound impact on tourism, employment, investment, migration, real estate development, etc. Thus, the study of PSs has important theoretical and practical significance. This paper proposes to put forward residential quarters where the mass media is displayed as the object of study and establishes the pseudo-settlement index system of Dalian in and elaborate analysis of the concept of PSs. From three aspects, including pseudo-buildings, pseudo-districts and pseudo-culture, this paper uses the ArcGIS 10.0 kernel density (spacial analyst) to analyze and interpret the basic characteristics and spatial patterns of 14 elements of the PS in Dalian. Through systemic clustering analysis, it identifies eight major types of PSs in Dalian. Then it systematically elaborates current situations and characteristics of the spatial pattern of PSs in Dalian, namely: regionally concentrated, widely scattered and blank spaces without pseudo-settlements. Finally, this paper discusses the mechanism of formation of PSs in Dalian. PMID:26805859

Spatial Pattern of Standing Timber Value across the Brazilian Amazon

PubMed Central

Ahmed, Sadia E.; Ewers, Robert M.

2012-01-01

The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520

Spatial Analysis of Hemorrhagic Fever with Renal Syndrome in Zibo City, China, 2009–2012

PubMed Central

Wang, Ling; Yang, Shuxia; Zhang, Ling; Cao, Haixia; Zhang, Yan; Hu, Haodong; Zhai, Shenyong

2013-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, where human cases account for 90% of the total global cases. Zibo City is one of the most serious affected areas in Shandong Province China with the HFRS incidence increasing sharply from 2009 to 2012. However, the hotspots of HFRS in Zibo remained unclear. Thus, a spatial analysis was conducted with the aim to explore the spatial, spatial-temporal and seasonal patterns of HFRS in Zibo from 2009 to 2012, and to provide guidance for formulating regional prevention and control strategies. Methods The study was based on the reported cases of HFRS from the National Notifiable Disease Surveillance System. Annualized incidence maps and seasonal incidence maps were produced to analyze the spatial and seasonal distribution of HFRS in Zibo City. Then spatial scan statistics and space-time scan statistics were conducted to identify clusters of HFRS. Results There were 200 cases reported in Zibo City during the 4-year study period. One most likely cluster and one secondary cluster for high incidence of HFRS were identified by the space-time analysis. And the most likely cluster was found to exist at Yiyuan County in October to December 2012. The human infections in the fall and winter reflected a seasonal characteristic pattern of Hantaan virus (HTNV) transmission. The secondary cluster was detected at the center of Zibo in May to June 2009, presenting a seasonal characteristic of Seoul virus (SEOV) transmission. Conclusion To control and prevent HFRS in Zibo city, the comprehensive preventive strategy should be implemented in the southern areas of Zibo in autumn and in the northern areas of Zibo in spring. PMID:23840719

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

DOE PAGES

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...

2017-06-18

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

Fractal analysis of multiscale spatial autocorrelation among point data

USGS Publications Warehouse

De Cola, L.

1991-01-01

The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author

Hydrology Affects Environmental and Spatial Structuring of Microalgal Metacommunities in Tropical Pacific Coast Wetlands.

PubMed

Rojo, Carmen; Mesquita-Joanes, Francesc; Monrós, Juan S; Armengol, Javier; Sasa, Mahmood; Bonilla, Fabián; Rueda, Ricardo; Benavent-Corai, José; Piculo, Rubén; Segura, M Matilde

2016-01-01

The alternating climate between wet and dry periods has important effects on the hydrology and therefore on niche-based processes of water bodies in tropical areas. Additionally, assemblages of microorganism can show spatial patterns, in the form of a distance decay relationship due to their size or life form. We aimed to test spatial and environmental effects, modulated by a seasonal flooding climatic pattern, on the distribution of microalgae in 30 wetlands of a tropical dry forest region: the Pacific coast of Costa Rica and Nicaragua. Three surveys were conducted corresponding to the beginning, the highest peak, and the end of the hydrological year during the wet season, and species abundance and composition of planktonic and benthic microalgae was determined. Variation partitioning analysis (as explained by spatial distance or environmental factors) was applied to each seasonal dataset by means of partial redundancy analysis. Our results show that microalgal assemblages were structured by spatial and environmental factors depending on the hydrological period of the year. At the onset of hydroperiod and during flooding, neutral effects dominated community dynamics, but niche-based local effects resulted in more structured algal communities at the final periods of desiccating water bodies. Results suggest that climate-mediated effects on hydrology can influence the relative role of spatial and environmental factors on metacommunities of microalgae. Such variability needs to be accounted in order to describe accurately community dynamics in tropical coastal wetlands.

Hydrology Affects Environmental and Spatial Structuring of Microalgal Metacommunities in Tropical Pacific Coast Wetlands

PubMed Central

Rojo, Carmen; Mesquita-Joanes, Francesc; Monrós, Juan S.; Armengol, Javier; Sasa, Mahmood; Bonilla, Fabián; Rueda, Ricardo; Benavent-Corai, José; Piculo, Rubén; Segura, M. Matilde

2016-01-01

The alternating climate between wet and dry periods has important effects on the hydrology and therefore on niche-based processes of water bodies in tropical areas. Additionally, assemblages of microorganism can show spatial patterns, in the form of a distance decay relationship due to their size or life form. We aimed to test spatial and environmental effects, modulated by a seasonal flooding climatic pattern, on the distribution of microalgae in 30 wetlands of a tropical dry forest region: the Pacific coast of Costa Rica and Nicaragua. Three surveys were conducted corresponding to the beginning, the highest peak, and the end of the hydrological year during the wet season, and species abundance and composition of planktonic and benthic microalgae was determined. Variation partitioning analysis (as explained by spatial distance or environmental factors) was applied to each seasonal dataset by means of partial redundancy analysis. Our results show that microalgal assemblages were structured by spatial and environmental factors depending on the hydrological period of the year. At the onset of hydroperiod and during flooding, neutral effects dominated community dynamics, but niche-based local effects resulted in more structured algal communities at the final periods of desiccating water bodies. Results suggest that climate-mediated effects on hydrology can influence the relative role of spatial and environmental factors on metacommunities of microalgae. Such variability needs to be accounted in order to describe accurately community dynamics in tropical coastal wetlands. PMID:26900916

Spatial analysis on human brucellosis incidence in mainland China: 2004–2010

PubMed Central

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 <0.01), which persisted during the 7-year study period. High-risk counties were centred in the Inner Mongolia Autonomous Region and other Northern provinces (ie, Hebei, Shanxi, Jilin and Heilongjiang provinces) around the border with the Inner Mongolia Autonomous Region where animal husbandry was highly developed. The number of high-risk counties increased from 25 in 2004 to 54 in 2010. Conclusions ESDA methods and the EB smoothing technique can assist public health officials in identifying high-risk areas. Allocating more resources to high-risk areas is an effective way to reduce human brucellosis incidence. PMID:24713215

The spatial epidemiology of trauma: the potential of geographic information science to organize data and reveal patterns of injury and services

PubMed Central

Schuurman, Nadine; Hameed, S. Morad; Fiedler, Robert; Bell, Nathaniel; Simons, Richard K.

2008-01-01

Despite important advances in the prevention and treatment of trauma, preventable injuries continue to impact the lives of millions of people. Motor vehicle collisions and violence claim close to 3 million lives each year worldwide. Public health agencies have promoted the need for systematic and ongoing surveillance as a foundation for successful injury control. Surveillance has been used to quantify the incidence of injury for the prioritization of further research, monitor trends over time, identify new injury patterns, and plan and evaluate prevention and intervention efforts. Advances in capability to handle spatial data and substantial increases in computing power have positioned geographic information science (GIS) as a potentially important tool for health surveillance and the spatial organization of health care, and for informing prevention and acute care interventions. Two themes emerge in the trauma literature with respect to GIS theory and techniques: identifying determinants associated with the risk of trauma to guide injury prevention efforts and evaluating the spatial organization and accessibility of acute trauma care systems. We review the current literature on trauma and GIS research and provide examples of the importance of accounting for spatial scale when using spatial analysis for surveillance. The examples illustrate the effect of scale on incident analysis, the geographic variation of major injury across British Columbia's health service delivery areas (HSDAs) and the rates of variation of injury within individual HSDAs. PMID:18841227

Influences of land use on leaf breakdown in Southern Appalachian headwater streams: a multiple-scale analysis

Treesearch

R.A. Sponseller; E.F. Benfield

2001-01-01

Stream ecosystems can be strongly influenced by land use within watersheds. The extent of this influence may depend on the spatial distribution of developed land and the scale at which it is evaluated. Effects of land-cover patterns on leaf breakdown were studied in 8 Southern Appalachian headwater streams. Using a GIS, land cover was evaluated at several spatial...

Multilocus sequence analysis of Thermoanaerobacter isolates reveals recombining, but differentiated, populations from geothermal springs of the Uzon Caldera, Kamchatka, Russia

PubMed Central

Wagner, Isaac D.; Varghese, Litty B.; Hemme, Christopher L.; Wiegel, Juergen

2013-01-01

Thermal environments have island-like characteristics and provide a unique opportunity to study population structure and diversity patterns of microbial taxa inhabiting these sites. Strains having ≥98% 16S rRNA gene sequence similarity to the obligately anaerobic Firmicutes Thermoanaerobacter uzonensis were isolated from seven geothermal springs, separated by up to 1600 m, within the Uzon Caldera (Kamchatka, Russian Far East). The intraspecies variation and spatial patterns of diversity for this taxon were assessed by multilocus sequence analysis (MLSA) of 106 strains. Analysis of eight protein-coding loci (gyrB, lepA, leuS, pyrG, recA, recG, rplB, and rpoB) revealed that all loci were polymorphic and that nucleotide substitutions were mostly synonymous. There were 148 variable nucleotide sites across 8003 bp concatenates of the protein-coding loci. While pairwise FST values indicated a small but significant level of genetic differentiation between most subpopulations, there was a negligible relationship between genetic divergence and spatial separation. Strains with the same allelic profile were only isolated from the same hot spring, occasionally from consecutive years, and single locus variant (SLV) sequence types were usually derived from the same spring. While recombination occurred, there was an “epidemic” population structure in which a particular T. uzonensis sequence type rose in frequency relative to the rest of the population. These results demonstrate spatial diversity patterns for an anaerobic bacterial species in a relative small geographic location and reinforce the view that terrestrial geothermal springs are excellent places to look for biogeographic diversity patterns regardless of the involved distances. PMID:23801987

The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.

2015-12-01

Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

Spatial patterns of recreational impact on experimental campsites

Treesearch

David N. Cole; Christopher A. Monz

2004-01-01

Management of camping impacts in protected areas worldwide is limited by inadequate understanding of spatial patterns of impact and attention to spatial management strategies. Spatial patterns of campsite impact were studied in two subalpine plant communities in the Wind River Mountains, Wyoming, USA (a forest and a meadow). Response to chronic disturbance and recovery...

Surface NO2 fields derived from joint use of OMI and GOME-2A observations with EMEP model output

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Svendby, Tove; Stebel, Kerstin

2016-04-01

Nitrogen dioxide (NO2) is one of the most prominent air pollutants. Emitted primarily by transport and industry, NO2 has a major impact on health and economy. In contrast to the very sparse network of air quality monitoring stations, satellite data of NO2 is ubiquitous and allows for quantifying the NO2 levels worldwide. However, one drawback of satellite-derived NO2 products is that they provide solely an estimate of the entire tropospheric column, whereas what is generally needed for air quality applications are the concentrations of NO2 near the surface. Here we derive surface NO2 concentration fields from OMI and GOME-2A tropospheric column products using the EMEP chemical transport model as auxiliary information. The model is used for providing information of the boundary layer contribution to the total tropospheric column. For preparation of deriving the surface product, a comprehensive model-based analysis of the spatial and temporal patterns of the NO2 surface-to-column ratio in Europe was carried out for the year 2011. The results from this analysis indicate that the spatial patterns of the surface-to-column ratio vary only slightly. While the highest ratio values can be found in some shipping lanes, the spatial variability of the ratio in some of the most polluted areas of Europe is not very high. Some but not all urban agglomeration shows high ratio values. Focusing on the temporal behavior, the analysis showed that the European-wide average ratio varies throughout the year. The surface-to-column ratio increases from January all the way through April when it reaches its maximum, then decreases relatively rapidly to average levels and then stays mostly constant throughout the summer. The minimum ratio is observed in December. The knowledge gained from analyzing the spatial and temporal patterns of the surface-to-column ratio was then used to produce surface NO2 products from the daily NO2 data for OMI and GOME-2A. This was carried out using two methods, namely using 1) hourly surface-to-column ratio at the time of the satellite overpass as well as 2) using annual average ratios thus eliminating the temporal variability and focusing solely on the spatial patterns. A validation of the resulting surface NO2 fields was performed using station observations of NO2 as provided by the Airbase database maintained by the European Environment Agency. First results indicate that the methodology is capable of producing surface concentration fields that reproduce the station-observed surface NO2 levels significantly better than the model surface fields as measured by the root mean squared error. The results also show that the spatial patterns of the surface-to-column ratio are more significant than its temporal variability. In addition to deriving satellite-based surface NO2, we further present initial results of a geostatistical methodology for downscaling satellite products of NO2 to spatial scales that are more relevant for applications in urban air quality. This is being carried out by applying area-to-point kriging techniques while using high-resolution (1-2 km spatial resolution) runs of a chemical transport model as a spatial proxy. In combination, these two techniques for deriving surface NO2 and spatially downscaling satellite-based NO2 fields have significant potential for improving satellite-based monitoring and mapping of regional and local-scale air pollution.

Retrospective 70 y-spatial analysis of repeated vine mortality patterns using ancient aerial time series, Pléiades images and multi-source spatial and field data

NASA Astrophysics Data System (ADS)

Vaudour, E.; Leclercq, L.; Gilliot, J. M.; Chaignon, B.

2017-06-01

For any wine estate, there is a need to demarcate homogeneous within-vineyard zones ('terroirs') so as to manage grape production, which depends on vine biological condition. Until now, the studies performing digital zoning of terroirs have relied on recent spatial data and scant attention has been paid to ancient geoinformation likely to retrace past biological condition of vines and especially occurrence of vine mortality. Is vine mortality characterized by recurrent and specific patterns and if so, are these patterns related to terroir units and/or past landuse? This study aimed at performing a historical and spatial tracing of vine mortality patterns using a long time-series of aerial survey images (1947-2010), in combination with recent data: soil apparent electrical conductivity EM38 measurements, very high resolution Pléiades satellite images, and a detailed field survey. Within a 6 ha-estate in the Southern Rhone Valley, landuse and planting history were retraced and the map of missing vines frequency was constructed from the whole time series including a 2015-Pléiades panchromatic band. Within-field terroir units were obtained from a support vector machine classifier computed on the spectral bands and NDVI of Pléiades images, EM38 data and morphometric data. Repeated spatial patterns of missing vines were highlighted throughout several plantings, uprootings, and vine replacements, and appeared to match some within-field terroir units, being explained by their specific soil characteristics, vine/soil management choices and the past landuse of the 1940s. Missing vines frequency was spatially correlated with topsoil CaCO3 content, and negatively correlated with topsoil iron, clay, total N, organic C contents and NDVI. A retrospective spatio-temporal assessment of terroir therefore brings a renewed focus on some key parameters for maintaining a sustainable grape production.

Natural habitats matter: Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic

NASA Astrophysics Data System (ADS)

Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel

2014-08-01

Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.

The spatial and temporal patterns of falciparum and vivax malaria in Perú: 1994–2006

PubMed Central

Chowell, Gerardo; Munayco, Cesar V; Escalante, Ananias A; McKenzie, F Ellis

2009-01-01

Background Malaria is the direct cause of approximately one million deaths worldwide each year, though it is both preventable and curable. Increasing the understanding of the transmission dynamics of falciparum and vivax malaria and their relationship could suggest improvements for malaria control efforts. Here the weekly number of malaria cases due to Plasmodium falciparum (1994–2006) and Plasmodium vivax (1999–2006) in Perú at different spatial scales in conjunction with associated demographic, geographic and climatological data are analysed. Methods Malaria periodicity patterns were analysed through wavelet spectral analysis, studied patterns of persistence as a function of community size and assessed spatial heterogeneity via the Lorenz curve and the summary Gini index. Results Wavelet time series analyses identified annual cycles in the incidence of both malaria species as the dominant pattern. However, significant spatial heterogeneity was observed across jungle, mountain and coastal regions with slightly higher levels of spatial heterogeneity for P. vivax than P. falciparum. While the incidence of P. falciparum has been declining in recent years across geographic regions, P. vivax incidence has remained relatively steady in jungle and mountain regions with a slight decline in coastal regions. Factors that may be contributing to this decline are discussed. The time series of both malaria species were significantly synchronized in coastal (ρ = 0.9, P < 0.0001) and jungle regions (ρ = 0.76, P < 0.0001) but not in mountain regions. Community size was significantly associated with malaria persistence due to both species in jungle regions, but not in coastal and mountain regions. Conclusion Overall, findings highlight the importance of highly refined spatial and temporal data on malaria incidence together with demographic and geographic information in improving the understanding of malaria persistence patterns associated with multiple malaria species in human populations, impact of interventions, detection of heterogeneity and generation of hypotheses. PMID:19558695

Temporal and spatial analysis of psittacosis in association with poultry farming in the Netherlands, 2000-2015.

PubMed

Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim

2017-07-26

Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.

Geostatistical analysis of allele presence patterns among American black bears in eastern North Carolina

USGS Publications Warehouse

Thompson, L.M.; Van Manen, F.T.; King, T.L.

2005-01-01

Highways are one of the leading causes of wildlife habitat fragmentation and may particularly affect wide-ranging species, such as American black bears (Ursus americanus). We initiated a research project in 2000 to determine potential effects of a 4-lane highway on black bear ecology in Washington County, North Carolina. The research design included a treatment area (highway construction) and a control area and a pre- and post-construction phase. We used data from the pre-construction phase to determine whether we could detect scale dependency or directionality among allele occurrence patterns using geostatistics. Detection of such patterns could provide a powerful tool to measure the effects of landscape fragmentation on gene flow. We sampled DNA from roots of black bear hair at 70 hair-sampling sites on each study area for 7 weeks during fall of 2000. We used microsatellite analysis based on 10 loci to determine unique multi-locus genotypes. We examined all alleles sampled at ???25 sites on each study area and mapped their presence or absence at each hair-sample site. We calculated semivariograms, which measure the strength of statistical correlation as a function of distance, and adjusted them for anisotropy to determine the maximum direction of spatial continuity. We then calculated the mean direction of spatial continuity for all examined alleles. The mean direction of allele frequency variation was 118.3?? (SE = 8.5) on the treatment area and 172.3?? (SE = 6.0) on the control area. Rayleigh's tests showed that these directions differed from random distributions (P = 0.028 and P < 0.001, respectively), indicating consistent directional patterns for the alleles we examined in each area. Despite the small spatial scale of our study (approximately 11,000 ha for each study area), we observed distinct and consistent patterns of allele occurrence, suggesting different directions of gene flow between the study areas. These directions seemed to coincide with the primary orientation of the best habitat areas. Furthermore, the patterns we observed suggest directions of potential source populations beyond the 2 study areas. Indeed, nearby areas classified as core black bear habitat exist in the directions indicated by our analysis. Geostatistical analysis of allele occurrence patterns may provide a useful technique to identify potential barriers to gene flow among bear populations.

Exploratory spatial data analysis of global MODIS active fire data

NASA Astrophysics Data System (ADS)

Oom, D.; Pereira, J. M. C.

2013-04-01

We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.5° resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p = 0.001, α = 0.05) for Moran's I indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.

Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore

USGS Publications Warehouse

Mikle, Nathaniel; Graves, Tabitha A.; Kovach, Ryan P.; Kendall, Katherine C.; Macleod, Amy C.

2016-01-01

Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral.

Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore

PubMed Central

Kovach, Ryan; Kendall, Katherine C.; Macleod, Amy C.

2016-01-01

Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral. PMID:27655768

Variation of ecosystem services and human activities: A case study in the Yanhe Watershed of China

NASA Astrophysics Data System (ADS)

Su, Chang-hong; Fu, Bo-Jie; He, Chan-Sheng; Lü, Yi-He

2012-10-01

The concept of 'ecosystem service' provides cohesive views on mechanisms by which nature contributes to human well-being. Fast social and economic development calls for research on interactions between human and natural systems. We took the Yanhe Watershed as our study area, and valued the variation of ecosystem services and human activities of 2000 and 2008. Five ecosystem services were selected i.e. net primary production (NPP), carbon sequestration and oxygen production (CSOP), water conservation, soil conservation, and grain production. Human activity was represented by a composite human activity index (HAI) that integrates human population density, farmland ratio, influence of residential sites and road network. Analysis results of the five ecosystem services and human activity (HAI) are as follows: (i) NPP, CSOP, water conservation, and soil conservation increased from 2000 to 2008, while grain production declined. HAI decreased from 2000 to 2008. Spatially, NPP, CSOP, and water conservation in 2000 and 2008 roughly demonstrated a pattern of decline from south to north, while grain production shows an endocentric increasing spatial pattern. Soil conservation showed a spatial pattern of high in the south and low in the north in 2000 and a different pattern of high in the west and low in the east in 2008 respectively. HAI is proportional to the administrative level and economic development. Variation of NPP/CSOP between 2000 and 2008 show an increasing spatial pattern from northwest to southeast. In contrast, the variation of soil conservation shows an increasing pattern from southeast to northwest. Variation of water conservation shows a fanning out decreasing pattern. Variation of grain production doesn't show conspicuous spatial pattern. (ii) Variation of water conservation and of soil conservation is significantly positively correlated at 0.01 level. Both variations of water conservation and soil conservation are negatively correlated with variation of HAI at 0.01 level. Variations of NPP/CSOP are negatively correlated with variations of soil conservation and grain production at 0.05 level. (iii) Strong tradeoffs exist between regulation services and provision service, while synergies exist within regulation services. Driving effect of human activities on ecosystem services and tradeoffs and synergies among ecosystem service are also discussed.

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

On species persistence-time distributions.

PubMed

Suweis, S; Bertuzzo, E; Mari, L; Rodriguez-Iturbe, I; Maritan, A; Rinaldo, A

2012-06-21

We present new theoretical and empirical results on the probability distributions of species persistence times in natural ecosystems. Persistence times, defined as the timespans occurring between species' colonization and local extinction in a given geographic region, are empirically estimated from local observations of species' presence/absence. A connected sampling problem is presented, generalized and solved analytically. Species persistence is shown to provide a direct connection with key spatial macroecological patterns like species-area and endemics-area relationships. Our empirical analysis pertains to two different ecosystems and taxa: a herbaceous plant community and a estuarine fish database. Despite the substantial differences in ecological interactions and spatial scales, we confirm earlier evidence on the general properties of the scaling of persistence times, including the predicted effects of the structure of the spatial interaction network. The framework tested here allows to investigate directly nature and extent of spatial effects in the context of ecosystem dynamics. The notable coherence between spatial and temporal macroecological patterns, theoretically derived and empirically verified, is suggested to underlie general features of the dynamic evolution of ecosystems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Brazilian Road Traffic Fatalities: A Spatial and Environmental Analysis

PubMed Central

de Andrade, Luciano; Vissoci, João Ricardo Nickenig; Rodrigues, Clarissa Garcia; Finato, Karen; Carvalho, Elias; Pietrobon, Ricardo; de Souza, Eniuce Menezes; Nihei, Oscar Kenji; Lynch, Catherine; de Barros Carvalho, Maria Dalva

2014-01-01

Background Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. Methods and Findings Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. Conclusions By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies. PMID:24498051

Activity in Human Auditory Cortex Represents Spatial Separation Between Concurrent Sounds.

PubMed

Shiell, Martha M; Hausfeld, Lars; Formisano, Elia

2018-05-23

The primary and posterior auditory cortex (AC) are known for their sensitivity to spatial information, but how this information is processed is not yet understood. AC that is sensitive to spatial manipulations is also modulated by the number of auditory streams present in a scene (Smith et al., 2010), suggesting that spatial and nonspatial cues are integrated for stream segregation. We reasoned that, if this is the case, then it is the distance between sounds rather than their absolute positions that is essential. To test this hypothesis, we measured human brain activity in response to spatially separated concurrent sounds with fMRI at 7 tesla in five men and five women. Stimuli were spatialized amplitude-modulated broadband noises recorded for each participant via in-ear microphones before scanning. Using a linear support vector machine classifier, we investigated whether sound location and/or location plus spatial separation between sounds could be decoded from the activity in Heschl's gyrus and the planum temporale. The classifier was successful only when comparing patterns associated with the conditions that had the largest difference in perceptual spatial separation. Our pattern of results suggests that the representation of spatial separation is not merely the combination of single locations, but rather is an independent feature of the auditory scene. SIGNIFICANCE STATEMENT Often, when we think of auditory spatial information, we think of where sounds are coming from-that is, the process of localization. However, this information can also be used in scene analysis, the process of grouping and segregating features of a soundwave into objects. Essentially, when sounds are further apart, they are more likely to be segregated into separate streams. Here, we provide evidence that activity in the human auditory cortex represents the spatial separation between sounds rather than their absolute locations, indicating that scene analysis and localization processes may be independent. Copyright © 2018 the authors 0270-6474/18/384977-08$15.00/0.

Adaptation of video game UVW mapping to 3D visualization of gene expression patterns

NASA Astrophysics Data System (ADS)

Vize, Peter D.; Gerth, Victor E.

2007-01-01

Analysis of gene expression patterns within an organism plays a critical role in associating genes with biological processes in both health and disease. During embryonic development the analysis and comparison of different gene expression patterns allows biologists to identify candidate genes that may regulate the formation of normal tissues and organs and to search for genes associated with congenital diseases. No two individual embryos, or organs, are exactly the same shape or size so comparing spatial gene expression in one embryo to that in another is difficult. We will present our efforts in comparing gene expression data collected using both volumetric and projection approaches. Volumetric data is highly accurate but difficult to process and compare. Projection methods use UV mapping to align texture maps to standardized spatial frameworks. This approach is less accurate but is very rapid and requires very little processing. We have built a database of over 180 3D models depicting gene expression patterns mapped onto the surface of spline based embryo models. Gene expression data in different models can easily be compared to determine common regions of activity. Visualization software, both Java and OpenGL optimized for viewing 3D gene expression data will also be demonstrated.

A Method to Categorize 2-Dimensional Patterns Using Statistics of Spatial Organization.

PubMed

López-Sauceda, Juan; Rueda-Contreras, Mara D

2017-01-01

We developed a measurement framework of spatial organization to categorize 2-dimensional patterns from 2 multiscalar biological architectures. We propose that underlying shapes of biological entities can be approached using the statistical concept of degrees of freedom, defining it through expansion of area variability in a pattern. To help scope this suggestion, we developed a mathematical argument recognizing the deep foundations of area variability in a polygonal pattern (spatial heterogeneity). This measure uses a parameter called eutacticity . Our measuring platform of spatial heterogeneity can assign particular ranges of distribution of spatial areas for 2 biological architectures: ecological patterns of Namibia fairy circles and epithelial sheets. The spatial organizations of our 2 analyzed biological architectures are demarcated by being in a particular position among spatial order and disorder. We suggest that this theoretical platform can give us some insights about the nature of shapes in biological systems to understand organizational constraints.

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

PubMed

Bai, Ou; Lin, Peter; Vorbach, Sherry; Li, Jiang; Furlani, Steve; Hallett, Mark

2007-12-01

To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training. Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

USGS Publications Warehouse

Wedding, L.M.; Christopher, L.A.; Pittman, S.J.; Friedlander, A.M.; Jorgensen, S.

2011-01-01

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change. ?? Inter-Research 2011.

Cross-taxon congruence and environmental conditions.

PubMed

Toranza, Carolina; Arim, Matías

2010-07-16

Diversity patterns of different taxa typically covary in space, a phenomenon called cross-taxon congruence. This pattern has been explained by the effect of one taxon diversity on taxon diversity, shared biogeographic histories of different taxa, and/or common responses to environmental conditions. A meta-analysis of the association between environment and diversity patterns found that in 83 out of 85 studies, more than 60% of the spatial variability in species richness was related to variables representing energy, water or their interaction. The role of the environment determining taxa diversity patterns leads us to hypothesize that this would explain the observed cross-taxon congruence. However, recent analyses reported the persistence of cross-taxon congruence when environmental effect was statistically removed. Here we evaluate this hypothesis, analyzing the cross-taxon congruence between birds and mammals in the Brazilian Cerrado, and assess the environmental role on the spatial covariation in diversity patterns. We found a positive association between avian and mammal richness and a positive latitudinal trend for both groups in the Brazilian Cerrado. Regression analyses indicated an effect of latitude, PET, and mean temperature over both biological groups. In addition, we show that NDVI was only associated with avian diversity; while the annual relative humidity, was only correlated with mammal diversity. We determined the environmental effects on diversity in a path analysis that accounted for 73% and 76% of the spatial variation in avian and mammal richness. However, an association between avian and mammal diversity remains significant. Indeed, the importance of this link between bird and mammal diversity was also supported by a significant association between birds and mammal spatial autoregressive model residuals. Our study corroborates the main role of environmental conditions on diversity patterns, but suggests that other important mechanisms, which have not been properly evaluated, are involved in the observed cross-taxon congruence. The approaches introduced here indicate that the prevalence of a significant association among taxa, after considering the environmental determinant, could indicate both the need to incorporate additional processes (e.g. biogeographic and evolutionary history or trophic interactions) and/or the existence of a shared trend in detection biases among taxa and regions.

Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006.

PubMed

Liu, Chunxiao; Liu, Qiyong; Lin, Hualiang; Xin, Benqiang; Nie, Jun

2014-01-01

Guangdong Province is the area most seriously affected by dengue fever in China. In this study, we describe the spatial distribution of dengue fever in Guangdong Province from 2001 to 2006 with the objective of informing priority areas for public health planning and resource allocation. Annualized incidence at a county level was calculated and mapped to show crude incidence, excess hazard, and spatial smoothed incidence. Geographic information system-based spatial scan statistics was conducted to detect the spatial distribution pattern of dengue fever incidence at the county level. Spatial scan cluster analyses suggested that counties around Guangzhou City and Chaoshan Region were at increased risk for dengue fever (P < .01). Some spatial clusters of dengue fever were found in Guangdong Province, which allowed intervention measures to be targeted for maximum effect.

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

ERIC Educational Resources Information Center

Li, Xun

2012-01-01

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

Uses of GIS for Homeland Security and Emergency Management for Higher Education Institutions

ERIC Educational Resources Information Center

Murchison, Stuart B.

2010-01-01

Geographic information systems (GIS) are a major component of the geospatial sciences, which are also composed of geostatistical analysis, remote sensing, and global positional satellite systems. These systems can be integrated into GIS for georeferencing, pattern analysis, visualization, and understanding spatial concepts that transcend…

Developmental patterns of spatial ability: an early sex difference.

PubMed

Johnson, E S; Meade, A C

1987-06-01

Over 1,800 public school students (grades K-12, ages 6-18) took a battery of 7 spatial tests tailored to their respective developmental levels. Analyses of resulting data indicate that it is feasible to measure spatial ability throughout this developmental range with modified versions of adult paper-and-pencil tests, that a male advantage in spatial performance appears reliably by age 10, and that the magnitude of the advantage remains constant through age 18. Analysis of covariance suggests that an early female precocity in language skills may mask a male advantage in spatial ability during the primary school years. There is no indication of a sex difference in kindergarten children.

Distribution patterns in the native vascular flora of Iceland.

PubMed

Wasowicz, Pawel; Pasierbiński, Andrzej; Przedpelska-Wasowicz, Ewa Maria; Kristinsson, Hörður

2014-01-01

The aim of our study was to reveal biogeographical patterns in the native vascular flora of Iceland and to define ecological factors responsible for these patterns. We analysed dataset of more than 500,000 records containing information on the occurrence of vascular plants. Analysis of ecological factors included climatic (derived from WORLDCLIM data), topographic (calculated from digital elevation model) and geological (bedrock characteristics) variables. Spherical k-means clustering and principal component analysis were used to detect biogeographical patterns and to study the factors responsible for them. We defined 10 biotic elements exhibiting different biogeographical patterns. We showed that climatic (temperature-related) and topographic variables were the most important factors contributing to the spatial patterns within the Icelandic vascular flora and that these patterns are almost completely independent of edaphic factors (bedrock type). Our study is the first one to analyse the biogeographical differentiation of the native vascular flora of Iceland.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Exploring space-time structure of human mobility in urban space

NASA Astrophysics Data System (ADS)

Sun, J. B.; Yuan, J.; Wang, Y.; Si, H. B.; Shan, X. M.

2011-03-01

Understanding of human mobility in urban space benefits the planning and provision of municipal facilities and services. Due to the high penetration of cell phones, mobile cellular networks provide information for urban dynamics with a large spatial extent and continuous temporal coverage in comparison with traditional approaches. The original data investigated in this paper were collected by cellular networks in a southern city of China, recording the population distribution by dividing the city into thousands of pixels. The space-time structure of urban dynamics is explored by applying Principal Component Analysis (PCA) to the original data, from temporal and spatial perspectives between which there is a dual relation. Based on the results of the analysis, we have discovered four underlying rules of urban dynamics: low intrinsic dimensionality, three categories of common patterns, dominance of periodic trends, and temporal stability. It implies that the space-time structure can be captured well by remarkably few temporal or spatial predictable periodic patterns, and the structure unearthed by PCA evolves stably over time. All these features play a critical role in the applications of forecasting and anomaly detection.

Variation in the Mississippi River Plume from Data Synthesis of Model Outputs and MODIS Imagery

NASA Astrophysics Data System (ADS)

Fitzpatrick, C.; Kolker, A.; Chu, P. Y.

2017-12-01

Understanding the Mississippi River (MR) plume's interaction with the open ocean is crucial for understanding many processes in the Gulf of Mexico. Though the Mississippi River and its delta and plume have been studied extensively, recent archives of model products and satellite imagery have allowed us to highlight patterns in plume behavior over the last two decades through large scale data synthesis. Using 8 years of USGS discharge data and Landsat imagery, we identified the spatial extent, geographic patterns, depth, and freshwater concentration of the MR plume across seasons and years. Using 20 years of HYCOM (HYbrid Coordinate Ocean Model) analysis and reanalysis model output, and several years of NGOFS FVCOM model outputs, we mapped the minimum and maximum spatial area of the MR plume, and its varied extent east and west. From the synthesis and analysis of these data, the statistical probability of the MR plume's spatial area and geographical extent were computed. Measurements of the MR plume and its response to river discharge may predict future behavior and provide a path forward to understanding MR plume influence on nearby ecosystems.

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

Flow pattern changes influenced by variation of viscosities of a heterogeneous gas-liquid mixture flow in a vertical channel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keska, Jerry K.; Hincapie, Juan; Jones, Richard

In the steady-state flow of a heterogeneous mixture such as an air-liquid mixture, the velocity and void fraction are space- and time-dependent parameters. These parameters are the most fundamental in the analysis and description of a multiphase flow. The determination of flow patterns in an objective way is extremely critical, since this is directly related to sudden changes in spatial and temporal changes of the random like characteristic of concentration. Flow patterns can be described by concentration signals in time, amplitude, and frequency domains. Despite the vital importance and countless attempts to solve or incorporate the flow pattern phenomena intomore » multiphase models, it has still been a very challenging topic in the scientific community since the 1940's and has not yet reached a satisfactory solution. This paper reports the experimental results of the impact of fluid viscosity on flow patterns for two-phase flow. Two-phase flow was created in laboratory equipment using air and liquid as phase medium. The liquid properties were changed by using variable concentrations of glycerol in water mixture which generated a wide-range of dynamic viscosities ranging from 1 to 1060 MPa s. The in situ spatial concentration vs. liquid viscosity and airflow velocity of two-phase flow in a vertical ID=50.8 mm pipe were measured using two concomitant computer-aided measurement systems. After acquiring data, the in situ special concentration signals were analyzed in time (spatial concentration and RMS of spatial concentration vs. time), amplitude (PDF and CPDF), and frequency (PSD and CPSD) domains that documented broad flow pattern changes caused by the fluid viscosity and air velocity changes. (author)« less

Automated measurement and classification of pulmonary blood-flow velocity patterns using phase-contrast MRI and correlation analysis.

PubMed

van Amerom, Joshua F P; Kellenberger, Christian J; Yoo, Shi-Joon; Macgowan, Christopher K

2009-01-01

An automated method was evaluated to detect blood flow in small pulmonary arteries and classify each as artery or vein, based on a temporal correlation analysis of their blood-flow velocity patterns. The method was evaluated using velocity-sensitive phase-contrast magnetic resonance data collected in vitro with a pulsatile flow phantom and in vivo in 11 human volunteers. The accuracy of the method was validated in vitro, which showed relative velocity errors of 12% at low spatial resolution (four voxels per diameter), but was reduced to 5% at increased spatial resolution (16 voxels per diameter). The performance of the method was evaluated in vivo according to its reproducibility and agreement with manual velocity measurements by an experienced radiologist. In all volunteers, the correlation analysis was able to detect and segment peripheral pulmonary vessels and distinguish arterial from venous velocity patterns. The intrasubject variability of repeated measurements was approximately 10% of peak velocity, or 2.8 cm/s root-mean-variance, demonstrating the high reproducibility of the method. Excellent agreement was obtained between the correlation analysis and radiologist measurements of pulmonary velocities, with a correlation of R2=0.98 (P<.001) and a slope of 0.99+/-0.01.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Epidemiological analysis, detection, and comparison of space-time patterns of Beijing hand-foot-mouth disease (2008-2012).

PubMed

Wang, Jiaojiao; Cao, Zhidong; Zeng, Daniel Dajun; Wang, Quanyi; Wang, Xiaoli; Qian, Haikun

2014-01-01

Hand, foot, and mouth disease (HFMD) mostly affects the health of infants and preschool children. Many studies of HFMD in different regions have been published. However, the epidemiological characteristics and space-time patterns of individual-level HFMD cases in a major city such as Beijing are unknown. The objective of this study was to investigate epidemiological features and identify high relative risk space-time HFMD clusters at a fine spatial scale. Detailed information on age, occupation, pathogen and gender was used to analyze the epidemiological features of HFMD epidemics. Data on individual-level HFMD cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify the spatial autocorrelation of HFMD incidence. Spatial filtering combined with scan statistics methods were used to detect HFMD clusters. A total of 157,707 HFMD cases (60.25% were male, 39.75% were female) reported in Beijing from 2008 to 2012 included 1465 severe cases and 33 fatal cases. The annual average incidence rate was 164.3 per 100,000 (ranged from 104.2 in 2008 to 231.5 in 2010). Male incidence was higher than female incidence for the 0 to 14-year age group, and 93.88% were nursery children or lived at home. Areas at a higher relative risk were mainly located in the urban-rural transition zones (the percentage of the population at risk ranged from 33.89% in 2011 to 39.58% in 2012) showing High-High positive spatial association for HFMD incidence. The most likely space-time cluster was located in the mid-east part of the Fangshan district, southwest of Beijing. The spatial-time patterns of Beijing HFMD (2008-2012) showed relatively steady. The population at risk were mainly distributed in the urban-rural transition zones. Epidemiological features of Beijing HFMD were generally consistent with the previous research. The findings generated computational insights useful for disease surveillance, risk assessment and early warning.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis.

PubMed

Gupta, Cota Navin; Calhoun, Vince D; Rachakonda, Srinivas; Chen, Jiayu; Patel, Veena; Liu, Jingyu; Segall, Judith; Franke, Barbara; Zwiers, Marcel P; Arias-Vasquez, Alejandro; Buitelaar, Jan; Fisher, Simon E; Fernandez, Guillen; van Erp, Theo G M; Potkin, Steven; Ford, Judith; Mathalon, Daniel; McEwen, Sarah; Lee, Hyo Jong; Mueller, Bryon A; Greve, Douglas N; Andreassen, Ole; Agartz, Ingrid; Gollub, Randy L; Sponheim, Scott R; Ehrlich, Stefan; Wang, Lei; Pearlson, Godfrey; Glahn, David C; Sprooten, Emma; Mayer, Andrew R; Stephen, Julia; Jung, Rex E; Canive, Jose; Bustillo, Juan; Turner, Jessica A

2015-09-01

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Accounting for rate instability and spatial patterns in the boundary analysis of cancer mortality maps

PubMed Central

Goovaerts, Pierre

2006-01-01

Boundary analysis of cancer maps may highlight areas where causative exposures change through geographic space, the presence of local populations with distinct cancer incidences, or the impact of different cancer control methods. Too often, such analysis ignores the spatial pattern of incidence or mortality rates and overlooks the fact that rates computed from sparsely populated geographic entities can be very unreliable. This paper proposes a new methodology that accounts for the uncertainty and spatial correlation of rate data in the detection of significant edges between adjacent entities or polygons. Poisson kriging is first used to estimate the risk value and the associated standard error within each polygon, accounting for the population size and the risk semivariogram computed from raw rates. The boundary statistic is then defined as half the absolute difference between kriged risks. Its reference distribution, under the null hypothesis of no boundary, is derived through the generation of multiple realizations of the spatial distribution of cancer risk values. This paper presents three types of neutral models generated using methods of increasing complexity: the common random shuffle of estimated risk values, a spatial re-ordering of these risks, or p-field simulation that accounts for the population size within each polygon. The approach is illustrated using age-adjusted pancreatic cancer mortality rates for white females in 295 US counties of the Northeast (1970–1994). Simulation studies demonstrate that Poisson kriging yields more accurate estimates of the cancer risk and how its value changes between polygons (i.e. boundary statistic), relatively to the use of raw rates or local empirical Bayes smoother. When used in conjunction with spatial neutral models generated by p-field simulation, the boundary analysis based on Poisson kriging estimates minimizes the proportion of type I errors (i.e. edges wrongly declared significant) while the frequency of these errors is predicted well by the p-value of the statistical test. PMID:19023455

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

[Spatial patterns and influence factors of specialization in tea cultivation based on geographically weighted regression model: A case study of Anxi County of Fujian Province, China].

PubMed

Shui, Wei; DU, Yong; Chen, Yi Ping; Jian, Xiao Mei; Fan, Bing Xiong

2017-04-18

Anxi County, specializing in tea cultivation, was taken as a case in this research. Pearson correlation analysis, ordinary least squares model (OLS) and geographically weighted regression model (GWR) were used to select four primary influence factors of specialization in tea cultivation (i.e., the average elevation, net income per capita, proportion of agricultural population, and the distance from roads) by analyzing the specialization degree of each town of Anxi County. Meanwhile, the spatial patterns of specialization in tea cultivation of Anxi County were evaluated. The results indicated that specialization in tea cultivation of Anxi County showed an obvious spatial auto-correlation, and a spatial pattern with "low-middle-high" circle structure, which was similar to Von Thünen's circle structure model, appeared from the county town to its surrounding region. Meanwhile, GWR (0.624) had a better fitting degree than OLS (0.595), and GWR could reasonably expound the spatial data. Contrary to the agricultural location theory of Von Thünen's model, which indicated that distance from market was a determination factor, the specialization degree of tea cultivation in Anxi was mainly decided by natural conditions of mountain area, instead of the social factors. Specialization degree of tea cultivation was positively correlated with the average elevation, net income per capita and the proportion of agricultural population, while a negative correlation was found between the distance from roads and specialization degree of tea cultivation. Coefficients of regression between the specialization degree of tea cultivation and two factors (i.e., the average elevation and net income per capita) showed a spatial pattern of higher level in the north direction and lower level in the south direction. On the contrary, the regression coefficients for the proportion of agricultural population increased from south to north of Anxi County. Furthermore, regression coefficient for the distance from roads showed a spatial pattern of higher level in the northeast direction and lower level in the southwest direction of Anxi County.

Characterization of Disease-Related Covariance Topographies with SSMPCA Toolbox: Effects of Spatial Normalization and PET Scanners

PubMed Central

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2013-01-01

In order to generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [18F]fluorodeoxyglucose PET scans from PD patients and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5 and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in PD patients imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. PMID:23671030

Characterization of disease-related covariance topographies with SSMPCA toolbox: effects of spatial normalization and PET scanners.

PubMed

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2014-05-01

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. Copyright © 2013 Wiley Periodicals, Inc.

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Can the functional stability of forest ecosystems be evaluated from the spatial analysis of stands? A case study from the Bialowieza Primeval Forest (Poland)

Treesearch

Andrzej Bobiec

2000-01-01

Variability of external and internal factors entails specific spatial patterns and functional dynamics of communities. The study of the oak-lime-hornbeam (Quercus robur-Tilia cordata-Carpimus) forest in the Bialowieza Primeval Forest supports the concept of silvatic unit, determining the minimal structural area. To find out if the dynamics of a stand...

Landscape-scale spatial patterns of winter injury to red spruce foliage in a year of heavy region-wide injury

Treesearch

Brynne E. Lazarus; Paul G. Schaberg; Gary J. Hawley; Donald H. DeHayes

2006-01-01

Red spruce (Picea rubens Sarg.) winter injury is caused by freezing damage that results in the abscission of the most recent foliar age-class. Injury was widespread and severe in the northeastern United States in 2003 and was assessed at multiple elevations at 23 sites in Vermont and adjacent states. This paper presents a spatial analysis of these...

Latitude delineates patterns of biogeography in terrestrial Streptomyces.

PubMed

Choudoir, Mallory J; Doroghazi, James R; Buckley, Daniel H

2016-12-01

The biogeography of Streptomyces was examined at regional spatial scales to identify factors that govern patterns of microbial diversity. Streptomyces are spore forming filamentous bacteria which are widespread in soil. Streptomyces strains were isolated from perennial grass habitats sampled across a spatial scale of more than 6000 km. Previous analysis of this geographically explicit culture collection provided evidence for a latitudinal diversity gradient in Streptomyces species. Here the hypothesis that this latitudinal diversity gradient is a result of evolutionary dynamics associated with historical demographic processes was evaluated. Historical demographic phenomena have genetic consequences that can be evaluated through analysis of population genetics. Population genetic approaches were applied to analyze population structure in six of the most numerically abundant and geographically widespread Streptomyces phylogroups from our culture collection. Streptomyces population structure varied at regional spatial scales, and allelic diversity correlated with geographic distance. In addition, allelic diversity and gene flow are partitioned by latitude. Finally, it was found that nucleotide diversity within phylogroups was negatively correlated with latitude. These results indicate that phylogroup diversification is constrained by dispersal limitation at regional spatial scales, and they are consistent with the hypothesis that historical demographic processes have influenced the contemporary biogeography of Streptomyces. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Thin-film Faraday patterns in three dimensions

NASA Astrophysics Data System (ADS)

Richter, Sebastian; Bestehorn, Michael

2017-04-01

We investigate the long time evolution of a thin fluid layer in three spatial dimensions located on a horizontal planar substrate. The substrate is subjected to time-periodic external vibrations in normal and in tangential direction with respect to the plane surface. The governing partial differential equation system of our model is obtained from the incompressible Navier-Stokes equations considering the limit of a thin fluid geometry and using the long wave lubrication approximation. It includes inertia and viscous friction. Numerical simulations evince the existence of persistent spatially complex surface patterns (periodic and quasiperiodic) for certain superpositions of two vertical excitations and initial conditions. Additional harmonic lateral excitations cause deformations but retain the basic structure of the patterns. Horizontal ratchet-shaped forces lead to a controllable lateral movement of the fluid. A Floquet analysis is used to determine the stability of the linearized system.

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

Lead spatio-temporal pattern identification in urban microenvironments using moss bags and the Kohonen self-organizing maps

NASA Astrophysics Data System (ADS)

Deljanin, Isidora; Antanasijević, Davor; Vuković, Gordana; Urošević, Mira Aničić; Tomašević, Milica; Perić-Grujić, Aleksandra; Ristić, Mirjana

2015-09-01

The first investigation of the use of the Kohonen self-organizing map (SOM) which includes lead concentration and its isotopic composition in moss bags to assess the spatial and temporal patterns of lead in the urban microenvironments is presented in this paper. The moss bags experiment was carried out during 2011 in the city tunnel in Belgrade, as well as in street canyons at different heights (4, 8 and 16 m) and in public garages. The moss bags were exposed for 5 and 10 weeks. The results revealed that the 10 weeks period represents suitable exposure time in screening Pb isotopic composition in active biomonitoring analysis. The obtained results showed that the SOM analysis, by recognizing slight differences among moss samples regarding exposure time, horizontal and vertical spatial distribution, with both, contribution of stable lead isotopes and Pb concentration, could be recommended in biomonitoring analysis of lead distribution in urban microenvironments.

Status of GeoTASO Trace Gas Data Analysis for the KORUS-AQ Campaign

NASA Astrophysics Data System (ADS)

Janz, S. J.; Nowlan, C. R.; Lamsal, L. N.; Kowalewski, M. G.; Judd, L. M.; Wang, J.

2017-12-01

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument measures spectrally resolved backscattered solar radiation at high spatial resolution. The instrument completed 30 sorties on board the NASA LaRC UC-12 aircraft during the KORUS-AQ deployment in May-June of 2016. GeoTASO collects spatially resolved spectra with sufficient sensitivity to retrieve column amounts of the trace gas molecules NO2, SO2, H2CO, O3, and C2H2O2 as well as aerosol products. Typical product retrievals are done in 250 m2 bins with multiple overpasses of key ground sites, allowing for detailed spatio-temporal analysis. Flight patterns consisted of both contiguous overlapping grid patterns to simulate satellite observational strategies in support of future geostationary satellite algorithm development, and "race-track" sampling to perform calibration and validation with the in-situ DC-8 platform as well as ground based assets. We will summarize the status of the radiance data set as well as ongoing analysis from our co-Investigators.

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

A platform for the advanced spatial and temporal control of biomolecules

NASA Astrophysics Data System (ADS)

Hook, Andrew L.; Thissen, Helmut; Hayes, Jason P.; Voelcker, Nicolas H.

2007-01-01

Manipulating biomolecules at solid/liquid interfaces is important for the development of various biodevices including microarrays. Smart materials that enable both spatial and temporal control of biomolecules by combining switchability with patterned surface chemistry offer unprecedented levels of control of biomolecule manipulation. Such a system has been developed for the microscale spatial control over both DNA and cell growth on highly doped p-type silicon. Surface modification, involving plasma polymerisation of allylamine and poly(ethlylene glycol) grafting with subsequent laser ablation, led to the production of a patterned surface with dual biomolecule adsorption and desorption properties. On patterned surfaces, preferential electro-stimulated adsorption of DNA to the allylamine plasma polymer surface and subsequent desorption by the application of a negative bias was observed. The ability of this surface to control both DNA and cell attachment in four dimensions has been demonstrated, exemplifying its capacity to be used for complex biological studies such as gene function analysis. This system has been successfully applied to living microarray applications and is an exciting platform for any system incorporating biomolecules.

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

To evaluate the Models-3/Community Multiscale Air Quality (CMAQ) modeling system in reproducing the spatial patterns of aerosol concentrations over the country on timescales of months and years, the spatial patterns of model output are compared with those derived from observation...

Mathematical study on robust tissue pattern formation in growing epididymal tubule.

PubMed

Hirashima, Tsuyoshi

2016-10-21

Tissue pattern formation during development is a reproducible morphogenetic process organized by a series of kinetic cellular activities, leading to the building of functional and stable organs. Recent studies focusing on mechanical aspects have revealed physical mechanisms on how the cellular activities contribute to the formation of reproducible tissue patterns; however, the understanding for what factors achieve the reproducibility of such patterning and how it occurs is far from complete. Here, I focus on a tube pattern formation during murine epididymal development, and show that two factors influencing physical design for the patterning, the proliferative zone within the tubule and the viscosity of tissues surrounding to the tubule, control the reproducibility of epididymal tubule pattern, using a mathematical model based on experimental data. Extensive numerical simulation of the simple mathematical model revealed that a spatially localized proliferative zone within the tubule, observed in experiments, results in more reproducible tubule pattern. Moreover, I found that the viscosity of tissues surrounding to the tubule imposes a trade-off regarding pattern reproducibility and spatial accuracy relating to the region where the tubule pattern is formed. This indicates an existence of optimality in material properties of tissues for the robust patterning of epididymal tubule. The results obtained by numerical analysis based on experimental observations provide a general insight on how physical design realizes robust tissue pattern formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigating univariate temporal patterns for intrinsic connectivity networks based on complexity and low-frequency oscillation: a test-retest reliability study.

PubMed

Wang, X; Jiao, Y; Tang, T; Wang, H; Lu, Z

2013-12-19

Intrinsic connectivity networks (ICNs) are composed of spatial components and time courses. The spatial components of ICNs were discovered with moderate-to-high reliability. So far as we know, few studies focused on the reliability of the temporal patterns for ICNs based their individual time courses. The goals of this study were twofold: to investigate the test-retest reliability of temporal patterns for ICNs, and to analyze these informative univariate metrics. Additionally, a correlation analysis was performed to enhance interpretability. Our study included three datasets: (a) short- and long-term scans, (b) multi-band echo-planar imaging (mEPI), and (c) eyes open or closed. Using dual regression, we obtained the time courses of ICNs for each subject. To produce temporal patterns for ICNs, we applied two categories of univariate metrics: network-wise complexity and network-wise low-frequency oscillation. Furthermore, we validated the test-retest reliability for each metric. The network-wise temporal patterns for most ICNs (especially for default mode network, DMN) exhibited moderate-to-high reliability and reproducibility under different scan conditions. Network-wise complexity for DMN exhibited fair reliability (ICC<0.5) based on eyes-closed sessions. Specially, our results supported that mEPI could be a useful method with high reliability and reproducibility. In addition, these temporal patterns were with physiological meanings, and certain temporal patterns were correlated to the node strength of the corresponding ICN. Overall, network-wise temporal patterns of ICNs were reliable and informative and could be complementary to spatial patterns of ICNs for further study. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Spatial Patterns in Alternative States and Thresholds: A Missing Link for Management of Landscapes?

USDA-ARS?s Scientific Manuscript database

The detection of threshold dynamics (and other dynamics of interest) would benefit from explicit representations of spatial patterns of disturbance, spatial dependence in responses to disturbance, and the spatial structure of feedbacks in the design of monitoring and management strategies. Spatially...

Contributions of ignitions, fuels, and weather to the spatial patterns of burn probability of a boreal landscape

Treesearch

Marc-Andre Parisien; Sean A. Parks; Carol Miller; Meg A. Krawchuck; Mark Heathcott; Max A. Moritz

2011-01-01

The spatial pattern of fire observed across boreal landscapes is the outcome of complex interactions among components of the fire environment. We investigated how the naturally occurring patterns of ignitions, fuels, and weather generate spatial pattern of burn probability (BP) in a large and highly fireprone boreal landscape of western Canada, Wood Buffalo National...

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada.

PubMed

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.

Photomorphic analysis techniques: An interim spatial analysis using satellite remote sensor imagery and historical data

NASA Technical Reports Server (NTRS)

Keuper, H. R.; Peplies, R. W.; Gillooly, R. P.

1977-01-01

The use of machine scanning and/or computer-based techniques to provide greater objectivity in the photomorphic approach was investigated. Photomorphic analysis and its application in regional planning are discussed. Topics included: delineation of photomorphic regions; inadequacies of existing classification systems; tonal and textural characteristics and signature analysis techniques; pattern recognition and Fourier transform analysis; and optical experiments. A bibliography is included.

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

Seeing shapes in seemingly random spatial patterns: Fractal analysis of Rorschach inkblots

PubMed Central

Taylor, R. P.; Martin, T. P.; Montgomery, R. D.; Smith, J. H.; Micolich, A. P.; Boydston, C.; Scannell, B. C.; Fairbanks, M. S.; Spehar, B.

2017-01-01

Rorschach inkblots have had a striking impact on the worlds of art and science because of the remarkable variety of associations with recognizable and namable objects they induce. Originally adopted as a projective psychological tool to probe mental health, psychologists and artists have more recently interpreted the variety of induced images simply as a signature of the observers’ creativity. Here we analyze the relationship between the spatial scaling parameters of the inkblot patterns and the number of induced associations, and suggest that the perceived images are induced by the fractal characteristics of the blot edges. We discuss how this relationship explains the frequent observation of images in natural scenery. PMID:28196082

Topoisomerase II Mediates Meiotic Crossover Interference

PubMed Central

Zhang, Liangran; Wang, Shunxin; Yin, Shen; Hong, Soogil; Kim, Keun P.; Kleckner, Nancy

2014-01-01

Summary Spatial patterning is a ubiquitous feature of biological systems. Meiotic crossovers provide an interesting example, defined by the classical phenomenon of crossover interference. Here, analysis of crossover patterns in budding yeast identifies a molecular pathway for interference. Topoisomerase II (Topo II) plays a central role, thus identifying a new function for this critical molecule. SUMOylation [of TopoII and axis component Red1] and ubiquitin-mediated removal of SUMOylated proteins are also required. These and other findings support the hypothesis that crossover interference involves accumulation, relief and redistribution of mechanical stress along the protein/DNA meshwork of meiotic chromosome axes, with TopoII required to adjust spatial relationships among DNA segments. PMID:25043020

Heavy Metal Pollution of Lakes along the Mid-Lower Reaches of the Yangtze River in China: Intensity, Sources and Spatial Patterns

PubMed Central

Zeng, Haiao; Wu, Jinglu

2013-01-01

Lakes in the middle and lower reaches of the Yangtze River form a shallow lake group unique in the World that is becoming increasingly polluted by heavy metals. Previous studies have largely focused on individual lakes, with limited exploration of the regional pattern of heavy metal pollution of the lake group in this area. This paper explores the sources, intensity and spatial patterns of heavy metal pollution of lake sediments. A total of 45 sample lakes were selected and the concentrations of key metal elements in the sediments of each lake were measured. The cluster analysis (CA), principal component analysis (PCA) and Geo-accumulation index (Ig) analysis permitted analysis of the source and pollution intensity of the target lakes. Results suggested a notable spatial variation amongst the sample lakes. Lakes in the upper part of the lower reach of the Yangtze River surrounded by typical urban landscapes were strongly or extremely polluted, with high concentrations of Pb, Zn, Cu and Cd in their sediments. This was attributed to large amount of untreated industrial discharges and municipal sewage produced within the lake catchments. In contrast, the heavy-metal pollution of lakes in the Taihu Delta area was notably lower due to industrial restructuring and implementation of effective environmental protection measures. Lakes along the middle reach of Yangtze River surrounded by agricultural areas were unpolluted to moderately polluted by heavy metals overall. Our results suggested that lakes in the central part of China require immediate attention and efforts should be made to implement management plans to prevent further degradation of water quality in these lakes. PMID:23442559

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals

NASA Astrophysics Data System (ADS)

Chen, Youhua; Peng, Shushi

2017-03-01

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals.

PubMed

Chen, Youhua; Peng, Shushi

2017-03-16

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Regional co-location pattern scoping on a street network considering distance decay effects of spatial interaction

PubMed Central

Yu, Wenhao

2017-01-01

Regional co-location scoping intends to identify local regions where spatial features of interest are frequently located together. Most of the previous researches in this domain are conducted on a global scale and they assume that spatial objects are embedded in a 2-D space, but the movement in urban space is actually constrained by the street network. In this paper we refine the scope of co-location patterns to 1-D paths consisting of nodes and segments. Furthermore, since the relations between spatial events are usually inversely proportional to their separation distance, the proposed method introduces the “Distance Decay Effects” to improve the result. Specifically, our approach first subdivides the street edges into continuous small linear segments. Then a value representing the local distribution intensity of events is estimated for each linear segment using the distance-decay function. Each kind of geographic feature can lead to a tessellated network with density attribute, and the generated multiple networks for the pattern of interest will be finally combined into a composite network by calculating the co-location prevalence measure values, which are based on the density variation between different features. Our experiments verify that the proposed approach is effective in urban analysis. PMID:28763496

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template

PubMed Central

Dong, Xiaoli; Grimm, Nancy B.

2017-01-01

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template.

PubMed

Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B

2017-06-13

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

A combinatorial code for pattern formation in Drosophila oogenesis.

PubMed

Yakoby, Nir; Bristow, Christopher A; Gong, Danielle; Schafer, Xenia; Lembong, Jessica; Zartman, Jeremiah J; Halfon, Marc S; Schüpbach, Trudi; Shvartsman, Stanislav Y

2008-11-01

Two-dimensional patterning of the follicular epithelium in Drosophila oogenesis is required for the formation of three-dimensional eggshell structures. Our analysis of a large number of published gene expression patterns in the follicle cells suggests that they follow a simple combinatorial code based on six spatial building blocks and the operations of union, difference, intersection, and addition. The building blocks are related to the distribution of inductive signals, provided by the highly conserved epidermal growth factor receptor and bone morphogenetic protein signaling pathways. We demonstrate the validity of the code by testing it against a set of patterns obtained in a large-scale transcriptional profiling experiment. Using the proposed code, we distinguish 36 distinct patterns for 81 genes expressed in the follicular epithelium and characterize their joint dynamics over four stages of oogenesis. The proposed combinatorial framework allows systematic analysis of the diversity and dynamics of two-dimensional transcriptional patterns and guides future studies of gene regulation.

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

PubMed

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.

Network analysis reveals multiscale controls on streamwater chemistry

Treesearch

Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.