Spectrum of classes of point emitters of electromagnetic wave fields.

PubMed

Castañeda, Román

2016-09-01

The spectrum of classes of point emitters has been introduced as a numerical tool suitable for the design, analysis, and synthesis of non-paraxial optical fields in arbitrary states of spatial coherence. In this paper, the polarization state of planar electromagnetic wave fields is included in the spectrum of classes, thus increasing its modeling capabilities. In this context, optical processing is realized as a filtering on the spectrum of classes of point emitters, performed by the complex degree of spatial coherence and the two-point correlation of polarization, which could be implemented dynamically by using programmable optical devices.

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.

Tree invasion of a montane meadow complex: temporal trends, spatial patterns, and biotic interactions

Treesearch

Charles B. Halpern; Joseph A. Antos; Janine M. Rice; Ryan D. Haugo; Nicole L. Lang

2010-01-01

We combined spatial point pattern analysis, population age structures, and a time-series of stem maps to quantify spatial and temporal patterns of conifer invasion over a 200-yr period in three plots totaling 4 ha. In combination, spatial and temporal patterns of establishment suggest an invasion process shaped by biotic interactions, with facilitation promoting...

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

2013-04-01

High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

Compressing interpreted satellite imagery for geographic information systems applications over extensive regions

USGS Publications Warehouse

Miller, Stephan W.

1981-01-01

A second set of related problems deals with how this format and other representations of spatial entities, such as vector formats for point and line features, can be interrelated for manipulation, retrieval, and analysis by a spatial database management subsystem. Methods have been developed for interrelating areal data sets in the raster format with point and line data in a vector format and these are described.

Geostatistics and spatial analysis in biological anthropology.

PubMed

Relethford, John H

2008-05-01

A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology. (c) 2008 Wiley-Liss, Inc.

Analysis of data from NASA B-57B gust gradient program

NASA Technical Reports Server (NTRS)

Frost, W.; Lin, M. C.; Chang, H. P.; Ringnes, E.

1985-01-01

Statistical analysis of the turbulence measured in flight 6 of the NASA B-57B over Denver, Colorado, from July 7 to July 23, 1982 included the calculations of average turbulence parameters, integral length scales, probability density functions, single point autocorrelation coefficients, two point autocorrelation coefficients, normalized autospectra, normalized two point autospectra, and two point cross sectra for gust velocities. The single point autocorrelation coefficients were compared with the theoretical model developed by von Karman. Theoretical analyses were developed which address the effects spanwise gust distributions, using two point spatial turbulence correlations.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

elevatr: Access Elevation Data from Various APIs | Science ...

EPA Pesticide Factsheets

Several web services are available that provide access to elevation data. This package provides access to several of those services and returns elevation data either as a SpatialPointsDataFrame from point elevation services or as a raster object from raster elevation services. Currently, the package supports access to the Mapzen Elevation Service, Mapzen Terrain Service, and the USGS Elevation Point Query Service. The R language for statistical computing is increasingly used for spatial data analysis . This R package, elevatr, is in response to this and provides access to elevation data from various sources directly in R. The impact of `elevatr` is that it will 1) facilitate spatial analysis in R by providing access to foundational dataset for many types of analyses (e.g. hydrology, limnology) 2) open up a new set of users and uses for APIs widely used outside of R, and 3) provide an excellent example federal open source development as promoted by the Federal Source Code Policy (https://sourcecode.cio.gov/).

Monitoring urban subsidence based on SAR lnterferometric point target analysis

USGS Publications Warehouse

Zhang, Y.; Zhang, Jiahua; Gong, W.; Lu, Z.

2009-01-01

lnterferometric point target analysis (IPTA) is one of the latest developments in radar interferometric processing. It is achieved by analysis of the interferometric phases of some individual point targets, which are discrete and present temporarily stable backscattering characteristics, in long temporal series of interferometric SAR images. This paper analyzes the interferometric phase model of point targets, and then addresses two key issues within IPTA process. Firstly, a spatial searching method is proposed to unwrap the interferometric phase difference between two neighboring point targets. The height residual error and linear deformation rate of each point target can then be calculated, when a global reference point with known height correction and deformation history is chosen. Secondly, a spatial-temporal filtering scheme is proposed to further separate the atmosphere phase and nonlinear deformation phase from the residual interferometric phase. Finally, an experiment of the developed IPTA methodology is conducted over Suzhou urban area. Totally 38 ERS-1/2 SAR scenes are analyzed, and the deformation information over 3 546 point targets in the time span of 1992-2002 are generated. The IPTA-derived deformation shows very good agreement with the published result, which demonstrates that the IPTA technique can be developed into an operational tool to map the ground subsidence over urban area.

Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft

NASA Technical Reports Server (NTRS)

Frost, Walter; Chang, Ho-Pen; Ringnes, Erik A.

1987-01-01

Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.

A dynamical system approach to Bianchi III cosmology for Hu-Sawicki type f( R) gravity

NASA Astrophysics Data System (ADS)

Banik, Sebika Kangsha; Banik, Debika Kangsha; Bhuyan, Kalyan

2018-02-01

The cosmological dynamics of spatially homogeneous but anisotropic Bianchi type-III space-time is investigated in presence of a perfect fluid within the framework of Hu-Sawicki model. We use the dynamical system approach to perform a detailed analysis of the cosmological behaviour of this model for the model parameters n=1, c_1=1, determining all the fixed points, their stability and corresponding cosmological evolution. We have found stable fixed points with de Sitter solution along with unstable radiation like fixed points. We have identified a matter like point which act like an unstable spiral and when the initial conditions of a trajectory are very close to this point, it stabilizes at a stable accelerating point. Thus, in this model, the universe can naturally approach to a phase of accelerated expansion following a radiation or a matter dominated phase. It is also found that the isotropisation of this model is affected by the spatial curvature and that all the isotropic fixed points are found to be spatially flat.

Soil moisture optimal sampling strategy for Sentinel 1 validation super-sites in Poland

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Lipiec, Jerzy; Usowicz, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan

2014-05-01

Soil moisture (SM) exhibits a high temporal and spatial variability that is dependent not only on the rainfall distribution, but also on the topography of the area, physical properties of soil and vegetation characteristics. Large variability does not allow on certain estimation of SM in the surface layer based on ground point measurements, especially in large spatial scales. Remote sensing measurements allow estimating the spatial distribution of SM in the surface layer on the Earth, better than point measurements, however they require validation. This study attempts to characterize the SM distribution by determining its spatial variability in relation to the number and location of ground point measurements. The strategy takes into account the gravimetric and TDR measurements with different sampling steps, abundance and distribution of measuring points on scales of arable field, wetland and commune (areas: 0.01, 1 and 140 km2 respectively), taking into account the different status of SM. Mean values of SM were lowly sensitive on changes in the number and arrangement of sampling, however parameters describing the dispersion responded in a more significant manner. Spatial analysis showed autocorrelations of the SM, which lengths depended on the number and the distribution of points within the adopted grids. Directional analysis revealed a differentiated anisotropy of SM for different grids and numbers of measuring points. It can therefore be concluded that both the number of samples, as well as their layout on the experimental area, were reflected in the parameters characterizing the SM distribution. This suggests the need of using at least two variants of sampling, differing in the number and positioning of the measurement points, wherein the number of them must be at least 20. This is due to the value of the standard error and range of spatial variability, which show little change with the increase in the number of samples above this figure. Gravimetric method gives a more varied distribution of SM than those derived from TDR measurements. It should be noted that reducing the number of samples in the measuring grid leads to flattening the distribution of SM from both methods and increasing the estimation error at the same time. Grid of sensors for permanent measurement points should include points that have similar distributions of SM in the vicinity. Results of the analysis including number, the maximum correlation ranges and the acceptable estimation error should be taken into account when choosing of the measurement points. Adoption or possible adjustment of the distribution of the measurement points should be verified by performing additional measuring campaigns during the dry and wet periods. Presented approach seems to be appropriate for creation of regional-scale test (super) sites, to validate products of satellites equipped with SAR (Synthetic Aperture Radar), operating in C-band, with spatial resolution suited to single field scale, as for example: ERS-1, ERS-2, Radarsat and Sentinel-1, which is going to be launched in next few months. The work was partially funded by the Government of Poland through an ESA Contract under the PECS ELBARA_PD project No. 4000107897/13/NL/KML.

Fusion of UAV photogrammetry and digital optical granulometry for detection of structural changes in floodplains

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Lendzioch, Theodora; Mirijovsky, Jakub

2016-04-01

Granulometric analysis represents a traditional, important and for the description of sedimentary material substantial method with various applications in sedimentology, hydrology and geomorphology. However, the conventional granulometric field survey methods are time consuming, laborious, costly and are invasive to the surface being sampled, which can be limiting factor for their applicability in protected areas.. The optical granulometry has recently emerged as an image analysis technique, enabling non-invasive survey, employing semi-automated identification of clasts from calibrated digital imagery, taken on site by conventional high resolution digital camera and calibrated frame. The image processing allows detection and measurement of mixed size natural grains, their sorting and quantitative analysis using standard granulometric approaches. Despite known limitations, the technique today presents reliable tool, significantly easing and speeding the field survey in fluvial geomorphology. However, the nature of such survey has still limitations in spatial coverage of the sites and applicability in research at multitemporal scale. In our study, we are presenting novel approach, based on fusion of two image analysis techniques - optical granulometry and UAV-based photogrammetry, allowing to bridge the gap between the needs of high resolution structural information for granulometric analysis and spatially accurate and data coverage. We have developed and tested a workflow that, using UAV imaging platform enabling to deliver seamless, high resolution and spatially accurate imagery of the study site from which can be derived the granulometric properties of the sedimentary material. We have set up a workflow modeling chain, providing (i) the optimum flight parameters for UAV imagery to balance the two key divergent requirements - imagery resolution and seamless spatial coverage, (ii) the workflow for the processing of UAV acquired imagery by means of the optical granulometry and (iii) the workflow for analysis of spatial distribution and temporal changes of granulometric properties across the point bar. The proposed technique was tested on a case study of an active point bar of mid-latitude mountain stream at Sumava mountains, Czech Republic, exposed to repeated flooding. The UAV photogrammetry was used to acquire very high resolution imagery to build high-precision digital terrain models and orthoimage. The orthoimage was then analyzed using the digital optical granulometric tool BaseGrain. This approach allowed us (i) to analyze the spatial distribution of the grain size in a seamless transects over an active point bar and (ii) to assess the multitemporal changes of granulometric properties of the point bar material resulting from flooding. The tested framework prove the applicability of the proposed method for granulometric analysis with accuracy comparable with field optical granulometry. The seamless nature of the data enables to study spatial distribution of granulometric properties across the study sites as well as the analysis of multitemporal changes, resulting from repeated imaging.

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...

Subdiffraction incoherent optical imaging via spatial-mode demultiplexing: Semiclassical treatment

NASA Astrophysics Data System (ADS)

Tsang, Mankei

2018-02-01

I present a semiclassical analysis of a spatial-mode demultiplexing (SPADE) measurement scheme for far-field incoherent optical imaging under the effects of diffraction and photon shot noise. Building on previous results that assume two point sources or the Gaussian point-spread function, I generalize SPADE for a larger class of point-spread functions and evaluate its errors in estimating the moments of an arbitrary subdiffraction object. Compared with the limits to direct imaging set by the Cramér-Rao bounds, the results show that SPADE can offer far superior accuracy in estimating second- and higher-order moments.

Spatial sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

NASA Astrophysics Data System (ADS)

Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

2014-10-01

The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

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.

sLORETA current source density analysis of evoked potentials for spatial updating in a virtual navigation task

PubMed Central

Nguyen, Hai M.; Matsumoto, Jumpei; Tran, Anh H.; Ono, Taketoshi; Nishijo, Hisao

2014-01-01

Previous studies have reported that multiple brain regions are activated during spatial navigation. However, it is unclear whether these activated brain regions are specifically associated with spatial updating or whether some regions are recruited for parallel cognitive processes. The present study aimed to localize current sources of event related potentials (ERPs) associated with spatial updating specifically. In the control phase of the experiment, electroencephalograms (EEGs) were recorded while subjects sequentially traced 10 blue checkpoints on the streets of a virtual town, which were sequentially connected by a green line, by manipulating a joystick. In the test phase of the experiment, the checkpoints and green line were not indicated. Instead, a tone was presented when the subjects entered the reference points where they were then required to trace the 10 invisible spatial reference points corresponding to the checkpoints. The vertex-positive ERPs with latencies of approximately 340 ms from the moment when the subjects entered the unmarked reference points were significantly larger in the test than in the control phases. Current source density analysis of the ERPs by standardized low-resolution brain electromagnetic tomography (sLORETA) indicated activation of brain regions in the test phase that are associated with place and landmark recognition (entorhinal cortex/hippocampus, parahippocampal and retrosplenial cortices, fusiform, and lingual gyri), detecting self-motion (posterior cingulate and posterior insular cortices), motor planning (superior frontal gyrus, including the medial frontal cortex), and regions that process spatial attention (inferior parietal lobule). The present results provide the first identification of the current sources of ERPs associated with spatial updating, and suggest that multiple systems are active in parallel during spatial updating. PMID:24624067

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.

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.

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

PubMed

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Statistical analysis of atmospheric turbulence about a simulated block building

NASA Technical Reports Server (NTRS)

Steely, S. L., Jr.

1981-01-01

An array of towers instrumented to measure the three components of wind speed was used to study atmospheric flow about a simulated block building. Two-point spacetime correlations of the longitudinal velocity component were computed along with two-point spatial correlations. These correlations are in good agreement with fundamental concepts of fluid mechanics. The two-point spatial correlations computed directly were compared with correlations predicted by Taylor's hypothesis and excellent agreement was obtained at the higher levels which were out of the building influence. The correlations fall off significantly in the building wake but recover beyond the wake to essentially the same values in the undisturbed, higher regions.

Improvements of the two-dimensional FDTD method for the simulation of normal- and superconducting planar waveguides using time series analysis

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

Hofschen, S.; Wolff, I.

1996-08-01

Time-domain simulation results of two-dimensional (2-D) planar waveguide finite-difference time-domain (FDTD) analysis are normally analyzed using Fourier transform. The introduced method of time series analysis to extract propagation and attenuation constants reduces the desired computation time drastically. Additionally, a nonequidistant discretization together with an adequate excitation technique is used to reduce the number of spatial grid points. Therefore, it is possible to reduce the number of spatial grid points. Therefore, it is possible to simulate normal- and superconducting planar waveguide structures with very thin conductors and small dimensions, as they are used in MMIC technology. The simulation results are comparedmore » with measurements and show good agreement.« less

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Visualizing Uncertainty of Point Phenomena by Redesigned Error Ellipses

NASA Astrophysics Data System (ADS)

Murphy, Christian E.

2018-05-01

Visualizing uncertainty remains one of the great challenges in modern cartography. There is no overarching strategy to display the nature of uncertainty, as an effective and efficient visualization depends, besides on the spatial data feature type, heavily on the type of uncertainty. This work presents a design strategy to visualize uncertainty con-nected to point features. The error ellipse, well-known from mathematical statistics, is adapted to display the uncer-tainty of point information originating from spatial generalization. Modified designs of the error ellipse show the po-tential of quantitative and qualitative symbolization and simultaneous point based uncertainty symbolization. The user can intuitively depict the centers of gravity, the major orientation of the point arrays as well as estimate the ex-tents and possible spatial distributions of multiple point phenomena. The error ellipse represents uncertainty in an intuitive way, particularly suitable for laymen. Furthermore it is shown how applicable an adapted design of the er-ror ellipse is to display the uncertainty of point features originating from incomplete data. The suitability of the error ellipse to display the uncertainty of point information is demonstrated within two showcases: (1) the analysis of formations of association football players, and (2) uncertain positioning of events on maps for the media.

Exploring behavior of an unusual megaherbivore: A spatially explicit foraging model of the hippopotamus

USGS Publications Warehouse

Lewison, R.L.; Carter, J.

2004-01-01

Herbivore foraging theories have been developed for and tested on herbivores across a range of sizes. Due to logistical constraints, however, little research has focused on foraging behavior of megaherbivores. Here we present a research approach that explores megaherbivore foraging behavior, and assesses the applicability of foraging theories developed on smaller herbivores to megafauna. With simulation models as reference points for the analysis of empirical data, we investigate foraging strategies of the common hippopotamus (Hippopotamus amphibius). Using a spatially explicit individual based foraging model, we apply traditional herbivore foraging strategies to a model hippopotamus, compare model output, and then relate these results to field data from wild hippopotami. Hippopotami appear to employ foraging strategies that respond to vegetation characteristics, such as vegetation quality, as well as spatial reference information, namely distance to a water source. Model predictions, field observations, and comparisons of the two support that hippopotami generally conform to the central place foraging construct. These analyses point to the applicability of general herbivore foraging concepts to megaherbivores, but also point to important differences between hippopotami and other herbivores. Our synergistic approach of models as reference points for empirical data highlights a useful method of behavioral analysis for hard-to-study megafauna. ?? 2003 Elsevier B.V. All rights reserved.

[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.

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.

Managing distance and covariate information with point-based clustering.

PubMed

Whigham, Peter A; de Graaf, Brandon; Srivastava, Rashmi; Glue, Paul

2016-09-01

Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley's K and applied to the problem of clustering with deliberate self-harm (DSH), is presented. Point-based Monte-Carlo simulation of Ripley's K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years' emergency hospital presentations (n = 136) in a New Zealand town (population ~50,000). Study area was defined by residential (housing) land parcels representing a finite set of possible point addresses. Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley's K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for covariate measures that exhibit spatial clustering, such as deprivation, are crucial when assessing point-based clustering.

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 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

Multi-time scale analysis of the spatial representativeness of in situ soil moisture data within satellite footprints

USDA-ARS?s Scientific Manuscript database

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies ...

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

Two-Point Orientation Discrimination Versus the Traditional Two-Point Test for Tactile Spatial Acuity Assessment

PubMed Central

Tong, Jonathan; Mao, Oliver; Goldreich, Daniel

2013-01-01

Two-point discrimination is widely used to measure tactile spatial acuity. The validity of the two-point threshold as a spatial acuity measure rests on the assumption that two points can be distinguished from one only when the two points are sufficiently separated to evoke spatially distinguishable foci of neural activity. However, some previous research has challenged this view, suggesting instead that two-point task performance benefits from an unintended non-spatial cue, allowing spuriously good performance at small tip separations. We compared the traditional two-point task to an equally convenient alternative task in which participants attempt to discern the orientation (vertical or horizontal) of two points of contact. We used precision digital readout calipers to administer two-interval forced-choice versions of both tasks to 24 neurologically healthy adults, on the fingertip, finger base, palm, and forearm. We used Bayesian adaptive testing to estimate the participants’ psychometric functions on the two tasks. Traditional two-point performance remained significantly above chance levels even at zero point separation. In contrast, two-point orientation discrimination approached chance as point separation approached zero, as expected for a valid measure of tactile spatial acuity. Traditional two-point performance was so inflated at small point separations that 75%-correct thresholds could be determined on all tested sites for fewer than half of participants. The 95%-correct thresholds on the two tasks were similar, and correlated with receptive field spacing. In keeping with previous critiques, we conclude that the traditional two-point task provides an unintended non-spatial cue, resulting in spuriously good performance at small spatial separations. Unlike two-point discrimination, two-point orientation discrimination rigorously measures tactile spatial acuity. We recommend the use of two-point orientation discrimination for neurological assessment. PMID:24062677

New approaches for calculating Moran's index of spatial autocorrelation.

PubMed

Chen, Yanguang

2013-01-01

Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

[Spatial distribution of occupational disease prevalence in Guangzhou and Foshan city by geographic information system].

PubMed

Tan, Q; Tu, H W; Gu, C H; Li, X D; Li, R Z; Wang, M; Chen, S G; Cheng, Y J; Liu, Y M

2017-11-20

Objective: To explore the occupational disease spatial distribution characteristics in Guangzhou and Foshan city in 2006-2013 with Geographic Information System and to provide evidence for making control strategy. Methods: The data on occupational disease diagnosis in Guangzhou and Foshan city from 2006 through 2013 were collected and linked to the digital map at administrative county level with Arc GIS12.0 software for spatial analysis. Results: The maps of occupational disease and Moran's spatial autocor-relation analysis showed that the spatial aggregation existed in Shunde and Nanhai region with Moran's index 1.727, -0.003. Local Moran's I spatial autocorrelation analysis pointed out the "positive high incidence re-gion" and the "negative high incidence region" during 2006~2013. Trend analysis showed that the diagnosis case increased slightly then declined from west to east, increase obviously from north to south, declined from? southwest to northeast, high in the middle and low on both sides in northwest-southeast direction. Conclusions: The occupational disease is obviously geographical distribution in Guangzhou and Foshan city. The corresponding prevention measures should be made according to the geographical distribution.

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.

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.

Dual-domain point diffraction interferometer

DOEpatents

Naulleau, Patrick P.; Goldberg, Kenneth Alan

2000-01-01

A hybrid spatial/temporal-domain point diffraction interferometer (referred to as the dual-domain PS/PDI) that is capable of suppressing the scattered-reference-light noise that hinders the conventional PS/PDI is provided. The dual-domain PS/PDI combines the separate noise-suppression capabilities of the widely-used phase-shifting and Fourier-transform fringe pattern analysis methods. The dual-domain PS/PDI relies on both a more restrictive implementation of the image plane PS/PDI mask and a new analysis method to be applied to the interferograms generated and recorded by the modified PS/PDI. The more restrictive PS/PDI mask guarantees the elimination of spatial-frequency crosstalk between the signal and the scattered-light noise arising from scattered-reference-light interfering with the test beam. The new dual-domain analysis method is then used to eliminate scattered-light noise arising from both the scattered-reference-light interfering with the test beam and the scattered-reference-light interfering with the "true" pinhole-diffracted reference light. The dual-domain analysis method has also been demonstrated to provide performance enhancement when using the non-optimized standard PS/PDI design. The dual-domain PS/PDI is essentially a three-tiered filtering system composed of lowpass spatial-filtering the test-beam electric field using the more restrictive PS/PDI mask, bandpass spatial-filtering the individual interferogram irradiance frames making up the phase-shifting series, and bandpass temporal-filtering the phase-shifting series as a whole.

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

NASA Astrophysics Data System (ADS)

Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

2017-12-01

The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

Frontiers in Fluctuation Spectroscopy: Measuring protein dynamics and protein spatio-temporal connectivity

NASA Astrophysics Data System (ADS)

Digman, Michelle

Fluorescence fluctuation spectroscopy has evolved from single point detection of molecular diffusion to a family of microscopy imaging correlation tools (i.e. ICS, RICS, STICS, and kICS) useful in deriving spatial-temporal dynamics of proteins in living cells The advantage of the imaging techniques is the simultaneous measurement of all points in an image with a frame rate that is increasingly becoming faster with better sensitivity cameras and new microscopy modalities such as the sheet illumination technique. A new frontier in this area is now emerging towards a high level of mapping diffusion rates and protein dynamics in the 2 and 3 dimensions. In this talk, I will discuss the evolution of fluctuation analysis from the single point source to mapping diffusion in whole cells and the technology behind this technique. In particular, new methods of analysis exploit correlation of molecular fluctuations originating from measurement of fluctuation correlations at distant points (pair correlation analysis) and methods that exploit spatial averaging of fluctuations in small regions (iMSD). For example the pair correlation fluctuation (pCF) analyses done between adjacent pixels in all possible radial directions provide a window into anisotropic molecular diffusion. Similar to the connectivity atlas of neuronal connections from the MRI diffusion tensor imaging these new tools will be used to map the connectome of protein diffusion in living cells. For biological reaction-diffusion systems, live single cell spatial-temporal analysis of protein dynamics provides a mean to observe stochastic biochemical signaling in the context of the intracellular environment which may lead to better understanding of cancer cell invasion, stem cell differentiation and other fundamental biological processes. National Institutes of Health Grant P41-RRO3155.

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.

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.

Analysis on the Spatial Difference of Bacterial Community Structure in Micro-pressure Air-lift Loop Reactor

NASA Astrophysics Data System (ADS)

Wan, L. G.; Lin, Q.; Bian, D. J.; Ren, Q. K.; Xiao, Y. B.; Lu, W. X.

2018-02-01

In order to reveal the spatial difference of the bacterial community structure in the Micro-pressure Air-lift Loop Reactor, the activated sludge bacterial at five different representative sites in the reactor were studied by denaturing gradient gel electrophoresis (DGGE). The results of DGGE showed that the difference of environmental conditions (such as substrate concentration, dissolved oxygen and PH, etc.) resulted in different diversity and similarity of microbial flora in different spatial locations. The Shannon-Wiener diversity index of the total bacterial samples from five sludge samples varied from 0.92 to 1.28, the biodiversity index was the smallest at point 5, and the biodiversity index was the highest at point 2. The similarity of the flora between the point 2, 3 and 4 was 80% or more, respectively. The similarity of the flora between the point 5 and the other samples was below 70%, and the similarity of point 2 was only 59.2%. Due to the different contribution of different strains to the removal of pollutants, it can give full play to the synergistic effect of bacterial degradation of pollutants, and further improve the efficiency of sewage treatment.

Shapes on a plane: Evaluating the impact of projection distortion on spatial binning

USGS Publications Warehouse

Battersby, Sarah E.; Strebe, Daniel “daan”; Finn, Michael P.

2017-01-01

One method for working with large, dense sets of spatial point data is to aggregate the measure of the data into polygonal containers, such as political boundaries, or into regular spatial bins such as triangles, squares, or hexagons. When mapping these aggregations, the map projection must inevitably distort relationships. This distortion can impact the reader’s ability to compare count and density measures across the map. Spatial binning, particularly via hexagons, is becoming a popular technique for displaying aggregate measures of point data sets. Increasingly, we see questionable use of the technique without attendant discussion of its hazards. In this work, we discuss when and why spatial binning works and how mapmakers can better understand the limitations caused by distortion from projecting to the plane. We introduce equations for evaluating distortion’s impact on one common projection (Web Mercator) and discuss how the methods used generalize to other projections. While we focus on hexagonal binning, these same considerations affect spatial bins of any shape, and more generally, any analysis of geographic data performed in planar space.

Incorporating Human Movement Behavior into the Analysis of Spatially Distributed Infrastructure.

PubMed

Wu, Lihua; Leung, Henry; Jiang, Hao; Zheng, Hong; Ma, Li

2016-01-01

For the first time in human history, the majority of the world's population resides in urban areas. Therefore, city managers are faced with new challenges related to the efficiency, equity and quality of the supply of resources, such as water, food and energy. Infrastructure in a city can be viewed as service points providing resources. These service points function together as a spatially collaborative system to serve an increasing population. To study the spatial collaboration among service points, we propose a shared network according to human's collective movement and resource usage based on data usage detail records (UDRs) from the cellular network in a city in western China. This network is shown to be not scale-free, but exhibits an interesting triangular property governed by two types of nodes with very different link patterns. Surprisingly, this feature is consistent with the urban-rural dualistic context of the city. Another feature of the shared network is that it consists of several spatially separated communities that characterize local people's active zones but do not completely overlap with administrative areas. According to these features, we propose the incorporation of human movement into infrastructure classification. The presence of well-defined spatially separated clusters confirms the effectiveness of this approach. In this paper, our findings reveal the spatial structure inside a city, and the proposed approach provides a new perspective on integrating human movement into the study of a spatially distributed system.

Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Hayashi, Toshiyuki; Kato, Toshinori; Okada, Eiji

2004-06-01

Near-infrared (NIR) topography can obtain a topographical distribution of the activated region in the brain cortex. Near-infrared light is strongly scattered in the head, and the volume of tissue sampled by a source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. In this study, a one-dimensional distribution of absorption change in a head model is calculated by mapping and reconstruction methods to evaluate the effect of the image reconstruction algorithm and the interval of measurement points for topographic imaging on the accuracy of the topographic image. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The measurement points are one-dimensionally arranged on the surface of the model, and the distance between adjacent measurement points is varied from 4 mm to 28 mm. Small intervals of the measurement points improve the topographic image calculated by both the mapping and reconstruction methods. In the conventional mapping method, the limit of the spatial resolution depends upon the interval of the measurement points and spatial sensitivity profile for source-detector pairs. The reconstruction method has advantages over the mapping method which improve the results of one-dimensional analysis when the interval of measurement points is less than 12 mm. The effect of overlapping of spatial sensitivity profiles indicates that the reconstruction method may be effective to improve the spatial resolution of a two-dimensional reconstruction of topographic image obtained with larger interval of measurement points. Near-infrared topography with the reconstruction method potentially obtains an accurate distribution of absorption change in the brain even if the size of absorption change is less than 10 mm.

New Approaches for Calculating Moran’s Index of Spatial Autocorrelation

PubMed Central

Chen, Yanguang

2013-01-01

Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran’s index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran’s index. Moran’s scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran’s index and Geary’s coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran’s index and Geary’s coefficient will be clarified and defined. One of theoretical findings is that Moran’s index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation. PMID:23874592

[Spatial heterogeneity and classified control of agricultural non-point source pollution in Huaihe River Basin].

PubMed

Zhou, Liang; Xu, Jian-Gang; Sun, Dong-Qi; Ni, Tian-Hua

2013-02-01

Agricultural non-point source pollution is of importance in river deterioration. Thus identifying and concentrated controlling the key source-areas are the most effective approaches for non-point source pollution control. This study adopts inventory method to analysis four kinds of pollution sources and their emissions intensity of the chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) in 173 counties (cities, districts) in Huaihe River Basin. The four pollution sources include livestock breeding, rural life, farmland cultivation, aquacultures. The paper mainly addresses identification of non-point polluted sensitivity areas, key pollution sources and its spatial distribution characteristics through cluster, sensitivity evaluation and spatial analysis. A geographic information system (GIS) and SPSS were used to carry out this study. The results show that: the COD, TN and TP emissions of agricultural non-point sources were 206.74 x 10(4) t, 66.49 x 10(4) t, 8.74 x 10(4) t separately in Huaihe River Basin in 2009; the emission intensity were 7.69, 2.47, 0.32 t.hm-2; the proportions of COD, TN, TP emissions were 73%, 24%, 3%. The paper achieves that: the major pollution source of COD, TN and TP was livestock breeding and rural life; the sensitivity areas and priority pollution control areas among the river basin of non-point source pollution are some sub-basins of the upper branches in Huaihe River, such as Shahe River, Yinghe River, Beiru River, Jialu River and Qingyi River; livestock breeding is the key pollution source in the priority pollution control areas. Finally, the paper concludes that pollution type of rural life has the highest pollution contribution rate, while comprehensive pollution is one type which is hard to control.

Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains

USGS Publications Warehouse

Chang, A.T.C.; Kelly, R.E.J.; Josberger, E.G.; Armstrong, R.L.; Foster, J.L.; Mognard, N.M.

2005-01-01

Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 ?? 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1?? ?? 1?? in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations. ?? 2005 American Meteorological Society.

Development of spatial scaling technique of forest health sample point information

NASA Astrophysics Data System (ADS)

Lee, J.; Ryu, J.; Choi, Y. Y.; Chung, H. I.; Kim, S. H.; Jeon, S. W.

2017-12-01

Most forest health assessments are limited to monitoring sampling sites. The monitoring of forest health in Britain in Britain was carried out mainly on five species (Norway spruce, Sitka spruce, Scots pine, Oak, Beech) Database construction using Oracle database program with density The Forest Health Assessment in GreatBay in the United States was conducted to identify the characteristics of the ecosystem populations of each area based on the evaluation of forest health by tree species, diameter at breast height, water pipe and density in summer and fall of 200. In the case of Korea, in the first evaluation report on forest health vitality, 1000 sample points were placed in the forests using a systematic method of arranging forests at 4Km × 4Km at regular intervals based on an sample point, and 29 items in four categories such as tree health, vegetation, soil, and atmosphere. As mentioned above, existing researches have been done through the monitoring of the survey sample points, and it is difficult to collect information to support customized policies for the regional survey sites. In the case of special forests such as urban forests and major forests, policy and management appropriate to the forest characteristics are needed. Therefore, it is necessary to expand the survey headquarters for diagnosis and evaluation of customized forest health. For this reason, we have constructed a method of spatial scale through the spatial interpolation according to the characteristics of each index of the main sample point table of 29 index in the four points of diagnosis and evaluation report of the first forest health vitality report, PCA statistical analysis and correlative analysis are conducted to construct the indicators with significance, and then weights are selected for each index, and evaluation of forest health is conducted through statistical grading.

Apparatus and method for optimal phase balancing using dynamic programming with spatial consideration

DOEpatents

Robertazzi, Thomas G.; Skiena, Steven; Wang, Kai

2017-08-08

Provided are an apparatus and method for load-balancing of a three-phase electric power distribution system having a multi-phase feeder, including obtaining topology information of the feeder identifying supply points for customer loads and feeder sections between the supply points, obtaining customer information that includes peak customer load at each of the points between each of the feeder sections, performing a phase balancing analysis, and recommending phase assignment at the customer load supply points.

Wavenumber-frequency Spectra of Pressure Fluctuations Measured via Fast Response Pressure Sensitive Paint

NASA Technical Reports Server (NTRS)

Panda, J.; Roozeboom, N. H.; Ross, J. C.

2016-01-01

The recent advancement in fast-response Pressure-Sensitive Paint (PSP) allows time-resolved measurements of unsteady pressure fluctuations from a dense grid of spatial points on a wind tunnel model. This capability allows for direct calculations of the wavenumber-frequency (k-?) spectrum of pressure fluctuations. Such data, useful for the vibro-acoustics analysis of aerospace vehicles, are difficult to obtain otherwise. For the present work, time histories of pressure fluctuations on a flat plate subjected to vortex shedding from a rectangular bluff-body were measured using PSP. The light intensity levels in the photographic images were then converted to instantaneous pressure histories by applying calibration constants, which were calculated from a few dynamic pressure sensors placed at selective points on the plate. Fourier transform of the time-histories from a large number of spatial points provided k-? spectra for pressure fluctuations. The data provides first glimpse into the possibility of creating detailed forcing functions for vibro-acoustics analysis of aerospace vehicles, albeit for a limited frequency range.

Spatial Variations of DOM Compositions in the River with Multi-functional Weir

NASA Astrophysics Data System (ADS)

Yoon, S. M.; Choi, J. H.

2017-12-01

With the global trend to construct artificial impoundments over the last decades, there was a Large River Restoration Project conducted in South Korea from 2010 to 2011. The project included enlargement of river channel capacity and construction of multi-functional weirs, which can alter the hydrological flow of the river and cause spatial variations of water quality indicators, especially DOM (Dissolved Organic Matter) compositions. In order to analyze the spatial variations of organic matter, water samples were collected longitudinally (5 points upstream from the weir), horizontally (left, center, right at each point) and vertically (1m interval at each point). The specific UV-visible absorbance (SUVA) and fluorescence excitation-emission matrices (EEMs) have been used as rapid and non-destructive analytical methods for DOM compositions. In addition, parallel factor analysis (PARAFAC) has adopted for extracting a set of representative fluorescence components from EEMs. It was assumed that autochthonous DOM would be dominant near the weir due to the stagnation of hydrological flow. However, the results showed that the values of fluorescence index (FI) were 1.29-1.47, less than 2, indicating DOM of allochthonous origin dominated in the water near the weir. PARAFAC analysis also showed the peak at 450 nm of emission and < 250 nm of excitation which represented the humic substances group with terrestrial origins. There was no significant difference in the values of Biological index (BIX), however, values of humification index (HIX) spatially increased toward the weir. From the results of the water sample analysis, the river with multi-functional weir is influenced by the allochthonous DOM instead of autochthonous DOM and seems to accumulate humic substances near the weir.

Using vadose zone data and spatial statistics to assess the impact of cultivated land and dairy waste lagoons on groundwater contamination

NASA Astrophysics Data System (ADS)

Baram, S.; Ronen, Z.; Kurtzman, D.; Peeters, A.; Dahan, O.

2013-12-01

Land cultivation and dairy waste lagoons are considered to be nonpoint and point sources of groundwater contamination by chloride (Cl-) and nitrate (NO3-). The objective of this work is to introduce a methodology to assess the past and future impacts of such agricultural activities on regional groundwater quality. The method is based on mass balances and on spatial statistical analysis of Cl- and NO3-concentration distributions in the saturated and unsaturated zones. The method enables quantitative analysis of the relation between the locations of pollution point sources and the spatial variability in Cl- and NO3- concentrations in groundwater. The method was applied to the Beer-Tuvia region, Israel, where intensive dairy farming along with land cultivation has been practiced for over 50 years above the local phreatic aquifer. Mass balance calculations accounted for the various groundwater recharge and abstraction sources and sinks in the entire region. The mass balances showed that leachates from lagoons and the cultivated land have contributed 6.0 and 89.4 % of the total mass of Cl- added to the aquifer and 12.6 and 77.4 % of the total mass of NO3-. The chemical composition of the aquifer and vadose zone water suggested that irrigated agricultural activity in the region is the main contributor of Cl- and NO3- to the groundwater. A low spatial correlation between the Cl- and NO3- concentrations in the groundwater and the on-land location of the dairy farms strengthened this assumption, despite the dairy waste lagoon being a point source for groundwater contamination by Cl- and NO3-. Results demonstrate that analyzing vadose zone and groundwater data by spatial statistical analysis methods can significantly contribute to the understanding of the relations between groundwater contaminating sources, and to assessing appropriate remediation steps.

Multiple window spatial registration error of a gamma camera: 133Ba point source as a replacement of the NEMA procedure.

PubMed

Bergmann, Helmar; Minear, Gregory; Raith, Maria; Schaffarich, Peter M

2008-12-09

The accuracy of multiple window spatial resolution characterises the performance of a gamma camera for dual isotope imaging. In the present study we investigate an alternative method to the standard NEMA procedure for measuring this performance parameter. A long-lived 133Ba point source with gamma energies close to 67Ga and a single bore lead collimator were used to measure the multiple window spatial registration error. Calculation of the positions of the point source in the images used the NEMA algorithm. The results were validated against the values obtained by the standard NEMA procedure which uses a liquid 67Ga source with collimation. Of the source-collimator configurations under investigation an optimum collimator geometry, consisting of a 5 mm thick lead disk with a diameter of 46 mm and a 5 mm central bore, was selected. The multiple window spatial registration errors obtained by the 133Ba method showed excellent reproducibility (standard deviation < 0.07 mm). The values were compared with the results from the NEMA procedure obtained at the same locations and showed small differences with a correlation coefficient of 0.51 (p < 0.05). In addition, the 133Ba point source method proved to be much easier to use. A Bland-Altman analysis showed that the 133Ba and the 67Ga Method can be used interchangeably. The 133Ba point source method measures the multiple window spatial registration error with essentially the same accuracy as the NEMA-recommended procedure, but is easier and safer to use and has the potential to replace the current standard procedure.

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

Analysis of remote sensing data for evaluating vegetation resources

NASA Technical Reports Server (NTRS)

1971-01-01

Increased utilization studies for current remote sensor and analysis capabilities included: (1) a review of testing procedures for quantifying the accuracy of photointerpretation; (2) field tests of a fully portable spectral data gathering system, both on the ground and from a helicopter; and (3) a comparison of three methods for obtaining ground information necessary for regional agricultural inventories. A version of the LARS point-by-point classification system was upgraded by the addition of routines to analyze spatial data information.

Using R to implement spatial analysis in open source environment

NASA Astrophysics Data System (ADS)

Shao, Yixi; Chen, Dong; Zhao, Bo

2007-06-01

R is an open source (GPL) language and environment for spatial analysis, statistical computing and graphics which provides a wide variety of statistical and graphical techniques, and is highly extensible. In the Open Source environment it plays an important role in doing spatial analysis. So, to implement spatial analysis in the Open Source environment which we called the Open Source geocomputation is using the R data analysis language integrated with GRASS GIS and MySQL or PostgreSQL. This paper explains the architecture of the Open Source GIS environment and emphasizes the role R plays in the aspect of spatial analysis. Furthermore, one apt illustration of the functions of R is given in this paper through the project of constructing CZPGIS (Cheng Zhou Population GIS) supported by Changzhou Government, China. In this project we use R to implement the geostatistics in the Open Source GIS environment to evaluate the spatial correlation of land price and estimate it by Kriging Interpolation. We also use R integrated with MapServer and php to show how R and other Open Source software cooperate with each other in WebGIS environment, which represents the advantages of using R to implement spatial analysis in Open Source GIS environment. And in the end, we points out that the packages for spatial analysis in R is still scattered and the limited memory is still a bottleneck when large sum of clients connect at the same time. Therefore further work is to group the extensive packages in order or design normative packages and make R cooperate better with other commercial software such as ArcIMS. Also we look forward to developing packages for land price evaluation.

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

Assessing efficiency of spatial sampling using combined coverage analysis in geographical and feature spaces

NASA Astrophysics Data System (ADS)

Hengl, Tomislav

2015-04-01

Efficiency of spatial sampling largely determines success of model building. This is especially important for geostatistical mapping where an initial sampling plan should provide a good representation or coverage of both geographical (defined by the study area mask map) and feature space (defined by the multi-dimensional covariates). Otherwise the model will need to extrapolate and, hence, the overall uncertainty of the predictions will be high. In many cases, geostatisticians use point data sets which are produced using unknown or inconsistent sampling algorithms. Many point data sets in environmental sciences suffer from spatial clustering and systematic omission of feature space. But how to quantify these 'representation' problems and how to incorporate this knowledge into model building? The author has developed a generic function called 'spsample.prob' (Global Soil Information Facilities package for R) and which simultaneously determines (effective) inclusion probabilities as an average between the kernel density estimation (geographical spreading of points; analysed using the spatstat package in R) and MaxEnt analysis (feature space spreading of points; analysed using the MaxEnt software used primarily for species distribution modelling). The output 'iprob' map indicates whether the sampling plan has systematically missed some important locations and/or features, and can also be used as an input for geostatistical modelling e.g. as a weight map for geostatistical model fitting. The spsample.prob function can also be used in combination with the accessibility analysis (cost of field survey are usually function of distance from the road network, slope and land cover) to allow for simultaneous maximization of average inclusion probabilities and minimization of total survey costs. The author postulates that, by estimating effective inclusion probabilities using combined geographical and feature space analysis, and by comparing survey costs to representation efficiency, an optimal initial sampling plan can be produced which satisfies both criteria: (a) good representation (i.e. within a tolerance threshold), and (b) minimized survey costs. This sampling analysis framework could become especially interesting for generating sampling plans in new areas e.g. for which no previous spatial prediction model exists. The presentation includes data processing demos with standard soil sampling data sets Ebergotzen (Germany) and Edgeroi (Australia), also available via the GSIF package.

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

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

Keser, Saniye; Duzgun, Sebnem; Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara

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

Analyzing linear spatial features in ecology.

PubMed

Buettel, Jessie C; Cole, Andrew; Dickey, John M; Brook, Barry W

2018-06-01

The spatial analysis of dimensionless points (e.g., tree locations on a plot map) is common in ecology, for instance using point-process statistics to detect and compare patterns. However, the treatment of one-dimensional linear features (fiber processes) is rarely attempted. Here we appropriate the methods of vector sums and dot products, used regularly in fields like astrophysics, to analyze a data set of mapped linear features (logs) measured in 12 × 1-ha forest plots. For this demonstrative case study, we ask two deceptively simple questions: do trees tend to fall downhill, and if so, does slope gradient matter? Despite noisy data and many potential confounders, we show clearly that topography (slope direction and steepness) of forest plots does matter to treefall. More generally, these results underscore the value of mathematical methods of physics to problems in the spatial analysis of linear features, and the opportunities that interdisciplinary collaboration provides. This work provides scope for a variety of future ecological analyzes of fiber processes in space. © 2018 by the Ecological Society of America.

Spatial characteristics of observed precipitation fields: A catalog of summer storms in Arizona, Volume 2

NASA Technical Reports Server (NTRS)

Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodriguez-Iturbe, I.

1986-01-01

The parameters of the conceptual model are evaluated from the analysis of eight years of summer rainstorm data from the dense raingage network in the Walnut Gulch catchment near Tucson, Arizona. The occurrence of measurable rain at any one of the 93 gages during a noon to noon day defined a storm. The total rainfall at each of the gages during a storm day constituted the data set for a single storm. The data are interpolated onto a fine grid and analyzed to obtain: an isohyetal plot at 2 mm intervals, the first three moments of point storm depth, the spatial correlation function, the spatial variance function, and the spatial distribution of the total storm depth. The description of the data analysis and the computer programs necessary to read the associated data tapes are presented.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

Multidimensional extended spatial evolutionary games.

PubMed

Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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

Does the spatial arrangement of vegetation and anthropogenic land cover features matter? Case studies of urban warming and cooling in Phoenix and Las Vegas

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Fan, C.; Kaplan, S.; Brazel, A.; Middel, A.; Smith, M.

2014-12-01

While the relationship between fractional cover of anthropogenic and vegetation features and the urban heat island has been well studied, the effect of spatial arrangements (e.g., clustered, dispersed) of these features on urban warming or cooling are not well understood. The goal of this study is to examine if and how spatial configuration of land cover features influence land surface temperatures (LST) in urban areas. This study focuses on Phoenix, AZ and Las Vegas, NV that have undergone dramatic urban expansion. The data used to classify detailed urban land cover types include Geoeye-1 (Las Vegas) and QuickBird (Phoenix). The Geoeye-1 image (3 m resolution) was acquired on October 12, 2011 and the QuickBird image (2.4 m resolution) was taken on May 29, 2007. Classification was performed using object based image analysis (OBIA). We employed a spatial autocorrelation approach (i.e., Moran's I) that measures the spatial dependence of a point to its neighboring points and describes how clustered or dispersed points are arranged in space. We used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on June 10, 2011 and nighttime on October 17, 2011) and Las Vegas (daytime on July 6, 2005 and nighttime on August 27, 2005) to examine daytime and nighttime LST with regards to the spatial arrangement of anthropogenic and vegetation features. We spatially correlate Moran's I values of each land cover per surface temperature, and develop regression models. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, a clustered spatial arrangement of anthropogenic land-cover features, especially impervious surfaces, significantly elevates surface temperatures. Results from this study suggest that the spatial configuration of anthropogenic and vegetation features influence urban warming and cooling.

Spatial interpolation of hourly precipitation and dew point temperature for the identification of precipitation phase and hydrologic response in a mountainous catchment

NASA Astrophysics Data System (ADS)

Garen, D. C.; Kahl, A.; Marks, D. G.; Winstral, A. H.

2012-12-01

In mountainous catchments, it is well known that meteorological inputs, such as precipitation, air temperature, humidity, etc. vary greatly with elevation, spatial location, and time. Understanding and monitoring catchment inputs is necessary in characterizing and predicting hydrologic response to these inputs. This is true all of the time, but it is the most dramatically critical during large storms, when the input to the stream system due to rain and snowmelt creates the potential for flooding. Besides such crisis events, however, proper estimation of catchment inputs and their spatial distribution is also needed in more prosaic but no less important water and related resource management activities. The first objective of this study is to apply a geostatistical spatial interpolation technique (elevationally detrended kriging) to precipitation and dew point temperature on an hourly basis and explore its characteristics, accuracy, and other issues. The second objective is to use these spatial fields to determine precipitation phase (rain or snow) during a large, dynamic winter storm. The catchment studied is the data-rich Reynolds Creek Experimental Watershed near Boise, Idaho. As part of this analysis, precipitation-elevation lapse rates are examined for spatial and temporal consistency. A clear dependence of lapse rate on precipitation amount exists. Certain stations, however, are outliers from these relationships, showing that significant local effects can be present and raising the question of whether such stations should be used for spatial interpolation. Experiments with selecting subsets of stations demonstrate the importance of elevation range and spatial placement on the interpolated fields. Hourly spatial fields of precipitation and dew point temperature are used to distinguish precipitation phase during a large rain-on-snow storm in December 2005. This application demonstrates the feasibility of producing hourly spatial fields and the importance of doing so to support an accurate determination of precipitation phase for assessing catchment hydrologic response to the storm.

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

PubMed

Lakes, Tobia

2017-12-01

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

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

PubMed

Fitterer, Jessica L; Nelson, Trisalyn A

2015-01-01

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime

PubMed Central

Fitterer, Jessica L.; Nelson, Trisalyn A.

2015-01-01

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks). PMID:26418016

Spatial and temporal statistical analysis of bycatch data: Patterns of sea turtle bycatch in the North Atlantic

USGS Publications Warehouse

Gardner, B.; Sullivan, P.J.; Morreale, S.J.; Epperly, S.P.

2008-01-01

Loggerhead (Caretta caretta) and leatherback (Dermochelys coriacea) sea turtle distributions and movements in offshore waters of the western North Atlantic are not well understood despite continued efforts to monitor, survey, and observe them. Loggerhead and leatherback sea turtles are listed as endangered by the World Conservation Union, and thus anthropogenic mortality of these species, including fishing, is of elevated interest. This study quantifies spatial and temporal patterns of sea turtle bycatch distributions to identify potential processes influencing their locations. A Ripley's K function analysis was employed on the NOAA Fisheries Atlantic Pelagic Longline Observer Program data to determine spatial, temporal, and spatio-temporal patterns of sea turtle bycatch distributions within the pattern of the pelagic fishery distribution. Results indicate that loggerhead and leatherback sea turtle catch distributions change seasonally, with patterns of spatial clustering appearing from July through October. The results from the space-time analysis indicate that sea turtle catch distributions are related on a relatively fine scale (30-200 km and 1-5 days). The use of spatial and temporal point pattern analysis, particularly K function analysis, is a novel way to examine bycatch data and can be used to inform fishing practices such that fishing could still occur while minimizing sea turtle bycatch. ?? 2008 NRC.

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.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

[Chronic Malnutrition among Children under Five in Peru: A Spatial Analysis of Nutritional Data, 2010-2016].

PubMed

Hernández-Vásquez, Akram; Tapia-López, Elena

2017-05-19

Peru has implemented various strategies seeking to improve nutritional indicators in children under five years old. However, high prevalence of malnutrition in some regions still remains. The aim of this study was to assess changes in regional prevalence and to determine the presence of district conglomerates with a high prevalence of chronic childhood malnutrition (CCM) in 2010 and 2016. A comparative descriptive analysis by regions and a district-level spatial analysis were conducted employing indicators reported by the Nutritional Status Information System. 23.9% (561.090/2.343.806) children under five years evaluated in Peru during 2010 and 18.0% (394.049/2.193.268) evaluated during 2016 were chronic malnutrition (reduction of 5.9 percentage points). We identified a decline of 7.6 percent points in rural areas and the persistence of prevalence above 30% in only one region (Huancavelica). The spatial analysis identified clusters of districts with high prevalence in 20% (379/1834) of Peruvian districts in 2010, and 17.2% (316/1834) of those in 2016, which are mainly spread across the sierra and jungle regions. . Peru has made significant progress in reducing stunting in children. Nevertheless, it still represents a health problem due to high prevalence in the sierra region, as well as expansion to jungle districts in 2016. Licencia Creative Commons Atribución-NoComercial-SinDerivadas 3.0 Unported Licencia Creative Commons

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Microphone array measurement system for analysis of directional and spatial variations of sound fields.

PubMed

Gover, Bradford N; Ryan, James G; Stinson, Michael R

2002-11-01

A measurement system has been developed that is capable of analyzing the directional and spatial variations in a reverberant sound field. A spherical, 32-element array of microphones is used to generate a narrow beam that is steered in 60 directions. Using an omnidirectional loudspeaker as excitation, the sound pressure arriving from each steering direction is measured as a function of time, in the form of pressure impulse responses. By subsequent analysis of these responses, the variation of arriving energy with direction is studied. The directional diffusion and directivity index of the arriving sound can be computed, as can the energy decay rate in each direction. An analysis of the 32 microphone responses themselves allows computation of the point-to-point variation of reverberation time and of sound pressure level, as well as the spatial cross-correlation coefficient, over the extent of the array. The system has been validated in simple sound fields in an anechoic chamber and in a reverberation chamber. The system characterizes these sound fields as expected, both quantitatively from the measures and qualitatively from plots of the arriving energy versus direction. It is anticipated that the system will be of value in evaluating the directional distribution of arriving energy and the degree and diffuseness of sound fields in rooms.

spsann - optimization of sample patterns using spatial simulated annealing

NASA Astrophysics Data System (ADS)

Samuel-Rosa, Alessandro; Heuvelink, Gerard; Vasques, Gustavo; Anjos, Lúcia

2015-04-01

There are many algorithms and computer programs to optimize sample patterns, some private and others publicly available. A few have only been presented in scientific articles and text books. This dispersion and somewhat poor availability is holds back to their wider adoption and further development. We introduce spsann, a new R-package for the optimization of sample patterns using spatial simulated annealing. R is the most popular environment for data processing and analysis. Spatial simulated annealing is a well known method with widespread use to solve optimization problems in the soil and geo-sciences. This is mainly due to its robustness against local optima and easiness of implementation. spsann offers many optimizing criteria for sampling for variogram estimation (number of points or point-pairs per lag distance class - PPL), trend estimation (association/correlation and marginal distribution of the covariates - ACDC), and spatial interpolation (mean squared shortest distance - MSSD). spsann also includes the mean or maximum universal kriging variance (MUKV) as an optimizing criterion, which is used when the model of spatial variation is known. PPL, ACDC and MSSD were combined (PAN) for sampling when we are ignorant about the model of spatial variation. spsann solves this multi-objective optimization problem scaling the objective function values using their maximum absolute value or the mean value computed over 1000 random samples. Scaled values are aggregated using the weighted sum method. A graphical display allows to follow how the sample pattern is being perturbed during the optimization, as well as the evolution of its energy state. It is possible to start perturbing many points and exponentially reduce the number of perturbed points. The maximum perturbation distance reduces linearly with the number of iterations. The acceptance probability also reduces exponentially with the number of iterations. R is memory hungry and spatial simulated annealing is a computationally intensive method. As such, many strategies were used to reduce the computation time and memory usage: a) bottlenecks were implemented in C++, b) a finite set of candidate locations is used for perturbing the sample points, and c) data matrices are computed only once and then updated at each iteration instead of being recomputed. spsann is available at GitHub under a licence GLP Version 2.0 and will be further developed to: a) allow the use of a cost surface, b) implement other sensitive parts of the source code in C++, c) implement other optimizing criteria, d) allow to add or delete points to/from an existing point pattern.

Environmental assessment of spatial plan policies through land use scenarios

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

Geneletti, Davide, E-mail: davide.geneletti@ing.unitn.it

2012-01-15

This paper presents a method based on scenario analysis to compare the environmental effects of different spatial plan policies in a range of possible futures. The study aimed at contributing to overcome two limitations encountered in Strategic Environmental Assessment (SEA) for spatial planning: poor exploration of how the future might unfold, and poor consideration of alternative plan policies. Scenarios were developed through what-if functions and spatial modeling in a Geographical Information System (GIS), and consisted in maps that represent future land uses under different assumptions on key driving forces. The use of land use scenarios provided a representation of howmore » the different policies will look like on the ground. This allowed gaining a better understanding of the policies' implications on the environment, which could be measured through a set of indicators. The research undertook a case-study approach by developing and assessing land use scenarios for the future growth of Caia, a strategically-located and fast-developing town in rural Mozambique. The effects of alternative spatial plan policies were assessed against a set of environmental performance indicators, including deforestation, loss of agricultural land, encroachment of flood-prone areas and wetlands and access to water sources. In this way, critical environmental effects related to the implementation of each policy were identified and discussed, suggesting possible strategies to address them. - Graphical abstract: Display Omitted Research Highlights: Black-Right-Pointing-Pointer The method contributes to two critical issues in SEA: exploration of the future and consideration of alternatives. Black-Right-Pointing-Pointer Future scenarios are used to test the environmental performance of different spatial plan policies in uncertainty conditions. Black-Right-Pointing-Pointer Spatially-explicit land use scenarios provide a representation of how different policies will look like on the ground.« less

Clusters in irregular areas and lattices.

PubMed

Wieczorek, William F; Delmerico, Alan M; Rogerson, Peter A; Wong, David W S

2012-01-01

Geographic areas of different sizes and shapes of polygons that represent counts or rate data are often encountered in social, economic, health, and other information. Often political or census boundaries are used to define these areas because the information is available only for those geographies. Therefore, these types of boundaries are frequently used to define neighborhoods in spatial analyses using geographic information systems and related approaches such as multilevel models. When point data can be geocoded, it is possible to examine the impact of polygon shape on spatial statistical properties, such as clustering. We utilized point data (alcohol outlets) to examine the issue of polygon shape and size on visualization and statistical properties. The point data were allocated to regular lattices (hexagons and squares) and census areas for zip-code tabulation areas and tracts. The number of units in the lattices was set to be similar to the number of tract and zip-code areas. A spatial clustering statistic and visualization were used to assess the impact of polygon shape for zip- and tract-sized units. Results showed substantial similarities and notable differences across shape and size. The specific circumstances of a spatial analysis that aggregates points to polygons will determine the size and shape of the areal units to be used. The irregular polygons of census units may reflect underlying characteristics that could be missed by large regular lattices. Future research to examine the potential for using a combination of irregular polygons and regular lattices would be useful.

UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica)

NASA Astrophysics Data System (ADS)

Dąbski, Maciej; Zmarz, Anna; Pabjanek, Piotr; Korczak-Abshire, Małgorzata; Karsznia, Izabela; Chwedorzewska, Katarzyna J.

2017-08-01

High-resolution aerial images allow detailed analyses of periglacial landforms, which is of particular importance in light of climate change and resulting changes in active layer thickness. The aim of this study is to show possibilities of using UAV-based photography to perform spatial analysis of periglacial landforms on the Demay Point peninsula, King George Island, and hence to supplement previous geomorphological studies of the South Shetland Islands. Photogrammetric flights were performed using a PW-ZOOM fixed-winged unmanned aircraft vehicle. Digital elevation models (DEM) and maps of slope and contour lines were prepared in ESRI ArcGIS 10.3 with the Spatial Analyst extension, and three-dimensional visualizations in ESRI ArcScene 10.3 software. Careful interpretation of orthophoto and DEM, allowed us to vectorize polygons of landforms, such as (i) solifluction landforms (solifluction sheets, tongues, and lobes); (ii) scarps, taluses, and a protalus rampart; (iii) patterned ground (hummocks, sorted circles, stripes, nets and labyrinths, and nonsorted nets and stripes); (iv) coastal landforms (cliffs and beaches); (v) landslides and mud flows; and (vi) stone fields and bedrock outcrops. We conclude that geomorphological studies based on commonly accessible aerial and satellite images can underestimate the spatial extent of periglacial landforms and result in incomplete inventories. The PW-ZOOM UAV is well suited to gather detailed geomorphological data and can be used in spatial analysis of periglacial landforms in the Western Antarctic Peninsula region.

Congruence analysis of point clouds from unstable stereo image sequences

NASA Astrophysics Data System (ADS)

Jepping, C.; Bethmann, F.; Luhmann, T.

2014-06-01

This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.

Using Open data in analyzing urban growth: urban density and change detection

NASA Astrophysics Data System (ADS)

murgante, Beniamino; Nolè, Gabriele; Lasaponara, Rosa; Lanorte, Antonio

2013-04-01

In recent years a great attention has been paid to the evolution and the use of spatial data. Internet technologies accelerated such a process, allowing more direct access to spatial information. It is estimated that more than 600 million people have been connected to the Internet at least once to display maps on the web. Consequently, there is an irreversible process which considers geographical dimension as a fundamental attribute for the management of information flows. Furthermore, the great activity produced by open data movement leads to an easier and clearer access to geospatial information. This trend concerns, in a less evident way, also satellite data, which are increasingly accessible through the web. Spatial planning, geography and other regional sciences find it difficult to build knowledge related to spatial transformation. These problems can be significantly reduced due to a large data availability, producing significant opportunities to capture knowledge useful for a better territorial governance. This study has been developed in a heavily anthropized area in southern Italy, Apulia region, using free spatial data and free multispectral and multitemporal satellite data (Apulia region was one of the first regions in Italy to adopt open data policies). The analysis concerns urban growth, which, in recent decades, showed a rapid increase. In a first step the evolution in time and change detection of urban areas has been analyzed paying particular attention to soil consumption. In the second step Kernel Density has been adopted in order to assess development pressures. KDE (Kernel Density Estimation) function is a technique that provides the density of a phenomenon based on point data. A mobile three dimensional surface has been produced from a set of points distributed over a region of space, which weighs the events within its sphere of influence, depending on their distance from the point from which intensity is estimated. It produces, considering as input point data (vector), a density continuous raster as an output. In this case, the intensity of phenomenon will be given by buildings volume. References • Bailey T. C., Gatrell A. C. (1995). Interactive spatial data analysis. Prentice Hall. • Danese M., Lazzari M., Murgante B. (2009). "Geostatistics in Historical Macroseismic Data Analysis" Transactions on Computational Sciences VI, LNCS Vol. 5730, pp. 324-341, Springer-Verlag, Berlin ISSN: 1611-3349, doi:10.1007/978-3-642-10649-1_19 • Nolè G., Danese M., Murgante B., Lasaponara R., Lanorte, A., (2012) "Using Spatial Autocorrelation Techniques and Multi-temporal Satellite Data for Analyzing Urban Sprawl" Lecture Notes in Computer Science vol. 7335, pp. 512-527. Springer-Verlag, Berlin. ISSN: 0302-9743, doi: 10.1007/978-3-642-31137-6_39 • Murgante, B., Las Casas, G., Danese, M., (2012), "Analyzing Neighbourhoods Suitable for Urban Renewal Programs with Autocorrelation Techniques" In Burian J. (Eds.) "Advances in Spatial Planning" InTech — Open Access DOI: 10.5772/33747 ISBN:978-953-51-0377-6 • Lanorte, A., Danese M., Lasaponara R., Murgante B. (2011) "Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis" International Journal of Applied Earth Observation and Geoinformation, Elsevier, doi:10.1016/j.jag.2011.09.005 • O'Sullivan D., Unwin D., (2002). Geographic Information Analysis. John Wiley & Sons • Yang, X., Lo, C. P.: Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. Int. J. Rem. Sensing 23, pp. 1775--1798 (2002) • Yuan, F., Sawaya, K.,.Loeffelholz, B. C., Bauer, M. E.: Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing. Rem. Sensing Environ. 98, pp. 317--328 (2005)

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

NASA Astrophysics Data System (ADS)

Lakshmi Madhavan, Bomidi; Deneke, Hartwig; Witthuhn, Jonas; Macke, Andreas

2017-03-01

The time series of global radiation observed by a dense network of 99 autonomous pyranometers during the HOPE campaign around Jülich, Germany, are investigated with a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet. For different sky conditions, typical wavelet power spectra are calculated to quantify the timescale dependence of variability in global transmittance. Distinctly higher variability is observed at all frequencies in the power spectra of global transmittance under broken-cloud conditions compared to clear, cirrus, or overcast skies. The spatial autocorrelation function including its frequency dependence is determined to quantify the degree of similarity of two time series measurements as a function of their spatial separation. Distances ranging from 100 m to 10 km are considered, and a rapid decrease of the autocorrelation function is found with increasing frequency and distance. For frequencies above 1/3 min-1 and points separated by more than 1 km, variations in transmittance become completely uncorrelated. A method is introduced to estimate the deviation between a point measurement and a spatially averaged value for a surrounding domain, which takes into account domain size and averaging period, and is used to explore the representativeness of a single pyranometer observation for its surrounding region. Two distinct mechanisms are identified, which limit the representativeness; on the one hand, spatial averaging reduces variability and thus modifies the shape of the power spectrum. On the other hand, the correlation of variations of the spatially averaged field and a point measurement decreases rapidly with increasing temporal frequency. For a grid box of 10 km × 10 km and averaging periods of 1.5-3 h, the deviation of global transmittance between a point measurement and an area-averaged value depends on the prevailing sky conditions: 2.8 (clear), 1.8 (cirrus), 1.5 (overcast), and 4.2 % (broken clouds). The solar global radiation observed at a single station is found to deviate from the spatial average by as much as 14-23 (clear), 8-26 (cirrus), 4-23 (overcast), and 31-79 W m-2 (broken clouds) from domain averages ranging from 1 km × 1 km to 10 km × 10 km in area.

Landslide activity as a threat to infrastructure in river valleys - An example from outer Western Carpathians (Poland)

NASA Astrophysics Data System (ADS)

Łuszczyńska, Katarzyna; Wistuba, Małgorzata; Malik, Ireneusz

2017-11-01

Intensive development of the area of Polish Carpathians increases the scale of landslide risk. Thus detecting landslide hazards and risks became important issue for spatial planning in the area. We applied dendrochronological methods and GIS analysis for better understanding of landslide activity and related hazards in the test area (3,75 km2): Salomonka valley and nearby slopes in the Beskid Żywiecki Mts., Outer Western Carpathians, southern Poland. We applied eccentricity index of radial growth of trees to date past landslide events. Dendrochronological results allowed us to determine the mean frequency of landsliding at each sampling point which were next interpolated into a map of landslide hazard. In total we took samples at 46 points. In each point we sampled 3 coniferous trees. Landslide hazard map shows a medium (23 sampling points) and low (20 sampling points) level of landslide activity for most of the area. The highest level of activity was recorded for the largest landslide. Results of the dendrochronological study suggest that all landslides reaching downslope to Salomonka valley floor are active. LiDAR-based analysis of relief shows that there is an active coupling between those landslides and river channel. Thus channel damming and formation of an episodic lake are probable. The hazard of flooding valley floor upstream of active landslides should be included in the local spatial planning system and crisis management system.

Applicability of Various Interpolation Approaches for High Resolution Spatial Mapping of Climate Data in Korea

NASA Astrophysics Data System (ADS)

Jo, A.; Ryu, J.; Chung, H.; Choi, Y.; Jeon, S.

2018-04-01

The purpose of this study is to create a new dataset of spatially interpolated monthly climate data for South Korea at high spatial resolution (approximately 30m) by performing various spatio-statistical interpolation and comparing with forecast LDAPS gridded climate data provided from Korea Meterological Administration (KMA). Automatic Weather System (AWS) and Automated Synoptic Observing System (ASOS) data in 2017 obtained from KMA were included for the spatial mapping of temperature and rainfall; instantaneous temperature and 1-hour accumulated precipitation at 09:00 am on 31th March, 21th June, 23th September, and 24th December. Among observation data, 80 percent of the total point (478) and remaining 120 points were used for interpolations and for quantification, respectively. With the training data and digital elevation model (DEM) with 30 m resolution, inverse distance weighting (IDW), co-kriging, and kriging were performed by using ArcGIS10.3.1 software and Python 3.6.4. Bias and root mean square were computed to compare prediction performance quantitatively. When statistical analysis was performed for each cluster using 20 % validation data, co kriging was more suitable for spatialization of instantaneous temperature than other interpolation method. On the other hand, IDW technique was appropriate for spatialization of precipitation.

Short-Term Environmental Effects and Their Influence on Spatial Homogeneity of Organic Solar Cell Functionality.

PubMed

Chien, Huei-Ting; Zach, Peter W; Friedel, Bettina

2017-08-23

In this study, we focus on the induced degradation and spatial inhomogeneity of organic photovoltaic devices under different environmental conditions, uncoupled from the influence of any auxiliary hole-transport (HT) layer. During testing of the corresponding devices comprising the standard photoactive layer of poly(3-hexylthiophene) as donor, blended with phenyl-C 61 -butyric acid methyl ester as acceptor, a comparison was made between the nonencapsulated devices upon exposure to argon in the dark, dry air in the dark, dry air with illumination, and humid air in the dark. The impact on the active layer's photophysics is discussed, along with the device physics in terms of integral solar cell performance and spatially resolved photocurrent distribution with point-to-point analysis of the diode characteristics to determine the origin of the observed integrated organic photovoltaic device behavior. The results show that even without the widely used hygroscopic HT layer, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate), humidity is still a major factor in the short-term environmental degradation of organic solar cells with this architecture, and not only oxygen or light, as is often reported. Different from previous reports where water-induced device degradation was spatially homogeneous and formation of Al 2 O 3 islands was only seen for oxygen permeation through pinholes in aluminum, we observed insulating islands merely after humidity exposure in the present study. Further, we demonstrated with laser beam induced current mapping and point-to-point diode analysis that the water-induced performance losses are a result of the exposed device area comprising regions with entirely unaltered high output and intact diode behavior and those with severe degradation showing detrimentally lowered output and voltage-independent charge blocking, which is essentially insulating behavior. It is suggested that this is caused by transport of water through pinholes to the organic/metal interface, where they form insulating oxide or hydroxide islands, while the organic active layer stays unharmed.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

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.

Application of the integral manifold method to the analysis of the spatial motion of a rigid body fixed to a cable

NASA Astrophysics Data System (ADS)

Zabolotnov, Yu. M.

2016-07-01

We analyze the spatial motion of a rigid body fixed to a cable about its center of mass when the orbital cable system is unrolling. The analysis is based on the integral manifold method, which permits separating the rigid body motion into the slow and fast components. The motion of the rigid body is studied in the case of slow variations in the cable tension force and under the action of various disturbances.We estimate the influence of the static and dynamic asymmetry of the rigid body on its spatial motion about the cable fixation point. An example of the analysis of the rigid body motion when the orbital cable system is unrolling is given for a special program of variations in the cable tension force. The conditions of applicability of the integral manifold method are analyzed.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

NASA Astrophysics Data System (ADS)

Gong, Kuang; Cherry, Simon R.; Qi, Jinyi

2016-03-01

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

Parents' Spatial Language Mediates a Sex Difference in Preschoolers' Spatial-Language Use.

PubMed

Pruden, Shannon M; Levine, Susan C

2017-11-01

Do boys produce more terms than girls to describe the spatial world-that is, dimensional adjectives (e.g., big, little, tall, short), shape terms (e.g., circle, square), and words describing spatial features and properties (e.g., bent, curvy, edge)? If a sex difference in children's spatial-language use exists, is it related to the spatial language that parents use when interacting with children? We longitudinally tracked the development of spatial-language production in children between the ages of 14 and 46 months in a diverse sample of 58 parent-child dyads interacting in their homes. Boys produced and heard more of these three categories of spatial words, which we call "what" spatial types (i.e., unique "what" spatial words), but not more of all other word types, than girls. Mediation analysis revealed that sex differences in children's spatial talk at 34 to 46 months of age were fully mediated by parents' earlier spatial-language use, when children were 14 to 26 months old, time points at which there was no sex difference in children's spatial-language use.

Using stochastic models to incorporate spatial and temporal variability [Exercise 14

Treesearch

Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke

2003-01-01

To this point, our analysis of population processes and viability in the western prairie fringed orchid has used only deterministic models. In this exercise, we conduct a similar analysis, using a stochastic model instead. This distinction is of great importance to population biology in general and to conservation biology in particular. In deterministic models,...

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.

Effect of Spatial Resolution for Characterizing Soil Properties from Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Dutta, D.; Kumar, P.; Greenberg, J. A.

2015-12-01

The feasibility of quantifying soil constituents over large areas using airborne hyperspectral data [0.35 - 2.5 μm] in an ensemble bootstrapping lasso algorithmic framework has been demonstrated previously [1]. However the effects of coarsening the spatial resolution of hyperspectral data on the quantification of soil constituents are unknown. We use Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected at 7.6m resolution over Birds Point New Madrid (BPNM) floodway for up-scaling and generating multiple coarser resolution datasets including the 60m Hyperspectral Infrared Imager (HyspIRI) like data. HyspIRI is a proposed visible shortwave/thermal infrared mission, which will provide global data over a spectral range of 0.35 - 2.5μm at a spatial resolution of 60m. Our results show that the lasso method, which is based on point scale observational data, is scalable. We found consistent good model performance (R2) values (0.79 < R2 < 0.82) and correct classifications as per USDA soil texture classes at multiple spatial resolutions. The results further demonstrate that the attributes of the pdf for different soil constituents across the landscape and the within-pixel variance are well preserved across scales. Our analysis provides a methodological framework with a sufficient set of metrics for assessing the performance of scaling up analysis from point scale observational data and may be relevant for other similar remote sensing studies. [1] Dutta, D.; Goodwell, A.E.; Kumar, P.; Garvey, J.E.; Darmody, R.G.; Berretta, D.P.; Greenberg, J.A., "On the Feasibility of Characterizing Soil Properties From AVIRIS Data," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.9, pp.5133,5147, Sept. 2015. doi: 10.1109/TGRS.2015.2417547.

Denoising, deconvolving, and decomposing photon observations. Derivation of the D3PO algorithm

NASA Astrophysics Data System (ADS)

Selig, Marco; Enßlin, Torsten A.

2015-02-01

The analysis of astronomical images is a non-trivial task. The D3PO algorithm addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. In order to discriminate between these morphologically different signal components, a probabilistic algorithm is derived in the language of information field theory based on a hierarchical Bayesian parameter model. The signal inference exploits prior information on the spatial correlation structure of the diffuse component and the brightness distribution of the spatially uncorrelated point-like sources. A maximum a posteriori solution and a solution minimizing the Gibbs free energy of the inference problem using variational Bayesian methods are discussed. Since the derivation of the solution is not dependent on the underlying position space, the implementation of the D3PO algorithm uses the nifty package to ensure applicability to various spatial grids and at any resolution. The fidelity of the algorithm is validated by the analysis of simulated data, including a realistic high energy photon count image showing a 32 × 32 arcmin2 observation with a spatial resolution of 0.1 arcmin. In all tests the D3PO algorithm successfully denoised, deconvolved, and decomposed the data into a diffuse and a point-like signal estimate for the respective photon flux components. A copy of the code is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/574/A74

Spatial bedrock erosion distribution in a natural gorge

NASA Astrophysics Data System (ADS)

Beer, A. R.; Turowski, J. M.; Kirchner, J. W.

2015-12-01

Quantitative analysis of morphological evolution both in terrestrial and planetary landscapes is of increasing interest in the geosciences. In mountainous regions, bedrock channel formation as a consequence of the interaction of uplift and erosion processes is fundamental for the entire surface evolution. Hence, the accurate description of bedrock channel development is important for landscape modelling. To verify existing concepts developed in the lab and to analyse how in situ channel erosion rates depend on the interrelations of discharge, sediment transport and topography, there is a need of highly resolved topographic field data. We analyse bedrock erosion over two years in a bedrock gorge downstream of the Gorner glacier above the town of Zermatt, Switzerland. At the study site, the Gornera stream cuts through a roche moutonnée in serpentine rock of 25m length, 5m width and 8m depth. We surveyed bedrock erosion rates using repeat terrestrial laser scanning (TLS) with an average point spacing of 5mm. Bedrock erosion rates in direction of the individual surface normals were studied directly on the scanned point clouds applying the M3C2 algorithm (Lague et al., 2013, ISPRS). The surveyed erosion patterns were compared to a simple stream erosivity visualisation obtained from painted bedrock sections at the study location. Spatially distributed erosion rates on bedrock surfaces based on millions of scan points allow deduction of millimeter-scale mean annual values of lateral erosion, incision and downstream erosion on protruding streambed surfaces. The erosion rate on a specific surface point is shown to depend on the position of this surface point in the channel's cross section, its height above the streambed and its spatial orientation to the streamflow. Abrasion by impacting bedload was likely the spatially dominant erosion process, as confirmed by the observed patterns along the painted bedrock sections. However, a single plucking event accounted for the half of the total eroded material. Our results demonstrate the practicability of TLS for highly resolved spatio-temporal erosion monitoring in the field and quantitatively confirm concepts of spatially varying erosion rates based current thinking. Furthermore, we introduce an easy-to-apply method for qualitative spatial erosion detection by paint.

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

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

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less

Determining the Number of Clusters in a Data Set Without Graphical Interpretation

NASA Technical Reports Server (NTRS)

Aguirre, Nathan S.; Davies, Misty D.

2011-01-01

Cluster analysis is a data mining technique that is meant ot simplify the process of classifying data points. The basic clustering process requires an input of data points and the number of clusters wanted. The clustering algorithm will then pick starting C points for the clusters, which can be either random spatial points or random data points. It then assigns each data point to the nearest C point where "nearest usually means Euclidean distance, but some algorithms use another criterion. The next step is determining whether the clustering arrangement this found is within a certain tolerance. If it falls within this tolerance, the process ends. Otherwise the C points are adjusted based on how many data points are in each cluster, and the steps repeat until the algorithm converges,

Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

PubMed

Esposito, Fabrizio; Formisano, Elia; Seifritz, Erich; Goebel, Rainer; Morrone, Renato; Tedeschi, Gioacchino; Di Salle, Francesco

2002-07-01

Independent component analysis (ICA) has been successfully employed to decompose functional MRI (fMRI) time-series into sets of activation maps and associated time-courses. Several ICA algorithms have been proposed in the neural network literature. Applied to fMRI, these algorithms might lead to different spatial or temporal readouts of brain activation. We compared the two ICA algorithms that have been used so far for spatial ICA (sICA) of fMRI time-series: the Infomax (Bell and Sejnowski [1995]: Neural Comput 7:1004-1034) and the Fixed-Point (Hyvärinen [1999]: Adv Neural Inf Proc Syst 10:273-279) algorithms. We evaluated the Infomax- and Fixed Point-based sICA decompositions of simulated motor, and real motor and visual activation fMRI time-series using an ensemble of measures. Log-likelihood (McKeown et al. [1998]: Hum Brain Mapp 6:160-188) was used as a measure of how significantly the estimated independent sources fit the statistical structure of the data; receiver operating characteristics (ROC) and linear correlation analyses were used to evaluate the algorithms' accuracy of estimating the spatial layout and the temporal dynamics of simulated and real activations; cluster sizing calculations and an estimation of a residual gaussian noise term within the components were used to examine the anatomic structure of ICA components and for the assessment of noise reduction capabilities. Whereas both algorithms produced highly accurate results, the Fixed-Point outperformed the Infomax in terms of spatial and temporal accuracy as long as inferential statistics were employed as benchmarks. Conversely, the Infomax sICA was superior in terms of global estimation of the ICA model and noise reduction capabilities. Because of its adaptive nature, the Infomax approach appears to be better suited to investigate activation phenomena that are not predictable or adequately modelled by inferential techniques. Copyright 2002 Wiley-Liss, Inc.

False Discovery Control in Large-Scale Spatial Multiple Testing

PubMed Central

Sun, Wenguang; Reich, Brian J.; Cai, T. Tony; Guindani, Michele; Schwartzman, Armin

2014-01-01

Summary This article develops a unified theoretical and computational framework for false discovery control in multiple testing of spatial signals. We consider both point-wise and cluster-wise spatial analyses, and derive oracle procedures which optimally control the false discovery rate, false discovery exceedance and false cluster rate, respectively. A data-driven finite approximation strategy is developed to mimic the oracle procedures on a continuous spatial domain. Our multiple testing procedures are asymptotically valid and can be effectively implemented using Bayesian computational algorithms for analysis of large spatial data sets. Numerical results show that the proposed procedures lead to more accurate error control and better power performance than conventional methods. We demonstrate our methods for analyzing the time trends in tropospheric ozone in eastern US. PMID:25642138

Spectral analysis and filtering techniques in digital spatial data processing

USGS Publications Warehouse

Pan, Jeng-Jong

1989-01-01

A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

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.

Geostatistical analysis of disease data: accounting for spatial support and population density in the isopleth mapping of cancer mortality risk using area-to-point Poisson kriging

PubMed Central

Goovaerts, Pierre

2006-01-01

Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data) is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1) state of Indiana that consists of 92 counties of fairly similar size and shape, and 2) four states in the Western US (Arizona, California, Nevada and Utah) forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP) Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth maps is the common biased visual perception that larger rural and sparsely populated areas are of greater importance. The approach presented in this paper allows the continuous mapping of mortality risk, while accounting locally for population density and areal data through the coherence constraint. This form of Poisson kriging will facilitate the analysis of relationships between health data and putative covariates that are typically measured over different spatial supports. PMID:17137504

Optical communication for space missions

NASA Technical Reports Server (NTRS)

Firtmaurice, M.

1991-01-01

Activities performed at NASA/GSFC (Goddard Space Flight Center) related to direct detection optical communications for space applications are discussed. The following subject areas are covered: (1) requirements for optical communication systems (data rates and channel quality; spatial acquisition; fine tracking and pointing; and transmit point-ahead correction); (2) component testing and development (laser diodes performance characterization and life testing; and laser diode power combining); (3) system development and simulations (The GSFC pointing, acquisition and tracking system; hardware description; preliminary performance analysis; and high data rate transmitter/receiver systems); and (4) proposed flight demonstration of optical communications.

Spatial analyses for nonoverlapping objects with size variations and their application to coral communities.

PubMed

Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko

2014-07-01

Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Spatial point analysis based on dengue surveys at household level in central Brazil

PubMed Central

Siqueira-Junior, João B; Maciel, Ivan J; Barcellos, Christovam; Souza, Wayner V; Carvalho, Marilia S; Nascimento, Nazareth E; Oliveira, Renato M; Morais-Neto, Otaliba; Martelli, Celina MT

2008-01-01

Background Dengue virus (DENV) affects nonimunne human populations in tropical and subtropical regions. In the Americas, dengue has drastically increased in the last two decades and Brazil is considered one of the most affected countries. The high frequency of asymptomatic infection makes difficult to estimate prevalence of infection using registered cases and to locate high risk intra-urban area at population level. The goal of this spatial point analysis was to identify potential high-risk intra-urban areas of dengue, using data collected at household level from surveys. Methods Two household surveys took place in the city of Goiania (~1.1 million population), Central Brazil in the year 2001 and 2002. First survey screened 1,586 asymptomatic individuals older than 5 years of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were selected by multistage sampling (census tracts; blocks; households) using available digital maps. Sera from participants were tested by dengue virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to detect the spatial varying risk over the region. Initially without any fixed covariates, to depict the overall risk map, followed by a model including the main covariates and the year, where the resulting maps show the risk associated with living place, controlled for the individual risk factors. This method has the advantage to generate smoothed risk factors maps, adjusted by socio-demographic covariates. Results The prevalence of antibody against dengue infection was 37.3% (95%CI [35.5–39.1]) in the year 2002; 7.8% increase in one-year interval. The spatial variation in risk of dengue infection significantly changed when comparing 2001 with 2002, (ORadjusted = 1.35; p < 0.001), while controlling for potential confounders using GAM model. Also increasing age and low education levels were associated with dengue infection. Conclusion This study showed spatial heterogeneity in the risk areas of dengue when using a spatial multivariate approach in a short time interval. Data from household surveys pointed out that low prevalence areas in 2001 surveys shifted to high-risk area in consecutive year. This mapping of dengue risks should give insights for control interventions in urban areas. PMID:18937868

Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation

NASA Astrophysics Data System (ADS)

Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.

2017-12-01

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.

A Corner-Point-Grid-Based Voxelization Method for Complex Geological Structure Model with Folds

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Mariethoz, Gregoire; Liu, Gang

2017-04-01

3D voxelization is the foundation of geological property modeling, and is also an effective approach to realize the 3D visualization of the heterogeneous attributes in geological structures. The corner-point grid is a representative data model among all voxel models, and is a structured grid type that is widely applied at present. When carrying out subdivision for complex geological structure model with folds, we should fully consider its structural morphology and bedding features to make the generated voxels keep its original morphology. And on the basis of which, they can depict the detailed bedding features and the spatial heterogeneity of the internal attributes. In order to solve the shortage of the existing technologies, this work puts forward a corner-point-grid-based voxelization method for complex geological structure model with folds. We have realized the fast conversion from the 3D geological structure model to the fine voxel model according to the rule of isocline in Ramsay's fold classification. In addition, the voxel model conforms to the spatial features of folds, pinch-out and other complex geological structures, and the voxels of the laminas inside a fold accords with the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation based on the spatial voxels. Ultimately, we use examples and the contrastive analysis between the examples and the Ramsay's description of isoclines to discuss the effectiveness and advantages of the method proposed in this work when dealing with the voxelization of 3D geologic structural model with folds based on corner-point grids.

The geography of patient safety: a topical analysis of sterility.

PubMed

Mesman, Jessica

2009-12-01

Many studies on patient safety are geared towards prevention of adverse events by eliminating causes of error. In this article, I argue that patient safety research needs to widen its analytical scope and include causes of strength as well. This change of focus enables me to ask other questions, like why don't things go wrong more often? Or, what is the significance of time and space for patient safety? The focal point of this article is on the spatial dimension of patient safety. To gain insight into the 'geography' of patient safety and perform a topical analysis, I will focus on one specific kind of space (sterile space), one specific medical procedure (insertion of an intravenous line) and one specific medical ward (neonatology). Based on ethnographic data from research in the Netherlands, I demonstrate how spatial arrangements produce sterility and how sterility work produces spatial orders at the same time. Detailed analysis shows how a sterile line insertion involves the convergence of spatially distributed resources, relocations of the field of activity, an assemblage of an infrastructure of attention, a specific compositional order of materials, and the scaling down of one's degree of mobility. Sterility, I will argue, turns out to be a product of spatial orderings. Simultaneously, sterility work generates particular spatial orders, like open and restricted areas, by producing buffers and boundaries. However, the spatial order of sterility intersects with the spatial order of other lines of activity. Insight into the normative structure of these co-existing spatial orders turns out to be crucial for patient safety. By analyzing processes of spatial fine-tuning in everyday practice, it becomes possible to identify spatial competences and circumstances that enable staff members to provide safe health care. As such, a topical analysis offers an alternative perspective of patient safety, one that takes into account its spatial dimension.

Potential Applications of Gosat Based Carbon Budget Products to Refine Terrestrial Ecosystem Model

NASA Astrophysics Data System (ADS)

Kondo, M.; Ichii, K.

2011-12-01

Estimation of carbon exchange in terrestrial ecosystem associates with difficulties due to complex entanglement of physical and biological processes: thus, the net ecosystem productivity (NEP) estimated from simulation often differs among process-based terrestrial ecosystem models. In addition to complexity of the system, validation can only be conducted in a point scale since reliable observation is only available from ground observations. With a lack of large spatial data, extension of model simulation to a global scale results in significant uncertainty in the future carbon balance and climate change. Greenhouse gases Observing SATellite (GOSAT), launched by the Japanese space agency (JAXA) in January, 2009, is the 1st operational satellite promised to deliver the net land-atmosphere carbon budget to the terrestrial biosphere research community. Using that information, the model reproducibility of carbon budget is expected to improve: hence, gives a better estimation of the future climate change. This initial analysis is to seek and evaluate the potential applications of GOSAT observation toward the sophistication of terrestrial ecosystem model. The present study was conducted in two processes: site-based analysis using eddy covariance observation data to assess the potential use of terrestrial carbon fluxes (GPP, RE, and NEP) to refine the model, and extension of the point scale analysis to spatial using Carbon Tracker product as a prototype of GOSAT product. In the first phase of the experiment, it was verified that an optimization routine adapted to a terrestrial model, Biome-BGC, yielded the improved result with respect to eddy covariance observation data from AsiaFlux Network. Spatial data sets used in the second phase were consists of GPP from empirical algorithm (e.g. support vector machine), NEP from Carbon Tracker, and RE from the combination of these. These spatial carbon flux estimations was used to refine the model applying the exactly same optimization procedure as the point analysis, and found that these spatial data help to improve the model's overall reproducibility. The GOSAT product is expected to have higher accuracy since it uses global CO2 observations. Therefore, with the application of GOSAT data, a better estimation of terrestrial carbon cycle can be achieved with optimization. It is anticipated to carry out more detailed analysis upon the arrival of GOSAT product and to verify the reduction in the uncertainty in the future carbon budget and the climate change with the calibrated models, which is the major contribution can be achieved from GOSAT.

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.

Spatial distribution of child pedestrian injuries along census tract boundaries: Implications for identifying area-based correlates.

PubMed

Curtis, Jacqueline W

2017-01-01

Census tracts are often used to investigate area-based correlates of a variety of health outcomes. This approach has been shown to be valuable in understanding the ways that health is shaped by place and to design appropriate interventions that account for community-level processes. Following this line of inquiry, it is common in the study of pedestrian injuries to aggregate the point level locations of these injuries to the census tracts in which they occur. Such aggregation enables investigation of the relationships between a range of socioeconomic variables and areas of notably high or low incidence. This study reports on the spatial distribution of child pedestrian injuries in a mid-sized U.S. city over a three-year period. Utilizing a combination of geospatial approaches, Near Analysis, Kernel Density Estimation, and Local Moran's I, enables identification, visualization, and quantification of close proximity between incidents and tract boundaries. Specifically, results reveal that nearly half of the 100 incidents occur within roads that are also census tract boundaries. Results also uncover incidents that occur on tract boundaries, not merely near them. This geographic pattern raises the question of the utility of associating area-based census data from any one tract to the injuries occurring in these border zones. Furthermore, using a standard spatial join technique in a Geographic Information System (GIS), these points located on the border are counted as falling into census tracts on both sides of the boundary, which introduces uncertainty in any subsequent analysis. Therefore, two additional approaches of aggregating points to polygons were tested in this study. Results differ with each approach, but without any alert of such differences to the GIS user. This finding raises a fundamental concern about techniques through which points are aggregated to polygons in any study using point level incidents and their surrounding census tract socioeconomic data to understand health and place. This study concludes with a suggested protocol to test for this source of uncertainty in analysis and an approach that may remove it.

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.

Imaging of Al/Fe ratios in synthetic Al-goethite revealed by nanoscale secondary ion mass spectrometry.

PubMed

Pohl, Lydia; Kölbl, Angelika; Werner, Florian; Mueller, Carsten W; Höschen, Carmen; Häusler, Werner; Kögel-Knabner, Ingrid

2018-04-30

Aluminium (Al)-substituted goethite is ubiquitous in soils and sediments. The extent of Al-substitution affects the physicochemical properties of the mineral and influences its macroscale properties. Bulk analysis only provides total Al/Fe ratios without providing information with respect to the Al-substitution of single minerals. Here, we demonstrate that nanoscale secondary ion mass spectrometry (NanoSIMS) enables the precise determination of Al-content in single minerals, while simultaneously visualising the variation of the Al/Fe ratio. Al-substituted goethite samples were synthesized with increasing Al concentrations of 0.1, 3, and 7 % and analysed by NanoSIMS in combination with established bulk spectroscopic methods (XRD, FTIR, Mössbauer spectroscopy). The high spatial resolution (50-150 nm) of NanoSIMS is accompanied by a high number of single-point measurements. We statistically evaluated the Al/Fe ratios derived from NanoSIMS, while maintaining the spatial information and reassigning it to its original localization. XRD analyses confirmed increasing concentration of incorporated Al within the goethite structure. Mössbauer spectroscopy revealed 11 % of the goethite samples generated at high Al concentrations consisted of hematite. The NanoSIMS data show that the Al/Fe ratios are in agreement with bulk data derived from total digestion and demonstrated small spatial variability between single-point measurements. More advantageously, statistical analysis and reassignment of single-point measurements allowed us to identify distinct spots with significantly higher or lower Al/Fe ratios. NanoSIMS measurements confirmed the capacity to produce images, which indicated the uniform increase in Al-concentrations in goethite. Using a combination of statistical analysis with information from complementary spectroscopic techniques (XRD, FTIR and Mössbauer spectroscopy) we were further able to reveal spots with lower Al/Fe ratios as hematite. Copyright © 2018 John Wiley & Sons, Ltd.

Spatially intensive sampling by electrofishing for assessing longitudinal discontinuities in fish distribution in a headwater stream

USGS Publications Warehouse

Le Pichon, Céline; Tales, Évelyne; Belliard, Jérôme; Torgersen, Christian E.

2017-01-01

Spatially intensive sampling by electrofishing is proposed as a method for quantifying spatial variation in fish assemblages at multiple scales along extensive stream sections in headwater catchments. We used this method to sample fish species at 10-m2 points spaced every 20 m throughout 5 km of a headwater stream in France. The spatially intensive sampling design provided information at a spatial resolution and extent that enabled exploration of spatial heterogeneity in fish assemblage structure and aquatic habitat at multiple scales with empirical variograms and wavelet analysis. These analyses were effective for detecting scales of periodicity, trends, and discontinuities in the distribution of species in relation to tributary junctions and obstacles to fish movement. This approach to sampling riverine fishes may be useful in fisheries research and management for evaluating stream fish responses to natural and altered habitats and for identifying sites for potential restoration.

Spatial statistical analysis of basal stem root disease under natural field epidemic of oil palm

NASA Astrophysics Data System (ADS)

Kamu, Assis; Phin, Chong Khim; Seman, Idris Abu; Wan, Hoong Hak; Mun, Ho Chong

2015-02-01

Oil palm or scientifically known as Elaeis guineensis Jacq. is the most important commodity crop in Malaysia and has greatly contributed to the economy growth of the country. As far as disease is concerned in the industry, Basal Stem Rot (BSR) caused by Ganoderma boninence remains the most important disease. BSR disease is the most widely studied with information available for oil palm disease in Malaysia. However, there is still limited study on the spatial as well as temporal pattern or distribution of the disease especially under natural field epidemic condition in oil palm plantation. The objective of this study is to spatially identify the pattern of BSR disease under natural field epidemic using two geospatial analytical techniques, which are quadrat analysis for the first order properties of partial pattern analysis and nearest-neighbor analysis (NNA) for the second order properties of partial pattern analysis. Two study sites were selected with different age of tree. Both sites are located in Tawau, Sabah and managed by the same company. The results showed that at least one of the point pattern analysis used which is NNA (i.e. the second order properties of partial pattern analysis) has confirmed the disease is complete spatial randomness. This suggests the spread of the disease is not from tree to tree and the age of palm does not play a significance role in determining the spatial pattern of the disease. From the spatial pattern of the disease, it would help in the disease management program and for the industry in the future. The statistical modelling is expected to help in identifying the right model to estimate the yield loss of oil palm due to BSR disease in the future.

Spatial luminescence imaging of dopant incorporation in CdTe Films

DOE PAGES

Guthrey, Harvey; Moseley, John; Colegrove, Eric; ...

2017-01-25

State-of-the-art cathodoluminescence (CL) spectrum imaging with spectrum-per-pixel CL emission mapping is applied to spatially profile how dopant elements are incorporated into Cadmium telluride (CdTe). Emission spectra and intensity monitor the spatial distribution of additional charge carriers through characteristic variations in the CL emission based on computational modeling. Our results show that grain boundaries play a role in incorporating dopants in CdTe exposed to copper, phosphorus, and intrinsic point defects in CdTe. Furthermore, the image analysis provides critical, unique feedback to understand dopant incorporation and activation in the inhomogeneous CdTe material, which has struggled to reach high levels of hole density.

Analysis of Particle Image Velocimetry (PIV) Data for Application to Subsonic Jet Noise Studies

NASA Technical Reports Server (NTRS)

Blackshire, James L.

1997-01-01

Global velocimetry measurements were taken using Particle Image Velocimetry (PIV) in the subsonic flow exiting a 1 inch circular nozzle in an attempt to better understand the turbulence characteristics of its shear layer region. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Custom data analysis and data validation algorithms were developed and applied to a data ensemble consisting of over 750 PIV 70 mm photographs taken in the 0.85 mach flow facility. Results are presented detailing spatial characteristics of the flow including ensemble mean and standard deviation, turbulence intensities and Reynold's stress levels, and 2-point spatial correlations.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Multiscale recurrence analysis of spatio-temporal data.

PubMed

Riedl, M; Marwan, N; Kurths, J

2015-12-01

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

Quantitative characterization of the spatial distribution of particles in materials: Application to materials processing

NASA Technical Reports Server (NTRS)

Parse, Joseph B.; Wert, J. A.

1991-01-01

Inhomogeneities in the spatial distribution of second phase particles in engineering materials are known to affect certain mechanical properties. Progress in this area has been hampered by the lack of a convenient method for quantitative description of the spatial distribution of the second phase. This study intends to develop a broadly applicable method for the quantitative analysis and description of the spatial distribution of second phase particles. The method was designed to operate on a desktop computer. The Dirichlet tessellation technique (geometrical method for dividing an area containing an array of points into a set of polygons uniquely associated with the individual particles) was selected as the basis of an analysis technique implemented on a PC. This technique is being applied to the production of Al sheet by PM processing methods; vacuum hot pressing, forging, and rolling. The effect of varying hot working parameters on the spatial distribution of aluminum oxide particles in consolidated sheet is being studied. Changes in distributions of properties such as through-thickness near-neighbor distance correlate with hot-working reduction.

Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.

PubMed

Igne, Benoît; Talwar, Sameer; Feng, Hanzhou; Drennen, James K; Anderson, Carl A

2015-12-01

Near-infrared (NIR) spectroscopy has become a well-established tool for the characterization of solid oral dosage forms manufacturing processes and finished products. In this work, the utility of a traditional single-point NIR measurement was compared with that of a spatially resolved spectroscopic (SRS) measurement for the determination of tablet assay. Experimental designs were used to create samples that allowed for calibration models to be developed and tested on both instruments. Samples possessing a poor distribution of ingredients (highly heterogeneous) were prepared by under-blending constituents prior to compaction to compare the analytical capabilities of the two NIR methods. The results indicate that SRS can provide spatial information that is usually obtainable only through imaging experiments for the determination of local heterogeneity and detection of abnormal tablets that would not be detected with single-point spectroscopy, thus complementing traditional NIR measurement systems for in-line, and in real-time tablet analysis. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Fundamental procedures of geographic information analysis

NASA Technical Reports Server (NTRS)

Berry, J. K.; Tomlin, C. D.

1981-01-01

Analytical procedures common to most computer-oriented geographic information systems are composed of fundamental map processing operations. A conceptual framework for such procedures is developed and basic operations common to a broad range of applications are described. Among the major classes of primitive operations identified are those associated with: reclassifying map categories as a function of the initial classification, the shape, the position, or the size of the spatial configuration associated with each category; overlaying maps on a point-by-point, a category-wide, or a map-wide basis; measuring distance; establishing visual or optimal path connectivity; and characterizing cartographic neighborhoods based on the thematic or spatial attributes of the data values within each neighborhood. By organizing such operations in a coherent manner, the basis for a generalized cartographic modeling structure can be developed which accommodates a variety of needs in a common, flexible and intuitive manner. The use of each is limited only by the general thematic and spatial nature of the data to which it is applied.

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.

In situ analysis of the organic framework in the prismatic layer of mollusc shell.

PubMed

Tong, Hua; Hu, Jiming; Ma, Wentao; Zhong, Guirong; Yao, Songnian; Cao, Nianxing

2002-06-01

A novel in situ analytic approach was constructed by means of ion sputtering, decalcification and deprotein techniques combining with scanning electron microscopy (SEM) and transmission electron microscope (TEM) ultrastructural analysis. The method was employed to determine the spatial distribution of the organic framework outside and the inner crystal and organic/inorganic interface spatial geometrical relationship in the prismatic layer of cristaris plicate (leach). The results show that there is a substructure of organic matrix in the intracrystalline region. The prismatic layer forms according to strict hierarchical configuration of regular pattern. Each unit of organic template of prismatic layer can uniquely determine the column crystal growth direction, spatial orientation and size. Cavity templates are responsible for supporting. limiting size and shape and determining the crystal growth spatial orientation, while the intracrystal organic matrix is responsible for providing nucleation point and inducing the nucleation process of calcite. The stereo hierarchical fabrication of prismatic layer was elucidated for the first time.

Spatial association of marine dockage with land-borne infestations of invasive termites (Isoptera: Rhinotermitidae: Coptotermes) in urban south Florida.

PubMed

Hochmair, Hartwig H; Scheffrahn, Rudolf H

2010-08-01

Marine vessels have been implicated in the anthropogenic dispersal of invasive termites for the past 500 yr. It has long been suspected that two invasive termites, the Formosan subterranean termite, Coptotermes formosanus Shiraki, and Coptotermes gestroi (Wasmann) (Isoptera: Rhinotermitidae), were introduced to and dispersed throughout South Florida by sailboats and yachts. We compared the distances between 190 terrestrial point records for Formosan subterranean termite, 177 records for C. gestroi, and random locations with the nearest marine dockage by using spatial analysis. Results show that the median distance to nearest docks associated with C. gestroi is significantly smaller than for the random points. Results also reveal that the median distance to nearest docks associated with Formosan subterranean termite is significantly smaller than for the random points. These results support the hypothesis that C. gestroi and Formosan subterranean termite are significantly closer to potential infested boat locations, i.e., marine docks, than random points in these urban areas. The results of our study suggest yet another source of aggregation in the context of exotic species, namely, hubs for pleasure boating.

Habitat classification modeling with incomplete data: Pushing the habitat envelope

USGS Publications Warehouse

Zarnetske, P.L.; Edwards, T.C.; Moisen, Gretchen G.

2007-01-01

Habitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical techniques for HCMs. One option is to generate pseudo-absence points so that the many available statistical modeling tools can be used. Traditional techniques generate pseudoabsence points at random across broadly defined species ranges, often failing to include biological knowledge concerning the species-habitat relationship. We incorporated biological knowledge of the species-habitat relationship into pseudo-absence points by creating habitat envelopes that constrain the region from which points were randomly selected. We define a habitat envelope as an ecological representation of a species, or species feature's (e.g., nest) observed distribution (i.e., realized niche) based on a single attribute, or the spatial intersection of multiple attributes. We created HCMs for Northern Goshawk (Accipiter gentilis atricapillus) nest habitat during the breeding season across Utah forests with extant nest presence points and ecologically based pseudo-absence points using logistic regression. Predictor variables were derived from 30-m USDA Landfire and 250-m Forest Inventory and Analysis (FIA) map products. These habitat-envelope-based models were then compared to null envelope models which use traditional practices for generating pseudo-absences. Models were assessed for fit and predictive capability using metrics such as kappa, thresholdindependent receiver operating characteristic (ROC) plots, adjusted deviance (Dadj2), and cross-validation, and were also assessed for ecological relevance. For all cases, habitat envelope-based models outperformed null envelope models and were more ecologically relevant, suggesting that incorporating biological knowledge into pseudo-absence point generation is a powerful tool for species habitat assessments. Furthermore, given some a priori knowledge of the species-habitat relationship, ecologically based pseudo-absence points can be applied to any species, ecosystem, data resolution, and spatial extent. ?? 2007 by the Ecological Society of America.

Coherence properties of the radiation from FLASH

NASA Astrophysics Data System (ADS)

Schneidmiller, E. A.; Yurkov, M. V.

2016-02-01

Free electron LASer in Hamburg is the first free electron laser user facility operating in the vacuum ultraviolet and soft X-ray wavelength range. Many user experiments require knowledge of the spatial and temporal coherence properties of the radiation. In this paper, we present a theoretical analysis of the coherence properties of the radiation for the fundamental and for the higher odd frequency harmonics. We show that temporal and spatial coherence reach their maxima close to the free electron laser (FEL) saturation but may degrade significantly in the post-saturation regime. We also find that the pointing stability of short FEL pulses is limited due to the fact that nonazimuthal FEL eigenmodes are not sufficiently suppressed. We discuss possible ways for improving the degree of transverse coherence and the pointing stability.

Information Theoretic Studies and Assessment of Space Object Identification

DTIC Science & Technology

2014-03-24

localization are contained in Ref. [5]. 1.7.1 A Bayesian MPE Based Analysis of 2D Point-Source-Pair Superresolution In a second recently submitted paper [6], a...related problem of the optical superresolution (OSR) of a pair of equal-brightness point sources separated spatially by a distance (or angle) smaller...1403.4897 [physics.optics] (19 March 2014). 6. S. Prasad, “Asymptotics of Bayesian error probability and 2D pair superresolution ,” submitted to Opt. Express

Spatial Correlation of Solar-Wind Turbulence from Two-Point Measurements

NASA Technical Reports Server (NTRS)

Matthaeus, W. H.; Milano, L. J.; Dasso, S.; Weygand, J. M.; Smith, C. W.; Kivelson, M. G.

2005-01-01

Interplanetary turbulence, the best studied case of low frequency plasma turbulence, is the only directly quantified instance of astrophysical turbulence. Here, magnetic field correlation analysis, using for the first time only proper two-point, single time measurements, provides a key step in unraveling the space-time structure of interplanetary turbulence. Simultaneous magnetic field data from the Wind, ACE, and Cluster spacecraft are analyzed to determine the correlation (outer) scale, and the Taylor microscale near Earth's orbit.

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning.

PubMed

Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

2017-03-15

Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

An implicit spatial and high-order temporal finite difference scheme for 2D acoustic modelling

NASA Astrophysics Data System (ADS)

Wang, Enjiang; Liu, Yang

2018-01-01

The finite difference (FD) method exhibits great superiority over other numerical methods due to its easy implementation and small computational requirement. We propose an effective FD method, characterised by implicit spatial and high-order temporal schemes, to reduce both the temporal and spatial dispersions simultaneously. For the temporal derivative, apart from the conventional second-order FD approximation, a special rhombus FD scheme is included to reach high-order accuracy in time. Compared with the Lax-Wendroff FD scheme, this scheme can achieve nearly the same temporal accuracy but requires less floating-point operation times and thus less computational cost when the same operator length is adopted. For the spatial derivatives, we adopt the implicit FD scheme to improve the spatial accuracy. Apart from the existing Taylor series expansion-based FD coefficients, we derive the least square optimisation based implicit spatial FD coefficients. Dispersion analysis and modelling examples demonstrate that, our proposed method can effectively decrease both the temporal and spatial dispersions, thus can provide more accurate wavefields.

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

The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L.) Link

PubMed Central

León Ruiz, Eduardo J.; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps. PMID:22629169

The use of geostatistics in the study of floral phenology of Vulpia geniculata (L.) link.

PubMed

León Ruiz, Eduardo J; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered throughout the city and low mountains in the "Sierra de Córdoba" were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to elaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

Effects of beta-adrenergic antagonist, propranolol on spatial memory and exploratory behavior in mice.

PubMed

Sun, Huaying; Mao, Yu; Wang, Jianhong; Ma, Yuanye

2011-07-08

The beta-adrenergic system has been suggested to be involved in novelty detection and memory modulation. The present study aimed to investigate the role of beta-adrenergic receptors on novelty-based spatial recognition memory and exploratory behavior in mice using Y-maze test and open-field respectively. Mice were injected with three doses of beta-adrenergic receptor antagonist, propranolol (2, 10 and 20 mg/kg) or saline at three different time points (15 min prior to training, immediately after training and 15 min before test). The results showed that higher doses of propranolol (10 and 20 mg/kg) given before the training trial impaired spatial recognition memory while those injected at other two time points did not. A detailed analysis of exploratory behavior in open-field showed that lower dose (2 mg/kg) of propranolol reduced exploratory behavior of mice. Our findings indicate that higher dose of propranolol can impair acquisition of spatial information in the Y-maze without altering locomotion, suggesting that the beta-adrenergic system may be involved in modulating memory processes at the time of learning. Copyright © 2011. Published by Elsevier Ireland Ltd.

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

The value of spatial analysis for tracking supply for family planning: the case of Kinshasa, DRC.

PubMed

Hernandez, Julie H; Akilimali, Pierre; Kayembe, Patrick; Dikamba, Nelly; Bertrand, Jane

2016-10-01

While geographic information systems (GIS) are frequently used to research accessibility issues for healthcare services around the world, sophisticated spatial analysis protocols and outputs often prove inappropriate and unsustainable to support evidence-based programme strategies in resource-constrained environments. This article examines how simple, open-source and interactive GIS tools have been used to locate family planning (FP) services delivery points in Kinshasa (Democratic Republic of Congo) and to identify underserved areas, determining the potential location of new service points, and to support advocacy for FP programmes. Using smartphone-based data collection applications (OpenDataKit), we conducted two surveys of FP facilities supported by partner organizations in 2012 and 2013 and used the results to assess gaps in FP services coverage, using both ratio of facilities per population and distance-based accessibility criteria. The cartographic outputs included both static analysis maps and interactive Google Earth displays, and sought to support advocacy and evidence-based planning for the placement of new service points. These maps, at the scale of Kinshasa or for each of the 35 health zones that cover the city, garnered a wide interest from the operational level of the health zones' Chief Medical Officers, who were consulted to contribute field knowledge on potential new service delivery points, to the FP programmes officers at the Ministry of Health, who could use the map to inform resources allocation decisions throughout the city. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Film characteristics pertinent to coherent optical data processing systems.

PubMed

Thomas, C E

1972-08-01

Photographic film is studied quantitatively as the input mechanism for coherent optical data recording and processing systems. The two important film characteristics are the amplitude transmission vs exposure (T(A) - E) curve and the film noise power spectral density. Both functions are measured as a function of the type of film, the type of developer, developer time and temperature, and the exposing and readout light wavelengths. A detailed analysis of a coherent optical spatial frequency analyzer reveals that the optimum do bias point for 649-F film is an amplitude transmission of about 70%. This operating point yields minimum harmonic and intermodulation distortion, whereas the 50% amplitude transmission bias point recommended by holographers yields maximum diffraction efficiency. It is also shown that the effective ac gain or contrast of the film is nearly independent of the development conditions for a given film. Finally, the linear dynamic range of one particular coherent optical spatial frequency analyzer is shown to be about 40-50 dB.

Midline Body Actions and Leftward Spatial “Aiming” in Patients with Spatial Neglect

PubMed Central

Chaudhari, Amit; Pigott, Kara; Barrett, A. M.

2015-01-01

Spatial motor–intentional “Aiming” bias is a dysfunction in initiation/execution of motor–intentional behavior, resulting in hypokinetic and hypometric leftward movements. Aiming bias may contribute to posture, balance, and movement problems and uniquely account for disability in post-stroke spatial neglect. Body movement may modify and even worsen Aiming errors, but therapy techniques, such as visual scanning training, do not take this into account. Here, we evaluated (1) whether instructing neglect patients to move midline body parts improves their ability to explore left space and (2) whether this has a different impact on different patients. A 68-year-old woman with spatial neglect after a right basal ganglia infarct had difficulty orienting to and identifying left-sided objects. She was prompted with four instructions: “look to the left,” “point with your nose to the left,” “point with your [right] hand to the left,” and “stick out your tongue and point it to the left.” She oriented leftward dramatically better when pointing with the tongue/nose, than she did when pointing with the hand. We then tested nine more consecutive patients with spatial neglect using the same instructions. Only four of them made any orienting errors. Only one patient made >50% errors when pointing with the hand, and she did not benefit from pointing with the tongue/nose. We observed that pointing with the tongue could facilitate left-sided orientation in a stroke survivor with spatial neglect. If midline structures are represented more bilaterally, they may be less affected by Aiming bias. Alternatively, moving the body midline may be more permissive for leftward orienting than moving right body parts. We were not able to replicate this effect in another patient; we suspect that the magnitude of this effect may depend upon the degree to which patients have directional akinesia, spatial Where deficits, or cerebellar/frontal cortical lesions. Future research could examine these hypotheses. PMID:26217211

Rainfall Observed Over Bangladesh 2000-2008: A Comparison of Spatial Interpolation Methods

NASA Astrophysics Data System (ADS)

Pervez, M.; Henebry, G. M.

2010-12-01

In preparation for a hydrometeorological study of freshwater resources in the greater Ganges-Brahmaputra region, we compared the results of four methods of spatial interpolation applied to point measurements of daily rainfall over Bangladesh during a seven year period (2000-2008). Two univariate (inverse distance weighted and spline-regularized and tension) and two multivariate geostatistical (ordinary kriging and kriging with external drift) methods were used to interpolate daily observations from a network of 221 rain gauges across Bangladesh spanning an area of 143,000 sq km. Elevation and topographic index were used as the covariates in the geostatistical methods. The validity of the interpolated maps was analyzed through cross-validation. The quality of the methods was assessed through the Pearson and Spearman correlations and root mean square error measurements of accuracy in cross-validation. Preliminary results indicated that the univariate methods performed better than the geostatistical methods at daily scales, likely due to the relatively dense sampled point measurements and a weak correlation between the rainfall and covariates at daily scales in this region. Inverse distance weighted produced the better results than the spline. For the days with extreme or high rainfall—spatially and quantitatively—the correlation between observed and interpolated estimates appeared to be high (r2 ~ 0.6 RMSE ~ 10mm), although for low rainfall days the correlations were poor (r2 ~ 0.1 RMSE ~ 3mm). The performance quality of these methods was influenced by the density of the sample point measurements, the quantity of the observed rainfall along with spatial extent, and an appropriate search radius defining the neighboring points. Results indicated that interpolated rainfall estimates at daily scales may introduce uncertainties in the successive hydrometeorological analysis. Interpolations at 5-day, 10-day, 15-day, and monthly time scales are currently under investigation.

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

Integration of health into urban spatial planning through impact assessment: Identifying governance and policy barriers and facilitators

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

Carmichael, Laurence, E-mail: Laurence.carmichael@uwe.ac.uk; Barton, Hugh; Gray, Selena

This article presents the results of a review of literature examining the barriers and facilitators in integrating health in spatial planning at the local, mainly urban level, through appraisals. Our literature review covered the UK and non UK experiences of appraisals used to consider health issues in the planning process. We were able to identify four main categories of obstacles and facilitators including first the different knowledge and conceptual understanding of health by different actors/stakeholders, second the types of governance arrangements, in particular partnerships, in place and the political context, third the way institutions work, the responsibilities they have andmore » their capacity and resources and fourth the timeliness, comprehensiveness and inclusiveness of the appraisal process. The findings allowed us to draw some lessons on the governance and policy framework regarding the integration of health impact into spatial planning, in particular considering the pros and cons of integrating health impact assessment (HIA) into other forms of impact assessment of spatial planning decisions such as environmental impact assessment (EIA) and strategic environment assessment (SEA). In addition, the research uncovered a gap in the literature that tends to focus on the mainly voluntary HIA to assess health outcomes of planning decisions and neglect the analysis of regulatory mechanisms such as EIA and SEA. - Highlights: Black-Right-Pointing-Pointer Governance and policy barriers and facilitators to the integration of health into urban planning. Black-Right-Pointing-Pointer Review of literature on impact assessment methods used across the world. Black-Right-Pointing-Pointer Knowledge, partnerships, management/resources and processes can impede integration. Black-Right-Pointing-Pointer HIA evaluations prevail uncovering research opportunities for evaluating other techniques.« less

A Practical Decision-Analysis Process for Forest Ecosystem Management

Treesearch

H. Michael Rauscher; F. Thomas Lloyd; David L. Loftis; Mark J. Twery

2000-01-01

Many authors have pointed out the need to firm up the 'fuzzy' ecosystem management paradigm and develop operationally practical processes to allow forest managers to accommodate more effectively the continuing rapid change in societal perspectives and goals. There are three spatial scales where clear, precise, practical ecosystem management processes are...

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

NASA Astrophysics Data System (ADS)

Cai, Jingya; Pang, Zhiguo; Fu, Jun'e.

2018-04-01

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

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.

3-D Deformation analysis via invariant geodetic obsevations.

NASA Astrophysics Data System (ADS)

Ardalan, A.; Esmaeili, R.

2003-04-01

In this paper a new method for 3-D deformation analysis based on invariant observations like distances and spatial angles is presented. Displacement field that is used in the classical deformation analysis is not reliable because the stability of the coordinate systems between successive epochs of observations cannot be guaranteed. On the contrary distances and spatial angles, i.e. measurements that are related to geometry between the constituent points of an object is independent of the definition of coordinate system. In this paper we have devised a new approach for the calculation of elements of the strain tensor directly from the geometrical observations such as angels and distances. This new method besides enjoys 3-D nature and as such guarantees the complete deformation study in 3-D space.

LLR data analysis and impact on lunar dynamics from recent developments at OCA LLR Station

NASA Astrophysics Data System (ADS)

Viswanathan, Vishnu; Fienga, Agnes; Courde, Clement; Torre, Jean-Marie; Exertier, Pierre; Samain, Etienne; Feraudy, Dominique; Albanese, Dominique; Aimar, Mourad; Mariey, Hervé; Viot, Hervé; Martinot-Lagarde, Gregoire

2016-04-01

Since late 2014, OCA LLR station has been able to range with infrared wavelength (1064nm). IR ranging provides both temporal and spatial improvement in the LLR observations. IR detection also permits in densification of normal points, including the L1 and L2 retroreflectors due to better signal to noise ratio. This contributes to a better modelisation of the lunar libration. The hypothesis of lunar dust and environmental effects due to the chromatic behavior noticed on returns from L2 retroreflector is discussed. In addition, data analysis shows that the effect of retroreflector tilt and the use of calibration profile for the normal point deduction algorithm, contributes to improving the precision of normal points, thereby impacting lunar dynamical models and inner physics.

High-resolution scanning precession electron diffraction: Alignment and spatial resolution.

PubMed

Barnard, Jonathan S; Johnstone, Duncan N; Midgley, Paul A

2017-03-01

Methods are presented for aligning the pivot point of a precessing electron probe in the scanning transmission electron microscope (STEM) and for assessing the spatial resolution in scanning precession electron diffraction (SPED) experiments. The alignment procedure is performed entirely in diffraction mode, minimising probe wander within the bright-field (BF) convergent beam electron diffraction (CBED) disk and is used to obtain high spatial resolution SPED maps. Through analysis of the power spectra of virtual bright-field images extracted from the SPED data, the precession-induced blur was measured as a function of precession angle. At low precession angles, SPED spatial resolution was limited by electronic noise in the scan coils; whereas at high precession angles SPED spatial resolution was limited by tilt-induced two-fold astigmatism caused by the positive spherical aberration of the probe-forming lens. Copyright © 2016 Elsevier B.V. All rights reserved.

A line-scan hyperspectral Raman system for spatially offset Raman spectroscopy

USDA-ARS?s Scientific Manuscript database

Conventional methods of spatially offset Raman spectroscopy (SORS) typically use single-fiber optical measurement probes to slowly and incrementally collect a series of spatially offset point measurements moving away from the laser excitation point on the sample surface, or arrays of multiple fiber ...

Inventory of File WAFS_blended_2014102006f06.grib2

Science.gov Websites

) [%] 004 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 005 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial max,code table 4.15=3,#points=1 006 600 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 007 600 mb CTP 6 hour fcst In

Spatial and spectral imaging of point-spread functions using a spatial light modulator

NASA Astrophysics Data System (ADS)

Munagavalasa, Sravan; Schroeder, Bryce; Hua, Xuanwen; Jia, Shu

2017-12-01

We develop a point-spread function (PSF) engineering approach to imaging the spatial and spectral information of molecular emissions using a spatial light modulator (SLM). We show that a dispersive grating pattern imposed upon the emission reveals spectral information. We also propose a deconvolution model that allows the decoupling of the spectral and 3D spatial information in engineered PSFs. The work is readily applicable to single-molecule measurements and fluorescent microscopy.

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects.

PubMed

Sollmann, Nico; Hauck, Theresa; Tussis, Lorena; Ille, Sebastian; Maurer, Stefanie; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-10-24

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated. Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7-30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0-26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9-27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0-24.2 mm) were measured. According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

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

NASA Astrophysics Data System (ADS)

Fauzi, A. F.; Aditianata, A.

2018-02-01

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

Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

NASA Astrophysics Data System (ADS)

Lee, Sang-Il

This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.

Analysis of Spatial Distribution And Statistical Characteristics of Typhoon In The Western Pacific Based On Spatial Point Model

NASA Astrophysics Data System (ADS)

Wang, Jingmei; Gong, Adu; Li, Jing; Chen, Yanling

2017-04-01

Typhoon is a kind of strong weather system formed in tropical or subtropical oceans. China, located on the west side of the Pacific Ocean, is the country affected by the typhoon most frequently and seriously. To provide theoretical support for effectively reducing the damage caused by typhoon, the variation law of typhoon frequency is explored by analyzing the distribution of typhoon path and landing sites, sphere of influence, and the statistical characteristics of typhoon for every 5 years. In this study, the typhoon point data set was formed using the Best Path Data Set (0.1 ° × 0.1 °) compiled by China Meteorological Administration from 1950 to 2014. By using the tool of Point to Line in software ArgGIS, the typhoon paths are produced from the point data set. The influence sphere of typhoon is calculated from Euclidean distance of typhoon, whose threshold is set to 1°.The typhoon landing site was extracted by using the Chinese vector layer provided by the research group. By counting the frequency of typhoons, the landing sites, and the sphere of influence, some conclusions can be drawn as follows. In recent years, the number of typhoons generated has been reduced, typhoon intensity is relatively stable, but the impact of typhoon area has increased. Specific performance can be seen from the typhoon statistical and spatial distribution characteristics in China. In terms of frequency of typhoon landing, the number of typhoons landing in China has increased while the total number of typhoons is reduced. In terms of distribution of landing sites, the range of typhoon landing fluctuates. However, during the process of fluctuation, the range is gradually expanding. For example, in south of China, Hainan Island is affected by typhoon more frequently meanwhile China's northeast region is also gradually affected, which is extremely unusual before. Key words: spatial point model, distribution of typhoon, frequency of typhoon

Tree species exhibit complex patterns of distribution in bottomland hardwood forests

Treesearch

Luben D Dimov; Jim L Chambers; Brian R. Lockhart

2013-01-01

& Context Understanding tree interactions requires an insight into their spatial distribution. & Aims We looked for presence and extent of tree intraspecific spatial point pattern (random, aggregated, or overdispersed) and interspecific spatial point pattern (independent, aggregated, or segregated). & Methods We established twelve 0.64-ha plots in natural...

Visual Data Analysis for Satellites

NASA Technical Reports Server (NTRS)

Lau, Yee; Bhate, Sachin; Fitzpatrick, Patrick

2008-01-01

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Some practicable applications of quadtree data structures/representation in astronomy

NASA Technical Reports Server (NTRS)

Pasztor, L.

1992-01-01

Development of quadtree as hierarchical data structuring technique for representing spatial data (like points, regions, surfaces, lines, curves, volumes, etc.) has been motivated to a large extent by storage requirements of images, maps, and other multidimensional (spatially structured) data. For many spatial algorithms, time-efficiency of quadtrees in terms of execution may be as important as their space-efficiency concerning storage conditions. Briefly, the quadtree is a class of hierarchical data structures which is based on the recursive partition of a square region into quadrants and sub-quadrants until a predefined limit. Beyond the wide applicability of quadtrees in image processing, spatial information analysis, and building digital databases (processes becoming ordinary for the astronomical community), there may be numerous further applications in astronomy. Some of these practicable applications based on quadtree representation of astronomical data are presented and suggested for further considerations. Examples are shown for use of point as well as region quadtrees. Statistics of different leaf and non-leaf nodes (homogeneous and heterogeneous sub-quadrants respectively) at different levels may provide useful information on spatial structure of astronomical data in question. By altering the principle guiding the decomposition process, different types of spatial data may be focused on. Finally, a sampling method based on quadtree representation of an image is proposed which may prove to be efficient in the elaboration of sampling strategy in a region where observations were carried out previously either with different resolution or/and in different bands.

Global and local indicators of spatial association between points and polygons: A study of land use change

NASA Astrophysics Data System (ADS)

Guo, Luo; Du, Shihong; Haining, Robert; Zhang, Lianjun

2013-04-01

The existing indicators related to spatial association, especially the K function, can measure only the same dimension of vector data, such as points, lines and polygons, respectively. We develop four new indicators that can analyze and model spatial association for the mixture of different dimensions of vector data, such as lines and points, points and polygons, lines and polygons. The four indicators can measure the spatial association between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the association of temples and villages on land-use change at multiple distance scales in the Guoluo Tibetan Autonomous Prefecture in Qinghai Province, PR China. Global indicators show that temples are positively associated with land-use change at large spatial distances (e.g., >6000 m), while the association between villages and land-use change is insignificant at all distance scales. Thus temples, as religious and cultural centers, have a stronger association with land-use change than the places where people live. However, local indicators show that these associations vary significantly in different sub-areas of the study region. Furthermore, the association of temples with land-use change is also dependent on the specific type of land-use change. The case study demonstrates that the presented indicators are powerful tools for analyzing the spatial association between points and polygons.

Multilevel spatiotemporal change-point models for evaluating the effect of an alcohol outlet control policy on changes in neighborhood assaultive violence rates.

PubMed

Xu, Yanjun; Yu, Qingzhao; Scribner, Richard; Theall, Katherine; Scribner, Scott; Simonsen, Neal

2012-06-01

Many previous studies have suggested a link between alcohol outlets and assaultive violence rates. In 1997 the City of New Orleans adopted a series of policies, e.g., increased license fee, additional enforcement staff, and expanded powers for the alcohol license board. The policies were specifically enacted to address the proliferation of problem alcohol outlets believed to be the source of a variety of social problems including assaultive violence. In this research, we evaluate the impact of a city level policy in New Orleans to address the problem alcohol outlets and their influence on assaultive violence. The spatial association between rates of assaultive violence at the census tract level (n=170) over a ten year period raises a challenge in statistical analysis. To meet this challenge we developed a hierarchical change-point model that controls for important covariates of assaultive violence and accounts for unexplained spatial and temporal variability. While our model is somewhat complex, its hierarchical Bayesian analysis is accessible via the WinBUGS software program. Keeping other effects fixed, the implementation of the new city level policy was associated with a decrease in the positive association between census tract level rates of assaultive violence and alcohol outlet density. Comparing several candidate change-point models using the DIC criterion, the positive association began decreasing the year of the policy implementation. The magnitude of the association continued to decrease for roughly two years and then stabilized. We also created maps of the fitted assaultive violence rates in New Orleans, as well as spatial residual maps which, together with Moran's I's, suggest that the spatial variation of the data is well accounted for by our model. We reach the conclusion that the implementation of the policy is associated with a significant decrease in the positive relationship between assaultive violence and the off-sale alcohol outlet density. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial analysis of toxic emissions in LCA: a sub-continental nested USEtox model with freshwater archetypes.

PubMed

Kounina, Anna; Margni, Manuele; Shaked, Shanna; Bulle, Cécile; Jolliet, Olivier

2014-08-01

This paper develops continent-specific factors for the USEtox model and analyses the accuracy of different model architectures, spatial scales and archetypes in evaluating toxic impacts, with a focus on freshwater pathways. Inter-continental variation is analysed by comparing chemical fate and intake fractions between sub-continental zones of two life cycle impact assessment models: (1) the nested USEtox model parameterized with sub-continental zones and (2) the spatially differentiated IMPACTWorld model with 17 interconnected sub-continental regions. Substance residence time in water varies by up to two orders of magnitude among the 17 zones assessed with IMPACTWorld and USEtox, and intake fraction varies by up to three orders of magnitude. Despite this variation, the nested USEtox model succeeds in mimicking the results of the spatially differentiated model, with the exception of very persistent volatile pollutants that can be transported to polar regions. Intra-continental variation is analysed by comparing fate and intake fractions modelled with the a-spatial (one box) IMPACT Europe continental model vs. the spatially differentiated version of the same model. Results show that the one box model might overestimate chemical fate and characterisation factors for freshwater eco-toxicity of persistent pollutants by up to three orders of magnitude for point source emissions. Subdividing Europe into three archetypes, based on freshwater residence time (how long it takes water to reach the sea), improves the prediction of fate and intake fractions for point source emissions, bringing them within a factor five compared to the spatial model. We demonstrated that a sub-continental nested model such as USEtox, with continent-specific parameterization complemented with freshwater archetypes, can thus represent inter- and intra-continental spatial variations, whilst minimizing model complexity. Copyright © 2014 Elsevier Ltd. All rights reserved.

The spatial-temporal variations of water quality in controlling points of the main rivers flowing into the Miyun Reservoir from 1991 to 2011.

PubMed

Li, Dongqing; Liang, Ji; Di, Yanming; Gong, Huili; Guo, Xiaoyu

2016-01-01

Cluster analysis (CA), discriminant analysis (DA), and principal component analysis/factor analysis (PCA/FA) were used to analyze the interannual, seasonal, and spatial variations of water quality from 1991 to 2011 in controlling points (Xinzhuang Bridge, Daguan Bridge) of the main rivers (Chaohe River, Baihe River) flowing into the Miyun Reservoir. The results demonstrated that total nitrogen (TN) and total phosphorus (TP) exceeded China National Standard II for surface water separately 5.08 times and 1 time. CA showed that the water quality could be divided into three interannual (IA) groups: IAI (1991-1995, 1998), IAII (1996-1997, 1999-2000, 2002-2006), and IAIII (2001, 2007-2011) and two seasonal clusters: dry season 1 (December), dry season 2 (January-February), and non-dry season (March-November). At interannual scale, the higher concentration of SO4 (2-) from industrial activities, atmospheric sedimentation, and fertilizer use in IAIII accelerated dissolution of carbonate, which increased Ca(2+), Mg(2+), total hardness (T-Hard), and total alkalinity (T-Alk). The decreasing trend of CODMn contributed to the establishment of sewage treatment plants and water and soil conservation in the Miyun upstream. The changing trend of NO3 (-)-N indicated increasing non-point pollution load of IAII and effective non-point pollution controlling of IAIII. Only one parameter T in the seasonal scale verified improved non-point pollution controlling. The major pollution in two controlling points was NO3 (-)-N, T-Hard, TN, and other ion pollution (SO4 (2-), F(-), Ca(2+), Mg(2+), T-Hard, T-Alk). Higher concentration of NO3 (-)-N in Xinzhuang and CODMn in Daguan indicated different controlling measures, especially controlling agriculture intensification in Chaohe River to decrease N pollution and decreasing water and soil loss and cage culture in Baihe River to weaken organic pollution. Controlling SO4 (2-) from industrial activity, atmospheric sedimentation and fertilizer use in watershed can effectively control Ca(2+), Mg(2+), T-Hard, and T-Alk.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis.

PubMed

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis

PubMed Central

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one. PMID:29467698

Is social attention impaired in schizophrenia? Gaze, but not pointing gestures, is associated with spatial attention deficits.

PubMed

Dalmaso, Mario; Galfano, Giovanni; Tarqui, Luana; Forti, Bruno; Castelli, Luigi

2013-09-01

The nature of possible impairments in orienting attention to social signals in schizophrenia is controversial. The present research was aimed at addressing this issue further by comparing gaze and arrow cues. Unlike previous studies, we also included pointing gestures as social cues, with the goal of addressing whether any eventual impairment in the attentional response was specific to gaze signals or reflected a more general deficit in dealing with social stimuli. Patients with schizophrenia or schizoaffective disorder and matched controls performed a spatial-cuing paradigm in which task-irrelevant centrally displayed gaze, pointing finger, and arrow cues oriented rightward or leftward, preceded a lateralized target requiring a simple detection response. Healthy controls responded faster to spatially congruent targets than to spatially incongruent targets, irrespective of cue type. In contrast, schizophrenic patients responded faster to spatially congruent targets than to spatially incongruent targets only for arrow and pointing finger cues. No cuing effect emerged for gaze cues. The results support the notion that gaze cuing is impaired in schizophrenia, and suggest that this deficit may not extend to all social cues.

Determination of geostatistically representative sampling locations in Porsuk Dam Reservoir (Turkey)

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yenilmez, F.; Duzgun, S.

2013-12-01

Several factors such as wind action, bathymetry and shape of a lake/reservoir, inflows, outflows, point and diffuse pollution sources result in spatial and temporal variations in water quality of lakes and reservoirs. The guides by the United Nations Environment Programme and the World Health Organization to design and implement water quality monitoring programs suggest that even a single monitoring station near the center or at the deepest part of a lake will be sufficient to observe long-term trends if there is good horizontal mixing. In stratified water bodies, several samples can be required. According to the guide of sampling and analysis under the Turkish Water Pollution Control Regulation, a minimum of five sampling locations should be employed to characterize the water quality in a reservoir or a lake. The European Union Water Framework Directive (2000/60/EC) states to select a sufficient number of monitoring sites to assess the magnitude and impact of point and diffuse sources and hydromorphological pressures in designing a monitoring program. Although existing regulations and guidelines include frameworks for the determination of sampling locations in surface waters, most of them do not specify a procedure in establishment of monitoring aims with representative sampling locations in lakes and reservoirs. In this study, geostatistical tools are used to determine the representative sampling locations in the Porsuk Dam Reservoir (PDR). Kernel density estimation and kriging were used in combination to select the representative sampling locations. Dissolved oxygen and specific conductivity were measured at 81 points. Sixteen of them were used for validation. In selection of the representative sampling locations, care was given to keep similar spatial structure in distributions of measured parameters. A procedure was proposed for that purpose. Results indicated that spatial structure was lost under 30 sampling points. This was as a result of varying water quality in the reservoir due to inflows, point and diffuse inputs, and reservoir hydromorphology. Moreover, hot spots were determined based on kriging and standard error maps. Locations of minimum number of sampling points that represent the actual spatial structure of DO distribution in the Porsuk Dam Reservoir

Error analysis for creating 3D face templates based on cylindrical quad-tree structure

NASA Astrophysics Data System (ADS)

Gutfeter, Weronika

2015-09-01

Development of new biometric algorithms is parallel to advances in technology of sensing devices. Some of the limitations of the current face recognition systems may be eliminated by integrating 3D sensors into these systems. Depth sensing devices can capture a spatial structure of the face in addition to the texture and color. This kind of data is yet usually very voluminous and requires large amount of computer resources for being processed (face scans obtained with typical depth cameras contain more than 150 000 points per face). That is why defining efficient data structures for processing spatial images is crucial for further development of 3D face recognition methods. The concept described in this work fulfills the aforementioned demands. Modification of the quad-tree structure was chosen because it can be easily transformed into less dimensional data structures and maintains spatial relations between data points. We are able to interpret data stored in the tree as a pyramid of features which allow us to analyze face images using coarse-to-fine strategy, often exploited in biometric recognition systems.

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning

PubMed Central

Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

2017-01-01

Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood. PMID:28294963

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

PubMed Central

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers. PMID:25206325

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Karlsson, Caroline S. J.; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W.

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis.

PubMed

Karlsson, Caroline S J; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

The effects of context on multidimensional spatial cognitive models. Ph.D. Thesis - Arizona Univ.

NASA Technical Reports Server (NTRS)

Dupnick, E. G.

1979-01-01

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Spatial regression analysis of traffic crashes in Seoul.

PubMed

Rhee, Kyoung-Ah; Kim, Joon-Ki; Lee, Young-ihn; Ulfarsson, Gudmundur F

2016-06-01

Traffic crashes can be spatially correlated events and the analysis of the distribution of traffic crash frequency requires evaluation of parameters that reflect spatial properties and correlation. Typically this spatial aspect of crash data is not used in everyday practice by planning agencies and this contributes to a gap between research and practice. A database of traffic crashes in Seoul, Korea, in 2010 was developed at the traffic analysis zone (TAZ) level with a number of GIS developed spatial variables. Practical spatial models using available software were estimated. The spatial error model was determined to be better than the spatial lag model and an ordinary least squares baseline regression. A geographically weighted regression model provided useful insights about localization of effects. The results found that an increased length of roads with speed limit below 30 km/h and a higher ratio of residents below age of 15 were correlated with lower traffic crash frequency, while a higher ratio of residents who moved to the TAZ, more vehicle-kilometers traveled, and a greater number of access points with speed limit difference between side roads and mainline above 30 km/h all increased the number of traffic crashes. This suggests, for example, that better control or design for merging lower speed roads with higher speed roads is important. A key result is that the length of bus-only center lanes had the largest effect on increasing traffic crashes. This is important as bus-only center lanes with bus stop islands have been increasingly used to improve transit times. Hence the potential negative safety impacts of such systems need to be studied further and mitigated through improved design of pedestrian access to center bus stop islands. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spacecraft Jitter Attenuation Using Embedded Piezoelectric Actuators

NASA Technical Reports Server (NTRS)

Belvin, W. Keith

1995-01-01

Remote sensing from spacecraft requires precise pointing of measurement devices in order to achieve adequate spatial resolution. Unfortunately, various spacecraft disturbances induce vibrational jitter in the remote sensing instruments. The NASA Langley Research Center has performed analysis, simulations, and ground tests to identify the more promising technologies for minimizing spacecraft pointing jitter. These studies have shown that the use of smart materials to reduce spacecraft jitter is an excellent match between a maturing technology and an operational need. This paper describes the use of embedding piezoelectric actuators for vibration control and payload isolation. In addition, recent advances in modeling, simulation, and testing of spacecraft pointing jitter are discussed.

Unwrapping 3D complex hollow organs for spatial dose surface analysis.

PubMed

Witztum, A; George, B; Warren, S; Partridge, M; Hawkins, M A

2016-11-01

Toxicity dose-response models describe the correlation between dose delivered to an organ and a given toxic endpoint. Duodenal toxicity is a dose limiting factor in the treatment of pancreatic cancer with radiation but the relationship between dose and toxicity in the duodenum is not well understood. While there have been limited studies into duodenal toxicity through investigations of the volume of the organ receiving dose over a specific threshold, both dose-volume and dose-surface histograms lack spatial information about the dose distribution, which may be important in determining normal tissue response. Due to the complex geometry of the duodenum, previous methods for unwrapping tubular organs for spatial modeling of toxicity are insufficient. A geometrically robust method for producing 2D dose surface maps (DSMs), specifically for the duodenum, has been developed and tested in order to characterize the spatial dose distribution. The organ contour is defined using Delaunay triangulation. The user selects a start and end coordinate in the structure and a path is found by regulating both length and curvature. This path is discretized and rays are cast from each point on the plane normal to the vector between the previous and the next point on the path and the dose at the closest perimeter point recorded. These angular perimeter slices are "unwrapped" from the edge distal to the pancreas to ensure the high dose region (proximal to the tumor) falls in the centre of the dose map. Gamma analysis is used to quantify the robustness of this method and the effect of overlapping planes. This method was used to extract DSMs for 15 duodena, with one esophagus case to illustrate the application to simpler geometries. Visual comparison indicates that a 30 × 30 map provides sufficient resolution to view gross spatial features of interest. A lookup table is created to store the area (cm 2 ) represented by each pixel in the DSMs in order to allow spatial descriptors in absolute size. The method described in this paper is robust, requires minimal human interaction, has been shown to be generalizable to simpler geometries, and uses readily available commercial software. The difference seen in DSMs due to overlapping planes is large and justifies the need for a solution that removes such planes. This is the first time 2D dose surface maps have been produced for the duodenum and provide spatial dose distribution information which can be explored to create models that may improve toxicity prediction in treatments for locally advanced pancreatic cancer.

Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

PubMed Central

Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

2015-01-01

Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

Feature Geo Analytics and Big Data Processing: Hybrid Approaches for Earth Science and Real-Time Decision Support

NASA Astrophysics Data System (ADS)

Wright, D. J.; Raad, M.; Hoel, E.; Park, M.; Mollenkopf, A.; Trujillo, R.

2016-12-01

Introduced is a new approach for processing spatiotemporal big data by leveraging distributed analytics and storage. A suite of temporally-aware analysis tools summarizes data nearby or within variable windows, aggregates points (e.g., for various sensor observations or vessel positions), reconstructs time-enabled points into tracks (e.g., for mapping and visualizing storm tracks), joins features (e.g., to find associations between features based on attributes, spatial relationships, temporal relationships or all three simultaneously), calculates point densities, finds hot spots (e.g., in species distributions), and creates space-time slices and cubes (e.g., in microweather applications with temperature, humidity, and pressure, or within human mobility studies). These "feature geo analytics" tools run in both batch and streaming spatial analysis mode as distributed computations across a cluster of servers on typical "big" data sets, where static data exist in traditional geospatial formats (e.g., shapefile) locally on a disk or file share, attached as static spatiotemporal big data stores, or streamed in near-real-time. In other words, the approach registers large datasets or data stores with ArcGIS Server, then distributes analysis across a cluster of machines for parallel processing. Several brief use cases will be highlighted based on a 16-node server cluster at 14 Gb RAM per node, allowing, for example, the buffering of over 8 million points or thousands of polygons in 1 minute. The approach is "hybrid" in that ArcGIS Server integrates open-source big data frameworks such as Apache Hadoop and Apache Spark on the cluster in order to run the analytics. In addition, the user may devise and connect custom open-source interfaces and tools developed in Python or Python Notebooks; the common denominator being the familiar REST API.

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

NASA Astrophysics Data System (ADS)

Bouma, Johan

2015-04-01

Considering the spatial-scale factor when modelling sustainable land management. J.Bouma Em.prof. soil science, Wageningen University, Netherlands. Modelling soil-plant processes is a necessity when exploring future effects of climate change and innovative soil management on agricultural productivity. Soil data are needed to run models and traditional soil maps and the associated databases (based on various soil Taxonomies ), have widely been applied to provide such data obtained at "representative" points in the field. Pedotransferfunctions (PTF)are used to feed simulation models, statistically relating soil survey data ( obtained at a given point in the landscape) to physical parameters for simulation, thus providing a link with soil functionality. Soil science has a basic problem: their object of study is invisible. Only point data are obtained by augering or in pits. Only occasionally roadcuts provide a better view. Extrapolating point to area data is essential for all applications and presents a basic problem for soil science, because mapping units on soil maps, named for a given soil type,may also contain other soil types and quantitative information about the composition of soil map units is usually not available. For detailed work at farm level ( 1:5000-1:10000), an alternative procedure is proposed. Based on a geostatistical analysis, onsite soil observations are made in a grid pattern with spacings based on a geostatistical analysis. Multi-year simulations are made for each point of the functional properties that are relevant for the case being studied, such as the moisture supply capacity, nitrate leaching etc. under standardized boundary conditions to allow comparisons. Functional spatial units are derived next by aggregating functional point data. These units, which have successfully functioned as the basis for precision agriculture, do not necessarily correspond with Taxonomic units but when they do the Taxonomic names should be noted . At lower landscape and watershed scale ( 1:25.000 -1:50000) digital soil mapping can provide soil data for small grids that can be used for modeling, again through pedotransferfunctions. There is a risk, however, that digital mapping results in an isolated series of projects that don't increase the knowledge base on soil functionality, e.g.linking Taxonomic names ( such as soil series) to functionality, allowing predictions of soil behavior at new sites where certain soil series occur. We therefore suggest that aside from collecting 13 soil characteristics for each grid, as occurs in digital soil mapping, also the Taxonomic name of the representative soil in the grid is recorded. At spatial scales of 1:50000 and smaller, use of Taxonomic names becomes ever more attractive because at such small scales relations between soil types and landscape features become more pronounced. But in all cases, selection of procedures should not be science-based but based on the type of questions being asked including their level of generalization. These questions are quite different at the different spatial-scale levels and so should be the procedures.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Creative use of pilot points to address site and regional scale heterogeneity in a variable-density model

USGS Publications Warehouse

Dausman, Alyssa M.; Doherty, John; Langevin, Christian D.

2010-01-01

Pilot points for parameter estimation were creatively used to address heterogeneity at both the well field and regional scales in a variable-density groundwater flow and solute transport model designed to test multiple hypotheses for upward migration of fresh effluent injected into a highly transmissive saline carbonate aquifer. Two sets of pilot points were used within in multiple model layers, with one set of inner pilot points (totaling 158) having high spatial density to represent hydraulic conductivity at the site, while a second set of outer points (totaling 36) of lower spatial density was used to represent hydraulic conductivity further from the site. Use of a lower spatial density outside the site allowed (1) the total number of pilot points to be reduced while maintaining flexibility to accommodate heterogeneity at different scales, and (2) development of a model with greater areal extent in order to simulate proper boundary conditions that have a limited effect on the area of interest. The parameters associated with the inner pilot points were log transformed hydraulic conductivity multipliers of the conductivity field obtained by interpolation from outer pilot points. The use of this dual inner-outer scale parameterization (with inner parameters constituting multipliers for outer parameters) allowed smooth transition of hydraulic conductivity from the site scale, where greater spatial variability of hydraulic properties exists, to the regional scale where less spatial variability was necessary for model calibration. While the model is highly parameterized to accommodate potential aquifer heterogeneity, the total number of pilot points is kept at a minimum to enable reasonable calibration run times.

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).

A microreactor array for spatially resolved measurement of catalytic activity for high-throughput catalysis science

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

Kondratyuk, Petro; Gumuslu, Gamze; Shukla, Shantanu

2013-04-01

We describe a 100 channel microreactor array capable of spatially resolved measurement of catalytic activity across the surface of a flat substrate. When used in conjunction with a composition spread alloy film (CSAF, e.g. Pd{sub x}Cu{sub y}Au{sub 1-x-y}) across which component concentrations vary smoothly, such measurements permit high-throughput analysis of catalytic activity and selectivity as a function of catalyst composition. In the reported implementation, the system achieves spatial resolution of 1 mm{sup 2} over a 10×10 mm{sup 2} area. During operation, the reactant gases are delivered at constant flow rate to 100 points of differing composition on the CSAF surfacemore » by means of a 100-channel microfluidic device. After coming into contact with the CSAF catalyst surface, the product gas mixture from each of the 100 points is withdrawn separately through a set of 100 isolated channels for analysis using a mass spectrometer. We demonstrate the operation of the device on a Pd{sub x}Cu{sub y}Au{sub 1-x-y} CSAF catalyzing the H{sub 2}-D{sub 2} exchange reaction at 333 K. In essentially a single experiment, we measured the catalytic activity over a broad swathe of concentrations from the ternary composition space of the Pd{sub x}Cu{sub y}Au{sub 1-x-y} alloy.« less

Space-time measurements of oceanic sea states

NASA Astrophysics Data System (ADS)

Fedele, Francesco; Benetazzo, Alvise; Gallego, Guillermo; Shih, Ping-Chang; Yezzi, Anthony; Barbariol, Francesco; Ardhuin, Fabrice

2013-10-01

Stereo video techniques are effective for estimating the space-time wave dynamics over an area of the ocean. Indeed, a stereo camera view allows retrieval of both spatial and temporal data whose statistical content is richer than that of time series data retrieved from point wave probes. We present an application of the Wave Acquisition Stereo System (WASS) for the analysis of offshore video measurements of gravity waves in the Northern Adriatic Sea and near the southern seashore of the Crimean peninsula, in the Black Sea. We use classical epipolar techniques to reconstruct the sea surface from the stereo pairs sequentially in time, viz. a sequence of spatial snapshots. We also present a variational approach that exploits the entire data image set providing a global space-time imaging of the sea surface, viz. simultaneous reconstruction of several spatial snapshots of the surface in order to guarantee continuity of the sea surface both in space and time. Analysis of the WASS measurements show that the sea surface can be accurately estimated in space and time together, yielding associated directional spectra and wave statistics at a point in time that agrees well with probabilistic models. In particular, WASS stereo imaging is able to capture typical features of the wave surface, especially the crest-to-trough asymmetry due to second order nonlinearities, and the observed shape of large waves are fairly described by theoretical models based on the theory of quasi-determinism (Boccotti, 2000). Further, we investigate space-time extremes of the observed stationary sea states, viz. the largest surface wave heights expected over a given area during the sea state duration. The WASS analysis provides the first experimental proof that a space-time extreme is generally larger than that observed in time via point measurements, in agreement with the predictions based on stochastic theories for global maxima of Gaussian fields.

Preferential sampling and Bayesian geostatistics: Statistical modeling and examples.

PubMed

Cecconi, Lorenzo; Grisotto, Laura; Catelan, Dolores; Lagazio, Corrado; Berrocal, Veronica; Biggeri, Annibale

2016-08-01

Preferential sampling refers to any situation in which the spatial process and the sampling locations are not stochastically independent. In this paper, we present two examples of geostatistical analysis in which the usual assumption of stochastic independence between the point process and the measurement process is violated. To account for preferential sampling, we specify a flexible and general Bayesian geostatistical model that includes a shared spatial random component. We apply the proposed model to two different case studies that allow us to highlight three different modeling and inferential aspects of geostatistical modeling under preferential sampling: (1) continuous or finite spatial sampling frame; (2) underlying causal model and relevant covariates; and (3) inferential goals related to mean prediction surface or prediction uncertainty. © The Author(s) 2016.

Spherical earth gravity and magnetic anomaly analysis by equivalent point source inversion

NASA Technical Reports Server (NTRS)

Von Frese, R. R. B.; Hinze, W. J.; Braile, L. W.

1981-01-01

To facilitate geologic interpretation of satellite elevation potential field data, analysis techniques are developed and verified in the spherical domain that are commensurate with conventional flat earth methods of potential field interpretation. A powerful approach to the spherical earth problem relates potential field anomalies to a distribution of equivalent point sources by least squares matrix inversion. Linear transformations of the equivalent source field lead to corresponding geoidal anomalies, pseudo-anomalies, vector anomaly components, spatial derivatives, continuations, and differential magnetic pole reductions. A number of examples using 1 deg-averaged surface free-air gravity anomalies of POGO satellite magnetometer data for the United States, Mexico, and Central America illustrate the capabilities of the method.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

Designing efficient surveys: spatial arrangement of sample points for detection of invasive species

Treesearch

Ludek Berec; John M. Kean; Rebecca Epanchin-Niell; Andrew M. Liebhold; Robert G. Haight

2015-01-01

Effective surveillance is critical to managing biological invasions via early detection and eradication. The efficiency of surveillance systems may be affected by the spatial arrangement of sample locations. We investigate how the spatial arrangement of sample points, ranging from random to fixed grid arrangements, affects the probability of detecting a target...

Remote Sensing Analysis of Temperature and Suspended Sediment Concentration in Ayeyarwady River in Myanmar

NASA Astrophysics Data System (ADS)

Thanda Ko, Nyein; Rutten, Martine

2017-04-01

Detailed spatial coverage of water quality parameters are crucial to better manage rivers. However, collection of water quality parameters is both time consuming and costly for large rivers. This study demonstrates that Operational Land Image (OLI) Sensor on board of Landsat 8 can be successfully applied for the detection of spatial patterns of water temperature as well as suspended sediment concentration (SSC) using the Ayeyarwady river, Myanmar as a case study. Water temperature estimation was obtained from the brightness thermal Band 10 by using the Split-Window algorithm. The study finds that there is a close agreement between the remote sensing temperature and in-situ temperature with relative error in the range from 4.5% to 8.2%. The sediment load of Ayeyarwady river is ranked as the third-largest sediment load among the world's rivers but there is very little known about this important parameter, due to a lack of adequate gauge data. The single band reflectance of Landsat image (Band 5) seems a good indicator for the estimation of SSC with relative error in the range of less than 10% but the developed empirical formula by the power relation with the only seven ground reference points is uncertain to apply for the entire river basin. It is to note that an important constraint for the sediment analysis is the availability of spatial and temporal ground reference data. Future studies should also focus on the improvement of ground reference data points to become more reliable, because most of the river in Asia, especially in Myanmar, don't have readily available continuous ground sediment data points due to lack of measurement gauge stations through the river.

Parameterized approximation of lacunarity functions derived from airborne laser scanning point clouds of forested areas

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Varga, Katalin; Heilmeier, Hermann

2017-04-01

Lacunarity, a measure of the spatial distribution of the empty space is found to be a useful descriptive quantity of the forest structure. Its calculation, based on laser-scanned point clouds, results in a four-dimensional data set. The evaluation of results needs sophisticated tools and visualization techniques. To simplify the evaluation, it is straightforward to use approximation functions fitted to the results. The lacunarity function L(r), being a measure of scale-independent structural properties, has a power-law character. Previous studies showed that log(log(L(r))) transformation is suitable for analysis of spatial patterns. Accordingly, transformed lacunarity functions can be approximated by appropriate functions either in the original or in the transformed domain. As input data we have used a number of laser-scanned point clouds of various forests. The lacunarity distribution has been calculated along a regular horizontal grid at various (relative) elevations. The lacunarity data cube then has been logarithm-transformed and the resulting values became the input of parameter estimation at each point (point of interest, POI). This way at each POI a parameter set is generated that is suitable for spatial analysis. The expectation is that the horizontal variation and vertical layering of the vegetation can be characterized by this procedure. The results show that the transformed L(r) functions can be typically approximated by exponentials individually, and the residual values remain low in most cases. However, (1) in most cases the residuals may vary considerably, and (2) neighbouring POIs often give rather differing estimates both in horizontal and in vertical directions, of them the vertical variation seems to be more characteristic. In the vertical sense, the distribution of estimates shows abrupt changes at places, presumably related to the vertical structure of the forest. In low relief areas horizontal similarity is more typical, in higher relief areas horizontal similarity fades out in short distances. Some of the input data have been acquired in the framework of the ChangeHabitats2 project financed by the European Union. BS contributed as an Alexander von Humboldt Research Fellow.

Vibration of a spatial elastica constrained inside a straight tube

NASA Astrophysics Data System (ADS)

Chen, Jen-San; Fang, Joyce

2014-04-01

In this paper we study the dynamic behavior of a clamped-clamped spatial elastica under edge thrust constrained inside a straight cylindrical tube. Attention is focused on the calculation of the natural frequencies and mode shapes of the planar and spatial one-point-contact deformations. The main issue in determining the natural frequencies of a constrained rod is the movement of the contact point during vibration. In order to capture the physical essence of the contact-point movement, an Eulerian description of the equations of motion based on director theory is formulated. After proper linearization of the equations of motion, boundary conditions, and contact conditions, the natural frequencies and mode shapes of the elastica can be obtained by solving a system of eighteen first-order differential equations with shooting method. It is concluded that the planar one-point-contact deformation becomes unstable and evolves to a spatial deformation at a bifurcation point in both displacement and force control procedures.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Privacy protection versus cluster detection in spatial epidemiology.

PubMed

Olson, Karen L; Grannis, Shaun J; Mandl, Kenneth D

2006-11-01

Patient data that includes precise locations can reveal patients' identities, whereas data aggregated into administrative regions may preserve privacy and confidentiality. We investigated the effect of varying degrees of address precision (exact latitude and longitude vs the center points of zip code or census tracts) on detection of spatial clusters of cases. We simulated disease outbreaks by adding supplementary spatially clustered emergency department visits to authentic hospital emergency department syndromic surveillance data. We identified clusters with a spatial scan statistic and evaluated detection rate and accuracy. More clusters were identified, and clusters were more accurately detected, when exact locations were used. That is, these clusters contained at least half of the simulated points and involved few additional emergency department visits. These results were especially apparent when the synthetic clustered points crossed administrative boundaries and fell into multiple zip code or census tracts. The spatial cluster detection algorithm performed better when addresses were analyzed as exact locations than when they were analyzed as center points of zip code or census tracts, particularly when the clustered points crossed administrative boundaries. Use of precise addresses offers improved performance, but this practice must be weighed against privacy concerns in the establishment of public health data exchange policies.

[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.

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons

PubMed Central

Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley’s K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains. PMID:28662210

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons.

PubMed

Anton-Sanchez, Laura; Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley's K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains.

TESS

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

Dmitriy Morozov, Tom Peterka

2014-07-29

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets. As the scale of simulations and observations surpasses billions of particles, a distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this software is a distributed-memory parallel Delaunay and Voronoi tessellation algorithm based on existing serial computational geometry libraries that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions.

A method of 3D object recognition and localization in a cloud of points

NASA Astrophysics Data System (ADS)

Bielicki, Jerzy; Sitnik, Robert

2013-12-01

The proposed method given in this article is prepared for analysis of data in the form of cloud of points directly from 3D measurements. It is designed for use in the end-user applications that can directly be integrated with 3D scanning software. The method utilizes locally calculated feature vectors (FVs) in point cloud data. Recognition is based on comparison of the analyzed scene with reference object library. A global descriptor in the form of a set of spatially distributed FVs is created for each reference model. During the detection process, correlation of subsets of reference FVs with FVs calculated in the scene is computed. Features utilized in the algorithm are based on parameters, which qualitatively estimate mean and Gaussian curvatures. Replacement of differentiation with averaging in the curvatures estimation makes the algorithm more resistant to discontinuities and poor quality of the input data. Utilization of the FV subsets allows to detect partially occluded and cluttered objects in the scene, while additional spatial information maintains false positive rate at a reasonably low level.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

PubMed

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds

PubMed Central

Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds. PMID:27974884

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

NPP VIIRS Geometric Performance Status

NASA Technical Reports Server (NTRS)

Lin, Guoqing; Wolfe, Robert E.; Nishihama, Masahiro

2011-01-01

Visible Infrared Imager Radiometer Suite (VIIRS) instrument on-board the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite is scheduled for launch in October, 2011. It is to provide satellite measured radiance/reflectance data for both weather and climate applications. Along with radiometric calibration, geometric characterization and calibration of Sensor Data Records (SDRs) are crucial to the VIIRS Environmental Data Record (EDR) algorithms and products which are used in numerical weather prediction (NWP). The instrument geometric performance includes: 1) sensor (detector) spatial response, parameterized by the dynamic field of view (DFOV) in the scan direction and instantaneous FOV (IFOV) in the track direction, modulation transfer function (MTF) for the 17 moderate resolution bands (M-bands), and horizontal spatial resolution (HSR) for the five imagery bands (I-bands); 2) matrices of band-to-band co-registration (BBR) from the corresponding detectors in all band pairs; and 3) pointing knowledge and stability characteristics that includes scan plane tilt, scan rate and scan start position variations, and thermally induced variations in pointing with respect to orbital position. They have been calibrated and characterized through ground testing under ambient and thermal vacuum conditions, numerical modeling and analysis. This paper summarizes the results, which are in general compliance with specifications, along with anomaly investigations, and describes paths forward for characterizing on-orbit BBR and spatial response, and for improving instrument on-orbit performance in pointing and geolocation.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

Analysis of point source size on measurement accuracy of lateral point-spread function of confocal Raman microscopy

NASA Astrophysics Data System (ADS)

Fu, Shihang; Zhang, Li; Hu, Yao; Ding, Xiang

2018-01-01

Confocal Raman Microscopy (CRM) has matured to become one of the most powerful instruments in analytical science because of its molecular sensitivity and high spatial resolution. Compared with conventional Raman Microscopy, CRM can perform three dimensions mapping of tiny samples and has the advantage of high spatial resolution thanking to the unique pinhole. With the wide application of the instrument, there is a growing requirement for the evaluation of the imaging performance of the system. Point-spread function (PSF) is an important approach to the evaluation of imaging capability of an optical instrument. Among a variety of measurement methods of PSF, the point source method has been widely used because it is easy to operate and the measurement results are approximate to the true PSF. In the point source method, the point source size has a significant impact on the final measurement accuracy. In this paper, the influence of the point source sizes on the measurement accuracy of PSF is analyzed and verified experimentally. A theoretical model of the lateral PSF for CRM is established and the effect of point source size on full-width at half maximum of lateral PSF is simulated. For long-term preservation and measurement convenience, PSF measurement phantom using polydimethylsiloxane resin, doped with different sizes of polystyrene microspheres is designed. The PSF of CRM with different sizes of microspheres are measured and the results are compared with the simulation results. The results provide a guide for measuring the PSF of the CRM.

Statistical and Spatial Analysis of Bathymetric Data for the St. Clair River, 1971-2007

USGS Publications Warehouse

Bennion, David

2009-01-01

To address questions concerning ongoing geomorphic processes in the St. Clair River, selected bathymetric datasets spanning 36 years were analyzed. Comparisons of recent high-resolution datasets covering the upper river indicate a highly variable, active environment. Although statistical and spatial comparisons of the datasets show that some changes to the channel size and shape have taken place during the study period, uncertainty associated with various survey methods and interpolation processes limit the statistically certain results. The methods used to spatially compare the datasets are sensitive to small variations in position and depth that are within the range of uncertainty associated with the datasets. Characteristics of the data, such as the density of measured points and the range of values surveyed, can also influence the results of spatial comparison. With due consideration of these limitations, apparently active and ongoing areas of elevation change in the river are mapped and discussed.

Spatial and Temporal Changes of Aerosol Optical Depth and its Driving Factors Based on Modis in Jiangsu Province

NASA Astrophysics Data System (ADS)

Jiang, C.; Xu, Q.; Gu, Y. K.; Qian, X. Y.; He, J. N.

2018-04-01

Aerosol Optical Depth (AOD) is of great value for studying air mass and its changes. In this paper, we studied the spatial-temporal changes of AOD and its driving factors based on spatial autocorrelation model, gravity model and multiple regression analysis in Jiangsu Province from 2007 to 2016. The results showed that in terms of spatial distribution, the southern AOD value is higher, and the high-value aggregation areas are significant, while the northern AOD value is lower, but the low-value aggregation areas constantly change. The AOD gravity centers showed a clear point-like aggregation. In terms of temporal changes, the overall AOD in Jiangsu Province increased year by year in fluctuation. In terms of driving factors, the total amount of vehicles, precipitation and temperature are important factors for the growth of AOD.

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

NASA Astrophysics Data System (ADS)

Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; De Leo, Giulio A.; Casagrandi, Renato; Gatto, Marino

2017-10-01

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Unleashing spatially distributed ecohydrology modeling using Big Data tools

NASA Astrophysics Data System (ADS)

Miles, B.; Idaszak, R.

2015-12-01

Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well as point time series of arbitrary variables at arbitrary points in space within a watershed or river basin. By treating ecohydrology modeling as a Big Data problem, we hope to provide a platform for answering transformative science and management questions related to water quantity and quality in a world of non-stationary climate.

Statistical analysis of the surface figure of the James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Lightsey, Paul A.; Chaney, David; Gallagher, Benjamin B.; Brown, Bob J.; Smith, Koby; Schwenker, John

2012-09-01

The performance of an optical system is best characterized by either the point spread function (PSF) or the optical transfer function (OTF). However, for system budgeting purposes, it is convenient to use a single scalar metric, or a combination of a few scalar metrics to track performance. For the James Webb Space Telescope, the Observatory level requirements were expressed in metrics of Strehl Ratio, and Encircled Energy. These in turn were converted to the metrics of total rms WFE and rms WFE within spatial frequency domains. The 18 individual mirror segments for the primary mirror segment assemblies (PMSA), the secondary mirror (SM), tertiary mirror (TM), and Fine Steering Mirror have all been fabricated. They are polished beryllium mirrors with a protected gold reflective coating. The statistical analysis of the resulting Surface Figure Error of these mirrors has been analyzed. The average spatial frequency distribution and the mirror-to-mirror consistency of the spatial frequency distribution are reported. The results provide insight to system budgeting processes for similar optical systems.

GIS-based analysis of drinking-water supply structures: a module for microbial risk assessment.

PubMed

Kistemann, T; Herbst, S; Dangendorf, F; Exner, M

2001-05-01

Water-related infections constitute an important health impact world-wide. A set of tools serving for Microbial Risk Assessment (MRA) of waterborne diseases should comprise the entire drinking-water management system and take into account the Hazard Analysis and Critical Control Point (HACCP) concept which provides specific Critical Control Points (CCPs) reflecting each step of drinking-water provision. A Geographical Information System (GIS) study concerning water-supply structure (WSS) was conducted in the Rhein-Berg District (North Rhine-Westphalia, Germany). As a result, suitability of the existing water databases HYGRIS (hydrological basis geo-information system) and TEIS (drinking-water recording and information system) for the development of a WSS-GIS module could be demonstrated. Spatial patterns within the integrated raw and drinking-water data can easily be uncovered by GIS-specific options. The application of WSS-GIS allows a rapid visualization and analysis of drinking-water supply structure and offers huge advantages concerning microbial monitoring of raw and drinking water as well as recognition and investigation of incidents and outbreaks. Increasing requests regarding health protection and health reporting, demands for a better outbreak management and water-related health impacts of global climate change are major challenges of future water management to be tackled with methods including spatial analysis. GIS is assumed to be a very useful tool to meet these requirements.

Analysis of the dependence of extreme rainfalls

NASA Astrophysics Data System (ADS)

Padoan, Simone; Ancey, Christophe; Parlange, Marc

2010-05-01

The aim of spatial analysis is to quantitatively describe the behavior of environmental phenomena such as precipitation levels, wind speed or daily temperatures. A number of generic approaches to spatial modeling have been developed[1], but these are not necessarily ideal for handling extremal aspects given their focus on mean process levels. The areal modelling of the extremes of a natural process observed at points in space is important in environmental statistics; for example, understanding extremal spatial rainfall is crucial in flood protection. In light of recent concerns over climate change, the use of robust mathematical and statistical methods for such analyses has grown in importance. Multivariate extreme value models and the class of maxstable processes [2] have a similar asymptotic motivation to the univariate Generalized Extreme Value (GEV) distribution , but providing a general approach to modeling extreme processes incorporating temporal or spatial dependence. Statistical methods for max-stable processes and data analyses of practical problems are discussed by [3] and [4]. This work illustrates methods to the statistical modelling of spatial extremes and gives examples of their use by means of a real extremal data analysis of Switzerland precipitation levels. [1] Cressie, N. A. C. (1993). Statistics for Spatial Data. Wiley, New York. [2] de Haan, L and Ferreria A. (2006). Extreme Value Theory An Introduction. Springer, USA. [3] Padoan, S. A., Ribatet, M and Sisson, S. A. (2009). Likelihood-Based Inference for Max-Stable Processes. Journal of the American Statistical Association, Theory & Methods. In press. [4] Davison, A. C. and Gholamrezaee, M. (2009), Geostatistics of extremes. Journal of the Royal Statistical Society, Series B. To appear.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations

NASA Astrophysics Data System (ADS)

Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter

2013-04-01

Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the development of a 3D geometric plant model. The results are expected to improve knowledge on how the architectural system and allometric relationships of the plants relate to ecological and hydrodynamic properties.

A look back on how far to walk: Systematic review and meta-analysis of physical access to skilled care for childbirth in Sub-Saharan Africa

PubMed Central

2017-01-01

Objectives To (i) summarize the methods undertaken to measure physical accessibility as the spatial separation between women and health services, and (ii) establish the extent to which distance to skilled care for childbirth affects utilization in Sub-Saharan Africa. Method We defined spatial separation as the distance/travel time between women and skilled care services. The use of skilled care at birth referred to either the location or attendant of childbirth. The main criterion for inclusion was any quantification of the relationship between spatial separation and use of skilled care at birth. The approaches undertaken to measure distance/travel time were summarized in a narrative format. We obtained pooled adjusted odds ratios (aOR) from studies that controlled for financial means, education and (perceived) need of care in a meta-analysis. Results 57 articles were included (40 studied distance and 25 travel time), in which distance/travel time were found predominately self-reported or estimated in a geographic information system based on geographic coordinates. Approaches of distance/travel time measurement were generally poorly detailed, especially for self-reported data. Crucial features such as start point of origin and the mode of transportation for travel time were most often unspecified. Meta-analysis showed that increased distance to maternity care had an inverse association with utilization (n = 10, pooled aOR = 0.90/1km, 95%CI = 0.85–0.94). Distance from a hospital for rural women showed an even more pronounced effect on utilization (n = 2, pooled aOR = 0.58/1km increase, 95%CI = 0.31,1.09). The effect of spatial separation appears to level off beyond critical point when utilization was generally low. Conclusion Although the reporting and measurements of spatial separation in low-resource settings needs further development, we found evidence that a lack of geographic access impedes use. Utilization is conditioned on access, researchers and policy makers should therefore prioritize quality data for the evidence-base to ensure that women everywhere have the potential to access obstetric care. PMID:28910302

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.

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.

Analysis of temporal decay of diffuse broadband sound fields in enclosures by decomposition in powers of an absorption parameter

NASA Astrophysics Data System (ADS)

Bliss, Donald; Franzoni, Linda; Rouse, Jerry; Manning, Ben

2005-09-01

An analysis method for time-dependent broadband diffuse sound fields in enclosures is described. Beginning with a formulation utilizing time-dependent broadband intensity boundary sources, the strength of these wall sources is expanded in a series in powers of an absorption parameter, thereby giving a separate boundary integral problem for each power. The temporal behavior is characterized by a Taylor expansion in the delay time for a source to influence an evaluation point. The lowest-order problem has a uniform interior field proportional to the reciprocal of the absorption parameter, as expected, and exhibits relatively slow exponential decay. The next-order problem gives a mean-square pressure distribution that is independent of the absorption parameter and is primarily responsible for the spatial variation of the reverberant field. This problem, which is driven by input sources and the lowest-order reverberant field, depends on source location and the spatial distribution of absorption. Additional problems proceed at integer powers of the absorption parameter, but are essentially higher-order corrections to the spatial variation. Temporal behavior is expressed in terms of an eigenvalue problem, with boundary source strength distributions expressed as eigenmodes. Solutions exhibit rapid short-time spatial redistribution followed by long-time decay of a predominant spatial mode.

Fine-scale spatial distribution of the common lugworm Arenicola marina, and effects of intertidal clam fishing

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.

2014-04-01

Despite its ubiquity and its role as an ecosystem engineer on temperate intertidal mudflats, little is known of the spatial ecology of the lugworm Arenicola marina. We estimated lugworm densities and analyzed the spatial distribution of A. marina on a French Atlantic mudflat subjected to long-term clam digging activities, and compared these to a nearby pristine reference mudflat, using a combination of geostatistical techniques: point-pattern analysis, autocorrelation, and wavelet analysis. Lugworm densities were an order of magnitude greater at the reference site. Although A. marina showed an aggregative spatial distribution at both sites, the characteristics and intensity of aggregation differed markedly between sites. The reference site showed an inhibition process (regular distribution) at distances <7.5 cm, whereas the impacted site showed a random distribution at this scale. At distances from 15 cm to several tens of meters, the spatial distribution of A. marina was clearly aggregated at both sites; however, the autocorrelation strength was much weaker at the impacted site. In addition, the non-impacted site presented multi-scale spatial distribution, which was not evident at the impacted site. The differences observed between the spatial distributions of the fishing-impacted vs. the non-impacted site reflect similar findings for other components of these two mudflat ecosystems, suggesting common community-level responses to prolonged mechanical perturbation: a decrease in naturally-occurring aggregation. This change may have consequences for basic biological characteristics such as reproduction, recruitment, growth, and feeding.

High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation

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

Peterka, Tom; Morozov, Dmitriy; Phillips, Carolyn

2014-11-14

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization; but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared-memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbormore » points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.« less

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

Evaluating spatial interaction of soil property with non-point source pollution at watershed scale: the phosphorus indicator in Northeast China.

PubMed

Ouyang, Wei; Huang, Haobo; Hao, Fanghua; Shan, Yushu; Guo, Bobo

2012-08-15

To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20-40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area. Copyright © 2012 Elsevier B.V. All rights reserved.

Predicting wildfire occurrence distribution with spatial point process models and its uncertainty assessment: a case study in the Lake Tahoe Basin, USA

Treesearch

Jian Yang; Peter J. Weisberg; Thomas E. Dilts; E. Louise Loudermilk; Robert M. Scheller; Alison Stanton; Carl Skinner

2015-01-01

Strategic fire and fuel management planning benefits from detailed understanding of how wildfire occurrences are distributed spatially under current climate, and from predictive models of future wildfire occurrence given climate change scenarios. In this study, we fitted historical wildfire occurrence data from 1986 to 2009 to a suite of spatial point process (SPP)...

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.

Effective intracortical microstimulation parameters applied to primary motor cortex for evoking forelimb movements to stable spatial end points

PubMed Central

Van Acker, Gustaf M.; Amundsen, Sommer L.; Messamore, William G.; Zhang, Hongyu Y.; Luchies, Carl W.; Kovac, Anthony

2013-01-01

High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) applied to motor cortex is recognized as a useful and informative method for corticomotor mapping by evoking natural-appearing movements of the limb to consistent stable end-point positions. An important feature of these movements is that stimulation of a specific site in motor cortex evokes movement to the same spatial end point regardless of the starting position of the limb. The goal of this study was to delineate effective stimulus parameters for evoking forelimb movements to stable spatial end points from HFLD-ICMS applied to primary motor cortex (M1) in awake monkeys. We investigated stimulation of M1 as combinations of frequency (30–400 Hz), amplitude (30–200 μA), and duration (0.5–2 s) while concurrently recording electromyographic (EMG) activity from 24 forelimb muscles and movement kinematics with a motion capture system. Our results suggest a range of parameters (80–140 Hz, 80–140 μA, and 1,000-ms train duration) that are effective and safe for evoking forelimb translocation with subsequent stabilization at a spatial end point. The mean time for stimulation to elicit successful movement of the forelimb to a stable spatial end point was 475.8 ± 170.9 ms. Median successful frequency and amplitude were 110 Hz and 110 μA, respectively. Attenuated parameters resulted in inconsistent, truncated, or undetectable movements, while intensified parameters yielded no change to movement end points and increased potential for large-scale physiological spread and adverse focal motor effects. Establishing cortical stimulation parameters yielding consistent forelimb movements to stable spatial end points forms the basis for a systematic and comprehensive mapping of M1 in terms of evoked movements and associated muscle synergies. Additionally, the results increase our understanding of how the central nervous system may encode movement. PMID:23741044

Restoring method for missing data of spatial structural stress monitoring based on correlation

NASA Astrophysics Data System (ADS)

Zhang, Zeyu; Luo, Yaozhi

2017-07-01

Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.

Spatial distribution and ecological environment analysis of great gerbil in Xinjiang Plague epidemic foci based on remote sensing

NASA Astrophysics Data System (ADS)

Gao, Mengxu; Li, Qun; Cao, Chunxiang; Wang, Juanle

2014-03-01

Yersinia pestis (Plague bacterium) from great gerbil was isolated in 2005 in Xinjiang Dzungarian Basin, which confirmed the presence of the plague epidemic foci. This study analysed the spatial distribution and suitable habitat of great gerbil based on the monitoring data of great gerbil from Chinese Center for Disease Control and Prevention, as well as the ecological environment elements obtained from remote sensing products. The results showed that: (1) 88.5% (277/313) of great gerbil distributed in the area of elevation between 200 and 600 meters. (2) All the positive points located in the area with a slope of 0-3 degree, and the sunny tendency on aspect was not obvious. (3) All 313 positive points of great gerbil distributed in the area with an average annual temperature from 5 to 11 °C, and 165 points with an average annual temperature from 7 to 9 °C. (4) 72.8% (228/313) of great gerbil survived in the area with an annual precipitation of 120-200mm. (5) The positive points of great gerbil increased correspondingly with the increasing of NDVI value, but there is no positive point when NDVI is higher than 0.521, indicating the suitability of vegetation for great gerbil. This study explored a broad and important application for the monitoring and prevention of plague using remote sensing and geographic information system.

Expading fluvial remote sensing to the riverscape: Mapping depth and grain size on the Merced River, California

NASA Astrophysics Data System (ADS)

Richardson, Ryan T.

This study builds upon recent research in the field of fluvial remote sensing by applying techniques for mapping physical attributes of rivers. Depth, velocity, and grain size are primary controls on the types of habitat present in fluvial ecosystems. This thesis focuses on expanding fluvial remote sensing to larger spatial extents and sub-meter resolutions, which will increase our ability to capture the spatial heterogeneity of habitat at a resolution relevant to individual salmonids and an extent relevant to species. This thesis consists of two chapters, one focusing on expanding the spatial extent over which depth can be mapped using Optimal Band Ratio Analysis (OBRA) and the other developing general relations for mapping grain size from three-dimensional topographic point clouds. The two chapters are independent but connected by the overarching goal of providing scientists and managers more useful tools for quantifying the amount and quality of salmonid habitat via remote sensing. The OBRA chapter highlights the true power of remote sensing to map depths from hyperspectral images as a central component of watershed scale analysis, while also acknowledging the great challenges involved with increasing spatial extent. The grain size mapping chapter establishes the first general relations for mapping grain size from roughness using point clouds. These relations will significantly reduce the time needed in the field by eliminating the need for independent measurements of grain size for calibrating the roughness-grain size relationship and thus making grain size mapping with SFM more cost effective for river restoration and monitoring. More data from future studies are needed to refine these relations and establish their validity and generality. In conclusion, this study adds to the rapidly growing field of fluvial remote sensing and could facilitate river research and restoration.

Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

NASA Astrophysics Data System (ADS)

Hiebl, Johann; Frei, Christoph

2018-04-01

Spatial precipitation datasets that are long-term consistent, highly resolved and extend over several decades are an increasingly popular basis for modelling and monitoring environmental processes and planning tasks in hydrology, agriculture, energy resources management, etc. Here, we present a grid dataset of daily precipitation for Austria meant to promote such applications. It has a grid spacing of 1 km, extends back till 1961 and is continuously updated. It is constructed with the classical two-tier analysis, involving separate interpolations for mean monthly precipitation and daily relative anomalies. The former was accomplished by kriging with topographic predictors as external drift utilising 1249 stations. The latter is based on angular distance weighting and uses 523 stations. The input station network was kept largely stationary over time to avoid artefacts on long-term consistency. Example cases suggest that the new analysis is at least as plausible as previously existing datasets. Cross-validation and comparison against experimental high-resolution observations (WegenerNet) suggest that the accuracy of the dataset depends on interpretation. Users interpreting grid point values as point estimates must expect systematic overestimates for light and underestimates for heavy precipitation as well as substantial random errors. Grid point estimates are typically within a factor of 1.5 from in situ observations. Interpreting grid point values as area mean values, conditional biases are reduced and the magnitude of random errors is considerably smaller. Together with a similar dataset of temperature, the new dataset (SPARTACUS) is an interesting basis for modelling environmental processes, studying climate change impacts and monitoring the climate of Austria.

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

NASA Astrophysics Data System (ADS)

Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

2018-01-01

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

Geomorphological activity at a rock glacier front detected with a 3D density-based clustering algorithm

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2017-02-01

Acquisition of high density point clouds using terrestrial laser scanners (TLSs) has become commonplace in geomorphic science. The derived point clouds are often interpolated onto regular grids and the grids compared to detect change (i.e. erosion and deposition/advancement movements). This procedure is necessary for some applications (e.g. digital terrain analysis), but it inevitably leads to a certain loss of potentially valuable information contained within the point clouds. In the present study, an alternative methodology for geomorphological analysis and feature detection from point clouds is proposed. It rests on the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN), applied to TLS data for a rock glacier front slope in the Swiss Alps. The proposed methods allowed the detection and isolation of movements directly from point clouds which yield to accuracies in the following computation of volumes that depend only on the actual registered distance between points. We demonstrated that these values are more conservative than volumes computed with the traditional DEM comparison. The results are illustrated for the summer of 2015, a season of enhanced geomorphic activity associated with exceptionally high temperatures.

Privacy Protection Versus Cluster Detection in Spatial Epidemiology

PubMed Central

Olson, Karen L.; Grannis, Shaun J.; Mandl, Kenneth D.

2006-01-01

Objectives. Patient data that includes precise locations can reveal patients’ identities, whereas data aggregated into administrative regions may preserve privacy and confidentiality. We investigated the effect of varying degrees of address precision (exact latitude and longitude vs the center points of zip code or census tracts) on detection of spatial clusters of cases. Methods. We simulated disease outbreaks by adding supplementary spatially clustered emergency department visits to authentic hospital emergency department syndromic surveillance data. We identified clusters with a spatial scan statistic and evaluated detection rate and accuracy. Results. More clusters were identified, and clusters were more accurately detected, when exact locations were used. That is, these clusters contained at least half of the simulated points and involved few additional emergency department visits. These results were especially apparent when the synthetic clustered points crossed administrative boundaries and fell into multiple zip code or census tracts. Conclusions. The spatial cluster detection algorithm performed better when addresses were analyzed as exact locations than when they were analyzed as center points of zip code or census tracts, particularly when the clustered points crossed administrative boundaries. Use of precise addresses offers improved performance, but this practice must be weighed against privacy concerns in the establishment of public health data exchange policies. PMID:17018828

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

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

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch; Zaidi, Habib; Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailedmore » investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.« less

Rapid Analysis of Mass Distribution of Radiation Shielding

NASA Technical Reports Server (NTRS)

Zapp, Edward

2007-01-01

Radiation Shielding Evaluation Toolset (RADSET) is a computer program that rapidly calculates the spatial distribution of mass of an arbitrary structure for use in ray-tracing analysis of the radiation-shielding properties of the structure. RADSET was written to be used in conjunction with unmodified commercial computer-aided design (CAD) software that provides access to data on the structure and generates selected three-dimensional-appearing views of the structure. RADSET obtains raw geometric, material, and mass data on the structure from the CAD software. From these data, RADSET calculates the distribution(s) of the masses of specific materials about any user-specified point(s). The results of these mass-distribution calculations are imported back into the CAD computing environment, wherein the radiation-shielding calculations are performed.

GazeAppraise v. 0.1

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

Wilson, Andrew; Haass, Michael; Rintoul, Mark Daniel

GazeAppraise advances the state of the art of gaze pattern analysis using methods that simultaneously analyze spatial and temporal characteristics of gaze patterns. GazeAppraise enables novel research in visual perception and cognition; for example, using shape features as distinguishing elements to assess individual differences in visual search strategy. Given a set of point-to-point gaze sequences, hereafter referred to as scanpaths, the method constructs multiple descriptive features for each scanpath. Once the scanpath features have been calculated, they are used to form a multidimensional vector representing each scanpath and cluster analysis is performed on the set of vectors from all scanpaths.more » An additional benefit of this method is the identification of causal or correlated characteristics of the stimuli, subjects, and visual task through statistical analysis of descriptive metadata distributions within and across clusters.« less

New spatial clustering-based models for optimal urban facility location considering geographical obstacles

NASA Astrophysics Data System (ADS)

Javadi, Maryam; Shahrabi, Jamal

2014-03-01

The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising improvements of the allocation, the logistics costs and the response time. It can also be inferred from this study that the P2D-based model and the SPD-based model yield similar results in terms of the facility location and the demand allocation. It is noted that the P2D-based model showed better execution time than the SPD-based model. Considering logistic costs, facility location and response time, the P2D-based model was appropriate choice for urban facility location problem considering the geographical obstacles.

Inland waterway ports nodal attraction indices relevant in development strategies on regional level

NASA Astrophysics Data System (ADS)

Dinu, O.; Burciu, Ş.; Oprea, C.; Ilie, A.; Rosca, M.

2016-08-01

Present paper aims to propose a set of ranking indices and related criteria, concerning mainly spatial analysis, for the inland waterway port, with special view on inland ports of Danube. Commonly, the attraction potential of a certain transport node is assessed by its spatial accessibility indices considering both spatial features of the location provided by the networks that connect into that node and its economic potential defining the level of traffic flows depending on the economic centers of its hinterland. Paper starts with a overview of the critical needs that are required for potential sites to become inland waterway ports and presents nodal functions that coexist at different levels, leading to a port hierarchy from the points of view of: capacity, connection to hinterland, traffic structure and volume. After a brief review of the key inland waterway port ranking criterion, a selection of nodal attraction measures is made. Particular considerations for the Danube inland port case follows proposed methodology concerning indices of performance for network scale and centrality. As expected, the shorter the distance from an inland port to the nearest access point the greater accessibility. Major differences in ranking, dependent on selected criterion, were registered.

Local spatial frequency analysis for computer vision

NASA Technical Reports Server (NTRS)

Krumm, John; Shafer, Steven A.

1990-01-01

A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

PubMed Central

Ibrahim, Bashar; Henze, Richard; Gruenert, Gerd; Egbert, Matthew; Huwald, Jan; Dittrich, Peter

2013-01-01

A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models. PMID:24709796

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

NASA Astrophysics Data System (ADS)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi-precision information assimilation method of other geotechnical parameters.

Relative impacts of the fragmentation and spatial structure of habitats on freshwater fish distributions: application on French watersheds (Invited)

NASA Astrophysics Data System (ADS)

Le Pichon, C.; Belliard, J.; Talès, E.; Gorges, G.; Clément, F.

2009-12-01

Most of the rivers of the Ile de France region, intimately linked with the megalopolis of Paris, are severely altered and freshwater fishes are exposed to habitat alteration, reduced connectivity and pollution. Several species thus present fragmented distributions and decreasing densities. In this context, the European Water Framework Directive (2000) has goals of hydrosystems rehabilitation and no further damage. In particular, the preservation and restoration of ecological connectivity of river networks is a key element for fish populations. These goals require the identification of natural and anthropological factors which influence the spatial distribution of species. We have proposed a riverscape approach, based on landscape ecology concepts, combined with a set of spatial analysis methods to assess the multiscale relationships between the spatial pattern of fish habitats and processes depending on fish movements. In particular, we used this approach to test the relative roles of spatial arrangement of fish habitats and the presence of physical barriers in explaining fish spatial distributions in a small rural watershed (106 km2). We performed a spatially continuous analysis of fish-habitat relationships. Fish habitats and physical barriers were mapped along the river network (33 km) with a GPS and imported into a GIS. In parallel, a longitudinal electrofishing survey of the distribution and abundance of fishes was made using a point abundance sampling scheme. Longitudinal arrangement of fish habitats were evaluated using spatial analysis methods: patch/distance metrics and moving window analysis. Explanatory models were developed to test the relative contribution of local environmental variables and spatial context in explaining fish presence. We have recorded about 100 physical barriers, on average one every 330 meters; most artificial barriers were road pipe culverts, falls associated with ponds and sluice gates. Contrasted fish communities and densities were observed in the different areas of the watershed, related to various land use (riparian forest or agriculture). The first results of fish-habitat association analysis on a 5 km stream are that longitudinal distribution of fish species was mainly impacted by falls associated with ponds. The impact was both due to the barrier effect and to the modification of aquatic habitats. Abundance distribution of Salmo trutta and Cottus gobio was particularly affected. Spatially continuous analysis of fish-habitat relationships allowed us to identify the relative impacts of habitat alteration and presence of physical barriers to fish movements. These techniques could help prioritize preservation and restoration policies in human-impacted watersheds, in particular, identifying the key physical barriers to remove.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Updating visual memory across eye movements for ocular and arm motor control.

PubMed

Thompson, Aidan A; Henriques, Denise Y P

2008-11-01

Remembered object locations are stored in an eye-fixed reference frame, so that every time the eyes move, spatial representations must be updated for the arm-motor system to reflect the target's new relative position. To date, studies have not investigated how the brain updates these spatial representations during other types of eye movements, such as smooth-pursuit. Further, it is unclear what information is used in spatial updating. To address these questions we investigated whether remembered locations of pointing targets are updated following smooth-pursuit eye movements, as they are following saccades, and also investigated the role of visual information in estimating eye-movement amplitude for updating spatial memory. Misestimates of eye-movement amplitude were induced when participants visually tracked stimuli presented with a background that moved in either the same or opposite direction of the eye before pointing or looking back to the remembered target location. We found that gaze-dependent pointing errors were similar following saccades and smooth-pursuit and that incongruent background motion did result in a misestimate of eye-movement amplitude. However, the background motion had no effect on spatial updating for pointing, but did when subjects made a return saccade, suggesting that the oculomotor and arm-motor systems may rely on different sources of information for spatial updating.

Spatial and temporal variations of aridity indices in Iraq

NASA Astrophysics Data System (ADS)

Şarlak, Nermin; Mahmood Agha, Omar M. A.

2017-06-01

This study investigates the spatial and temporal variations of the aridity indices to reveal the desertification vulnerability of Iraq region. Relying on temperature and precipitation data taken from 28 meteorological stations for 31 years, the study aims to determine (1) dry land types and their delineating boundaries and (2) temporal change in aridity conditions in Iraq. Lang's aridity (Im), De Martonne's aridity (Am), United Nations Environmental Program (UNEP) aridity (AIu), and Erinç aridity (IE) indices were selected in this study because of the scarcity of the observed data. The analysis of the spatial variation of aridity indices exhibited that the arid and semi-arid regions cover about 97% of the country's areas. As for temporal variations, it was observed that the aridity indices tend to decrease (statistically significant or not) for all stations. The cumulative sum charts (CUSUMs) were applied to detect the year on which the climate pattern of aridity indices had changed from one pattern to another. The abrupt change point was detected around year 1997 for the majority of the stations. Thus, the spatial and temporal aridity characteristics in Iraq were examined for the two periods 1980-1997 and 1998-2011 (before and after the change-point year) to observe the influence of abrupt change point on aridity phenomena. The spatial variation after 1997 was observed from semi-arid (dry sub humid) to arid (semi-arid) especially at the stations located in northern Iraq, while hyper-arid and arid climatic conditions were still dominant over southern and central Iraq. Besides, the negative temporal variations of the two periods 1980-1997 and 1998-2011 were obtained for almost every station. As a result, it was emphasized that Iraq region, like other Middle East regions, has become drier after 1997. The observed reduction in precipitation and increase in temperature for this region seem to make the situation worse in future.

Topological Relations-Based Detection of Spatial Inconsistency in GLOBELAND30

NASA Astrophysics Data System (ADS)

Kang, S.; Chen, J.; Peng, S.

2017-09-01

Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.

Pattern analysis of community health center location in Surabaya using spatial Poisson point process

NASA Astrophysics Data System (ADS)

Kusumaningrum, Choriah Margareta; Iriawan, Nur; Winahju, Wiwiek Setya

2017-11-01

Community health center (puskesmas) is one of the closest health service facilities for the community, which provide healthcare for population on sub-district level as one of the government-mandated community health clinics located across Indonesia. The increasing number of this puskesmas does not directly comply the fulfillment of basic health services needed in such region. Ideally, a puskesmas has to cover up to maximum 30,000 people. The number of puskesmas in Surabaya indicates an unbalance spread in all of the area. This research aims to analyze the spread of puskesmas in Surabaya using spatial Poisson point process model in order to get the effective location of Surabaya's puskesmas which based on their location. The results of the analysis showed that the distribution pattern of puskesmas in Surabaya is non-homogeneous Poisson process and is approched by mixture Poisson model. Based on the estimated model obtained by using Bayesian mixture model couple with MCMC process, some characteristics of each puskesmas have no significant influence as factors to decide the addition of health center in such location. Some factors related to the areas of sub-districts have to be considered as covariate to make a decision adding the puskesmas in Surabaya.

Patterns of Racial Diversity and Segregation in the United States: 1990–2010*

PubMed Central

Wright, Richard; Ellis, Mark; Holloway, Steven R.; Wong, Sandy

2014-01-01

The growing ethnic and racial diversity of the United States is evident at all spatial scales. One of the striking features of this new mixture of peoples, however, is that this new diversity often occurs in tandem with racial concentration. This article surveys these new geographies from four points of view: the nation as a whole, states, large metropolitan areas, and neighborhoods. The analysis at each scale relies on a new taxonomy of racial composition that simultaneously appraises both diversity and the lack thereof (Holloway, Wright, and Ellis 2012). Urban analysis often posits neighborhood racial segregation and diversity as either endpoints on a continuum of racial dominance or mirror images of one another. We disturb that perspective and stress that segregation and diversity must be jointly understood—they are necessarily related, although not as inevitable binary opposites. Using census data from 1990, 2000, and 2010, the research points to how patterns of racial diversity and dominance interact across varying spatial scales. This investigation helps answer some basic questions about the changing geographies of racialized groups, setting the stage for the following articles that explore the relationship between geography and the participation of underrepresented groups in higher education. PMID:25083001

Using GIS to analyze animal movements in the marine environment

USGS Publications Warehouse

Hooge, Philip N.; Eichenlaub, William M.; Solomon, Elizabeth K.; Kruse, Gordon H.; Bez, Nicolas; Booth, Anthony; Dorn, Martin W.; Hills, Susan; Lipcius, Romuald N.; Pelletier, Dominique; Roy, Claude; Smith, Stephen J.; Witherell, David B.

2001-01-01

Advanced methods for analyzing animal movements have been little used in the aquatic research environment compared to the terrestrial. In addition, despite obvious advantages of integrating geographic information systems (GIS) with spatial studies of animal movement behavior, movement analysis tools have not been integrated into GIS for either aquatic or terrestrial environments. We therefore developed software that integrates one of the most commonly used GIS programs (ArcView®) with a large collection of animal movement analysis tools. This application, the Animal Movement Analyst Extension (AMAE), can be loaded as an extension to ArcView® under multiple operating system platforms (PC, Unix, and Mac OS). It contains more than 50 functions, including parametric and nonparametric home range analyses, random walk models, habitat analyses, point and circular statistics, tests of complete spatial randomness, tests for autocorrelation and sample size, point and line manipulation tools, and animation tools. This paper describes the use of these functions in analyzing animal location data; some limited examples are drawn from a sonic-tracking study of Pacific halibut (Hippoglossus stenolepis) in Glacier Bay, Alaska. The extension is available on the Internet at www.absc.usgs.gov/glba/gistools/index.htm.

Spatial Statistics for Tumor Cell Counting and Classification

NASA Astrophysics Data System (ADS)

Wirjadi, Oliver; Kim, Yoo-Jin; Breuel, Thomas

To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.

The Impact of Soil Sampling Errors on Variable Rate Fertilization

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

R. L. Hoskinson; R C. Rope; L G. Blackwood

2004-07-01

Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and amore » predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash differences accounted for almost 87% of the cost difference. The sum of these differences could result in a $34 per acre cost difference for the fertilization. Because of these differences, better analysis or better sampling methods may need to be done, or more samples collected, to ensure that the soil measurements are truly representative of the field’s spatial variability.« less

Direct statistical modeling and its implications for predictive mapping in mining exploration

NASA Astrophysics Data System (ADS)

Sterligov, Boris; Gumiaux, Charles; Barbanson, Luc; Chen, Yan; Cassard, Daniel; Cherkasov, Sergey; Zolotaya, Ludmila

2010-05-01

Recent advances in geosciences make more and more multidisciplinary data available for mining exploration. This allowed developing methodologies for computing forecast ore maps from the statistical combination of such different input parameters, all based on an inverse problem theory. Numerous statistical methods (e.g. algebraic method, weight of evidence, Siris method, etc) with varying degrees of complexity in their development and implementation, have been proposed and/or adapted for ore geology purposes. In literature, such approaches are often presented through applications on natural examples and the results obtained can present specificities due to local characteristics. Moreover, though crucial for statistical computations, "minimum requirements" needed for input parameters (number of minimum data points, spatial distribution of objects, etc) are often only poorly expressed. From these, problems often arise when one has to choose between one and the other method for her/his specific question. In this study, a direct statistical modeling approach is developed in order to i) evaluate the constraints on the input parameters and ii) test the validity of different existing inversion methods. The approach particularly focused on the analysis of spatial relationships between location of points and various objects (e.g. polygons and /or polylines) which is particularly well adapted to constrain the influence of intrusive bodies - such as a granite - and faults or ductile shear-zones on spatial location of ore deposits (point objects). The method is designed in a way to insure a-dimensionality with respect to scale. In this approach, both spatial distribution and topology of objects (polygons and polylines) can be parametrized by the user (e.g. density of objects, length, surface, orientation, clustering). Then, the distance of points with respect to a given type of objects (polygons or polylines) is given using a probability distribution. The location of points is computed assuming either independency or different grades of dependency between the two probability distributions. The results show that i)polygons surface mean value, polylines length mean value, the number of objects and their clustering are critical and ii) the validity of the different tested inversion methods strongly depends on the relative importance and on the dependency between the parameters used. In addition, this combined approach of direct and inverse modeling offers an opportunity to test the robustness of the inferred distribution point laws with respect to the quality of the input data set.

Spatial Thinking in Atmospheric Science Education

NASA Astrophysics Data System (ADS)

McNeal, P. M.; Petcovic, H. L.; Ellis, T. D.

2016-12-01

Atmospheric science is a STEM discipline that involves the visualization of three-dimensional processes from two-dimensional maps, interpretation of computer-generated graphics and hand plotting of isopleths. Thus, atmospheric science draws heavily upon spatial thinking. Research has shown that spatial thinking ability can be a predictor of early success in STEM disciplines and substantial evidence demonstrates that spatial thinking ability is improved through various interventions. Therefore, identification of the spatial thinking skills and cognitive processes used in atmospheric science is the first step toward development of instructional strategies that target these skills and scaffold the learning of students in atmospheric science courses. A pilot study of expert and novice meteorologists identified mental animation and disembedding as key spatial skills used in the interpretation of multiple weather charts and images. Using this as a starting point, we investigated how these spatial skills, together with expertise, domain specific knowledge, and working memory capacity affect the ability to produce an accurate forecast. Participants completed a meteorology concept inventory, experience questionnaire and psychometric tests of spatial thinking ability and working memory capacity prior to completing a forecasting task. A quantitative analysis of the collected data investigated the effect of the predictor variables on the outcome task. A think-aloud protocol with individual participants provided a qualitative look at processes such as task decomposition, rule-based reasoning and the formation of mental models in an attempt to understand how individuals process this complex data and describe outcomes of particular meteorological scenarios. With our preliminary results we aim to inform atmospheric science education from a cognitive science perspective. The results point to a need to collaborate with the atmospheric science community broadly, such that multiple educational pipelines are affected including university meteorology courses for majors and non-majors, military weather forecaster preparation and professional training for operational meteorologists, thus improving student learning and the continued development of the current and future workforce.

Spatial ecology of refuge selection by an herbivore under risk of predation

USGS Publications Warehouse

Wilson, Tammy L.; Rayburn, Andrew P.; Edwards, Thomas C.

2012-01-01

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

Statistical 3D shape analysis of gender differences in lateral ventricles

NASA Astrophysics Data System (ADS)

He, Qing; Karpman, Dmitriy; Duan, Ye

2010-03-01

This paper aims at analyzing gender differences in the 3D shapes of lateral ventricles, which will provide reference for the analysis of brain abnormalities related to neurological disorders. Previous studies mostly focused on volume analysis, and the main challenge in shape analysis is the required step of establishing shape correspondence among individual shapes. We developed a simple and efficient method based on anatomical landmarks. 14 females and 10 males with matching ages participated in this study. 3D ventricle models were segmented from MR images by a semiautomatic method. Six anatomically meaningful landmarks were identified by detecting the maximum curvature point in a small neighborhood of a manually clicked point on the 3D model. Thin-plate spline was used to transform a randomly selected template shape to each of the rest shape instances, and the point correspondence was established according to Euclidean distance and surface normal. All shapes were spatially aligned by Generalized Procrustes Analysis. Hotelling T2 twosample metric was used to compare the ventricle shapes between males and females, and False Discovery Rate estimation was used to correct for the multiple comparison. The results revealed significant differences in the anterior horn of the right ventricle.

The analysis of the accuracy of spatial models using photogrammetric software: Agisoft Photoscan and Pix4D

NASA Astrophysics Data System (ADS)

Barbasiewicz, Adrianna; Widerski, Tadeusz; Daliga, Karol

2018-01-01

This article was created as a result of research conducted within the master thesis. The purpose of the measurements was to analyze the accuracy of the positioning of points by computer programs. Selected software was a specialized computer software dedicated to photogrammetric work. For comparative purposes it was decided to use tools with similar functionality. As the basic parameters that affect the results selected the resolution of the photos on which the key points were searched. In order to determine the location of the determined points, it was decided to follow the photogrammetric resection rule. In order to automate the measurement, the measurement session planning was omitted. The coordinates of the points collected by the tachymetric measure were used as a reference system. The resulting deviations and linear displacements oscillate in millimeters. The visual aspects of the cloud points have also been briefly analyzed.

Development and evaluation of spatial point process models for epidermal nerve fibers.

PubMed

Olsbo, Viktor; Myllymäki, Mari; Waller, Lance A; Särkkä, Aila

2013-06-01

We propose two spatial point process models for the spatial structure of epidermal nerve fibers (ENFs) across human skin. The models derive from two point processes, Φb and Φe, describing the locations of the base and end points of the fibers. Each point of Φe (the end point process) is connected to a unique point in Φb (the base point process). In the first model, both Φe and Φb are Poisson processes, yielding a null model of uniform coverage of the skin by end points and general baseline results and reference values for moments of key physiologic indicators. The second model provides a mechanistic model to generate end points for each base, and we model the branching structure more directly by defining Φe as a cluster process conditioned on the realization of Φb as its parent points. In both cases, we derive distributional properties for observable quantities of direct interest to neurologists such as the number of fibers per base, and the direction and range of fibers on the skin. We contrast both models by fitting them to data from skin blister biopsy images of ENFs and provide inference regarding physiological properties of ENFs. Copyright © 2013 Elsevier Inc. All rights reserved.

Reducing Spatial Uncertainty Through Attentional Cueing Improves Contrast Sensitivity in Regions of the Visual Field With Glaucomatous Defects

PubMed Central

Phu, Jack; Kalloniatis, Michael; Khuu, Sieu K.

2018-01-01

Purpose Current clinical perimetric test paradigms present stimuli randomly to various locations across the visual field (VF), inherently introducing spatial uncertainty, which reduces contrast sensitivity. In the present study, we determined the extent to which spatial uncertainty affects contrast sensitivity in glaucoma patients by minimizing spatial uncertainty through attentional cueing. Methods Six patients with open-angle glaucoma and six healthy subjects underwent laboratory-based psychophysical testing to measure contrast sensitivity at preselected locations at two eccentricities (9.5° and 17.5°) with two stimulus sizes (Goldmann sizes III and V) under different cueing conditions: 1, 2, 4, or 8 points verbally cued. Method of Constant Stimuli and a single-interval forced-choice procedure were used to generate frequency of seeing (FOS) curves at locations with and without VF defects. Results At locations with VF defects, cueing minimizes spatial uncertainty and improves sensitivity under all conditions. The effect of cueing was maximal when one point was cued, and rapidly diminished when more points were cued (no change to baseline with 8 points cued). The slope of the FOS curve steepened with reduced spatial uncertainty. Locations with normal sensitivity in glaucomatous eyes had similar performance to that of healthy subjects. There was a systematic increase in uncertainty with the depth of VF loss. Conclusions Sensitivity measurements across the VF are negatively affected by spatial uncertainty, which increases with greater VF loss. Minimizing uncertainty can improve sensitivity at locations of deficit. Translational Relevance Current perimetric techniques introduce spatial uncertainty and may therefore underestimate sensitivity in regions of VF loss. PMID:29600116

Spatial transformation abilities and their relation to later mathematics performance.

PubMed

Frick, Andrea

2018-04-10

Using a longitudinal approach, this study investigated the relational structure of different spatial transformation skills at kindergarten age, and how these spatial skills relate to children's later mathematics performance. Children were tested at three time points, in kindergarten, first grade, and second grade (N = 119). Exploratory factor analyses revealed two subcomponents of spatial transformation skills: one representing egocentric transformations (mental rotation and spatial scaling), and one representing allocentric transformations (e.g., cross-sectioning, perspective taking). Structural equation modeling suggested that egocentric transformation skills showed their strongest relation to the part of the mathematics test tapping arithmetic operations, whereas allocentric transformations were strongly related to Numeric-Logical and Spatial Functions as well as geometry. The present findings point to a tight connection between early mental transformation skills, particularly the ones requiring a high level of spatial flexibility and a strong sense for spatial magnitudes, and children's mathematics performance at the beginning of their school career.

Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Riva, Monica; Neuman, Shlomo P.

2018-07-01

Geostatistical analysis has been introduced over half a century ago to allow quantifying seemingly random spatial variations in earth quantities such as rock mineral content or permeability. The traditional approach has been to view such quantities as multivariate Gaussian random functions characterized by one or a few well-defined spatial correlation scales. There is, however, mounting evidence that many spatially varying quantities exhibit non-Gaussian behavior over a multiplicity of scales. The purpose of this minireview is not to paint a broad picture of the subject and its treatment in the literature. Instead, we focus on very recent advances in the recognition and analysis of this ubiquitous phenomenon, which transcends hydrology and the Earth sciences, brought about largely by our own work. In particular, we use porosity data from a deep borehole to illustrate typical aspects of such scalable non-Gaussian behavior, describe a very recent theoretical model that (for the first time) captures all these behavioral aspects in a comprehensive manner, show how this allows generating random realizations of the quantity conditional on sampled values, point toward ways of incorporating scalable non-Gaussian behavior in hydrologic analysis, highlight the significance of doing so, and list open questions requiring further research.

Dome diagnostics system of optical parameters and characteristics of LEDs

NASA Astrophysics Data System (ADS)

Peretyagin, Vladimir S.; Pavlenko, Nikita A.

2017-09-01

Scientific and technological progress of recent years in the production of the light emitting diodes (LEDs) has led to the expansion of areas of their application from the simplest systems to high precision lighting devices used in various fields of human activity. However, development and production (especially mass production) of LED lighting devices are impossible without a thorough analysis of its parameters and characteristics. There are many ways and devices for analysis the spatial, energy and colorimetric parameters of LEDs. The most methods are intended for definition only one parameter (for example, luminous flux) or one characteristic (for example, the angular distribution of energy or the spectral characteristics). Besides, devices used these methods are intended for measuring parameters in only one point or plane. This problem can be solved by using a dome diagnostics system of optical parameters and characteristics of LEDs, developed by specialists of the department OEDS chair of ITMO University in Russia. The paper presents the theoretical aspects of the analysis of LED's spatial (angular), energy and color parameters by using mentioned of diagnostics system. The article also presents the results of spatial), energy and color parameters measurements of some LEDs brands.

Understanding Local Spatial Variation Along the Care Continuum: The Potential Impact of Transportation Vulnerability on HIV Linkage to Care and Viral Suppression in High-Poverty Areas, Atlanta, Georgia.

PubMed

Goswami, Neela D; Schmitz, Michelle M; Sanchez, Travis; Dasgupta, Sharoda; Sullivan, Patrick; Cooper, Hannah; Rane, Deepali; Kelly, Jane; Del Rio, Carlos; Waller, Lance A

2016-05-01

Engagement in care is central to reducing mortality for HIV-infected persons and achieving the White House National AIDS Strategy of 80% viral suppression in the US by 2020. Where an HIV-infected person lives impacts his or her ability to achieve viral suppression. Reliable transportation access for healthcare may be a key determinant of this place-suppression relationship. ZIP code tabulation areas (ZCTAs) were the units of analysis. We used geospatial and ecologic analyses to examine spatial distributions of neighborhood-level variables (eg, transportation accessibility) and associations with: (1) community linkage to care, and (2) community viral suppression. Among Atlanta ZCTAs with data for newly diagnosed HIV cases (2006-2010), we used Moran I to evaluate spatial clustering and linear regression models to evaluate associations between neighborhood variables and outcomes. In 100 ZCTAs with 8413 newly diagnosed HIV-positive residents, a median of 60 HIV cases were diagnosed per ZCTA during the 5-year period. We found significant clustering of ZCTAs with low linkage to care and viral suppression (Moran I = 0.218, P < 0.05). In high-poverty ZCTAs, a 10% point increase in ZCTA-level household vehicle ownership was associated with a 4% point increase in linkage to care (P = 0.02, R = 0.16). In low-poverty ZCTAs, a 10% point increase in ZCTA-level household vehicle ownership was associated with a 30% point increase in ZCTA-level viral suppression (P = 0.01, R = 0.08). Correlations between transportation variables and community-level care linkage and viral suppression vary by area poverty level and provide opportunities for interventions beyond individual-level factors.

Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina.

PubMed

Curtis, Andrew J; Mills, Jacqueline W; Leitner, Michael

2006-10-10

Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS.

Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina

PubMed Central

Curtis, Andrew J; Mills, Jacqueline W; Leitner, Michael

2006-01-01

Background Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. Results We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. Conclusion The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS. PMID:17032448

Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data

NASA Astrophysics Data System (ADS)

Myra, J. R.; Zweben, S. J.; Russell, D. A.

2018-07-01

Gas puff imaging (GPI) observations made in NSTX (Zweben et al 2017 Phys. Plasmas 24 102509) have revealed two-point spatial correlations of edge and scrape-off layer (SOL) turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlation patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or SOL), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Other properties of the experimentally observed extrema are discussed.

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

Mismatch removal via coherent spatial relations

NASA Astrophysics Data System (ADS)

Chen, Jun; Ma, Jiayi; Yang, Changcai; Tian, Jinwen

2014-07-01

We propose a method for removing mismatches from the given putative point correspondences in image pairs based on "coherent spatial relations." Under the Bayesian framework, we formulate our approach as a maximum likelihood problem and solve a coherent spatial relation between the putative point correspondences using an expectation-maximization (EM) algorithm. Our approach associates each point correspondence with a latent variable indicating it as being either an inlier or an outlier, and alternatively estimates the inlier set and recovers the coherent spatial relation. It can handle not only the case of image pairs with rigid motions but also the case of image pairs with nonrigid motions. To parameterize the coherent spatial relation, we choose two-view geometry and thin-plate spline as models for rigid and nonrigid cases, respectively. The mismatches could be successfully removed via the coherent spatial relations after the EM algorithm converges. The quantitative results on various experimental data demonstrate that our method outperforms many state-of-the-art methods, it is not affected by low initial correct match percentages, and is robust to most geometric transformations including a large viewing angle, image rotation, and affine transformation.

Invariant Manifolds, the Spatial Three-Body Problem and Space Mission Design

NASA Technical Reports Server (NTRS)

Gomez, G.; Koon, W. S.; Lo, Martin W.; Marsden, J. E.; Masdemont, J.; Ross, S. D.

2001-01-01

The invariant manifold structures of the collinear libration points for the spatial restricted three-body problem provide the framework for understanding complex dynamical phenomena from a geometric point of view. In particular, the stable and unstable invariant manifold 'tubes' associated to libration point orbits are the phase space structures that provide a conduit for orbits between primary bodies for separate three-body systems. These invariant manifold tubes can be used to construct new spacecraft trajectories, such as 'Petit Grand Tour' of the moons of Jupiter. Previous work focused on the planar circular restricted three-body problem. The current work extends the results to the spatial case.

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Point-to-point migration functions and gravity model renormalization: approaches to aggregation in spatial interaction modeling.

PubMed

Slater, P B

1985-08-01

Two distinct approaches to assessing the effect of geographic scale on spatial interactions are modeled. In the first, the question of whether a distance deterrence function, which explains interactions for one system of zones, can also succeed on a more aggregate scale, is examined. Only the two-parameter function for which it is found that distances between macrozones are weighted averaged of distances between component zones is satisfactory in this regard. Estimation of continuous (point-to-point) functions--in the form of quadrivariate cubic polynomials--for US interstate migration streams, is then undertaken. Upon numerical integration, these higher order surfaces yield predictions of interzonal and intrazonal movements at any scale of interest. Test of spatial stationarity, isotropy, and symmetry of interstate migration are conducted in this framework.

Effects of pointing compared with naming and observing during encoding on item and source memory in young and older adults.

PubMed

Ouwehand, Kim; van Gog, Tamara; Paas, Fred

2016-10-01

Research showed that source memory functioning declines with ageing. Evidence suggests that encoding visual stimuli with manual pointing in addition to visual observation can have a positive effect on spatial memory compared with visual observation only. The present study investigated whether pointing at picture locations during encoding would lead to better spatial source memory than naming (Experiment 1) and visual observation only (Experiment 2) in young and older adults. Experiment 3 investigated whether response modality during the test phase would influence spatial source memory performance. Experiments 1 and 2 supported the hypothesis that pointing during encoding led to better source memory for picture locations than naming or observation only. Young adults outperformed older adults on the source memory but not the item memory task in both Experiments 1 and 2. In Experiments 1 and 2, participants manually responded in the test phase. Experiment 3 showed that if participants had to verbally respond in the test phase, the positive effect of pointing compared with naming during encoding disappeared. The results suggest that pointing at picture locations during encoding can enhance spatial source memory in both young and older adults, but only if the response modality is congruent in the test phase.

Classification of spatially unresolved objects

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Horwitz, H. M.; Hyde, P. D.; Morgenstern, J. P.

1972-01-01

A proportion estimation technique for classification of multispectral scanner images is reported that uses data point averaging to extract and compute estimated proportions for a single average data point to classify spatial unresolved areas. Example extraction calculations of spectral signatures for bare soil, weeds, alfalfa, and barley prove quite accurate.

On the spectrum of inhomogeneous turbulence

NASA Technical Reports Server (NTRS)

Trevino, G.

1979-01-01

Inhomogeneous turbulence is defined as turbulence whose statistics are functions of spatial position. The turbulence spectrum, and particularly how the shape of the spectrum varies, from point to point in space, as a consequence of well defined spatial variations in the turbulence intensity and/or integral scale is investigated.

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Unsteady three-dimensional thermal field prediction in turbine blades using nonlinear BEM

NASA Technical Reports Server (NTRS)

Martin, Thomas J.; Dulikravich, George S.

1993-01-01

A time-and-space accurate and computationally efficient fully three dimensional unsteady temperature field analysis computer code has been developed for truly arbitrary configurations. It uses boundary element method (BEM) formulation based on an unsteady Green's function approach, multi-point Gaussian quadrature spatial integration on each panel, and a highly clustered time-step integration. The code accepts either temperatures or heat fluxes as boundary conditions that can vary in time on a point-by-point basis. Comparisons of the BEM numerical results and known analytical unsteady results for simple shapes demonstrate very high accuracy and reliability of the algorithm. An example of computed three dimensional temperature and heat flux fields in a realistically shaped internally cooled turbine blade is also discussed.

Spatial interpolation of monthly mean air temperature data for Latvia

NASA Astrophysics Data System (ADS)

Aniskevich, Svetlana

2016-04-01

Temperature data with high spatial resolution are essential for appropriate and qualitative local characteristics analysis. Nowadays the surface observation station network in Latvia consists of 22 stations recording daily air temperature, thus in order to analyze very specific and local features in the spatial distribution of temperature values in the whole Latvia, a high quality spatial interpolation method is required. Until now inverse distance weighted interpolation was used for the interpolation of air temperature data at the meteorological and climatological service of the Latvian Environment, Geology and Meteorology Centre, and no additional topographical information was taken into account. This method made it almost impossible to reasonably assess the actual temperature gradient and distribution between the observation points. During this project a new interpolation method was applied and tested, considering auxiliary explanatory parameters. In order to spatially interpolate monthly mean temperature values, kriging with external drift was used over a grid of 1 km resolution, which contains parameters such as 5 km mean elevation, continentality, distance from the Gulf of Riga and the Baltic Sea, biggest lakes and rivers, population density. As the most appropriate of these parameters, based on a complex situation analysis, mean elevation and continentality was chosen. In order to validate interpolation results, several statistical indicators of the differences between predicted values and the values actually observed were used. Overall, the introduced model visually and statistically outperforms the previous interpolation method and provides a meteorologically reasonable result, taking into account factors that influence the spatial distribution of the monthly mean temperature.

Comparative analysis of hydroacoustic lakebed classification in three different Brazilian reservoirs

NASA Astrophysics Data System (ADS)

Hilgert, Stephan; Sotiri, Klajdi; Fuchs, Stephan

2017-04-01

Until today, the surface of artificial water bodies around the world reached an area of around 500,000 km2 equaling one third of the surface of natural water bodies. Most of the constructed waster bodies are reservoirs with a variety of usage purposes, reaching from drinking water supply, electricity production, flood protection to recreation. All reservoirs have in common, that they disrupt riverine systems and their biochemical cycles and promote the accumulation of sediments upstream of the dam. The accumulated sediments contain organic matter, nutrients and/or pollutants which have a direct influence on the water quality within the impoundment. Consequently, detailed knowledge about the amount and the quality of accumulated sediments is an essential information for reservoir management. In many cases the extensive areas covered by the impoundments make it difficult and expensive to assess sediment characteristics with a high spatial resolution. Spatial extrapolations and mass balances based on point information may suffer from strong deviations. We combined sediment point measurements (core and grab sampling) with hydroacoustic sediment classification in order to precisely map sediment parameters. Three different reservoirs (Vossoroca, Capivari, Passauna) in the south-east of Brazil were investigated between 2011 and 2015. A single beam echosounder (EA 400, Kongsberg) with two frequencies (200 & 38 kHz) was used for the hydroacoustic classification. Over 50 core samples and 30 grab samples were taken for physical and chemical analysis to serve as ground truthing of the hydroacoustic measurements. All three reservoirs were covered with dense measurement transects allowing for a lakebed classification of the entire sediment surface. Significant correlations of physical parameters like grain size distribution and density as well chemical parameters like organic carbon content and total phosphorous with a selection of hydroacoustic parameters were obtained. They enabled the derivation of empiric models used for the extrapolation of the sediment point information to the entire reservoir surface. With the obtained spatial information carbon and phosphorous budgets were calculated. Former stock calculations, which were based solely on point sampling, could be improved The results show that the method is transferable to different reservoirs with varying characteristics in regard of their catchments, morphology and trophic state.

Mesoscale variations in acoustic signals induced by atmospheric gravity waves.

PubMed

Chunchuzov, Igor; Kulichkov, Sergey; Perepelkin, Vitaly; Ziemann, Astrid; Arnold, Klaus; Kniffka, Anke

2009-02-01

The results of acoustic tomographic monitoring of the coherent structures in the lower atmosphere and the effects of these structures on acoustic signal parameters are analyzed in the present study. From the measurements of acoustic travel time fluctuations (periods 1 min-1 h) with distant receivers, the temporal fluctuations of the effective sound speed and wind speed are retrieved along different ray paths connecting an acoustic pulse source and several receivers. By using a coherence analysis of the fluctuations near spatially distanced ray turning points, the internal wave-associated fluctuations are filtered and their spatial characteristics (coherences, horizontal phase velocities, and spatial scales) are estimated. The capability of acoustic tomography in estimating wind shear near ground is shown. A possible mechanism describing the temporal modulation of the near-ground wind field by ducted internal waves in the troposphere is proposed.

Absence of internal conical refraction with the spatially dispersive index surface of fluorine; discussion of the orthogonality of the Poynting vector to the index surface.

PubMed

Dettwiller, Luc

2006-04-17

Since 2001 the intrinsic birefringence of fluorine has been accessible to experiment. It is known that its intrinsic anisotropy is entirely due to spatial dispersion, and that the index surface of fluorine and crystals with the same symmetry has seven optical axes, four of them intersecting this surface at pairs of conical points. I point out the fact that there is no internal conical refraction, but only simple refraction (and without walkoff), with these conical points. I also explain why the rays are not a priori normal to the index surface in the case of fluorine because of its spatial dispersion; and I discuss two particular cases of spatial dispersion where the Poynting vector remains orthogonal to the index surface.

Comparable Rest-related Promotion of Spatial Memory Consolidation in Younger and Older Adults

PubMed Central

Craig, Michael; Wolbers, Thomas; Harris, Mathew A.; Hauff, Patrick; Della Sala, Sergio; Dewar, Michaela

2017-01-01

Flexible spatial navigation depends on cognitive mapping, a function that declines with increasing age. In young adults, a brief period of post-navigation rest promotes the consolidation/integration of spatial memories into accurate cognitive maps. We examined (1) whether rest promotes spatial memory consolidation/integration in older adults and (2) whether the magnitude of the rest benefit changes with increasing age. Young and older adults learned a route through a virtual environment, followed by a 10min delay comprising either wakeful rest or a perceptual task, and a subsequent cognitive mapping task, requiring the pointing to landmarks from different locations. Pointing accuracy was lower in the older than younger adults. However, there was a comparable rest-related enhancement in pointing accuracy in the two age groups. Together our findings suggest that (i) the age-related decline in cognitive mapping cannot be explained by increased consolidation interference in older adults, and (ii) as we grow older rest continues to support the consolidation/integration of spatial memories. PMID:27689512

Seismic catalog condensation with applications to multifractal analysis of South Californian seismicity

NASA Astrophysics Data System (ADS)

Kamer, Yavor; Ouillon, Guy; Sornette, Didier; Wössner, Jochen

2014-05-01

Latest advances in the instrumentation field have increased the station coverage and lowered event detection thresholds. This has resulted in a vast increase in the number of located events with each year. The abundance of data comes as a double edged sword: while it facilitates more robust statistics and provides better confidence intervals, it also paralyzes computations whose execution times grow exponentially with the number of data points. In this study, we present a novel method that assesses the relative importance of each data point, reduces the size of datasets while preserving the information content. For a given seismic catalog, the goal is to express the same spatial probability density distribution with fewer data points. To achieve this, we exploit the fact that seismic catalogs are not optimally encoded. This coding deficiency is the result of the sequential data entry where new events are added without taking into account previous ones. For instance, if there are several events with identical parameters occurring at the same location, these could be grouped together rather than occupying the same memory space as if they were distinct events. Following this reasoning, the proposed condensation methodology is implemented by grouping all event according to their overall variance, starting from the group with the highest variance (worst location uncertainty), each event is sampled by a number of sample points, these points are then used to calculate which better located events are able to express these probable locations with a higher likelihood. Based on these likelihood comparisons, weights from poorly located events are successively transferred to better located ones. As a result of the process, a large portion of the events (~30%) ends up with zero weights (thus being fully represented by events increasing their weights), while the information content (i.e the sum of all weights) remains preserved. The resulting condensed catalog not only provides more optimally encoding but is also regularized with respect to the local information quality. By investigating the locations of mass enrichment and depletion at different scales, we observe that the areas of increased mass are in good agreement with reported surface fault traces. We also conduct multifractal spatial analysis on condensed catalogs and investigate different spatial scaling regimes made clearer by reducing the effect of location uncertainty.

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.

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

Methods for Data-based Delineation of Spatial Regions

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

Wilson, John E.

In data analysis, it is often useful to delineate or segregate areas of interest from the general population of data in order to concentrate further analysis efforts on smaller areas. Three methods are presented here for automatically generating polygons around spatial data of interest. Each method addresses a distinct data type. These methods were developed for and implemented in the sample planning tool called Visual Sample Plan (VSP). Method A is used to delineate areas of elevated values in a rectangular grid of data (raster). The data used for this method are spatially related. Although VSP uses data from amore » kriging process for this method, it will work for any type of data that is spatially coherent and appears on a regular grid. Method B is used to surround areas of interest characterized by individual data points that are congregated within a certain distance of each other. Areas where data are “clumped” together spatially will be delineated. Method C is used to recreate the original boundary in a raster of data that separated data values from non-values. This is useful when a rectangular raster of data contains non-values (missing data) that indicate they were outside of some original boundary. If the original boundary is not delivered with the raster, this method will approximate the original boundary.« less

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

USGS Publications Warehouse

Guymon, Gary L.; Yen, Chung-Cheng

1990-01-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

NASA Astrophysics Data System (ADS)

Guymon, Gary L.; Yen, Chung-Cheng

1990-07-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

Sex differences in the Simon task help to interpret sex differences in selective attention.

PubMed

Stoet, Gijsbert

2017-05-01

In the last decade, a number of studies have reported sex differences in selective attention, but a unified explanation for these effects is still missing. This study aims to better understand these differences and put them in an evolutionary psychological context. 418 adult participants performed a computer-based Simon task, in which they responded to the direction of a left or right pointing arrow appearing left or right from a fixation point. Women were more strongly influenced by task-irrelevant spatial information than men (i.e., the Simon effect was larger in women, Cohen's d = 0.39). Further, the analysis of sex differences in behavioral adjustment to errors revealed that women slow down more than men following mistakes (d = 0.53). Based on the combined results of previous studies and the current data, it is proposed that sex differences in selective attention are caused by underlying sex differences in core abilities, such as spatial or verbal cognition.

Effects of thermal noise on the transitional dynamics of an inextensible elastic filament in stagnation flow.

PubMed

Deng, Mingge; Grinberg, Leopold; Caswell, Bruce; Karniadakis, George Em

2015-06-28

We investigate the dynamics of a single inextensible elastic filament subject to anisotropic friction in a viscous stagnation-point flow, by employing both a continuum model represented by Langevin type stochastic partial differential equations (SPDEs) and a dissipative particle dynamics (DPD) method. Unlike previous works, the filament is free to rotate and the tension along the filament is determined by the local inextensible constraint. The kinematics of the filament is recorded and studied with normal modes analysis. The results show that the filament displays an instability induced by negative tension, which is analogous to Euler buckling of a beam. Symmetry breaking of normal modes dynamics and stretch-coil transitions are observed above the threshold of the buckling instability point. Furthermore, both temporal and spatial noise are amplified resulting from the interaction of thermal fluctuations and nonlinear filament dynamics. Specifically, the spatial noise is amplified with even normal modes being excited due to symmetry breaking, while the temporal noise is amplified with increasing time correlation length and variance.

Investigating the Spatial Trends in the Level of Organic Contaminants in the Ethiopian Rift Valley Lakes Using Semipermeable Membrane Devices.

PubMed

Deribe, Ermias

2018-05-21

Organic pollutants in the Ethiopian Rift Valley Lakes are the major factors that contribute to severe environmental problem. SPMDs were deployed for the analysis of selected organic pollutants for 1 month at 2 sites in Lakes Hawassa, Ziway and Koka, Ethiopia. From SPMDs placed in the three lakes, the predominant OCPs were DDT which comprise 67% and followed by endosulfan 23% of the total organochlorine pesticides (OCPs) retrieved. The highest level of OCPs, in general, was found in the SPMDs deployed in Lake Ziway with the mean concentration of 308.5 ng/SPMD. However, the concentrations of polychlorinated biphenyls (PCBs) were the highest in the SPMDs deployed in Lake Hawassa with mean concentration of 50.2 ng/SPMD. Spatial variation on the accumulation of OCPs and PCBs among the lakes depends on the shoreline activities, distance of the lakes from point and non-point sources, and the biofouling factors.

Measuring Spatial Dependence for Infectious Disease Epidemiology

PubMed Central

Grabowski, M. Kate; Cummings, Derek A. T.

2016-01-01

Global spatial clustering is the tendency of points, here cases of infectious disease, to occur closer together than expected by chance. The extent of global clustering can provide a window into the spatial scale of disease transmission, thereby providing insights into the mechanism of spread, and informing optimal surveillance and control. Here the authors present an interpretable measure of spatial clustering, τ, which can be understood as a measure of relative risk. When biological or temporal information can be used to identify sets of potentially linked and likely unlinked cases, this measure can be estimated without knowledge of the underlying population distribution. The greater our ability to distinguish closely related (i.e., separated by few generations of transmission) from more distantly related cases, the more closely τ will track the true scale of transmission. The authors illustrate this approach using examples from the analyses of HIV, dengue and measles, and provide an R package implementing the methods described. The statistic presented, and measures of global clustering in general, can be powerful tools for analysis of spatially resolved data on infectious diseases. PMID:27196422

Patterns induced by super cross-diffusion in a predator-prey system with Michaelis-Menten type harvesting.

PubMed

Liu, Biao; Wu, Ranchao; Chen, Liping

2018-04-01

Turing instability and pattern formation in a super cross-diffusion predator-prey system with Michaelis-Menten type predator harvesting are investigated. Stability of equilibrium points is first explored with or without super cross-diffusion. It is found that cross-diffusion could induce instability of equilibria. To further derive the conditions of Turing instability, the linear stability analysis is carried out. From theoretical analysis, note that cross-diffusion is the key mechanism for the formation of spatial patterns. By taking cross-diffusion rate as bifurcation parameter, we derive amplitude equations near the Turing bifurcation point for the excited modes by means of weakly nonlinear theory. Dynamical analysis of the amplitude equations interprets the structural transitions and stability of various forms of Turing patterns. Furthermore, the theoretical results are illustrated via numerical simulations. Copyright © 2018. Published by Elsevier Inc.

VizieR Online Data Catalog: First Fermi-LAT Inner Galaxy point source catalog (Ajello+, 2016)

NASA Astrophysics Data System (ADS)

Ajello, M.; Albert, A.; Atwood, W. B.; Barbiellini, G.; Bastieri, D.; Bechtol, K.; Bellazzini, R.; Bissaldi, E.; Blandford, R. D.; Bloom, E. D.; Bonino, R.; Bottacini, E.; Brandt, T. J.; Bregeon, J.; Bruel, P.; Buehler, R.; Buson, S.; Caliandro, G. A.; Cameron, R. A.; Caputo, R.; Caragiulo, M.; Caraveo, P. A.; Cecchi, C.; Chekhtman, A.; Chiang, J.; Chiaro, G.; Ciprini, S.; Cohen-Tanugi, J.; Cominsky, L. R.; Conrad, J.; Cutini, S.; D'Ammando, F.; de Angelis, A.; de Palma, F.; Desiante, R.; di Venere, L.; Drell, P. S.; Favuzzi, C.; Ferrara, E. C.; Fusco, P.; Gargano, F.; Gasparrini, D.; Giglietto, N.; Giommi, P.; Giordano, F.; Giroletti, M.; Glanzman, T.; Godfrey, G.; Gomez-Vargas, G. A.; Grenier, I. A.; Guiriec, S.; Gustafsson, M.; Harding, A. K.; Hewitt, J. W.; Hill, A. B.; Horan, D.; Jogler, T.; Johannesson, G.; Johnson, A. S.; Kamae, T.; Karwin, C.; Knodlseder, J.; Kuss, M.; Larsson, S.; Latronico, L.; Li, J.; Li, L.; Longo, F.; Loparco, F.; Lovellette, M. N.; Lubrano, P.; Magill, J.; Maldera, S.; Malyshev, D.; Manfreda, A.; Mayer, M.; Mazziotta, M. N.; Michelson, P. F.; Mitthumsiri, W.; Mizuno, T.; Moiseev, A. A.; Monzani, M. E.; Morselli, A.; Moskalenko, I. V.; Murgia, S.; Nuss, E.; Ohno, M.; Ohsugi, T.; Omodei, N.; Orlando, E.; Ormes, J. F.; Paneque, D.; Pesce-Rollins, M.; Piron, F.; Pivato, G.; Porter, T. A.; Raino, S.; Rando, R.; Razzano, M.; Reimer, A.; Reimer, O.; Ritz, S.; Sanchez-Conde, M.; Parkinson, P. M. S.; Sgro, C.; Siskind, E. J.; Smith, D. A.; Spada, F.; Spandre, G.; Spinelli, P.; Suson, D. J.; Tajima, H.; Takahashi, H.; Thayer, J. B.; Torres, D. F.; Tosti, G.; Troja, E.; Uchiyama, Y.; Vianello, G.; Winer, B. L.; Wood, K. S.; Zaharijas, G.; Zimmer, S.

2018-01-01

The Fermi Large Area Telescope (LAT) has provided the most detailed view to date of the emission toward the Galactic center (GC) in high-energy γ-rays. This paper describes the analysis of data taken during the first 62 months of the mission in the energy range 1-100GeV from a 15°x15° region about the direction of the GC. Specialized interstellar emission models (IEMs) are constructed to enable the separation of the γ-ray emissions produced by cosmic ray particles interacting with the interstellar gas and radiation fields in the Milky Way into that from the inner ~1kpc surrounding the GC, and that from the rest of the Galaxy. A catalog of point sources for the 15°x15° region is self-consistently constructed using these IEMs: the First Fermi-LAT Inner Galaxy Point Source Catalog (1FIG). The spatial locations, fluxes, and spectral properties of the 1FIG sources are presented, and compared with γ-ray point sources over the same region taken from existing catalogs. After subtracting the interstellar emission and point-source contributions a residual is found. If templates that peak toward the GC are used to model the positive residual the agreement with the data improves, but none of the additional templates tried account for all of its spatial structure. The spectrum of the positive residual modeled with these templates has a strong dependence on the choice of IEM. (2 data files).

a Comparitive Study Using Geometric and Vertical Profile Features Derived from Airborne LIDAR for Classifying Tree Genera

NASA Astrophysics Data System (ADS)

Ko, C.; Sohn, G.; Remmel, T. K.

2012-07-01

We present a comparative study between two different approaches for tree genera classification using descriptors derived from tree geometry and those derived from the vertical profile analysis of LiDAR point data. The different methods provide two perspectives for processing LiDAR point clouds for tree genera identification. The geometric perspective analyzes individual tree crowns in relation to valuable information related to characteristics of clusters and line segments derived within crowns and overall tree shapes to highlight the spatial distribution of LiDAR points within the crown. Conversely, analyzing vertical profiles retrieves information about the point distributions with respect to height percentiles; this perspective emphasizes of the importance that point distributions at specific heights express, accommodating for the decreased point density with respect to depth of canopy penetration by LiDAR pulses. The targeted species include white birch, maple, oak, poplar, white pine and jack pine at a study site northeast of Sault Ste. Marie, Ontario, Canada.

Paper-based analytical devices for environmental analysis.

PubMed

Meredith, Nathan A; Quinn, Casey; Cate, David M; Reilly, Thomas H; Volckens, John; Henry, Charles S

2016-03-21

The field of paper-based microfluidics has experienced rapid growth over the past decade. Microfluidic paper-based analytical devices (μPADs), originally developed for point-of-care medical diagnostics in resource-limited settings, are now being applied in new areas, such as environmental analyses. Low-cost paper sensors show great promise for on-site environmental analysis; the theme of ongoing research complements existing instrumental techniques by providing high spatial and temporal resolution for environmental monitoring. This review highlights recent applications of μPADs for environmental analysis along with technical advances that may enable μPADs to be more widely implemented in field testing.

Methodological approach in determination of small spatial units in a highly complex terrain in atmospheric pollution research: the case of Zasavje region in Slovenia.

PubMed

Kukec, Andreja; Boznar, Marija Z; Mlakar, Primoz; Grasic, Bostjan; Herakovic, Andrej; Zadnik, Vesna; Zaletel-Kragelj, Lijana; Farkas, Jerneja; Erzen, Ivan

2014-05-01

The study of atmospheric air pollution research in complex terrains is challenged by the lack of appropriate methodology supporting the analysis of the spatial relationship between phenomena affected by a multitude of factors. The key is optimal design of a meaningful approach based on small spatial units of observation. The Zasavje region, Slovenia, was chosen as study area with the main objective to investigate in practice the role of such units in a test environment. The process consisted of three steps: modelling of pollution in the atmosphere with dispersion models, transfer of the results to geographical information system software, and then moving on to final determination of the function of small spatial units. A methodology capable of designing useful units for atmospheric air pollution research in highly complex terrains was created, and the results were deemed useful in offering starting points for further research in the field of geospatial health.

A swash-backwash model of the single epidemic wave

NASA Astrophysics Data System (ADS)

Cliff, Andrew D.; Haggett, Peter

2006-09-01

While there is a large literature on the form of epidemic waves in the time domain, models of their structure and shape in the spatial domain remain poorly developed. This paper concentrates on the changing spatial distribution of an epidemic wave over time and presents a simple method for identifying the leading and trailing edges of the spatial advance and retreat of such waves. Analysis of edge characteristics is used to (a) disaggregate waves into ‘swash’ and ‘backwash’ stages, (b) measure the phase transitions of areas from susceptible, S, through infective, I, to recovered, R, status ( S → I → R) as dimensionless integrals and (c) estimate a spatial version of the basic reproduction number, R 0. The methods used are illustrated by application to measles waves in Iceland over a 60-year period from 1915 to 1974. Extensions of the methods for use with more complex waves are possible through modifying the threshold values used to define the start and end points of an event.

Spatial Lattice Modulation for MIMO Systems

NASA Astrophysics Data System (ADS)

Choi, Jiwook; Nam, Yunseo; Lee, Namyoon

2018-06-01

This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.

Study of the marine environment of the northern Gulf of California

NASA Technical Reports Server (NTRS)

Hendrickson, J. R. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Preliminary analysis of the first three months of ERTS-1 imagery have revealed that the MSS images have particular utility for study of turbidity patterns, current phenomena, and bathymetry throughout the test area. Early indications are that well defined spatial distributions of turbidity exist in the northern Gulf of California, and that for any one point in time, these distributions vary with depth. From a single set of images, as many as 3 turbidity maps may be generated, each indicating a vertical spatial relationship of the turbidity masses. The spatial distribution of turbidity masses depend partially upon the coincident currents. In the band of deepest penetration, a map can be gathered which roughly corresponds to the bathymetry of the area. The extreme tides in the northern Gulf of California result in vast areas which can be classified as intertidal mud flats. Information on the amount of exposure at the varying tidal states is important in analysis of these mud flat areas as nursery ground for Mexican commercial fisheries.

Precipitation areal-reduction factor estimation using an annual-maxima centered approach

USGS Publications Warehouse

Asquith, W.H.; Famiglietti, J.S.

2000-01-01

The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima. (C) 2000 Elsevier Science B.V.The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima.

Far field and wavefront characterization of a high-power semiconductor laser for free space optical communications

NASA Technical Reports Server (NTRS)

Cornwell, Donald M., Jr.; Saif, Babak N.

1991-01-01

The spatial pointing angle and far field beamwidth of a high-power semiconductor laser are characterized as a function of CW power and also as a function of temperature. The time-averaged spatial pointing angle and spatial lobe width were measured under intensity-modulated conditions. The measured pointing deviations are determined to be well within the pointing requirements of the NASA Laser Communications Transceiver (LCT) program. A computer-controlled Mach-Zehnder phase-shifter interferometer is used to characterize the wavefront quality of the laser. The rms phase error over the entire pupil was measured as a function of CW output power. Time-averaged measurements of the wavefront quality are also made under intensity-modulated conditions. The measured rms phase errors are determined to be well within the wavefront quality requirements of the LCT program.

Monitoring of urban subsidence with SAR interferometric point target analysis: A case study in Suzhou, China

NASA Astrophysics Data System (ADS)

Zhang, Yonghong; Zhang, Jixian; Wu, Hongan; Lu, Zhong; Guangtong, Sun

2011-10-01

Ground subsidence, mainly caused by over exploitation of groundwater and other underground resources, such as oil, gas and coal, occurs in many cities in China. The annual direct loss associated with subsidence across the country is estimated to exceed 100 million US dollar. Interferometric SAR (InSAR) is a powerful tool to map ground deformation at an unprecedented level of spatial detail. It has been widely used to investigate the deformation resulting from earthquakes, volcanoes and subsidence. Repeat-pass InSAR, however, may fail due to impacts of spatial decorrelation, temporal decorrelation and heterogeneous refractivity of atmosphere. In urban areas, a large amount of natural stable radar reflectors exists, such as buildings and engineering structures, at which radar signals can remain coherent during a long time interval. Interferometric point target analysis (IPTA) technique, also known as persistent scatterers (PS) InSAR is based on these reflectors. It overcomes the shortfalls in conventional InSAR. This paper presents a procedure for urban subsidence monitoring with IPTA. Calculation of linear deformation rate and height residual, and the non-linear deformation estimate, respectively, are discussed in detail. Especially, the former is highlighted by a novel and easily implemented 2-dimensional spatial search algorithm. Practically useful solutions that can significantly improve the robustness of IPTA, are recommended. Finally, the proposed procedure is applied to mapping the ground subsidence in Suzhou city, Jiangsu province, China. Thirty-four ERS-1/2 SAR scenes are analyzed, and the deformation information over 38,881 point targets between 1992 and 2000 are generated. The IPTA-derived deformation estimates correspond well with leveling measurements, demonstrating the potential of the proposed subsidence monitoring procedure based on IPTA technique. Two shortcomings of the IPTA-based procedure, e.g., the requirement of large number of SAR images and assumed linear plus non-linear deformation model, are discussed as the topics of further research.

Comparison of Interferometric Time-Series Analysis Techniques with Implications for Future Mission Design

NASA Astrophysics Data System (ADS)

Werner, C. L.; Wegmuller, U.; Strozzi, T.; Wiesmann, A.

2006-12-01

Principle contributors to the noise in differential SAR interferograms are temporal phase stability of the surface, geometry relating to baseline and surface slope, and propagation path delay variations due to tropospheric water vapor and the ionosphere. Time series analysis of multiple interferograms generated from a stack of SAR SLC images seeks to determine the deformation history of the surface while reducing errors. Only those scatterers within a resolution element that are stable and coherent for each interferometric pair contribute to the desired deformation signal. Interferograms with baselines exceeding 1/3 the critical baseline have substantial geometrical decorrelation for distributed targets. Short baseline pairs with multiple reference scenes can be combined using least-squares estimation to obtain a global deformation solution. Alternately point-like persistent scatterers can be identified in scenes that do not exhibit geometrical decorrelation associated with large baselines. In this approach interferograms are formed from a stack of SAR complex images using a single reference scene. Stable distributed scatter pixels are excluded however due to the presence of large baselines. We apply both point- based and short-baseline methodologies and compare results for a stack of fine-beam Radarsat data acquired in 2002-2004 over a rapidly subsiding oil field near Lost Hills, CA. We also investigate the density of point-like scatters with respect to image resolution. The primary difficulty encountered when applying time series methods is phase unwrapping errors due to spatial and temporal gaps. Phase unwrapping requires sufficient spatial and temporal sampling. Increasing the SAR range bandwidth increases the range resolution as well as increasing the critical interferometric baseline that defines the required satellite orbital tube diameter. Sufficient spatial sampling also permits unwrapping because of the reduced phase/pixel gradient. Short time intervals further reduce the differential phase due to deformation when the deformation is continuous. Lower frequency systems (L- vs. C-Band) substantially improve the ability to unwrap the phase correctly by directly reducing both interferometric phase amplitude and temporal decorrelation.

Analysis of a Spatial Point Pattern: Examining the Damage to Pavement and Pipes in Santa Clara Valley Resulting from the Loma Prieta Earthquake

USGS Publications Warehouse

Phelps, G.A.

2008-01-01

This report describes some simple spatial statistical methods to explore the relationships of scattered points to geologic or other features, represented by points, lines, or areas. It also describes statistical methods to search for linear trends and clustered patterns within the scattered point data. Scattered points are often contained within irregularly shaped study areas, necessitating the use of methods largely unexplored in the point pattern literature. The methods take advantage of the power of modern GIS toolkits to numerically approximate the null hypothesis of randomly located data within an irregular study area. Observed distributions can then be compared with the null distribution of a set of randomly located points. The methods are non-parametric and are applicable to irregularly shaped study areas. Patterns within the point data are examined by comparing the distribution of the orientation of the set of vectors defined by each pair of points within the data with the equivalent distribution for a random set of points within the study area. A simple model is proposed to describe linear or clustered structure within scattered data. A scattered data set of damage to pavement and pipes, recorded after the 1989 Loma Prieta earthquake, is used as an example to demonstrate the analytical techniques. The damage is found to be preferentially located nearer a set of mapped lineaments than randomly scattered damage, suggesting range-front faulting along the base of the Santa Cruz Mountains is related to both the earthquake damage and the mapped lineaments. The damage also exhibit two non-random patterns: a single cluster of damage centered in the town of Los Gatos, California, and a linear alignment of damage along the range front of the Santa Cruz Mountains, California. The linear alignment of damage is strongest between 45? and 50? northwest. This agrees well with the mean trend of the mapped lineaments, measured as 49? northwest.

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.

Integration of Heterogenous Digital Surface Models

NASA Astrophysics Data System (ADS)

Boesch, R.; Ginzler, C.

2011-08-01

The application of extended digital surface models often reveals, that despite an acceptable global accuracy for a given dataset, the local accuracy of the model can vary in a wide range. For high resolution applications which cover the spatial extent of a whole country, this can be a major drawback. Within the Swiss National Forest Inventory (NFI), two digital surface models are available, one derived from LiDAR point data and the other from aerial images. Automatic photogrammetric image matching with ADS80 aerial infrared images with 25cm and 50cm resolution is used to generate a surface model (ADS-DSM) with 1m resolution covering whole switzerland (approx. 41000 km2). The spatially corresponding LiDAR dataset has a global point density of 0.5 points per m2 and is mainly used in applications as interpolated grid with 2m resolution (LiDAR-DSM). Although both surface models seem to offer a comparable accuracy from a global view, local analysis shows significant differences. Both datasets have been acquired over several years. Concerning LiDAR-DSM, different flight patterns and inconsistent quality control result in a significantly varying point density. The image acquisition of the ADS-DSM is also stretched over several years and the model generation is hampered by clouds, varying illumination and shadow effects. Nevertheless many classification and feature extraction applications requiring high resolution data depend on the local accuracy of the used surface model, therefore precise knowledge of the local data quality is essential. The commercial photogrammetric software NGATE (part of SOCET SET) generates the image based surface model (ADS-DSM) and delivers also a map with figures of merit (FOM) of the matching process for each calculated height pixel. The FOM-map contains matching codes like high slope, excessive shift or low correlation. For the generation of the LiDAR-DSM only first- and last-pulse data was available. Therefore only the point distribution can be used to derive a local accuracy measure. For the calculation of a robust point distribution measure, a constrained triangulation of local points (within an area of 100m2) has been implemented using the Open Source project CGAL. The area of each triangle is a measure for the spatial distribution of raw points in this local area. Combining the FOM-map with the local evaluation of LiDAR points allows an appropriate local accuracy evaluation of both surface models. The currently implemented strategy ("partial replacement") uses the hypothesis, that the ADS-DSM is superior due to its better global accuracy of 1m. If the local analysis of the FOM-map within the 100m2 area shows significant matching errors, the corresponding area of the triangulated LiDAR points is analyzed. If the point density and distribution is sufficient, the LiDAR-DSM will be used in favor of the ADS-DSM at this location. If the local triangulation reflects low point density or the variance of triangle areas exceeds a threshold, the investigated location will be marked as NODATA area. In a future implementation ("anisotropic fusion") an anisotropic inverse distance weighting (IDW) will be used, which merges both surface models in the point data space by using FOM-map and local triangulation to derive a quality weight for each of the interpolation points. The "partial replacement" implementation and the "fusion" prototype for the anisotropic IDW make use of the Open Source projects CGAL (Computational Geometry Algorithms Library), GDAL (Geospatial Data Abstraction Library) and OpenCV (Open Source Computer Vision).

Do Sexually Oriented Massage Parlors Cluster in Specific Neighborhoods? A Spatial Analysis of Indoor Sex Work in Los Angeles and Orange Counties, California.

PubMed

Chin, John J; Kim, Anna J; Takahashi, Lois; Wiebe, Douglas J

2015-01-01

Social determinants of health may be substantially affected by spatial factors, which together may explain the persistence of health inequities. Clustering of possible sources of negative health and social outcomes points to a spatial focus for future interventions. We analyzed the spatial clustering of sex work businesses in Southern California to examine where and why they cluster. We explored economic and legal factors as possible explanations of clustering. We manually coded data from a website used by paying members to post reviews of female massage parlor workers. We identified clusters of sexually oriented massage parlor businesses using spatial autocorrelation tests. We conducted spatial regression using census tract data to identify predictors of clustering. A total of 889 venues were identified. Clusters of tracts having higher-than-expected numbers of sexually oriented massage parlors ("hot spots") were located outside downtowns. These hot spots were characterized by a higher proportion of adult males, a higher proportion of households below the federal poverty level, and a smaller average household size. Sexually oriented massage parlors in Los Angeles and Orange counties cluster in particular neighborhoods. More research is needed to ascertain the causal factors of such clusters and how interventions can be designed to leverage these spatial factors.

Assessing the quality of open spatial data for mobile location-based services research and applications

NASA Astrophysics Data System (ADS)

Ciepłuch, C.; Mooney, P.; Jacob, R.; Zheng, J.; Winstanely, A. C.

2011-12-01

New trends in GIS such as Volunteered Geographical Information (VGI), Citizen Science, and Urban Sensing, have changed the shape of the geoinformatics landscape. The OpenStreetMap (OSM) project provided us with an exciting, evolving, free and open solution as a base dataset for our geoserver and spatial data provider for our research. OSM is probably the best known and best supported example of VGI and user generated spatial content on the Internet. In this paper we will describe current results from the development of quality indicators for measures for OSM data. Initially we have analysed the Ireland OSM data in grid cells (5km) to gather statistical data about the completeness, accuracy, and fitness for purpose of the underlying spatial data. This analysis included: density of user contributions, spatial density of points and polygons, types of tags and metadata used, dominant contributors in a particular area or for a particular geographic feature type, etc. There greatest OSM activity and spatial data density is highly correlated with centres of large population. The ability to quantify and assess if VGI, such as OSM, is of sufficient quality for mobile mapping applications and Location-based services is critical to the future success of VGI as a spatial data source for these technologies.

Robot Manipulations: A Synergy of Visualization, Computation and Action for Spatial Instruction

ERIC Educational Resources Information Center

Verner, Igor M.

2004-01-01

This article considers the use of a learning environment, RoboCell, where manipulations of objects are performed by robot operations specified through the learner's application of mathematical and spatial reasoning. A curriculum is proposed relating to robot kinematics and point-to-point motion, rotation of objects, and robotic assembly of spatial…

A Review of High-Order and Optimized Finite-Difference Methods for Simulating Linear Wave Phenomena

NASA Technical Reports Server (NTRS)

Zingg, David W.

1996-01-01

This paper presents a review of high-order and optimized finite-difference methods for numerically simulating the propagation and scattering of linear waves, such as electromagnetic, acoustic, or elastic waves. The spatial operators reviewed include compact schemes, non-compact schemes, schemes on staggered grids, and schemes which are optimized to produce specific characteristics. The time-marching methods discussed include Runge-Kutta methods, Adams-Bashforth methods, and the leapfrog method. In addition, the following fourth-order fully-discrete finite-difference methods are considered: a one-step implicit scheme with a three-point spatial stencil, a one-step explicit scheme with a five-point spatial stencil, and a two-step explicit scheme with a five-point spatial stencil. For each method studied, the number of grid points per wavelength required for accurate simulation of wave propagation over large distances is presented. Recommendations are made with respect to the suitability of the methods for specific problems and practical aspects of their use, such as appropriate Courant numbers and grid densities. Avenues for future research are suggested.

Experimental assessment and analysis of super-resolution in fluorescence microscopy based on multiple-point spread function fitting of spectrally demultiplexed images

NASA Astrophysics Data System (ADS)

Nishimura, Takahiro; Kimura, Hitoshi; Ogura, Yusuke; Tanida, Jun

2018-06-01

This paper presents an experimental assessment and analysis of super-resolution microscopy based on multiple-point spread function fitting of spectrally demultiplexed images using a designed DNA structure as a test target. For the purpose, a DNA structure was designed to have binding sites at a certain interval that is smaller than the diffraction limit. The structure was labeled with several types of quantum dots (QDs) to acquire their spatial information as spectrally encoded images. The obtained images are analyzed with a point spread function multifitting algorithm to determine the QD locations that indicate the binding site positions. The experimental results show that the labeled locations can be observed beyond the diffraction-limited resolution using three-colored fluorescence images that were obtained with a confocal fluorescence microscope. Numerical simulations show that labeling with eight types of QDs enables the positions aligned at 27.2-nm pitches on the DNA structure to be resolved with high accuracy.

Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

NASA Astrophysics Data System (ADS)

Prasetyo, S. Y. J.; Hartomo, K. D.

2018-01-01

The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some area might exhibit the rainfall value of 0. The representation of 0 in the spatial interpolation is mainly caused by the absence of rainfall data in the nearest sample point or too far distance that produces smaller weight.

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior. PMID:29535614

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior.

Changes in spatial point patterns of pioneer woody plants across a large tropical landslide

NASA Astrophysics Data System (ADS)

Velázquez, Eduardo; De la Cruz, Marcelino; Gómez-Sal, Antonio

2014-11-01

We assessed whether the relative importance of positive and negative interactions in early successional communities varied across a large landslide on Casita Volcano (Nicaragua). We tested several hypotheses concerning the signatures of these processes in the spatial patterns of woody pioneer plants, as well as those of mortality and recruitment events, in several zones of the landslide differing in substrate stability and fertility, over a period of two years (2001 and 2002). We identified all woody individuals with a diameter >1 cm and mapped them in 28 plots measuring 10 × 10-m. On these maps, we performed a spatial point pattern analysis using univariate and bivariate pair-correlation functions; g (r) and g12 (r), and pairwise differences of univariate and bivariate functions. Spatial signatures of positive and negative interactions among woody plants were more prevalent in the most and least stressful zones of the landslide, respectively. Natural and human-induced disturbances such as the occurrence of fire, removal of newly colonizing plants through erosion and clearcutting of pioneer trees were also identified as potentially important pattern-creating processes. These results are in agreement with the stress-gradient hypothesis, which states that the relative importance of facilitation and competition varies inversely across gradients of abiotic stress. Our findings also indicate that the assembly of early successional plant communities in large heterogeneous landslides might be driven by a much larger array of processes than previously thought.

Relationship between sugarcane rust severity and soil properties in louisiana.

PubMed

Johnson, Richard M; Grisham, Michael P; Richard, Edward P

2007-06-01

ABSTRACT The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85-384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.

Assessing the impact of dairy waste lagoons on groundwater quality using a spatial analysis of vadose zone and groundwater information in a coastal phreatic aquifer.

PubMed

Baram, S; Kurtzman, D; Ronen, Z; Peeters, A; Dahan, O

2014-01-01

Dairy waste lagoons are considered to be point sources of groundwater contamination by chloride (Cl(-)), different nitrogen-species and pathogens/microorganisms. The objective of this work is to introduce a methodology to assess the past and future impacts of such lagoons on regional groundwater quality. The method is based on a spatial statistical analysis of Cl(-) and total nitrogen (TN) concentration distributions in the saturated and the vadose (unsaturated) zones. The method provides quantitative data on the relation between the locations of dairy lagoons and the spatial variability in Cl(-) and TN concentrations in groundwater. The method was applied to the Beer-Tuvia region, Israel, where intensive dairy farming has been practiced for over 50 years above the local phreatic aquifer. Mass balance calculations accounted for the various groundwater recharge and abstraction sources and sinks in the entire region. The mass balances showed that despite the small surface area covered by the dairy lagoons in this region (0.8%), leachates from lagoons have contributed 6.0% and 12.6% of the total mass of Cl(-) and TN (mainly as NO3(-)-N) added to the aquifer. The chemical composition of the aquifer and vadose zone water suggested that irrigated agricultural activity in the region is the main contributor of Cl(-) and TN to the groundwater. A low spatial correlation between the Cl(-) and NO3(-)-N concentrations in the groundwater and the on-land location of the dairy farms strengthened this assumption, despite the dairy waste lagoon being a point source for groundwater contamination by Cl(-) and NO3(-)-N. Mass balance calculations, for the vadose zone of the entire region, indicated that drying of the lagoons would decrease the regional groundwater salinization process (11% of the total Cl(-) load is stored under lagoons). A more considerable reduction in the groundwater contamination by NO3(-)-N is expected (25% of the NO3(-)-N load is stored under lagoons). Results demonstrate that analyzing vadose zone and groundwater data by spatial statistical analysis methods can significantly contribute to the understanding of the relations between groundwater contaminating sources, and to assessing appropriate remediation steps. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using GIS in ecological management: green assessment of the impacts of petroleum activities in the state of Texas.

PubMed

Merem, Edmund; Robinson, Bennetta; Wesley, Joan M; Yerramilli, Sudha; Twumasi, Yaw A

2010-05-01

Geo-information technologies are valuable tools for ecological assessment in stressed environments. Visualizing natural features prone to disasters from the oil sector spatially not only helps in focusing the scope of environmental management with records of changes in affected areas, but it also furnishes information on the pace at which resource extraction affects nature. Notwithstanding the recourse to ecosystem protection, geo-spatial analysis of the impacts remains sketchy. This paper uses GIS and descriptive statistics to assess the ecological impacts of petroleum extraction activities in Texas. While the focus ranges from issues to mitigation strategies, the results point to growth in indicators of ecosystem decline.

Using GIS in Ecological Management: Green Assessment of the Impacts of Petroleum Activities in the State of Texas

PubMed Central

Merem, Edmund; Robinson, Bennetta; Wesley, Joan M.; Yerramilli, Sudha; Twumasi, Yaw A.

2010-01-01

Geo-information technologies are valuable tools for ecological assessment in stressed environments. Visualizing natural features prone to disasters from the oil sector spatially not only helps in focusing the scope of environmental management with records of changes in affected areas, but it also furnishes information on the pace at which resource extraction affects nature. Notwithstanding the recourse to ecosystem protection, geo-spatial analysis of the impacts remains sketchy. This paper uses GIS and descriptive statistics to assess the ecological impacts of petroleum extraction activities in Texas. While the focus ranges from issues to mitigation strategies, the results point to growth in indicators of ecosystem decline. PMID:20623014

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

[Spatio-temporal characteristics and source identification of water pollutants in Wenruitang River watershed].

PubMed

Ma, Xiao-xue; Wang, La-chun; Liao, Ling-ling

2015-01-01

Identifying the temp-spatial distribution and sources of water pollutants is of great significance for efficient water quality management pollution control in Wenruitang River watershed, China. A total of twelve water quality parameters, including temperature, pH, dissolved oxygen (DO), total nitrogen (TN), ammonia nitrogen (NH4+ -N), electrical conductivity (EC), turbidity (Turb), nitrite-N (NO2-), nitrate-N(NO3-), phosphate-P(PO4(3-), total organic carbon (TOC) and silicate (SiO3(2-)), were analyzed from September, 2008 to October, 2009. Geographic information system(GIS) and principal component analysis(PCA) were used to determine the spatial distribution and to apportion the sources of pollutants. The results demonstrated that TN, NH4+ -N, PO4(3-) were the main pollutants during flow period, wet period, dry period, respectively, which was mainly caused by urban point sources and agricultural and rural non-point sources. In spatial terms, the order of pollution was tertiary river > secondary river > primary river, while the water quality was worse in city zones than in the suburb and wetland zone regardless of the river classification. In temporal terms, the order of pollution was dry period > wet period > flow period. Population density, land use type and water transfer affected the water quality in Wenruitang River.

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

Using Structure-from-Motion to Quantify Sediment Accumulation and Bedrock Erosion in a Debris-Flow Dominated Channel

NASA Astrophysics Data System (ADS)

Reitman, N. G.; Rengers, F.; Kean, J. W.

2016-12-01

One of the highest frequencies of observed debris flows in the US is located at the Chalk Cliffs in central Colorado. This high rate of debris-flow activity ( 3 per year) is supported by a similarly high rate of sediment supply from rock fall and ravel due to frost weathering of the highly-erodible, hydrothermally-altered quartz monzonite cliffs during the winter months. A first step toward understanding debris-flow initiation, and channel and hillslope evolution, is to quantify the magnitude and spatial distribution of sediment that accumulates by the end of the winter period. Here we test the ability of structure-from-motion photogrammetric surveys to produce high-resolution point clouds in order to quantify sediment deposition, and possibly bedrock erosion. We use point clouds obtained from surveys conducted in late September 2015 and early June 2016 to measure sediment deposition in a 42-m-long channel over one winter. All surveys are co-registered with control points (screws drilled into bedrock) measured in a local coordinate system with a total station. Point clouds derived from these surveys have average point densities >200,000 pts/m2, and accuracies within 2 cm. Initial analysis shows accumulation of 10-50 cm ( 10 m3) of unconsolidated loose sediment over eight months, providing ample material for debris-flow initiation during the following summer season. Sediment accumulated in a spatially-variable pattern dependent on existing channel-bottom bedrock topography. Future surveys are planned in order to measure bedrock erosion by debris flows and variation in sediment deposition rate through time. Our analysis indicates that photogrammetric surveys provide a high level of detail at low cost, and thus are a useful geomorphic monitoring tool that will ultimately lead to better understanding of the processes that contribute to debris-flow activity and landscape evolution.

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

PubMed Central

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-01-01

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data. PMID:27043594

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP-AES and Portable XRF Instruments: A Comparative Study.

PubMed

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-03-30

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP-AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP-AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP-AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP-AES analysis data, PXRF analysis data, both ICP-AES and transformed PXRF analysis data by considering the correlation between the ICP-AES and PXRF analysis data, and co-kriging to both the ICP-AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP-AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP-AES and PXRF analysis data.

Tailored vectorial light fields: flower, spider web and hybrid structures

NASA Astrophysics Data System (ADS)

Otte, Eileen; Alpmann, Christina; Denz, Cornelia

2017-04-01

We present the realization and analysis of tailored vector fields including polarization singularities. The fields are generated by a holographic method based on an advanced system including a spatial light modulator. We demonstrate our systems capabilities realizing specifically customized vector fields including stationary points of defined polarization in its transverse plane. Subsequently, vectorial flowers and spider webs as well as unique hybrid structures of these are introduced, and embedded singular points are characterized. These sophisticated light fields reveal attractive properties that pave the way to advanced application in e.g. optical micromanipulation. Beyond particle manipulation, they contribute essentially to actual questions in singular optics.

Development of Γ-ray tracking detectors

DOE PAGES

Lieder, R. M.; Gast, W.; Jäger, H. M.; ...

2001-12-01

The next generation of 4π arrays for high-precision γ-ray spectroscopy AGATA will consist of γ-ray tracking detectors. They represent high-fold segmented Ge detectors and a front-end electronics, based on digital signal processing techniques, which allows to extract energy, timing and spatial information on the interactions of a γ-ray in the Ge detector by pulse shape analysis of its signals. Utilizing the information on the positions of the interaction points and the energies released at each point the tracks of the γ-rays in a Ge shell can be reconstructed in three dimensions on the basis of the Compton-scattering formula.

Aspiration-based coevolution of link weight promotes cooperation in the spatial prisoner's dilemma game

PubMed Central

Shen, Chen; Chu, Chen; Shi, Lei

2018-01-01

In this article, we propose an aspiration-based coevolution of link weight, and explore how this set-up affects the evolution of cooperation in the spatial prisoner's dilemma game. In particular, an individual will increase the weight of its link to its neighbours only if the payoff received via this interaction exceeds a pre-defined aspiration. Conversely, if the received payoff is below this aspiration, the link weight with the corresponding neighbour will decrease. Our results show that an appropriate aspiration level leads to a high-cooperation plateau, whereas too high or too low aspiration will impede the evolution of cooperation. We explain these findings with a comprehensive analysis of transition points and with a systematic analysis of typical configuration patterns. The presented results provide further theoretical insights with regards to the impact of different aspiration levels on cooperation in human societies. PMID:29892454

Aspiration-based coevolution of link weight promotes cooperation in the spatial prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Shen, Chen; Chu, Chen; Shi, Lei; Perc, Matjaž; Wang, Zhen

2018-05-01

In this article, we propose an aspiration-based coevolution of link weight, and explore how this set-up affects the evolution of cooperation in the spatial prisoner's dilemma game. In particular, an individual will increase the weight of its link to its neighbours only if the payoff received via this interaction exceeds a pre-defined aspiration. Conversely, if the received payoff is below this aspiration, the link weight with the corresponding neighbour will decrease. Our results show that an appropriate aspiration level leads to a high-cooperation plateau, whereas too high or too low aspiration will impede the evolution of cooperation. We explain these findings with a comprehensive analysis of transition points and with a systematic analysis of typical configuration patterns. The presented results provide further theoretical insights with regards to the impact of different aspiration levels on cooperation in human societies.

Determining conduction patterns on a sparse electrode grid: Implications for the analysis of clinical arrhythmias

NASA Astrophysics Data System (ADS)

Vidmar, David; Narayan, Sanjiv M.; Krummen, David E.; Rappel, Wouter-Jan

2016-11-01

We present a general method of utilizing bioelectric recordings from a spatially sparse electrode grid to compute a dynamic vector field describing the underlying propagation of electrical activity. This vector field, termed the wave-front flow field, permits quantitative analysis of the magnitude of rotational activity (vorticity) and focal activity (divergence) at each spatial point. We apply this method to signals recorded during arrhythmias in human atria and ventricles using a multipolar contact catheter and show that the flow fields correlate with corresponding activation maps. Further, regions of elevated vorticity and divergence correspond to sites identified as clinically significant rotors and focal sources where therapeutic intervention can be effective. These flow fields can provide quantitative insights into the dynamics of normal and abnormal conduction in humans and could potentially be used to enhance therapies for cardiac arrhythmias.

Accounting for imperfect detection and survey bias in statistical analysis of presence-only data

USGS Publications Warehouse

Dorazio, Robert M.

2014-01-01

Using mathematical proof and simulation-based comparisons, I demonstrate that biases induced by errors in detection or biased selection of survey locations can be reduced or eliminated by using the hierarchical model to analyse presence-only data in conjunction with counts observed in planned surveys. I show that a relatively small number of high-quality data (from planned surveys) can be used to leverage the information in presence-only observations, which usually have broad spatial coverage but may not be informative of both occurrence and detectability of individuals. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. In addition, since the point-process model is formulated at the level of an individual, it can be extended to account for biological interactions between individuals and temporal changes in their spatial distributions.

Spatially explicit models for inference about density in unmarked or partially marked populations

USGS Publications Warehouse

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

Discriminating topology in galaxy distributions using network analysis

NASA Astrophysics Data System (ADS)

Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

2016-07-01

The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.

Development of Intelligent Unmanned Systems

DTIC Science & Technology

2011-05-01

statistical analysis on the terrain map. The data points are stored in the corresponding cells of the Traversability Grid as a linked list of 3-D Cartesian...allowed for multiple configurations of specified data to be as flexible as possible. For example, when an object is being created the knowledge store ...library was also used for querying and storing spatial data . It provided many geometric abstractions necessary such as overlap and intersects

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

Entangled communities and spatial synchronization lead to criticality in urban traffic

PubMed Central

Petri, Giovanni; Expert, Paul; Jensen, Henrik J.; Polak, John W.

2013-01-01

Understanding the relation between patterns of human mobility and the scaling of dynamical features of urban environments is a great importance for today's society. Although recent advancements have shed light on the characteristics of individual mobility, the role and importance of emerging human collective phenomena across time and space are still unclear. In this Article, we show by using two independent data-analysis techniques that the traffic in London is a combination of intertwined clusters, spanning the whole city and effectively behaving as a single correlated unit. This is due to algebraically decaying spatio-temporal correlations, that are akin to those shown by systems near a critical point. We describe these correlations in terms of Taylor's law for fluctuations and interpret them as the emerging result of an underlying spatial synchronisation. Finally, our results provide the first evidence for a large-scale spatial human system reaching a self-organized critical state. PMID:23660823

Abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947-1957, associated with a pronounced increase in the geographical rate of disease propagation.

PubMed

Smallman-Raynor, M R; Cliff, A D

2014-03-01

The abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947-1957, was associated with a profound change in the spatial dynamics of the disease. Drawing on the complete record of poliomyelitis notifications in England and Wales, we use a robust method of spatial epidemiological analysis (swash-backwash model) to evaluate the geographical rate of disease propagation in successive poliomyelitis seasons, 1940-1964. Comparisons with earlier and later time periods show that the period of heightened poliomyelitis epidemicity corresponded with a sudden and pronounced increase in the spatial rate of disease propagation. This change was observed for both urban and rural areas and points to an abrupt enhancement in the propensity for the geographical spread of polioviruses. Competing theories of the epidemic emergence of poliomyelitis in England and Wales should be assessed in the light of this evidence.

Non-reciprocity in nonlinear elastodynamics

NASA Astrophysics Data System (ADS)

Blanchard, Antoine; Sapsis, Themistoklis P.; Vakakis, Alexander F.

2018-01-01

Reciprocity is a fundamental property of linear time-invariant (LTI) acoustic waveguides governed by self-adjoint operators with symmetric Green's functions. The break of reciprocity in LTI elastodynamics is only possible through the break of time reversal symmetry on the micro-level, and this can be achieved by imposing external biases, adding nonlinearities or allowing for time-varying system properties. We present a Volterra-series based asymptotic analysis for studying spatial non-reciprocity in a class of one-dimensional (1D), time-invariant elastic systems with weak stiffness nonlinearities. We show that nonlinearity is neither necessary nor sufficient for breaking reciprocity in this class of systems; rather, it depends on the boundary conditions, the symmetries of the governing linear and nonlinear operators, and the choice of the spatial points where the non-reciprocity criterion is tested. Extension of the analysis to higher dimensions and time-varying systems is straightforward from a mathematical point of view (but not in terms of new non-reciprocal physical phenomena), whereas the connection of non-reciprocity and time irreversibility can be studied as well. Finally, we show that suitably defined non-reciprocity measures enable optimization, and can provide physical understanding of the nonlinear effects in the dynamics, enabling one to establish regimes of "maximum nonlinearity." We highlight the theoretical developments by means of a numerical example.

Spatial and temporal patterns of airflow across a foredune and beach surface under offshore winds: implications for aeolian sediment transport

NASA Astrophysics Data System (ADS)

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

2010-12-01

The input of aeolian sediment into foredune systems from beaches represents a key component of sediment budget analysis along many soft sedimentary coastlines. Where there are significant offshore wind components in local wind regimes this is normally excluded from analysis. However, recent work has shown that if the topography of the foredune is favourable then this offshore component is steered or undergoes flow reversal through leeside eddying to give onshore transport events at the back beach under offshore flow conditions. At particular distances from the foredune crest flow reattaches to the surface to continue its incident offshore direction. The location of this reattachment point has important implications for aeolian transport of sand on the back beach and foredune toe locations. This study reports initial results where the positioning of the reattachment point is mobile and is driven by incident wind velocity (at the foredune crest) and the actual undulations of the foredune crest’s topography, dictating heterogeneous flow behaviour at the beach. Using detailed field measurements (25 Hz, three-dimensional sonic anemometry) and computational fluid dynamic modelling, a temporal and spatial pattern of reattachment positions are described. Implications for aeolian transport and dune evolution are also examined.

[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.

Resolving galaxy cluster gas properties at z ˜ 1 with XMM-Newton and Chandra

NASA Astrophysics Data System (ADS)

Bartalucci, I.; Arnaud, M.; Pratt, G. W.; Démoclès, J.; van der Burg, R. F. J.; Mazzotta, P.

2017-02-01

Massive, high-redshift, galaxy clusters are useful laboratories to test cosmological models and to probe structure formation and evolution, but observations are challenging due to cosmological dimming and angular distance effects. Here we present a pilot X-ray study of the five most massive (M500 > 5 × 1014M⊙), distant (z 1), clusters detected via the Sunyaev-Zel'Dovich effect. We optimally combine XMM-Newton and Chandra X-ray observations by leveraging the throughput of XMM-Newton to obtain spatially-resolved spectroscopy, and the spatial resolution of Chandra to probe the bright inner parts and to detect embedded point sources. Capitalising on the excellent agreement in flux-related measurements, we present a new method to derive the density profiles, which are constrained in the centre by Chandra and in the outskirts by XMM-Newton. We show that the Chandra-XMM-Newton combination is fundamental for morphological analysis at these redshifts, the Chandra resolution being required to remove point source contamination, and the XMM-Newton sensitivity allowing higher significance detection of faint substructures. Measuring the morphology using images from both instruments, we found that the sample is dominated by dynamically disturbed objects. We use the combined Chandra-XMM-Newton density profiles and spatially-resolved temperature profiles to investigate thermodynamic quantities including entropy and pressure. From comparison of the scaled profiles with the local REXCESS sample, we find no significant departure from standard self-similar evolution, within the dispersion, at any radius, except for the entropy beyond 0.7 R500. The baryon mass fraction tends towards the cosmic value, with a weaker dependence on mass than that observed in the local Universe. We make a comparison with the predictions from numerical simulations. The present pilot study demonstrates the utility and feasibility of spatially-resolved analysis of individual objects at high-redshift through the combination of XMM-Newton and Chandra observations. Observations of a larger sample will allow a fuller statistical analysis to be undertaken, in particular of the intrinsic scatter in the structural and scaling properties of the cluster population.

Uncertainty in the modelling of spatial and temporal patterns of shallow groundwater flow paths: The role of geological and hydrological site information

NASA Astrophysics Data System (ADS)

Woodward, Simon J. R.; Wöhling, Thomas; Stenger, Roland

2016-03-01

Understanding the hydrological and hydrogeochemical responses of hillslopes and other small scale groundwater systems requires mapping the velocity and direction of groundwater flow relative to the controlling subsurface material features. Since point observations of subsurface materials and groundwater head are often the basis for modelling these complex, dynamic, three-dimensional systems, considerable uncertainties are inevitable, but are rarely assessed. This study explored whether piezometric head data measured at high spatial and temporal resolution over six years at a hillslope research site provided sufficient information to determine the flow paths that transfer nitrate leached from the soil zone through the shallow saturated zone into a nearby wetland and stream. Transient groundwater flow paths were modelled using MODFLOW and MODPATH, with spatial patterns of hydraulic conductivity in the three material layers at the site being estimated by regularised pilot point calibration using PEST, constrained by slug test estimates of saturated hydraulic conductivity at several locations. Subsequent Null Space Monte Carlo uncertainty analysis showed that this data was not sufficient to definitively determine the spatial pattern of hydraulic conductivity at the site, although modelled water table dynamics matched the measured heads with acceptable accuracy in space and time. Particle tracking analysis predicted that the saturated flow direction was similar throughout the year as the water table rose and fell, but was not aligned with either the ground surface or subsurface material contours; indeed the subsurface material layers, having relatively similar hydraulic properties, appeared to have little effect on saturated water flow at the site. Flow path uncertainty analysis showed that, while accurate flow path direction or velocity could not be determined on the basis of the available head and slug test data alone, the origin of well water samples relative to the material layers and site contour could still be broadly deduced. This study highlights both the challenge of collecting suitably informative field data with which to characterise subsurface hydrology, and the power of modern calibration and uncertainty modelling techniques to assess flow path uncertainty in hillslopes and other small scale systems.

Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data

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

Myra, J. R.; Zweben, S. J.; Russell, D. A.

We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less

Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data

DOE PAGES

Myra, J. R.; Zweben, S. J.; Russell, D. A.

2018-05-15

We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less

Multivariate Analysis and Modeling of Sediment Pollution Using Neural Network Models and Geostatistics

NASA Astrophysics Data System (ADS)

Golay, Jean; Kanevski, Mikhaïl

2013-04-01

The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal drift (ANNEX). Moreover, the exact number of output neurons and the selection of the corresponding variables were based on the subsets created during the exploratory phase. Concerning hidden layers, no restriction were made and multiple architectures were tested. For each MLP model, the quality of the modeling procedure was assessed by variograms: if the variogram of the residuals demonstrates pure nugget effect and if the level of the nugget exactly corresponds to the nugget value of the theoretical variogram of the corresponding variable, all the structured information has been correctly extracted without overfitting. Finally, it is worth mentioning that simple MLP models are not always able to remove all the spatial correlation structure from the data. In that case, Neural Network Residual Kriging (NNRK) can be carried out and risk assessment can be conducted with Neural Network Residual Simulations (NNRS). Finally, the results of the ANNEX models were compared to those of ordinary (co)kriging and (co)kriging with an external drift. It was shown that the ANNEX models performed better than traditional geostatistical algorithms when the relationship between the variable of interest and the auxiliary predictor was not linear. References Kanevski, M. and Maignan, M. (2004). Analysis and Modelling of Spatial Environmental Data. Lausanne: EPFL Press.

Improved spatial resolution of luminescence images acquired with a silicon line scanning camera

NASA Astrophysics Data System (ADS)

Teal, Anthony; Mitchell, Bernhard; Juhl, Mattias K.

2018-04-01

Luminescence imaging is currently being used to provide spatially resolved defect in high volume silicon solar cell production. One option to obtain the high throughput required for on the fly detection is the use a silicon line scan cameras. However, when using a silicon based camera, the spatial resolution is reduced as a result of the weakly absorbed light scattering within the camera's chip. This paper address this issue by applying deconvolution from a measured point spread function. This paper extends the methods for determining the point spread function of a silicon area camera to a line scan camera with charge transfer. The improvement in resolution is quantified in the Fourier domain and in spatial domain on an image of a multicrystalline silicon brick. It is found that light spreading beyond the active sensor area is significant in line scan sensors, but can be corrected for through normalization of the point spread function. The application of this method improves the raw data, allowing effective detection of the spatial resolution of defects in manufacturing.

Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012

PubMed Central

Carvalho, Silvia; Magalhães, Mônica de Avelar Figueiredo Mafra; Medronho, Roberto de Andrade

2017-01-01

ABSTRACT OBJECTIVE Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. METHODS Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields “street” and “number” were used. The ArcGis10 program’s Geocoding tool’s automatic process was performed. The spatial analysis was done through the kernel density estimator. RESULTS Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. CONCLUSIONS The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies. PMID:28832752

Spatial distribution and source apportionment of water pollution in different administrative zones of Wen-Rui-Tang (WRT) river watershed, China.

PubMed

Yang, Liping; Mei, Kun; Liu, Xingmei; Wu, Laosheng; Zhang, Minghua; Xu, Jianming; Wang, Fan

2013-08-01

Water quality degradation in river systems has caused great concerns all over the world. Identifying the spatial distribution and sources of water pollutants is the very first step for efficient water quality management. A set of water samples collected bimonthly at 12 monitoring sites in 2009 and 2010 were analyzed to determine the spatial distribution of critical parameters and to apportion the sources of pollutants in Wen-Rui-Tang (WRT) river watershed, near the East China Sea. The 12 monitoring sites were divided into three administrative zones of urban, suburban, and rural zones considering differences in land use and population density. Multivariate statistical methods [one-way analysis of variance, principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR) methods] were used to investigate the spatial distribution of water quality and to apportion the pollution sources. Results showed that most water quality parameters had no significant difference between the urban and suburban zones, whereas these two zones showed worse water quality than the rural zone. Based on PCA and APCS-MLR analysis, urban domestic sewage and commercial/service pollution, suburban domestic sewage along with fluorine point source pollution, and agricultural nonpoint source pollution with rural domestic sewage pollution were identified to the main pollution sources in urban, suburban, and rural zones, respectively. Understanding the water pollution characteristics of different administrative zones could put insights into effective water management policy-making especially in the area across various administrative zones.

GIS-assisted spatial analysis for urban regulatory detailed planning: designer's dimension in the Chinese code system

NASA Astrophysics Data System (ADS)

Yu, Yang; Zeng, Zheng

2009-10-01

By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach to regulatory detailed planning in China. The study first points out that the current compilation process of urban regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed planning. With a case study of the processes and results from the application of the framework, the paper concludes that the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.

GC/MS analysis of pesticides in the Ferrara area (Italy) surface water: a chemometric study.

PubMed

Pasti, Luisa; Nava, Elisabetta; Morelli, Marco; Bignami, Silvia; Dondi, Francesco

2007-01-01

The development of a network to monitor surface waters is a critical element in the assessment, restoration and protection of water quality. In this study, concentrations of 42 pesticides--determined by GC-MS on samples from 11 points along the Ferrara area rivers--have been analyzed by chemometric tools. The data were collected over a three-year period (2002-2004). Principal component analysis of the detected pesticides was carried out in order to define the best spatial locations for the sampling points. The results obtained have been interpreted in view of agricultural land use. Time series data regarding pesticide contents in surface waters has been analyzed using the Autocorrelation function. This chemometric tool allows for seasonal trends and makes it possible to optimize sampling frequency in order to detect the effective maximum pesticide content.

Topological data analysis of contagion maps for examining spreading processes on networks.

PubMed

Taylor, Dane; Klimm, Florian; Harrington, Heather A; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A; Mucha, Peter J

2015-07-21

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges-for example, due to airline transportation or communication media-allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

Topological data analysis of contagion maps for examining spreading processes on networks

NASA Astrophysics Data System (ADS)

Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

2015-07-01

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges--for example, due to airline transportation or communication media--allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct `contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

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.

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

2013-08-01

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport. Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3 emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOx differed among the emissions that were obtained from the different disaggregation methods. In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventories.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

On constraining pilot point calibration with regularization in PEST

USGS Publications Warehouse

Fienen, M.N.; Muffels, C.T.; Hunt, R.J.

2009-01-01

Ground water model calibration has made great advances in recent years with practical tools such as PEST being instrumental for making the latest techniques available to practitioners. As models and calibration tools get more sophisticated, however, the power of these tools can be misapplied, resulting in poor parameter estimates and/or nonoptimally calibrated models that do not suit their intended purpose. Here, we focus on an increasingly common technique for calibrating highly parameterized numerical models - pilot point parameterization with Tikhonov regularization. Pilot points are a popular method for spatially parameterizing complex hydrogeologic systems; however, additional flexibility offered by pilot points can become problematic if not constrained by Tikhonov regularization. The objective of this work is to explain and illustrate the specific roles played by control variables in the PEST software for Tikhonov regularization applied to pilot points. A recent study encountered difficulties implementing this approach, but through examination of that analysis, insight into underlying sources of potential misapplication can be gained and some guidelines for overcoming them developed. ?? 2009 National Ground Water Association.

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Spatially-protected Topology and Group Cohomology in Band Insulators

NASA Astrophysics Data System (ADS)

Alexandradinata, A.

This thesis investigates band topologies which rely fundamentally on spatial symmetries. A basic geometric property that distinguishes spatial symmetry regards their transformation of the spatial origin. Point groups consist of spatial transformations that preserve the spatial origin, while un-split extensions of the point groups by spatial translations are referred to as nonsymmorphic space groups. The first part of the thesis addresses topological phases with discretely-robust surface properties: we introduce theories for the Cnv point groups, as well as certain nonsymmorphic groups that involve glide reflections. These band insulators admit a powerful characterization through the geometry of quasimomentum space; parallel transport in this space is represented by the Wilson loop. The non-symmorphic topology we study is naturally described by a further extension of the nonsymmorphic space group by quasimomentum translations (the Wilson loop), thus placing real and quasimomentum space on equal footing -- here, we introduce the language of group cohomology into the theory of band insulators. The second part of the thesis addresses topological phases without surface properties -- their only known physical consequences are discrete signatures in parallel transport. We provide two such case studies with spatial-inversion and discrete-rotational symmetries respectively. One lesson learned here regards the choice of parameter loops in which we carry out transport -- the loop must be chosen to exploit the symmetry that protects the topology. While straight loops are popular for their connection with the geometric theory of polarization, we show that bent loops also have utility in topological band theory.

Research on presentation and query service of geo-spatial data based on ontology

NASA Astrophysics Data System (ADS)

Li, Hong-wei; Li, Qin-chao; Cai, Chang

2008-10-01

The paper analyzed the deficiency on presentation and query of geo-spatial data existed in current GIS, discussed the advantages that ontology possessed in formalization of geo-spatial data and the presentation of semantic granularity, taken land-use classification system as an example to construct domain ontology, and described it by OWL; realized the grade level and category presentation of land-use data benefited from the thoughts of vertical and horizontal navigation; and then discussed query mode of geo-spatial data based on ontology, including data query based on types and grade levels, instances and spatial relation, and synthetic query based on types and instances; these methods enriched query mode of current GIS, and is a useful attempt; point out that the key point of the presentation and query of spatial data based on ontology is to construct domain ontology that can correctly reflect geo-concept and its spatial relation and realize its fine formalization description.

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/

"Ten-point" 3D cephalometric analysis using low-dosage cone beam computed tomography.

PubMed

Farronato, Giampietro; Garagiola, Umberto; Dominici, Aldo; Periti, Giulia; de Nardi, Sandro; Carletti, Vera; Farronato, Davide

2010-01-01

The aim of this study was to combine the huge amount of information of low dose Cone Beam CT with a cephalometric simplified protocol thanks to the latest informatics aids. Lateral cephalograms are two-dimensional (2-D) radiographs that are used to represent three-dimensional (3-D) structures. Cephalograms have inherent limitations as a result of distortion, super imposition and differential magnification of the craniofacial complex. This may lead to errors of identification and reduced measurement accuracy. The advantages of CBCT over conventional CT include low radiation exposure, imaging quality improvement, potentially better access, high spatial resolution and lower cost. This study assessed cephalometric 2D and 3D measurements and the analysis of CBCT cephalograms of the volume and centroid of the maxilla and mandible, in 10 clinical cases. With a few exceptions the linear and angular cephalometric measurements obtained from CBCT and from conventional cephalograms did not differ statistically (p>0.01). There was a correlation between the variation in the skeletal malocclusion and growth direction of the jaws, and the variation in the spatial position (x, y, z) of the centroids and their volumes (p<0.01). The 3D cephalometric analysis is easier to interpret than 2D cephalometric analysis. In contrast to those made on projective radiographies, the angular and linear measurements detected on 3D become real, moreover the fewest points to select and the automatic measurements made by the computer drastically reduced human error, for a much more reliable reproducible and repeatable diagnosis. Copyright © 2010 Società Italiana di Ortodonzia SIDO. Published by Elsevier Srl. All rights reserved.

Development of using experimenter-given cues in infant chimpanzees: longitudinal changes in behavior and cognitive development.

PubMed

Okamoto-Barth, Sanae; Tomonaga, Masaki; Tanaka, Masayuki; Matsuzawa, Tetsuro

2008-01-01

The use of gaze shifts as social cues has various evolutionary advantages. To investigate the developmental processes of this ability, we conducted an object-choice task by using longitudinal methods with infant chimpanzees tested from 8 months old until 3 years old. The experimenter used one of six gestures towards a cup concealing food; tapping, touching, whole-hand pointing, gazing plus close-pointing, distant-pointing, close-gazing, and distant-gazing. Unlike any other previous study, we analyzed the behavioral changes that occurred before and after choosing the cup. We assumed that pre-choice behavior indicates the development of an attentional and spatial connection between a pointing cue and an object (e.g. Woodward, 2005); and post-choice behavior indicates the emergence of object permanence (e.g. Piaget, 1954). Our study demonstrated that infant chimpanzees begin to use experimenter-given cues with age (after 11 months of age). Moreover, the results from the behavioral analysis showed that the infants gradually developed the spatial link between the pointing as an object-directed action and the object. Moreover, when they were 11 months old, the infants began to inspect the inside of the cup, suggesting the onset of object permanence. Overall, our results imply that the ability to use the cues is developing and mutually related with other cognitive developments. The present study also suggests what the standard object-choice task actually measures by breaking the task down into the developmental trajectories of its component parts, and describes for the first time the social-physical cognitive development during the task with a longitudinal method.

Risk mapping of Rinderpest sero-prevalence in Central and Southern Somalia based on spatial and network risk factors.

PubMed

Ortiz-Pelaez, Angel; Pfeiffer, Dirk U; Tempia, Stefano; Otieno, F Tom; Aden, Hussein H; Costagli, Riccardo

2010-04-28

In contrast to most pastoral systems, the Somali livestock production system is oriented towards domestic trade and export with seasonal movement patterns of herds/flocks in search of water and pasture and towards export points. Data from a rinderpest survey and other data sources have been integrated to explore the topology of a contact network of cattle herds based on a spatial proximity criterion and other attributes related to cattle herd dynamics. The objective of the study is to integrate spatial mobility and other attributes with GIS and network approaches in order to develop a predictive spatial model of presence of rinderpest. A spatial logistic regression model was fitted using data for 562 point locations. It includes three statistically significant continuous-scale variables that increase the risk of rinderpest: home range radius, herd density and clustering coefficient of the node of the network whose link was established if the sum of the home ranges of every pair of nodes was equal or greater than the shortest distance between the points. The sensitivity of the model is 85.1% and the specificity 84.6%, correctly classifying 84.7% of the observations. The spatial autocorrelation not accounted for by the model is negligible and visual assessment of a semivariogram of the residuals indicated that there was no undue amount of spatial autocorrelation. The predictive model was applied to a set of 6176 point locations covering the study area. Areas at high risk of having serological evidence of rinderpest are located mainly in the coastal districts of Lower and Middle Juba, the coastal area of Lower Shabele and in the regions of Middle Shabele and Bay. There are also isolated spots of high risk along the border with Kenya and the southern area of the border with Ethiopia. The identification of point locations and areas with high risk of presence of rinderpest and their spatial visualization as a risk map will be useful for informing the prioritization of disease surveillance and control activities for rinderpest in Somalia. The methodology applied here, involving spatial and network parameters, could also be applied to other diseases and/or species as part of a standardized approach for the design of risk-based surveillance activities in nomadic pastoral settings.

A Navigation Analysis Tool (NAT) to assess spatial behavior in open-field and structured mazes.

PubMed

Jarlier, Frédéric; Arleo, Angelo; Petit, Géraldine H; Lefort, Julie M; Fouquet, Céline; Burguière, Eric; Rondi-Reig, Laure

2013-05-15

Spatial navigation calls upon mnemonic capabilities (e.g. remembering the location of a rewarding site) as well as adaptive motor control (e.g. fine tuning of the trajectory according to the ongoing sensory context). To study this complex process by means of behavioral measurements it is necessary to quantify a large set of meaningful parameters on multiple time scales (from milliseconds to several minutes), and to compare them across different paradigms. Moreover, the issue of automating the behavioral analysis is critical to cope with the consequent computational load and the sophistication of the measurements. We developed a general purpose Navigation Analysis Tool (NAT) that provides an integrated architecture consisting of a data management system (implemented in MySQL), a core analysis toolbox (in MATLAB), and a graphical user interface (in JAVA). Its extensive characterization of trajectories over time, from exploratory behavior to goal-oriented navigation with decision points using a wide range of parameters, makes NAT a powerful analysis tool. In particular, NAT supplies a new set of specific measurements assessing performances in multiple intersection mazes and allowing navigation strategies to be discriminated (e.g. in the starmaze). Its user interface enables easy use while its modular organization provides many opportunities of extension and customization. Importantly, the portability of NAT to any type of maze and environment extends its exploitation far beyond the field of spatial navigation. Copyright © 2013 Elsevier B.V. All rights reserved.

Patterns and predictors of β-diversity in the fragmented Brazilian Atlantic forest: a multiscale analysis of forest specialist and generalist birds.

PubMed

Morante-Filho, José Carlos; Arroyo-Rodríguez, Víctor; Faria, Deborah

2016-01-01

Biodiversity maintenance in human-altered landscapes (HALs) depends on the species turnover among localities, but the patterns and determinants of β-diversity in HALs are poorly known. In fact, declines, increases and neutral shifts in β-diversity have all been documented, depending on the landscape, ecological group and spatial scale of analysis. We shed some light on this controversy by assessing the patterns and predictors of bird β-diversity across multiple spatial scales considering forest specialist and habitat generalist bird assemblages. We surveyed birds from 144 point counts in 36 different forest sites across two landscapes with different amount of forest cover in the Brazilian Atlantic forest. We analysed β-diversity among points, among sites and between landscapes with multiplicative diversity partitioning of Hill numbers. We tested whether β-diversity among points was related to within-site variations in vegetation structure, and whether β-diversity among sites was related to site location and/or to differences among sites in vegetation structure and landscape composition (i.e. per cent forest and pasture cover surrounding each site). β-diversity between landscapes was lower than among sites and among points in both bird assemblages. In forest specialist birds, the landscape with less forest cover showed the highest β-diversity among sites (bird differentiation among sites), but generalist birds showed the opposite pattern. At the local scale, however, the less forested landscape showed the lowest β-diversity among points (bird homogenization within sites), independently of the bird assemblage. β-diversity among points was weakly related to vegetation structure, but higher β-diversity values were recorded among sites that were more isolated from each other, and among sites with higher differences in landscape composition, particularly in the less forested landscape. Our findings indicate that patterns of bird β-diversity vary across scales and are strongly related to landscape composition. Bird assemblages are shaped by both environmental filtering and dispersal limitation, particularly in less forested landscapes. Conservation and management strategies should therefore prevent deforestation in this biodiversity hotspot. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Noise Removal on Ocean Scalars by Means of Singularity-Based Fusion

NASA Astrophysics Data System (ADS)

Umbert, M.; Turiel, A.; Hoareau, N.; Ballabrera, J.; Martinez, J.; guimbard, S.; Font, J.

2013-12-01

Thanks to new remote sensing platforms as SMOS and Aquarius we have now access to synoptic maps of Sea Surface Salinity (SSS) at global scale. Both missions require a non-negligible amount of development in order to meet pre-launch requirements on the quality of the retrieved variables. Development efforts have been so far mainly concentrated in improving the accuracy of the acquired signals from the radiometric point of view, which is a point-wise characteristic, that is, the qualities of each point in the snapshot or swath are considered separately. However, some spatial redundancy (i.e., spatial correlation) is implicit in geophysical signals, and particularly in SSS. This redundancy is known since the beginning of the remote sensing age: eddies and fronts are visually evident in images of different variables, including Sea Surface Temperature (SST), Sea Surface Height (SSH), Ocean Color (OC), Synthetic Aperture Radars (SAR) and Brightness Temperatures (BT) at different bands. An assessment on the quality of SSS products accounting for this kind of spatial redundancy would be very interesting. So far, the structure of those correlations have been evidenced using correlation functions, but correlation functions vary from one variable to other; additionally, they are not characteristic to the points of the image but to a given large enough area. The introduction of singularity analysis for remote sensing maps of the ocean has shown that the correspondence among different scalars can be rigorously stated in terms of the correspondence of the values of their associated singularity exponents. The singularity exponents of a scalar at a given point is a unitless measure of the degree of regularity or irregularity of this function at that given point. Hence, singularity exponents can be directly compared disregarding the physical meaning of the variable from which they were derived. Using singularity analysis we can assess the quality of any scalar, as singularity exponents align in fronts following the streamlines of the flow, while noise breaks up the coherence of singularity fronts. The analysis of the output of numerical models show that up to the numerical accuracy singularity exponents of different scalars take the same values at every point. Taking the correspondence of the singularity exponents into account, it can be proved that two scalars having the same singularity exponents have a relation of functional dependence (a matricial identity involving their gradients). That functional relation can be approximated by a local linear regression under some hypothesis, which simplifies and speeds up the calculations and leads to a simple algorithm to reduce noise on a given ocean scalar using another higher- quality variable as template. This simple algorithm has been applied to SMOS data with a considerable quality gain. As a template, high-level SST maps from different sources have been used, while SMOS L2 and L3 SSS maps, and even brightness temperature maps play the role of the noisy data to be corrected. In all instances the noise level is divided by a factor of two at least. This quality gain opens the use of SMOS data for new applications, including the instant identification of ocean fronts, rain lenses, hurricane tracks, etc.

Total Nitrogen Sources of the Three Gorges Reservoir — A Spatio-Temporal Approach

PubMed Central

Ren, Chunping; Wang, Lijing; Zheng, Binghui; Holbach, Andreas

2015-01-01

Understanding the spatial and temporal variation of nutrient concentrations, loads, and their distribution from upstream tributaries is important for the management of large lakes and reservoirs. The Three Gorges Dam was built on the Yangtze River in China, the world’s third longest river, and impounded the famous Three Gorges Reservoir (TGR). In this study, we analyzed total nitrogen (TN) concentrations and inflow data from 2003 till 2010 for the main upstream tributaries of the TGR that contribute about 82% of the TGR’s total inflow. We used time series analysis for seasonal decomposition of TN concentrations and used non-parametric statistical tests (Kruskal-Walli H, Mann-Whitney U) as well as base flow segmentation to analyze significant spatial and temporal patterns of TN pollution input into the TGR. Our results show that TN concentrations had significant spatial heterogeneity across the study area (Tuo River> Yangtze River> Wu River> Min River> Jialing River>Jinsha River). Furthermore, we derived apparent seasonal changes in three out of five upstream tributaries of the TGR rivers (Kruskal-Walli H ρ = 0.009, 0.030 and 0.029 for Tuo River, Jinsha River and Min River in sequence). TN pollution from non-point sources in the upstream tributaries accounted for 68.9% of the total TN input into the TGR. Non-point source pollution of TN revealed increasing trends for 4 out of five upstream tributaries of the TGR. Land use/cover and soil type were identified as the dominant driving factors for the spatial distribution of TN. Intensifying agriculture and increasing urbanization in the upstream catchments of the TGR were the main driving factors for non-point source pollution of TN increase from 2003 till 2010. Land use and land cover management as well as chemical fertilizer use restriction were needed to overcome the threats of increasing TN pollution. PMID:26510158

Strategies for satellite-based monitoring of CO2 from distributed area and point sources

NASA Astrophysics Data System (ADS)

Schwandner, Florian M.; Miller, Charles E.; Duren, Riley M.; Natraj, Vijay; Eldering, Annmarie; Gunson, Michael R.; Crisp, David

2014-05-01

Atmospheric CO2 budgets are controlled by the strengths, as well as the spatial and temporal variabilities of CO2 sources and sinks. Natural CO2 sources and sinks are dominated by the vast areas of the oceans and the terrestrial biosphere. In contrast, anthropogenic and geogenic CO2 sources are dominated by distributed area and point sources, which may constitute as much as 70% of anthropogenic (e.g., Duren & Miller, 2012), and over 80% of geogenic emissions (Burton et al., 2013). Comprehensive assessments of CO2 budgets necessitate robust and highly accurate satellite remote sensing strategies that address the competing and often conflicting requirements for sampling over disparate space and time scales. Spatial variability: The spatial distribution of anthropogenic sources is dominated by patterns of production, storage, transport and use. In contrast, geogenic variability is almost entirely controlled by endogenic geological processes, except where surface gas permeability is modulated by soil moisture. Satellite remote sensing solutions will thus have to vary greatly in spatial coverage and resolution to address distributed area sources and point sources alike. Temporal variability: While biogenic sources are dominated by diurnal and seasonal patterns, anthropogenic sources fluctuate over a greater variety of time scales from diurnal, weekly and seasonal cycles, driven by both economic and climatic factors. Geogenic sources typically vary in time scales of days to months (geogenic sources sensu stricto are not fossil fuels but volcanoes, hydrothermal and metamorphic sources). Current ground-based monitoring networks for anthropogenic and geogenic sources record data on minute- to weekly temporal scales. Satellite remote sensing solutions would have to capture temporal variability through revisit frequency or point-and-stare strategies. Space-based remote sensing offers the potential of global coverage by a single sensor. However, no single combination of orbit and sensor provides the full range of temporal sampling needed to characterize distributed area and point source emissions. For instance, point source emission patterns will vary with source strength, wind speed and direction. Because wind speed, direction and other environmental factors change rapidly, short term variabilities should be sampled. For detailed target selection and pointing verification, important lessons have already been learned and strategies devised during JAXA's GOSAT mission (Schwandner et al, 2013). The fact that competing spatial and temporal requirements drive satellite remote sensing sampling strategies dictates a systematic, multi-factor consideration of potential solutions. Factors to consider include vista, revisit frequency, integration times, spatial resolution, and spatial coverage. No single satellite-based remote sensing solution can address this problem for all scales. It is therefore of paramount importance for the international community to develop and maintain a constellation of atmospheric CO2 monitoring satellites that complement each other in their temporal and spatial observation capabilities: Polar sun-synchronous orbits (fixed local solar time, no diurnal information) with agile pointing allow global sampling of known distributed area and point sources like megacities, power plants and volcanoes with daily to weekly temporal revisits and moderate to high spatial resolution. Extensive targeting of distributed area and point sources comes at the expense of reduced mapping or spatial coverage, and the important contextual information that comes with large-scale contiguous spatial sampling. Polar sun-synchronous orbits with push-broom swath-mapping but limited pointing agility may allow mapping of individual source plumes and their spatial variability, but will depend on fortuitous environmental conditions during the observing period. These solutions typically have longer times between revisits, limiting their ability to resolve temporal variations. Geostationary and non-sun-synchronous low-Earth-orbits (precessing local solar time, diurnal information possible) with agile pointing have the potential to provide, comprehensive mapping of distributed area sources such as megacities with longer stare times and multiple revisits per day, at the expense of global access and spatial coverage. An ad hoc CO2 remote sensing constellation is emerging. NASA's OCO-2 satellite (launch July 2014) joins JAXA's GOSAT satellite in orbit. These will be followed by GOSAT-2 and NASA's OCO-3 on the International Space Station as early as 2017. Additional polar orbiting satellites (e.g., CarbonSat, under consideration at ESA) and geostationary platforms may also become available. However, the individual assets have been designed with independent science goals and requirements, and limited consideration of coordinated observing strategies. Every effort must be made to maximize the science return from this constellation. We discuss the opportunities to exploit the complementary spatial and temporal coverage provided by these assets as well as the crucial gaps in the capabilities of this constellation. References Burton, M.R., Sawyer, G.M., and Granieri, D. (2013). Deep carbon emissions from volcanoes. Rev. Mineral. Geochem. 75: 323-354. Duren, R.M., Miller, C.E. (2012). Measuring the carbon emissions of megacities. Nature Climate Change 2, 560-562. Schwandner, F.M., Oda, T., Duren, R., Carn, S.A., Maksyutov, S., Crisp, D., Miller, C.E. (2013). Scientific Opportunities from Target-Mode Capabilities of GOSAT-2. NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA, White Paper, 6p., March 2013.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

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.

Dengue hemorrhagic fever and typhoid fever association based on spatial standpoint using scan statistics in DKI Jakarta

NASA Astrophysics Data System (ADS)

Hervind, Widyaningsih, Y.

2017-07-01

Concurrent infection with multiple infectious agents may occur in one patient, it appears frequently in dengue hemorrhagic fever (DHF) and typhoid fever. This paper depicted association between DHF and typhoid based on spatial point of view. Since paucity of data regarding dengue and typhoid co-infection, data that be used are the number of patients of those diseases in every district (kecamatan) in Jakarta in 2014 and 2015 obtained from Jakarta surveillance website. Poisson spatial scan statistics is used to detect DHF and typhoid hotspots area district in Jakarta separately. After obtain the hotspot, Fisher's exact test is applied to validate association between those two diseases' hotspot. The result exhibit hotspots of DHF and typhoid are located around central Jakarta. The further analysis used Poisson space-time scan statistics to reveal the hotspot in term of spatial and time. DHF and typhoid fever more likely occurr from January until May in the area which is relatively similar with pure spatial result. Preventive action could be done especially in the hotspot areas and it is required further study to observe the causes based on characteristics of the hotspot area.

Contextual Classification of Point Cloud Data by Exploiting Individual 3d Neigbourhoods

NASA Astrophysics Data System (ADS)

Weinmann, M.; Schmidt, A.; Mallet, C.; Hinz, S.; Rottensteiner, F.; Jutzi, B.

2015-03-01

The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification.

Reduced vision selectively impairs spatial updating in fall-prone older adults.

PubMed

Barrett, Maeve M; Doheny, Emer P; Setti, Annalisa; Maguinness, Corrina; Foran, Timothy G; Kenny, Rose Anne; Newell, Fiona N

2013-01-01

The current study examined the role of vision in spatial updating and its potential contribution to an increased risk of falls in older adults. Spatial updating was assessed using a path integration task in fall-prone and healthy older adults. Specifically, participants conducted a triangle completion task in which they were guided along two sides of a triangular route and were then required to return, unguided, to the starting point. During the task, participants could either clearly view their surroundings (full vision) or visuo-spatial information was reduced by means of translucent goggles (reduced vision). Path integration performance was measured by calculating the distance and angular deviation from the participant's return point relative to the starting point. Gait parameters for the unguided walk were also recorded. We found equivalent performance across groups on all measures in the full vision condition. In contrast, in the reduced vision condition, where participants had to rely on interoceptive cues to spatially update their position, fall-prone older adults made significantly larger distance errors relative to healthy older adults. However, there were no other performance differences between fall-prone and healthy older adults. These findings suggest that fall-prone older adults, compared to healthy older adults, have greater difficulty in reweighting other sensory cues for spatial updating when visual information is unreliable.

Generation of isolated asymmetric umbilics in light's polarization

NASA Astrophysics Data System (ADS)

Galvez, Enrique J.; Rojec, Brett L.; Kumar, Vijay; Viswanathan, Nirmal K.

2014-03-01

Polarization-singularity C points, a form of line singularities, are the vectorial counterparts of the optical vortices of spatial modes and fundamental optical features of polarization-spatial modes. Their generation in tailored beams has been limited to so-called "lemon" and "star" C points that contain symmetric dislocations in state-of-polarization patterns. In this Rapid Communication we present the theory and laboratory measurements of two complementary methods to generate isolated asymmetric C points in tailored beams, of which symmetric lemon and star patterns are limiting cases; and we report on the generation of so-called "monstar" patterns, an asymmetric C point with characteristics of both lemons and stars.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

The plasma filling factor of coronal bright points. II. Combined EIS and TRACE results

NASA Astrophysics Data System (ADS)

Dere, K. P.

2009-04-01

Aims: In a previous paper, the volumetric plasma filling factor of coronal bright points was determined from spectra obtained with the Extreme ultraviolet Imaging Spectrometer (EIS). The analysis of these data showed that the median plasma filling factor was 0.015. One interpretation of this result was that the small filling factor was consistent with a single coronal loop with a width of 1-2´´, somewhat below the apparent width. In this paper, higher spatial resolution observations with the Transition Region and Corona Explorer (TRACE) are used to test this interpretation. Methods: Rastered spectra of regions of the quiet Sun were recorded by the EIS during operations with the Hinode satellite. Many of these regions were simultaneously observed with TRACE. Calibrated intensities of Fe xii lines were obtained and images of the quiet corona were constructed from the EIS measurements. Emission measures were determined from the EIS spectra and geometrical widths of coronal bright points were obtained from the TRACE images. Electron densities were determined from density-sensitive line ratios measured with EIS. A comparison of the emission measure and bright point widths with the electron densities yielded the plasma filling factor. Results: The median electron density of coronal bright points is 3 × 109 cm-3 at a temperature of 1.6 × 106 K. The volumetric plasma filling factor of coronal bright points was found to vary from 3 × 10-3 to 0.3 with a median value of 0.04. Conclusions: The current set of EIS and TRACE coronal bright-point observations indicate the median value of their plasma filling factor is 0.04. This can be interpreted as evidence of a considerable subresolution structure in coronal bright points or as the result of a single completely filled plasma loop with widths on the order of 0.2-1.5´´ that has not been spatially resolved in these measurements.

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

A Point Spread Function for the EPOXI Mission

NASA Technical Reports Server (NTRS)

Barry, Richard K.

2010-01-01

The Extrasolar Planet Observation Characterization and the Deep Impact Extended Investigation missions (EPOXI) are currently observing the transits of exoplanets, two comet nuclei at short range, and the Earth and Mars using the High Resolution Instrument (HRI) - a 0.3 m f/35 telescope on the Deep Impact probe. The HRI is in a permanently defocused state with the instrument pOint of focus about 0.6 cm before the focal plane due to the use of a reference flat mirror that took a power during ground thermal-vacuum testing. Consequently, the point spread function (PSF) covers approximately nine pixels FWHM and is characterized by a patch with three-fold symmetry due to the three-point support structures of the primary and secondary mirrors. The PSF is also strongly color dependent varying in shape and size with change in filtration and target color. While defocus is highly desirable for exoplanet transit observations to limit sensitivity to intra-pixel variation, it is suboptimal for observations of spatially resolved targets. Consequently, all images used in our analysis of such objects were deconvolved with an instrument PSF. The instrument PSF is also being used to optimize transit analysis. We discuss development and usage of an instrument PSF for these observations.

How directions of route descriptions influence orientation specificity: the contribution of spatial abilities.

PubMed

Meneghetti, Chiara; Muffato, Veronica; Varotto, Diego; De Beni, Rossana

2017-03-01

Previous studies found mental representations of route descriptions north-up oriented when egocentric experience (given by the protagonist's initial view) was congruent with the global reference system. This study examines: (a) the development and maintenance of representations derived from descriptions when the egocentric and global reference systems are congruent or incongruent; and (b) how spatial abilities modulate these representations. Sixty participants (in two groups of 30) heard route descriptions of a protagonist's moves starting from the bottom of a layout and headed mainly northwards (SN description) in one group, and headed south from the top (NS description, the egocentric view facing in the opposite direction to the canonical north) in the other. Description recall was tested with map drawing (after hearing the description a first and second time; i.e. Time 1 and 2) and South-North (SN) or North-South (NS) pointing tasks; and spatial objective tasks were administered. The results showed that: (a) the drawings were more rotated in NS than in SN descriptions, and performed better at Time 2 than at Time 1 for both types of description; SN pointing was more accurate than NS pointing for the SN description, while SN and NS pointing accuracy did not differ for the NS description; (b) spatial (rotation) abilities were related to recall accuracy for both types of description, but were more so for the NS ones. Overall, our results showed that the way in which spatial information is conveyed (with/without congruence between the egocentric and global reference systems) and spatial abilities influence the development and maintenance of mental representations.

A spatial model to aggregate point-source and nonpoint-source water-quality data for large areas

USGS Publications Warehouse

White, D.A.; Smith, R.A.; Price, C.V.; Alexander, R.B.; Robinson, K.W.

1992-01-01

More objective and consistent methods are needed to assess water quality for large areas. A spatial model, one that capitalizes on the topologic relationships among spatial entities, to aggregate pollution sources from upstream drainage areas is described that can be implemented on land surfaces having heterogeneous water-pollution effects. An infrastructure of stream networks and drainage basins, derived from 1:250,000-scale digital-elevation models, define the hydrologic system in this spatial model. The spatial relationships between point- and nonpoint pollution sources and measurement locations are referenced to the hydrologic infrastructure with the aid of a geographic information system. A maximum-branching algorithm has been developed to simulate the effects of distance from a pollutant source to an arbitrary downstream location, a function traditionally employed in deterministic water quality models. ?? 1992.

Fusing Satellite-Derived Irradiance and Point Measurements through Optimal Interpolation

NASA Astrophysics Data System (ADS)

Lorenzo, A.; Morzfeld, M.; Holmgren, W.; Cronin, A.

2016-12-01

Satellite-derived irradiance is widely used throughout the design and operation of a solar power plant. While satellite-derived estimates cover a large area, they also have large errors compared to point measurements from sensors on the ground. We describe an optimal interpolation routine that fuses the broad spatial coverage of satellite-derived irradiance with the high accuracy of point measurements. The routine can be applied to any satellite-derived irradiance and point measurement datasets. Unique aspects of this work include the fact that information is spread using cloud location and thickness and that a number of point measurements are collected from rooftop PV systems. The routine is sensitive to errors in the satellite image geolocation, so care must be taken to adjust the cloud locations based on the solar and satellite geometries. Analysis of the optimal interpolation routine over Tucson, AZ, with 20 point measurements shows a significant improvement in the irradiance estimate for two distinct satellite image to irradiance algorithms. Improved irradiance estimates can be used for resource assessment, distributed generation production estimates, and irradiance forecasts.

Spatial and temporal assessment of cumulative disturbance impacts due to military training, burning, haying, and their interactions on land condition of Fort Riley.

PubMed

Wang, Guangxing; Murphy, Dana; Oller, Adam; Howard, Heidi R; Anderson, Alan B; Rijal, Santosh; Myers, Natalie R; Woodford, Philip

2014-07-01

The effects of military training activities on the land condition of Army installations vary spatially and temporally. Training activities observably degrade land condition while also increasing biodiversity and stabilizing ecosystems. Moreover, other anthropogenic activities regularly occur on military lands such as prescribed burns and agricultural haying-adding to the dynamics of land condition. Thus, spatially and temporally assessing the impacts of military training, prescribed burning, agricultural haying, and their interactions is critical to the management of military lands. In this study, the spatial distributions and patterns of military training-induced disturbance frequency were derived using plot observation and point observation-based method, at Fort Riley, Kansas from 1989 to 2001. Moreover, spatial and variance analysis of cumulative impacts due to military training, burning, haying, and their interactions on the land condition of Fort Riley were conducted. The results showed that: (1) low disturbance intensity dominated the majority of the study area with exception of concentrated training within centralized areas; (2) high and low values of disturbance frequency were spatially clustered and had spatial patterns that differed significantly from a random distribution; and (3) interactions between prescribed burning and agricultural haying were not significant in terms of either soil erosion or disturbance intensity although their means and variances differed significantly between the burned and non-burned areas and between the hayed and non-hayed areas.

Do Sexually Oriented Massage Parlors Cluster in Specific Neighborhoods? A Spatial Analysis of Indoor Sex Work in Los Angeles and Orange Counties, California

PubMed Central

Kim, Anna J.; Takahashi, Lois; Wiebe, Douglas J.

2015-01-01

Objective Social determinants of health may be substantially affected by spatial factors, which together may explain the persistence of health inequities. Clustering of possible sources of negative health and social outcomes points to a spatial focus for future interventions. We analyzed the spatial clustering of sex work businesses in Southern California to examine where and why they cluster. We explored economic and legal factors as possible explanations of clustering. Methods We manually coded data from a website used by paying members to post reviews of female massage parlor workers. We identified clusters of sexually oriented massage parlor businesses using spatial autocorrelation tests. We conducted spatial regression using census tract data to identify predictors of clustering. Results A total of 889 venues were identified. Clusters of tracts having higher-than-expected numbers of sexually oriented massage parlors (“hot spots”) were located outside downtowns. These hot spots were characterized by a higher proportion of adult males, a higher proportion of households below the federal poverty level, and a smaller average household size. Conclusion Sexually oriented massage parlors in Los Angeles and Orange counties cluster in particular neighborhoods. More research is needed to ascertain the causal factors of such clusters and how interventions can be designed to leverage these spatial factors. PMID:26327731

Resonant electrodynamic heating of stellar coronal loops: An LRC circuit analogue

NASA Technical Reports Server (NTRS)

Ionson, J. A.

1980-01-01

The electrodynamic coupling of stellar coronal loops to underlying beta velocity fields. A rigorous analysis revealed that the physics can be represented by a simple yet equivalent LRC circuit analogue. This analogue points to the existence of global structure oscillations which resonantly excite internal field line oscillations at a spatial resonance within the coronal loop. Although the width of this spatial resonance, as well as the induced currents and coronal velocity field, explicitly depend upon viscosity and resistivity, the resonant form of the generalized electrodynamic heating function is virtually independent of irreversibilities. This is a classic feature of high quality resonators that are externally driven by a broad band source of spectral power. Applications to solar coronal loops result in remarkable agreement with observations.

On the Limiting Markov Process of Energy Exchanges in a Rarely Interacting Ball-Piston Gas

NASA Astrophysics Data System (ADS)

Bálint, Péter; Gilbert, Thomas; Nándori, Péter; Szász, Domokos; Tóth, Imre Péter

2017-02-01

We analyse the process of energy exchanges generated by the elastic collisions between a point-particle, confined to a two-dimensional cell with convex boundaries, and a `piston', i.e. a line-segment, which moves back and forth along a one-dimensional interval partially intersecting the cell. This model can be considered as the elementary building block of a spatially extended high-dimensional billiard modeling heat transport in a class of hybrid materials exhibiting the kinetics of gases and spatial structure of solids. Using heuristic arguments and numerical analysis, we argue that, in a regime of rare interactions, the billiard process converges to a Markov jump process for the energy exchanges and obtain the expression of its generator.

Use of Larch Light Rings for an Evaluation of Volcanic Explosivity Index

NASA Astrophysics Data System (ADS)

Gurskaya, M. A.

2017-12-01

Volcanic eruptions lead to a global short-term drop in air temperature, including a shortening of the growing season. A reaction to these short-term climatic changes is the formation of light rings (LRs) in Siberian larches growing in the Siberian Subarctic area. The relationships between mass formation (and spatial spread) of LRs and the Volcanic Explosivity Index (VEI) are shown based on an analysis of larch cores collected at 18 points in the northern forest-tundra from 67°32' to 167°40' N. The eruptions with VEI = 6 and higher statistically differ from weaker eruptions by the number of LRs and their spatial distribution. The doubtful dates of several strong eruptions are discussed.

A Voronoi interior adjacency-based approach for generating a contour tree

NASA Astrophysics Data System (ADS)

Chen, Jun; Qiao, Chaofei; Zhao, Renliang

2004-05-01

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model.

Lateral Temperature-Gradient Method for High-Throughput Characterization of Material Processing by Millisecond Laser Annealing.

PubMed

Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O

2016-09-12

A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.

Finding Food Deserts: A Comparison of Methods Measuring Spatial Access to Food Stores.

PubMed

Jaskiewicz, Lara; Block, Daniel; Chavez, Noel

2016-05-01

Public health research has increasingly focused on how access to resources affects health behaviors. Mapping environmental factors, such as distance to a supermarket, can identify intervention points toward improving food access in low-income and minority communities. However, the existing literature provides little guidance on choosing the most appropriate measures of spatial access. This study compared the results of different measures of spatial access to large food stores and the locations of high and low access identified by each. The data set included U.S. Census population data and the locations of large food stores in the six-county area around Chicago, Illinois. Six measures of spatial access were calculated at the census block group level and the results compared. The analysis found that there was little agreement in the identified locations of high or low access between measures. This study illustrates the importance of considering the access measure used when conducting research, interpreting results, or comparing studies. Future research should explore the correlation of different measures with health behaviors and health outcomes. © 2015 Society for Public Health Education.

Assessment of frequency and duration of point counts when surveying for golden eagle presence

USGS Publications Warehouse

Skipper, Ben R.; Boal, Clint W.; Tsai, Jo-Szu; Fuller, Mark R.

2017-01-01

We assessed the utility of the recommended golden eagle (Aquila chrysaetos) survey methodology in the U.S. Fish and Wildlife Service 2013 Eagle Conservation Plan Guidance. We conducted 800-m radius, 1-hr point-count surveys broken into 20-min segments, during 2 sampling periods in 3 areas within the Intermountain West of the United States over 2 consecutive breeding seasons during 2012 and 2013. Our goal was to measure the influence of different survey time intervals and sampling periods on detectability and use estimates of golden eagles among different locations. Our results suggest that a less intensive effort (i.e., survey duration shorter than 1 hr and point-count survey radii smaller than 800 m) would likely be inadequate for rigorous documentation of golden eagle occurrence pre- or postconstruction of wind energy facilities. Results from a simulation analysis of detection probabilities and survey effort suggest that greater temporal and spatial effort could make point-count surveys more applicable for evaluating golden eagle occurrence in survey areas; however, increased effort would increase financial costs associated with additional person-hours and logistics (e.g., fuel, lodging). Future surveys can benefit from a pilot study and careful consideration of prior information about counts or densities of golden eagles in the survey area before developing a survey design. If information is lacking, survey planning may be best served by assuming low detection rates and increasing the temporal and spatial effort.

Fermi-Lat Observations of High-Energy Gamma-Ray Emission Toward the Galactic Center

NASA Technical Reports Server (NTRS)

Ajello, M.; Albert, A.; Atwood, W.B.; Barbiellini, G.; Bastieri, D.; Bechtol, K.; Bellazzini, R.; Bissaldi, E.; Blandford, R. D.; Brandt, T. J.;

Validation of SMAP Root Zone Soil Moisture Estimates with Improved Cosmic-Ray Neutron Probe Observations

NASA Astrophysics Data System (ADS)

Babaeian, E.; Tuller, M.; Sadeghi, M.; Franz, T.; Jones, S. B.

2017-12-01

Soil Moisture Active Passive (SMAP) soil moisture products are commonly validated based on point-scale reference measurements, despite the exorbitant spatial scale disparity. The difference between the measurement depth of point-scale sensors and the penetration depth of SMAP further complicates evaluation efforts. Cosmic-ray neutron probes (CRNP) with an approximately 500-m radius footprint provide an appealing alternative for SMAP validation. This study is focused on the validation of SMAP level-4 root zone soil moisture products with 9-km spatial resolution based on CRNP observations at twenty U.S. reference sites with climatic conditions ranging from semiarid to humid. The CRNP measurements are often biased by additional hydrogen sources such as surface water, atmospheric vapor, or mineral lattice water, which sometimes yield unrealistic moisture values in excess of the soil water storage capacity. These effects were removed during CRNP data analysis. Comparison of SMAP data with corrected CRNP observations revealed a very high correlation for most of the investigated sites, which opens new avenues for validation of current and future satellite soil moisture products.

Effects of Thermal Noise on the Transitional Dynamics of an Inextensible Elastic Filament in Stagnation Flow

PubMed Central

Deng, Mingge; Grinberg, Leopold; Caswell, Bruce

2015-01-01

We investigate the dynamics of a single inextensible elastic filament subject to anisotropic friction in a viscous stagnation-point flow, by employing both a continuum model represented by Langevin type stochastic partial differential equations (SPDEs) and a Dissipative Particle Dynamics (DPD) method. Unlike previous works1, the filament is free to rotate and the tension along the filament is determined by the local inextensible constraint. The kinematics of the filament is recorded and studied with normal modes analysis. The results show that the filament displays an instability induced by negative tension, which is analogous to Euler buckling of a beam. Symmetry breaking of normal modes dynamics and stretch-coil transitions are observed above the threshold of the buckling instability point. Furthermore, both temporal and spatial noise are amplified resulting from the interaction of thermal fluctuations and nonlinear filament dynamics. Specifically, the spatial noise is amplified with even normal modes being excited due to symmetry breaking, while the temporal noise is amplified with increasing time correlation length and variance. PMID:26023834

Validating spatial structure in canopy water content using geostatistics

NASA Technical Reports Server (NTRS)

Sanderson, E. W.; Zhang, M. H.; Ustin, S. L.; Rejmankova, E.; Haxo, R. S.

1995-01-01

Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.

Assessing the main threats to marine ecosystem components of the Adriatic - Ionian Region for the implementation of Maritime Spatial Planning

NASA Astrophysics Data System (ADS)

Lipizer, Marina

2015-04-01

Marine and coastal ecosystems and the related benefits they provide for humans are threatened by increasing pressures and competing usages. To address these issues, in the last decade, several EU legislations have been formulated to guarantee and promote sustainable use of the sea (e.g. Common Fishery Policy, Marine Strategy Framework Directive, Maritime Spatial Planning). As a first step to implement cross-border Maritime Spatial Planning (MSP) in the Adriatic - Ionian Seas, a review of the main anthropogenic pressures due to maritime activities involving the Adriatic - Ionian Region (AIR) as well as of the most relevant environmental components has been carried out. The main objective of the analysis is to better identify the spatial distribution of human uses of the sea and of the key environmental components and the ecosystem services provided. The analysis of the existing conditions includes a description of the human activities per economic sector, considering type, location, dimension and magnitude of the activity in the AIR and the spatial extent of the main environmental and ecological values present in the AIR. The environmental status has been characterized according to the descriptors proposed by the Marine Strategy Framework Directive (MSFD Directive 2008/56/EC) and the most sensitive ecosystem components in the AIR have been pointed out. A qualitative analysis of the relationships between good environmental status descriptors sensu MSFD and ecosystem services in the AIR has been carried out to provide useful information for the implementation of MSP. Cross-border Maritime Spatial Planning is particularly needed in a semi-enclosed basin such as the Adriatic Sea, hosting very diverse human activities, ranging from fishery to tourism, sand extraction, commercial and passenger transport, oil and gas exploration and exploitation, which may partially overlap and severely threaten ecosystem functioning and the associated services.

Persistent Scatterer Interferometry subsidence data exploitation using spatial tools: The Vega Media of the Segura River Basin case study

NASA Astrophysics Data System (ADS)

Tomas, R.; Herrera, G.; Cooksley, G.; Mulas, J.

2011-04-01

SummaryThe aim of this paper is to analyze the subsidence affecting the Vega Media of the Segura River Basin, using a Persistent Scatterers Interferometry technique (PSI) named Stable Point Network (SPN). This technique is capable of estimating mean deformation velocity maps of the ground surface and displacement time series from Synthetic Aperture Radar (SAR) images. A dataset acquired between January 2004 and December 2008 from ERS-2 and ENVISAT sensors has been processed measuring maximum subsidence and uplift rates of -25.6 and 7.54 mm/year respectively for the whole area. These data have been validated against ground subsidence measurements and compared with subsidence triggering and conditioning factors by means of a Geographical Information System (GIS). The spatial analysis shows a good relationship between subsidence and piezometric level evolution, pumping wells location, river distance, geology, the Arab wall, previously proposed subsidence predictive model and soil thickness. As a consequence, the paper shows the usefulness and the potential of combining Differential SAR Interferometry (DInSAR) and spatial analysis techniques in order to improve the knowledge of this kind of phenomenon.

Fractionating dead reckoning: role of the compass, odometer, logbook, and home base establishment in spatial orientation

NASA Astrophysics Data System (ADS)

Wallace, Douglas G.; Martin, Megan M.; Winter, Shawn S.

2008-06-01

Rats use multiple sources of information to maintain spatial orientation. Although previous work has focused on rats’ use of environmental cues, a growing number of studies have demonstrated that rats also use self-movement cues to organize navigation. This review examines the extent that kinematic analysis of naturally occurring behavior has provided insight into processes that mediate dead-reckoning-based navigation. This work supports a role for separate systems in processing self-movement cues that converge on the hippocampus. The compass system is involved in deriving directional information from self-movement cues; whereas, the odometer system is involved in deriving distance information from self-movement cues. The hippocampus functions similar to a logbook in that outward path unique information from the compass and odometer is used to derive the direction and distance of a path to the point at which movement was initiated. Finally, home base establishment may function to reset this system after each excursion and anchor environmental cues to self-movement cues. The combination of natural behaviors and kinematic analysis has proven to be a robust paradigm to investigate the neural basis of spatial orientation.

Fractionating dead reckoning: role of the compass, odometer, logbook, and home base establishment in spatial orientation

PubMed Central

Martin, Megan M.; Winter, Shawn S.

2008-01-01

Rats use multiple sources of information to maintain spatial orientation. Although previous work has focused on rats' use of environmental cues, a growing number of studies have demonstrated that rats also use self-movement cues to organize navigation. This review examines the extent that kinematic analysis of naturally occurring behavior has provided insight into processes that mediate dead-reckoning-based navigation. This work supports a role for separate systems in processing self-movement cues that converge on the hippocampus. The compass system is involved in deriving directional information from self-movement cues; whereas, the odometer system is involved in deriving distance information from self-movement cues. The hippocampus functions similar to a logbook in that outward path unique information from the compass and odometer is used to derive the direction and distance of a path to the point at which movement was initiated. Finally, home base establishment may function to reset this system after each excursion and anchor environmental cues to self-movement cues. The combination of natural behaviors and kinematic analysis has proven to be a robust paradigm to investigate the neural basis of spatial orientation. PMID:18553065

Hyperparameter Classification of Arctic Sea Ice and Snow Based on Aerial Laser Data, Passive Microwave Data and Field Data

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; Maslanik, J.; Williams, S.; Sturm, M.; Cavalieri, D.

2006-12-01

In the past year, the Arctic sea-ice cover has been shrinking at an alarming rate. Remote-sensing technologies provide opportunities for observations of the sea ice at unprecedented repetition rates and spatial resolutions. The advance of new observational technologies is not only fascinating, it also brings with it the challenge and necessity to derive adequate new geoinformatical and geomathematical methods as a basis for analysis and geophysical interpretation of new data types. Our research includes validation and analysis of NASA EOS data, development of observational instrumentation and advanced geoinformatics. In this talk we emphasize the close linkage between technological development and geoinformatics along case studies of sea-ice near Point Barrow, Alaska, based on the following data types: AMSR-E and PSR passive microwave data, RADARSAT and ERS SAR data, manually-collected snow-depth data and laser-elevation data from unmanned aerial vehicles. The hyperparameter concept is introduced to facilitate characterization and classification of the same sea-ice properties and spatial structures from these data sets, which differ with respect to spatial resolution, measured parameters and observed geophysical variables. Mathematically, this requires parameter identification in undersampled, oversampled or overprinted situations.

Aberrant temporal and spatial brain activity during rest in patients with chronic pain

PubMed Central

Malinen, Sanna; Vartiainen, Nuutti; Hlushchuk, Yevhen; Koskinen, Miika; Ramkumar, Pavan; Forss, Nina; Kalso, Eija; Hari, Riitta

2010-01-01

In the absence of external stimuli, human hemodynamic brain activity displays slow intrinsic variations. To find out whether such fluctuations would be altered by persistent pain, we asked 10 patients with unrelenting chronic pain of different etiologies and 10 sex- and age-matched control subjects to rest with eyes open during 3-T functional MRI. Independent component analysis was used to identify functionally coupled brain networks. Time courses of an independent component comprising the insular cortices of both hemispheres showed stronger spectral power at 0.12 to 0.25 Hz in patients than in control subjects, with the largest difference at 0.16 Hz. A similar but weaker effect was seen in the anterior cingulate cortex, whereas activity of the precuneus and early visual cortex, used as a control site, did not differ between the groups. In the patient group, seed point-based correlation analysis revealed altered spatial connectivity between insulae and anterior cingulate cortex. The results imply both temporally and spatially aberrant activity of the affective pain-processing areas in patients suffering from chronic pain. The accentuated 0.12- to 0.25-Hz fluctuations in the patient group might be related to altered activity of the autonomic nervous system. PMID:20308545

High Resolution Stratigraphic Mapping in Complex Terrain: A Comparison of Traditional Remote Sensing Techniques with Unmanned Aerial Vehicle - Structure from Motion Photogrammetry

NASA Astrophysics Data System (ADS)

Nesbit, P. R.; Hugenholtz, C.; Durkin, P.; Hubbard, S. M.; Kucharczyk, M.; Barchyn, T.

2016-12-01

Remote sensing and digital mapping have started to revolutionize geologic mapping in recent years as a result of their realized potential to provide high resolution 3D models of outcrops to assist with interpretation, visualization, and obtaining accurate measurements of inaccessible areas. However, in stratigraphic mapping applications in complex terrain, it is difficult to acquire information with sufficient detail at a wide spatial coverage with conventional techniques. We demonstrate the potential of a UAV and Structure from Motion (SfM) photogrammetric approach for improving 3D stratigraphic mapping applications within a complex badland topography. Our case study is performed in Dinosaur Provincial Park (Alberta, Canada), mapping late Cretaceous fluvial meander belt deposits of the Dinosaur Park formation amidst a succession of steeply sloping hills and abundant drainages - creating a challenge for stratigraphic mapping. The UAV-SfM dataset (2 cm spatial resolution) is compared directly with a combined satellite and aerial LiDAR dataset (30 cm spatial resolution) to reveal advantages and limitations of each dataset before presenting a unique workflow that utilizes the dense point cloud from the UAV-SfM dataset for analysis. The UAV-SfM dense point cloud minimizes distortion, preserves 3D structure, and records an RGB attribute - adding potential value in future studies. The proposed UAV-SfM workflow allows for high spatial resolution remote sensing of stratigraphy in complex topographic environments. This extended capability can add value to field observations and has the potential to be integrated with subsurface petroleum models.

Measurement and data processing approach for detecting anisotropic spatial statistics of the turbulence-induced index of refraction fluctuations in the upper atmosphere.

PubMed

Havens, Timothy C; Roggemann, Michael C; Schulz, Timothy J; Brown, Wade W; Beyer, Jeff T; Otten, L John

2002-05-20

We discuss a method of data reduction and analysis that has been developed for a novel experiment to detect anisotropic turbulence in the tropopause and to measure the spatial statistics of these flows. The experimental concept is to make measurements of temperature at 15 points on a hexagonal grid for altitudes from 12,000 to 18,000 m while suspended from a balloon performing a controlled descent. From the temperature data, we estimate the index of refraction and study the spatial statistics of the turbulence-induced index of refraction fluctuations. We present and evaluate the performance of a processing approach to estimate the parameters of an anisotropic model for the spatial power spectrum of the turbulence-induced index of refraction fluctuations. A Gaussian correlation model and a least-squares optimization routine are used to estimate the parameters of the model from the measurements. In addition, we implemented a quick-look algorithm to have a computationally nonintensive way of viewing the autocorrelation function of the index fluctuations. The autocorrelation of the index of refraction fluctuations is binned and interpolated onto a uniform grid from the sparse points that exist in our experiment. This allows the autocorrelation to be viewed with a three-dimensional plot to determine whether anisotropy exists in a specific data slab. Simulation results presented here show that, in the presence of the anticipated levels of measurement noise, the least-squares estimation technique allows turbulence parameters to be estimated with low rms error.

Effect of precursor solutions stirring on deep level defects concentration and spatial distribution in low temperature aqueous chemical synthesis of zinc oxide nanorods

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

Alnoor, Hatim, E-mail: hatim.alnoor@liu.se; Chey, Chan Oeurn; Pozina, Galia

Hexagonal c-axis oriented zinc oxide (ZnO) nanorods (NRs) with 120-300 nm diameters are synthesized via the low temperature aqueous chemical route at 80 °C on silver-coated glass substrates. The influence of varying the precursor solutions stirring durations on the concentration and spatial distributions of deep level defects in ZnO NRs is investigated. Room temperature micro-photoluminesnce (μ-PL) spectra were collected for all samples. Cathodoluminescence (CL) spectra of the as-synthesized NRs reveal a significant change in the intensity ratio of the near band edge emission (NBE) to the deep-level emission (DLE) peaks with increasing stirring durations. This is attributed to the variation inmore » the concentration of the oxygen-deficiency with increasing stirring durations as suggested from the X-ray photoelectron spectroscopy analysis. Spatially resolved CL spectra taken along individual NRs revealed that stirring the precursor solutions for relatively short duration (1-3 h), which likely induced high super saturation under thermodynamic equilibrium during the synthesis process, is observed to favor the formation of point defects moving towards the tip of the NRs. In contrary, stirring for longer duration (5-15 h) will induce low super saturation favoring the formation of point defects located at the bottom of the NRs. These findings demonstrate that it is possible to control the concentration and spatial distribution of deep level defects in ZnO NRs by varying the stirring durations of the precursor solutions.« less

Divertor with a third-order null of the poloidal field

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

Ryutov, D. D.; Umansky, M. V.

2013-09-15

A concept and preliminary feasibility analysis of a divertor with the third-order poloidal field null is presented. The third-order null is the point where not only the field itself but also its first and second spatial derivatives are zero. In this case, the separatrix near the null-point has eight branches, and the number of strike-points increases from 2 (as in the standard divertor) to six. It is shown that this magnetic configuration can be created by a proper adjustment of the currents in a set of three divertor coils. If the currents are somewhat different from the required values, themore » configuration becomes that of three closely spaced first-order nulls. Analytic approach, suitable for a quick orientation in the problem, is used. Potential advantages and disadvantages of this configuration are briefly discussed.« less

Challenging Hydrological Panaceas: Water poverty governance accounting for spatial scale in the Niger River Basin

NASA Astrophysics Data System (ADS)

Ward, John; Kaczan, David

2014-11-01

Water poverty in the Niger River Basin is a function of physical constraints affecting access and supply, and institutional arrangements affecting the ability to utilise the water resource. This distinction reflects the complexity of water poverty and points to the need to look beyond technical and financial means alone to reduce its prevalence and severity. Policy decisions affecting water resources are generally made at a state or national level. Hydrological and socio-economic evaluations at these levels, or at the basin level, cannot be presumed to be concordant with the differentiation of poverty or livelihood vulnerability at more local levels. We focus on three objectives: first, the initial mapping of observed poverty, using two health metrics and a household assets metric; second, the estimation of factors which potentially influence the observed poverty patterns; and third, a consideration of spatial non-stationarity, which identifies spatial correlates of poverty in the places where their effects appear most severe. We quantify the extent to which different levels of analysis influence these results. Comparative analysis of correlates of poverty at basin, national and local levels shows limited congruence. Variation in water quantity, and the presence of irrigation and dams had either limited or no significant correlation with observed variation in poverty measures across levels. Education and access to improved water quality were the only variables consistently significant and spatially stable across the entire basin. At all levels, education is the most consistent non-water correlate of poverty while access to protected water sources is the strongest water related correlate. The analysis indicates that landscape and scale matter for understanding water-poverty linkages and for devising policy concerned with alleviating water poverty. Interactions between environmental, social and institutional factors are complex and consequently a comprehensive understanding of poverty and its causes requires analysis at multiple spatial resolutions.

Assessing the condition of bayous and estuaries: Bayou Chico Gulf of Mexico demonstration study

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

Dickson, K.; Acevedo, M.; Waller, T.

1995-12-31

A demonstration study was conducted in May 1994 on Bayou Chico to assess the utility of various assessment and measurement endpoints in determining the condition of bayous and estuaries. Bayou Chico has water quality problems attributed to its low flushing rate and urban/industrial land use in its watershed. The sampling scheme assessed the within-sampling station and spatial variability of measurement endpoints. Fourteen sampling stations in Bayou Chico and 3 stations in Pensacola Bay were selected based on an intensified EMAP sampling grid. Time and space coordinated sampling was conducted for: sediment contaminants and properties, sediment toxicity, water quality, benthic infauna,more » zooplankton and phytoplankton populations. Fish and crabs were also collected and analyzed for a suite of biomarkers and organic chemical residues. Primary productivity was measured via the light bottle dark bottle oxygen method and via diurnal oxygen measurements made with continuous recording data sondes. Stream sites were evaluated for water and sediment quality, water and sediment toxicity, benthic invertebrates and fish. Watershed analyses included assessment of land use/landcover (via SPOT and TM images), soils, pollution sources (point and non-point) and hydrography. These data were coordinated via an Arc/Info GIS system for display and spatial analysis. 1994 survey data were used to parameterize environmental fate models such as SWMM (Storm Water Management Model), DYNHYD5 (WASP5 hydrodynamics model) and WASP5 (Water Quality Analysis Simulation Program) to make predictions about the dynamics and fate of chemical contaminants in Bayou Chico. This paper will present an overview, and report on the results in regards to within-site and spatial variability in Bayou Chico. Conclusions on the efficacy of the assessment and measurement endpoints in evaluating the condition (health) of Bayou Chico will be presented.« less

Socio-economic and ecological transformations of the peri-urban region of Gurgaon: an analysis of the trickle-down effect in the post globalization era

NASA Astrophysics Data System (ADS)

Yadav, A.; Punia, M.

2014-11-01

Economic processes are a manifestation of dynamic complex interdependent array of factors which involves resources, technology and an acting innovative human mind. Production, growth and development are the processes which has vast number of complex drivers, determinants and factors. Innovation, research, diffusion and dissemination are vital instrument of the economic processes of production, which are part of education. Whereas ecological transformations can be corroborated and analyzed by integrating remote sensing based information related to expansion of built-up area beyond city boundaries, extending to peripheries. City reflect economic, environmental, technological and social processes in their change, yet all are in turn profoundly driven by the urban spatial expansion. Metropolitan cities reflects expansion of existing urban and peri-urban areas with a significant socio-ecological transformation in terms of employment, education, and work force participation and land use changes. From the point of view of New Economic Geography (NEG) Theory 2009, the growth dynamic of metros is influenced by their proximity and dependence to a metropolis and the probable spillover effect. Entry point of discussion is the change in production of space in the post globalization era. It attempts to understand city morphology by using remote sensing datasets of LISS IV, IRS-P6 of 5.8 m spatial resolution for 2008 and 2013 and used Gurgaon Municipal Corporation's (GMC) ward boundary to represent socio-political meaning of this expansion and ways of life within the suburb. To understand how city works, detailed analysis related occupational structure, education and informality of ward 31 of Gurgaon and two villages namely Behlpa, Fazalwas and ward 11 of Nuh ( Mewat) along with the village Gabsanpur is attempted as the spatial units of study.

What's the Point of a Raster ? Advantages of 3D Point Cloud Processing over Raster Based Methods for Accurate Geomorphic Analysis of High Resolution Topography.

NASA Astrophysics Data System (ADS)

Lague, D.

2014-12-01

High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

PubMed

Wu, Dan; Faria, Andreia V; Younes, Laurent; Mori, Susumu; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Miller, Michael I

2017-10-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

A simple method for correcting spatially resolved solar intensity oscillation observations for variations in scattered light

NASA Technical Reports Server (NTRS)

Jefferies, S. M.; Duvall, T. L., Jr.

1991-01-01

A measurement of the intensity distribution in an image of the solar disk will be corrupted by a spatial redistribution of the light that is caused by the earth's atmosphere and the observing instrument. A simple correction method is introduced here that is applicable for solar p-mode intensity observations obtained over a period of time in which there is a significant change in the scattering component of the point spread function. The method circumvents the problems incurred with an accurate determination of the spatial point spread function and its subsequent deconvolution from the observations. The method only corrects the spherical harmonic coefficients that represent the spatial frequencies present in the image and does not correct the image itself.

Parallelization of PANDA discrete ordinates code using spatial decomposition

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

Humbert, P.

2006-07-01

We present the parallel method, based on spatial domain decomposition, implemented in the 2D and 3D versions of the discrete Ordinates code PANDA. The spatial mesh is orthogonal and the spatial domain decomposition is Cartesian. For 3D problems a 3D Cartesian domain topology is created and the parallel method is based on a domain diagonal plane ordered sweep algorithm. The parallel efficiency of the method is improved by directions and octants pipelining. The implementation of the algorithm is straightforward using MPI blocking point to point communications. The efficiency of the method is illustrated by an application to the 3D-Ext C5G7more » benchmark of the OECD/NEA. (authors)« less

Spatial analysis and source profiling of beta-agonists and sulfonamides in Langat River basin, Malaysia.

PubMed

Sakai, Nobumitsu; Mohd Yusof, Roslan; Sapar, Marni; Yoneda, Minoru; Ali Mohd, Mustafa

2016-04-01

Beta-agonists and sulfonamides are widely used for treating both humans and livestock for bronchial and cardiac problems, infectious disease and even as growth promoters. There are concerns about their potential environmental impacts, such as producing drug resistance in bacteria. This study focused on their spatial distribution in surface water and the identification of pollution sources in the Langat River basin, which is one of the most urbanized watersheds in Malaysia. Fourteen beta-agonists and 12 sulfonamides were quantitatively analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A geographic information system (GIS) was used to visualize catchment areas of the sampling points, and source profiling was conducted to identify the pollution sources based on a correlation between a daily pollutant load of the detected contaminant and an estimated density of human or livestock population in the catchment areas. As a result, 6 compounds (salbutamol, sulfadiazine, sulfapyridine, sulfamethazine, sulfadimethoxine and sulfamethoxazole) were widely detected in mid catchment areas towards estuary. The source profiling indicated that the pollution sources of salbutamol and sulfamethoxazole were from sewage, while sulfadiazine was from effluents of cattle, goat and sheep farms. Thus, this combination method of quantitative and spatial analysis clarified the spatial distribution of these drugs and assisted for identifying the pollution sources. Copyright © 2016 Elsevier B.V. All rights reserved.

Piping benchmark problems. Volume 1. Dynamic analysis uniform support motion response spectrum method

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

Bezler, P.; Hartzman, M.; Reich, M.

1980-08-01

A set of benchmark problems and solutions have been developed for verifying the adequacy of computer programs used for dynamic analysis and design of nuclear piping systems by the Response Spectrum Method. The problems range from simple to complex configurations which are assumed to experience linear elastic behavior. The dynamic loading is represented by uniform support motion, assumed to be induced by seismic excitation in three spatial directions. The solutions consist of frequencies, participation factors, nodal displacement components and internal force and moment components. Solutions to associated anchor point motion static problems are not included.

Registration of 4D cardiac CT sequences under trajectory constraints with multichannel diffeomorphic demons.

PubMed

Peyrat, Jean-Marc; Delingette, Hervé; Sermesant, Maxime; Xu, Chenyang; Ayache, Nicholas

2010-07-01

We propose a framework for the nonlinear spatiotemporal registration of 4D time-series of images based on the Diffeomorphic Demons (DD) algorithm. In this framework, the 4D spatiotemporal registration is decoupled into a 4D temporal registration, defined as mapping physiological states, and a 4D spatial registration, defined as mapping trajectories of physical points. Our contribution focuses more specifically on the 4D spatial registration that should be consistent over time as opposed to 3D registration that solely aims at mapping homologous points at a given time-point. First, we estimate in each sequence the motion displacement field, which is a dense representation of the point trajectories we want to register. Then, we perform simultaneously 3D registrations of corresponding time-points with the constraints to map the same physical points over time called the trajectory constraints. Under these constraints, we show that the 4D spatial registration can be formulated as a multichannel registration of 3D images. To solve it, we propose a novel version of the Diffeomorphic Demons (DD) algorithm extended to vector-valued 3D images, the Multichannel Diffeomorphic Demons (MDD). For evaluation, this framework is applied to the registration of 4D cardiac computed tomography (CT) sequences and compared to other standard methods with real patient data and synthetic data simulated from a physiologically realistic electromechanical cardiac model. Results show that the trajectory constraints act as a temporal regularization consistent with motion whereas the multichannel registration acts as a spatial regularization. Finally, using these trajectory constraints with multichannel registration yields the best compromise between registration accuracy, temporal and spatial smoothness, and computation times. A prospective example of application is also presented with the spatiotemporal registration of 4D cardiac CT sequences of the same patient before and after radiofrequency ablation (RFA) in case of atrial fibrillation (AF). The intersequence spatial transformations over a cardiac cycle allow to analyze and quantify the regression of left ventricular hypertrophy and its impact on the cardiac function.

Single scan parameterization of space-variant point spread functions in image space via a printed array: the impact for two PET/CT scanners.

PubMed

Kotasidis, F A; Matthews, J C; Angelis, G I; Noonan, P J; Jackson, A; Price, P; Lionheart, W R; Reader, A J

2011-05-21

Incorporation of a resolution model during statistical image reconstruction often produces images of improved resolution and signal-to-noise ratio. A novel and practical methodology to rapidly and accurately determine the overall emission and detection blurring component of the system matrix using a printed point source array within a custom-made Perspex phantom is presented. The array was scanned at different positions and orientations within the field of view (FOV) to examine the feasibility of extrapolating the measured point source blurring to other locations in the FOV and the robustness of measurements from a single point source array scan. We measured the spatially-variant image-based blurring on two PET/CT scanners, the B-Hi-Rez and the TruePoint TrueV. These measured spatially-variant kernels and the spatially-invariant kernel at the FOV centre were then incorporated within an ordinary Poisson ordered subset expectation maximization (OP-OSEM) algorithm and compared to the manufacturer's implementation using projection space resolution modelling (RM). Comparisons were based on a point source array, the NEMA IEC image quality phantom, the Cologne resolution phantom and two clinical studies (carbon-11 labelled anti-sense oligonucleotide [(11)C]-ASO and fluorine-18 labelled fluoro-l-thymidine [(18)F]-FLT). Robust and accurate measurements of spatially-variant image blurring were successfully obtained from a single scan. Spatially-variant resolution modelling resulted in notable resolution improvements away from the centre of the FOV. Comparison between spatially-variant image-space methods and the projection-space approach (the first such report, using a range of studies) demonstrated very similar performance with our image-based implementation producing slightly better contrast recovery (CR) for the same level of image roughness (IR). These results demonstrate that image-based resolution modelling within reconstruction is a valid alternative to projection-based modelling, and that, when using the proposed practical methodology, the necessary resolution measurements can be obtained from a single scan. This approach avoids the relatively time-consuming and involved procedures previously proposed in the literature.

Morphing of spatial objects in real time with interpolation by functions of radial and orthogonal basis

NASA Astrophysics Data System (ADS)

Kosnikov, Yu N.; Kuzmin, A. V.; Ho, Hoang Thai

2018-05-01

The article is devoted to visualization of spatial objects’ morphing described by the set of unordered reference points. A two-stage model construction is proposed to change object’s form in real time. The first (preliminary) stage is interpolation of the object’s surface by radial basis functions. Initial reference points are replaced by new spatially ordered ones. Reference points’ coordinates change patterns during the process of morphing are assigned. The second (real time) stage is surface reconstruction by blending functions of orthogonal basis. Finite differences formulas are applied to increase the productivity of calculations.

Influence of the distance between target surface and focal point on the expansion dynamics of a laser-induced silicon plasma with spatial confinement

NASA Astrophysics Data System (ADS)

Zhang, Dan; Chen, Anmin; Wang, Xiaowei; Wang, Ying; Sui, Laizhi; Ke, Da; Li, Suyu; Jiang, Yuanfei; Jin, Mingxing

2018-05-01

Expansion dynamics of a laser-induced plasma plume, with spatial confinement, for various distances between the target surface and focal point were studied by the fast photography technique. A silicon wafer was ablated to induce the plasma with a Nd:YAG laser in an atmospheric environment. The expansion dynamics of the plasma plume depended on the distance between the target surface and focal point. In addition, spatially confined time-resolved images showed the different structures of the plasma plumes at different distances between the target surface and focal point. By analyzing the plume images, the optimal distance for emission enhancement was found to be approximately 6 mm away from the geometrical focus using a 10 cm focal length lens. This optimized distance resulted in the strongest compression ratio of the plasma plume by the reflected shock wave. Furthermore, the duration of the interaction between the reflected shock wave and the plasma plume was also prolonged.

Structure-preserving interpolation of temporal and spatial image sequences using an optical flow-based method.

PubMed

Ehrhardt, J; Säring, D; Handels, H

2007-01-01

Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. The behavior and capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

Reconstruction and analysis of hybrid composite shells using meshless methods

NASA Astrophysics Data System (ADS)

Bernardo, G. M. S.; Loja, M. A. R.

2017-06-01

The importance of focusing on the research of viable models to predict the behaviour of structures which may possess in some cases complex geometries is an issue that is growing in different scientific areas, ranging from the civil and mechanical engineering to the architecture or biomedical devices fields. In these cases, the research effort to find an efficient approach to fit laser scanning point clouds, to the desired surface, has been increasing, leading to the possibility of modelling as-built/as-is structures and components' features. However, combining the task of surface reconstruction and the implementation of a structural analysis model is not a trivial task. Although there are works focusing those different phases in separate, there is still an effective need to find approaches able to interconnect them in an efficient way. Therefore, achieving a representative geometric model able to be subsequently submitted to a structural analysis in a similar based platform is a fundamental step to establish an effective expeditious processing workflow. With the present work, one presents an integrated methodology based on the use of meshless approaches, to reconstruct shells described by points' clouds, and to subsequently predict their static behaviour. These methods are highly appropriate on dealing with unstructured points clouds, as they do not need to have any specific spatial or geometric requirement when implemented, depending only on the distance between the points. Details on the formulation, and a set of illustrative examples focusing the reconstruction of cylindrical and double-curvature shells, and its further analysis, are presented.

Analysis of spatial patterns informs community assembly and sampling requirements for Collembola in forest soils

NASA Astrophysics Data System (ADS)

Dirilgen, Tara; Juceviča, Edite; Melecis, Viesturs; Querner, Pascal; Bolger, Thomas

2018-01-01

The relative importance of niche separation, non-equilibrial and neutral models of community assembly has been a theme in community ecology for many decades with none appearing to be applicable under all circumstances. In this study, Collembola species abundances were recorded over eleven consecutive years in a spatially explicit grid and used to examine (i) whether observed beta diversity differed from that expected under conditions of neutrality, (ii) whether sampling points differed in their relative contributions to overall beta diversity, and (iii) the number of samples required to provide comparable estimates of species richness across three forest sites. Neutrality could not be rejected for 26 of the forest by year combinations. However, there is a trend toward greater structure in the oldest forest, where beta diversity was greater than predicted by neutrality on five of the eleven sampling dates. The lack of difference in individual- and sample-based rarefaction curves also suggests randomness in the system at this particular scale of investigation. It seems that Collembola communities are not spatially aggregated and assembly is driven primarily by neutral processes particularly in the younger two sites. Whether this finding is due to small sample size or unaccounted for environmental variables cannot be determined. Variability between dates and sites illustrates the potential of drawing incorrect conclusions if data are collected at a single site and a single point in time.

Spatial analysis and hazard assessment on soil total nitrogen in the middle subtropical zone of China

NASA Astrophysics Data System (ADS)

Lu, Peng; Lin, Wenpeng; Niu, Zheng; Su, Yirong; Wu, Jinshui

2006-10-01

Nitrogen (N) is one of the main factors affecting environmental pollution. In recent years, non-point source pollution and water body eutrophication have become increasing concerns for both scientists and the policy-makers. In order to assess the environmental hazard of soil total N pollution, a typical ecological unit was selected as the experimental site. This paper showed that Box-Cox transformation achieved normality in the data set, and dampened the effect of outliers. The best theoretical model of soil total N was a Gaussian model. Spatial variability of soil total N at NE60° and NE150° directions showed that it had a strip anisotropic structure. The ordinary kriging estimate of soil total N concentration was mapped. The spatial distribution pattern of soil total N in the direction of NE150° displayed a strip-shaped structure. Kriging standard deviations (KSD) provided valuable information that will increase the accuracy of total N mapping. The probability kriging method is useful to assess the hazard of N pollution by providing the conditional probability of N concentration exceeding the threshold value, where we found soil total N>2.0g/kg. The probability distribution of soil total N will be helpful to conduct hazard assessment, optimal fertilization, and develop management practices to control the non-point sources of N pollution.

The California Baseline Methane Survey

NASA Astrophysics Data System (ADS)

Duren, R. M.; Thorpe, A. K.; Hopkins, F. M.; Rafiq, T.; Bue, B. D.; Prasad, K.; Mccubbin, I.; Miller, C. E.

2017-12-01

The California Baseline Methane Survey is the first systematic, statewide assessment of methane point source emissions. The objectives are to reduce uncertainty in the state's methane budget and to identify emission mitigation priorities for state and local agencies, utilities and facility owners. The project combines remote sensing of large areas with airborne imaging spectroscopy and spatially resolved bottom-up data sets to detect, quantify and attribute emissions from diverse sectors including agriculture, waste management, oil and gas production and the natural gas supply chain. Phase 1 of the project surveyed nearly 180,000 individual facilities and infrastructure components across California in 2016 - achieving completeness rates ranging from 20% to 100% per emission sector at < 5 meters spatial resolution. Additionally, intensive studies of key areas and sectors were performed to assess source persistence and variability at times scales ranging from minutes to months. Phase 2 of the project continues with additional data collection in Spring and Fall 2017. We describe the survey design and measurement, modeling and analysis methods. We present initial findings regarding the spatial, temporal and sectoral distribution of methane point source emissions in California and their estimated contribution to the state's total methane budget. We provide case-studies and lessons learned about key sectors including examples where super-emitters were identified and mitigated. We summarize challenges and recommendations for future methane research, inventories and mitigation guidance within and beyond California.

Exploratory Spatial Analysis of in vitro Respiratory Syncytial Virus Co-infections

PubMed Central

Simeonov, Ivan; Gong, Xiaoyan; Kim, Oekyung; Poss, Mary; Chiaromonte, Francesca; Fricks, John

2010-01-01

The cell response to virus infection and virus perturbation of that response is dynamic and is reflected by changes in cell susceptibility to infection. In this study, we evaluated the response of human epithelial cells to sequential infections with human respiratory syncytial virus strains A2 and B to determine if a primary infection with one strain will impact the ability of cells to be infected with the second as a function of virus strain and time elapsed between the two exposures. Infected cells were visualized with fluorescent markers, and location of all cells in the tissue culture well were identified using imaging software. We employed tools from spatial statistics to investigate the likelihood of a cell being infected given its proximity to a cell infected with either the homologous or heterologous virus. We used point processes, K-functions, and simulation procedures designed to account for specific features of our data when assessing spatial associations. Our results suggest that intrinsic cell properties increase susceptibility of cells to infection, more so for RSV-B than for RSV-A. Further, we provide evidence that the primary infection can decrease susceptibility of cells to the heterologous challenge virus but only at the 16 h time point evaluated in this study. Our research effort highlights the merits of integrating empirical and statistical approaches to gain greater insight on in vitro dynamics of virus-host interactions. PMID:21994640

Evaluating Water Budget Closure Across Spatial Scales: An Observational Approach through Texas Water Observatory

NASA Astrophysics Data System (ADS)

Gaur, N.; Jaimes, A.; Vaughan, S.; Morgan, C.; Moore, G. W.; Miller, G. R.; Everett, M. E.; Lawing, M.; Mohanty, B.

2017-12-01

Applications varying from improving water conservation practices at the field scale to predicting global hydrology under a changing climate depend upon our ability to achieve water budget closure. 1) Prevalent heterogeneity in soils, geology and land-cover, 2) uncertainties in observations and 3) space-time scales of our control volume and available data are the main factors affecting the percentage of water budget closure that we can achieve. The Texas Water Observatory presents a unique opportunity to observe the major components of the water cycle (namely precipitation, evapotranspiration, root zone soil moisture, streamflow and groundwater) in varying eco-hydrological regions representative of the lower Brazos River basin at multiple scales. The soils in these regions comprise of heavy clays that swell and shrink to create complex preferential pathways in the sub-surface, thus, making the hydrology in this region difficult to quantify. This work evaluates the water budget of the region by varying the control volume in terms of 3 temporal (weekly, monthly and seasonal) and 3 different spatial scales. The spatial scales are 1) Point scale - that is typical for process understanding of water dynamics, 2) Eddy Covariance footprint scale - that is typical of most eco-hydrological applications at the field scale and, 3) Satellite footprint scale- that is typically used in regional and global hydrological analysis. We employed a simple water balance model to evaluate the water budget at all scales. The point scale water budget was assessed using direct observations from hydro-geo-thematically located observation locations within different eddy covariance footprints. At the eddy covariance footprint scale, the sub-surface of each eddy covariance footprint was intensively characterized using electromagnetic induction (EM 38) and the resultant data was used to calculate the inter-point variability to upscale the sub-surface storage while the satellite scale water budget was evaluated using SMAP satellite observations supplemented with reanalysis products. At the point scale, we found differences in sub-surface storage in the same land-cover depending on the landscape position of the observation point while land-cover significantly affected water budget at the larger scales.

A Data Analytics Approach to Discovering Unique Microstructural Configurations Susceptible to Fatigue

NASA Astrophysics Data System (ADS)

Jha, S. K.; Brockman, R. A.; Hoffman, R. M.; Sinha, V.; Pilchak, A. L.; Porter, W. J.; Buchanan, D. J.; Larsen, J. M.; John, R.

2018-05-01

Principal component analysis and fuzzy c-means clustering algorithms were applied to slip-induced strain and geometric metric data in an attempt to discover unique microstructural configurations and their frequencies of occurrence in statistically representative instantiations of a titanium alloy microstructure. Grain-averaged fatigue indicator parameters were calculated for the same instantiation. The fatigue indicator parameters strongly correlated with the spatial location of the microstructural configurations in the principal components space. The fuzzy c-means clustering method identified clusters of data that varied in terms of their average fatigue indicator parameters. Furthermore, the number of points in each cluster was inversely correlated to the average fatigue indicator parameter. This analysis demonstrates that data-driven methods have significant potential for providing unbiased determination of unique microstructural configurations and their frequencies of occurrence in a given volume from the point of view of strain localization and fatigue crack initiation.

Gender differences in the use of external landmarks versus spatial representations updated by self-motion.

PubMed

Lambrey, Simon; Berthoz, Alain

2007-09-01

Numerous data in the literature provide evidence for gender differences in spatial orientation. In particular, it has been suggested that spatial representations of large-scale environments are more accurate in terms of metric information in men than in women but are richer in landmark information in women than in men. One explanatory hypothesis is that men and women differ in terms of navigational processes they used in daily life. The present study investigated this hypothesis by distinguishing two navigational processes: spatial updating by self-motion and landmark-based orientation. Subjects were asked to perform a pointing task in three experimental conditions, which differed in terms of reliability of the external landmarks that could be used. Two groups of subjects were distinguished, a mobile group and an immobile group, in which spatial updating of environmental locations did not have the same degree of importance for the correct performance of the pointing task. We found that men readily relied on an internal egocentric representation of where landmarks were expected to be in order to perform the pointing task, a representation that could be updated during self-motion (spatial updating). In contrast, women seemed to take their bearings more readily on the basis of the stable landmarks of the external world. We suggest that this gender difference in spatial orientation is not due to differences in information processing abilities but rather due to the differences in higher level strategies.

Identification of biogeochemical hot spots using time-lapse hydrogeophysics

NASA Astrophysics Data System (ADS)

Franz, T. E.; Loecke, T.; Burgin, A.

2016-12-01

The identification and monitoring of biogeochemical hot spots and hot moments is difficult using point based sampling techniques and sensors. Without proper monitoring and accounting of water, energy, and trace gas fluxes it is difficult to assess the environmental footprint of land management practices. One key limitation is optimal placement of sensors/chambers that adequately capture the point scale fluxes and thus a reasonable integration to landscape scale flux. In this work we present time-lapse hydrogeophysical imaging at an old agricultural field converted into a wetland mitigation bank near Dayton, Ohio. While the wetland was previously instrumented with a network of soil sensors and surface chambers to capture a suite of state variables and fluxes, we hypothesize that time-lapse hydrogeophysical imaging is an underutilized and critical reconnaissance tool for effective network design and landscape scaling. Here we combine the time-lapse hydrogeophysical imagery with the multivariate statistical technique of Empirical Orthogonal Functions (EOF) in order to isolate the spatial and temporal components of the imagery. Comparisons of soil core information (e.g. soil texture, soil carbon) from around the study site and organized within like spatial zones reveal statistically different mean values of soil properties. Moreover, the like spatial zones can be used to identify a finite number of future sampling locations, evaluation of the placement of existing sensors/chambers, upscale/downscale observations, all of which are desirable techniques for commercial use in precision agriculture. Finally, we note that combining the EOF analysis with continuous monitoring from point sensors or remote sensing products may provide a robust statistical framework for scaling observations through time as well as provide appropriate datasets for use in landscape biogeochemical models.

Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

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

Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane

2007-01-01

The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less

Entropy of Movement Outcome in Space-Time.

PubMed

Lai, Shih-Chiung; Hsieh, Tsung-Yu; Newell, Karl M

2015-07-01

Information entropy of the joint spatial and temporal (space-time) probability of discrete movement outcome was investigated in two experiments as a function of different movement strategies (space-time, space, and time instructional emphases), task goals (point-aiming and target-aiming) and movement speed-accuracy constraints. The variance of the movement spatial and temporal errors was reduced by instructional emphasis on the respective spatial or temporal dimension, but increased on the other dimension. The space-time entropy was lower in targetaiming task than the point aiming task but did not differ between instructional emphases. However, the joint probabilistic measure of spatial and temporal entropy showed that spatial error is traded for timing error in tasks with space-time criteria and that the pattern of movement error depends on the dimension of the measurement process. The unified entropy measure of movement outcome in space-time reveals a new relation for the speed-accuracy.

A Note on Spatial Averaging and Shear Stresses Within Urban Canopies

NASA Astrophysics Data System (ADS)

Xie, Zheng-Tong; Fuka, Vladimir

2018-04-01

One-dimensional urban models embedded in mesoscale numerical models may place several grid points within the urban canopy. This requires an accurate parametrization for shear stresses (i.e. vertical momentum fluxes) including the dispersive stress and momentum sinks at these points. We used a case study with a packing density of 33% and checked rigorously the vertical variation of spatially-averaged total shear stress, which can be used in a one-dimensional column urban model. We found that the intrinsic spatial average, in which the volume or area of the solid parts are not included in the average process, yield greater time-spatial average of total stress within the canopy and a more evident abrupt change at the top of the buildings than the comprehensive spatial average, in which the volume or area of the solid parts are included in the average.

Spatial adaptation procedures on tetrahedral meshes for unsteady aerodynamic flow calculations

NASA Technical Reports Server (NTRS)

Rausch, Russ D.; Batina, John T.; Yang, Henry T. Y.

1993-01-01

Spatial adaptation procedures for the accurate and efficient solution of steady and unsteady inviscid flow problems are described. The adaptation procedures were developed and implemented within a three-dimensional, unstructured-grid, upwind-type Euler code. These procedures involve mesh enrichment and mesh coarsening to either add points in high gradient regions of the flow or remove points where they are not needed, respectively, to produce solutions of high spatial accuracy at minimal computational cost. A detailed description of the enrichment and coarsening procedures are presented and comparisons with experimental data for an ONERA M6 wing and an exact solution for a shock-tube problem are presented to provide an assessment of the accuracy and efficiency of the capability. Steady and unsteady results, obtained using spatial adaptation procedures, are shown to be of high spatial accuracy, primarily in that discontinuities such as shock waves are captured very sharply.

Spatial adaptation procedures on tetrahedral meshes for unsteady aerodynamic flow calculations

NASA Technical Reports Server (NTRS)

Rausch, Russ D.; Batina, John T.; Yang, Henry T. Y.

1993-01-01

Spatial adaptation procedures for the accurate and efficient solution of steady and unsteady inviscid flow problems are described. The adaptation procedures were developed and implemented within a three-dimensional, unstructured-grid, upwind-type Euler code. These procedures involve mesh enrichment and mesh coarsening to either add points in high gradient regions of the flow or remove points where they are not needed, respectively, to produce solutions of high spatial accuracy at minimal computational cost. The paper gives a detailed description of the enrichment and coarsening procedures and presents comparisons with experimental data for an ONERA M6 wing and an exact solution for a shock-tube problem to provide an assessment of the accuracy and efficiency of the capability. Steady and unsteady results, obtained using spatial adaptation procedures, are shown to be of high spatial accuracy, primarily in that discontinuities such as shock waves are captured very sharply.

Geodata Modeling and Query in Geographic Information Systems

NASA Technical Reports Server (NTRS)

Adam, Nabil

1996-01-01

Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.

Flow Control

DTIC Science & Technology

2013-04-08

fined as p( xs , t), to the flow state which is modeled by the time coefficients of a POD truncation (a fj (t) in equation 17) (Note: the f superscript...spatially to desired flow features (e.g. vortex shedding, vortex pairing, boundary layer growth, separation points, etc.) are chosen and defined as ( xs ...within the numeric simulation. A surface POD analysis, p( xs , t)≃ k ∑ p=1 asp(t)ϕsp( xs ), (30) yields surface POD modes φ sp( xs ). The resulting

Mobile Visualization and Analysis Tools for Spatial Time-Series Data

NASA Astrophysics Data System (ADS)

Eberle, J.; Hüttich, C.; Schmullius, C.

2013-12-01

The Siberian Earth System Science Cluster (SIB-ESS-C) provides access and analysis services for spatial time-series data build on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and climate data from meteorological stations. Until now a webportal for data access, visualization and analysis with standard-compliant web services was developed for SIB-ESS-C. As a further enhancement a mobile app was developed to provide an easy access to these time-series data for field campaigns. The app sends the current position from the GPS receiver and a specific dataset (like land surface temperature or vegetation indices) - selected by the user - to our SIB-ESS-C web service and gets the requested time-series data for the identified pixel back in real-time. The data is then being plotted directly in the app. Furthermore the user has possibilities to analyze the time-series data for breaking points and other phenological values. These processings are executed on demand of the user on our SIB-ESS-C web server and results are transfered to the app. Any processing can also be done at the SIB-ESS-C webportal. The aim of this work is to make spatial time-series data and analysis functions available for end users without the need of data processing. In this presentation the author gives an overview on this new mobile app, the functionalities, the technical infrastructure as well as technological issues (how the app was developed, our made experiences).

Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems

NASA Astrophysics Data System (ADS)

Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

2015-04-01

In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the surface of a M-dimensional, unit radius hyper-sphere, (ii) relocating the N points on a representative set of N hyper-spheres of different radii, and (iii) transforming the coordinates of those points to lie on N different hyper-ellipsoids spanning the multivariate Gaussian distribution. The above method is applied in a dimensionality reduction context by defining flow-controlling points over which representative sampling of hydraulic conductivity is performed, thus also accounting for the sensitivity of the flow and transport model to the input hydraulic conductivity field. The performance of the various stratified sampling methods, LH, SL, and ME, is compared to that of SR sampling in terms of reproduction of ensemble statistics of hydraulic conductivity and solute concentration for different sample sizes N (numbers of realizations). The results indicate that ME sampling constitutes an equally if not more efficient simulation method than LH and SL sampling, as it can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than SR sampling. References [1] Gutjahr A.L. and Bras R.L. Spatial variability in subsurface flow and transport: A review. Reliability Engineering & System Safety, 42, 293-316, (1993). [2] Helton J.C. and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81, 23-69, (2003). [3] Switzer P. Multiple simulation of spatial fields. In: Heuvelink G, Lemmens M (eds) Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Coronet Books Inc., pp 629?635 (2000).

Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Abdelrahim, Mohamed Mahmoud Hosny

2001-11-01

In this research, an "Intelligent Imagery System Prototype" (IISP) was developed. IISP is an integration tool that facilitates the environment for active, direct, and on-the-fly usage of high resolution imagery, internally linked to hidden GIS vector layers, to query the real world phenomena and, consequently, to perform exploratory types of spatial analysis based on a clear/undisturbed image scene. The IISP was designed and implemented using the software components approach to verify the hypothesis that a fully rectified, partially rectified, or even unrectified digital image can be internally linked to a variety of different hidden vector databases/layers covering the end user area of interest, and consequently may be reliably used directly as a base for "on-the-fly" querying of real-world phenomena and for performing exploratory types of spatial analysis. Within IISP, differentially rectified, partially rectified (namely, IKONOS GEOCARTERRA(TM)), and unrectified imagery (namely, scanned aerial photographs and captured video frames) were investigated. The system was designed to handle four types of spatial functions, namely, pointing query, polygon/line-based image query, database query, and buffering. The system was developed using ESRI MapObjects 2.0a as the core spatial component within Visual Basic 6.0. When used to perform the pre-defined spatial queries using different combinations of image and vector data, the IISP provided the same results as those obtained by querying pre-processed vector layers even when the image used was not orthorectified and the vector layers had different parameters. In addition, the real-time pixel location orthorectification technique developed and presented within the IKONOS GEOCARTERRA(TM) case provided a horizontal accuracy (RMSE) of +/- 2.75 metres. This accuracy is very close to the accuracy level obtained when purchasing the orthorectified IKONOS PRECISION products (RMSE of +/- 1.9 metre). The latter cost approximately four times as much as the IKONOS GEOCARTERRA(TM) products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. (Abstract shortened by UMI.)

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

ERIC Educational Resources Information Center

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2011-01-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the…

Simulation of anisoplanatic imaging through optical turbulence using numerical wave propagation with new validation analysis

NASA Astrophysics Data System (ADS)

Hardie, Russell C.; Power, Jonathan D.; LeMaster, Daniel A.; Droege, Douglas R.; Gladysz, Szymon; Bose-Pillai, Santasri

2017-07-01

We present a numerical wave propagation method for simulating imaging of an extended scene under anisoplanatic conditions. While isoplanatic simulation is relatively common, few tools are specifically designed for simulating the imaging of extended scenes under anisoplanatic conditions. We provide a complete description of the proposed simulation tool, including the wave propagation method used. Our approach computes an array of point spread functions (PSFs) for a two-dimensional grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. The degradation includes spatially varying warping and blurring. To produce the PSF array, we generate a series of extended phase screens. Simulated point sources are numerically propagated from an array of positions on the object plane, through the phase screens, and ultimately to the focal plane of the simulated camera. Note that the optical path for each PSF will be different, and thus, pass through a different portion of the extended phase screens. These different paths give rise to a spatially varying PSF to produce anisoplanatic effects. We use a method for defining the individual phase screen statistics that we have not seen used in previous anisoplanatic simulations. We also present a validation analysis. In particular, we compare simulated outputs with the theoretical anisoplanatic tilt correlation and a derived differential tilt variance statistic. This is in addition to comparing the long- and short-exposure PSFs and isoplanatic angle. We believe this analysis represents the most thorough validation of an anisoplanatic simulation to date. The current work is also unique that we simulate and validate both constant and varying Cn2(z) profiles. Furthermore, we simulate sequences with both temporally independent and temporally correlated turbulence effects. Temporal correlation is introduced by generating even larger extended phase screens and translating this block of screens in front of the propagation area. Our validation analysis shows an excellent match between the simulation statistics and the theoretical predictions. Thus, we think this tool can be used effectively to study optical anisoplanatic turbulence and to aid in the development of image restoration methods.

Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

NASA Astrophysics Data System (ADS)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

PubMed

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

Novel microbiological and spatial statistical methods to improve strength of epidemiological evidence in a community-wide waterborne outbreak.

PubMed

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9-16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak.

Towards a Spatial Understanding of Trade-Offs in Sustainable Development: A Meso-Scale Analysis of the Nexus between Land Use, Poverty, and Environment in the Lao PDR.

PubMed

Messerli, Peter; Bader, Christoph; Hett, Cornelia; Epprecht, Michael; Heinimann, Andreas

2015-01-01

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use-poverty-environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local-highly contextual-development potentials is key to shaping outcomes of the land use-poverty-environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.

Towards a Spatial Understanding of Trade-Offs in Sustainable Development: A Meso-Scale Analysis of the Nexus between Land Use, Poverty, and Environment in the Lao PDR

PubMed Central

Messerli, Peter; Bader, Christoph; Hett, Cornelia; Epprecht, Michael; Heinimann, Andreas

2015-01-01

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change. PMID:26218646

Searching for Wolf-Rayet Stars Beyond the Local Group

NASA Astrophysics Data System (ADS)

Bibby, J. L.; Shara, M. M.; Crowther, P. A.; Moffat, A. F. J.

2012-12-01

We present preliminary results from our HST/WFC3 F469N narrow-band imaging of the nearby star-forming galaxy M101 in which we search for Wolf-Rayet (WR) stars, possible progenitors of Type Ibc core-collapse supernovae (ccSNe). From analysis of the central pointing of M101 we identify ˜1000 WR candidates from photometric analysis and estimate ˜ 450 using the “blinking” method. From analysis of a sample region we find that 35% of our WR candidates would not be detected in ground-based surveys and 40% of sources are not detected in the HST F435W images, highlighting the importance of high spatial resolution narrow-band imaging.

A computer software system for integration and analysis of grid-based remote sensing data with other natural resource data. Remote Sensing Project

NASA Technical Reports Server (NTRS)

Tilmann, S. E.; Enslin, W. R.; Hill-Rowley, R.

1977-01-01

A computer-based information system is described designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. Soil, land cover/use, topographic and geological maps were used as a data base to develope an eleven map portfolio. The major themes of the portfolio are land cover/use, non-point water pollution, waste disposal, and ground water recharge.

Spatial and temporal variability of thermohaline properties in the Bay of Koper (northern Adriatic Sea)

NASA Astrophysics Data System (ADS)

Soczka Mandac, Rok; Žagar, Dušan; Faganeli, Jadran

2013-04-01

In this study influence of fresh water discharge on the spatial and temporal variability of thermohaline (TH) conditions is explored for the Bay of Koper (Bay). The Bay is subject to different driving agents: wind stress (bora, sirocco), tidal and seiches effect, buoyancy fluxes, general circulation of the Adriatic Sea and discharge of the Rizana and Badaševica rivers. These rivers have torrential characteristics that are hard to forecast in relation to meteorological events (precipitation). Therefore, during episodic events the spatial and temporal variability of TH properties in the Bay is difficult to determine [1]. Measurements of temperature, salinity and turbidity were conducted monthly on 35 sampling points in the period: June 2011 - December 2012. The data were processed and spatial interpolated with an objective analysis method. Furthermore, empirical orthogonal function analysis (EOF) [2] was applied to investigate spatial and temporal TH variations. Strong horizontal and vertical stratification was observed in the beginning of June 2011 due to high fresh water discharge of the Rizana (31 m3/s) and Badaševica (2 m3/s) rivers. The horizontal gradient (ΔT = 6°C) was noticed near the mouth of the Rizana river. Similar pattern was identified for salinity field on the boundary of the front where the gradient was ΔS = 20 PSU. Vertical temperature gradient was ΔT = 4°C while salinity gradient was ΔS = 18 PSU in the subsurface layer at depth of 3 m. Spatial analysis of the first principal component (86% of the total variance) shows uniform temperature distribution in the surface layer (1m) during the studied period. Furthermore, temporal variability of temperature shows seasonal variation with a minimum in February and maximum in August. This confirms that episodic events have a negligible effect on spatial and temporal variation of temperature in the subsurface layer. Further analysis will include application of EOF on the salinity, density and total suspended matter. Additionally, we will investigate the cross correlations between the above mentioned parameters with singular value decomposition method. Reference: 1. Faganeli, J., Planinc, R., Pezdic, J., Smodis, B., Stegnar, P., and Ogorelec, B. 1991. Marine geology of Gulf of Trieste (northern Adriatic): Geochemical aspects. Marine Geology, 99: 93-108. 2. Glover, M., Jenkins, J., and Doney, S. C. 2011. Modeling methods for marine science. Cambridge University Press, 571 p.

Analysis, Thematic Maps and Data Mining from Point Cloud to Ontology for Software Development

NASA Astrophysics Data System (ADS)

Nespeca, R.; De Luca, L.

2016-06-01

The primary purpose of the survey for the restoration of Cultural Heritage is the interpretation of the state of building preservation. For this, the advantages of the remote sensing systems that generate dense point cloud (range-based or image-based) are not limited only to the acquired data. The paper shows that it is possible to extrapolate very useful information in diagnostics using spatial annotation, with the use of algorithms already implemented in open-source software. Generally, the drawing of degradation maps is the result of manual work, so dependent on the subjectivity of the operator. This paper describes a method of extraction and visualization of information, obtained by mathematical procedures, quantitative, repeatable and verifiable. The case study is a part of the east facade of the Eglise collégiale Saint-Maurice also called Notre Dame des Grâces, in Caromb, in southern France. The work was conducted on the matrix of information contained in the point cloud asci format. The first result is the extrapolation of new geometric descriptors. First, we create the digital maps with the calculated quantities. Subsequently, we have moved to semi-quantitative analyses that transform new data into useful information. We have written the algorithms for accurate selection, for the segmentation of point cloud, for automatic calculation of the real surface and the volume. Furthermore, we have created the graph of spatial distribution of the descriptors. This work shows that if we work during the data processing we can transform the point cloud into an enriched database: the use, the management and the data mining is easy, fast and effective for everyone involved in the restoration process.

Statistical analysis of the ionospheric ion density recorded by DEMETER in the epicenter areas of earthquakes as well as in their magnetically conjugate point areas

NASA Astrophysics Data System (ADS)

Li, Mei; Parrot, Michel

2018-02-01

Results of a statistical variation of total ion density observed in the vicinity of epicenters as well as around magnetically conjugated points of earthquakes are presented in this paper. Two data sets are used: the ion density measured by DEMETER during about 6.5 years and the list of strong earthquakes (MW ≥ 4.8) occurring globally during this period (14,764 earthquakes in total). First of all, ionospheric perturbations with 23-120 s observation time corresponding to spatial scales of 160-840 km are automatically detected by a software (64,287 anomalies in total). Second, it is checked if a perturbation could be associated either with the epicenter of an earthquake or with its magnetically conjugated point (distance < 1500 km and time < 15 days before the earthquake). The index Kp < 3 is also considered in order to reduce the effect of the geomagnetic activity on the ionosphere during this period. The results show that it is possible to detect variations of the ionospheric parameters above the epicenter areas as well as above their conjugated points. About one third of the earthquakes are detected with ionospheric influence on both sides of the Earth. There is a trend showing that the perturbation length increases as the magnitude of the detected EQs but it is more obvious for large magnitude. The probability that a perturbation appears is higher on the day of the earthquake and then gradually decreases when the time before the earthquake increases. The spatial distribution of perturbations shows that the probability of perturbations appearing southeast of the epicenter before an earthquake is a little bit higher and that there is an obvious trend because perturbations appear west of the conjugated point of an earthquake.

Image formation of volume holographic microscopy using point spread functions

NASA Astrophysics Data System (ADS)

Luo, Yuan; Oh, Se Baek; Kou, Shan Shan; Lee, Justin; Sheppard, Colin J. R.; Barbastathis, George

2010-04-01

We present a theoretical formulation to quantify the imaging properties of volume holographic microscopy (VHM). Volume holograms are formed by exposure of a photosensitive recording material to the interference of two mutually coherent optical fields. Recently, it has been shown that a volume holographic pupil has spatial and spectral sectioning capability for fluorescent samples. Here, we analyze the point spread function (PSF) to assess the imaging behavior of the VHM with a point source and detector. The coherent PSF of the VHM is derived, and the results are compared with those from conventional microscopy, and confocal microscopy with point and slit apertures. According to our analysis, the PSF of the VHM can be controlled in the lateral direction by adjusting the parameters of the VH. Compared with confocal microscopes, the performance of the VHM is comparable or even potentially better, and the VHM is also able to achieve real-time and three-dimensional (3D) imaging due to its multiplexing ability.

Spatial judgments in the horizontal and vertical planes from different vantage points.

PubMed

Prytz, Erik; Scerbo, Mark W

2012-01-01

Todorović (2008 Perception 37 106-125) reported that there are systematic errors in the perception of 3-D space when viewing 2-D linear perspective drawings depending on the observer's vantage point. Because these findings were restricted to the horizontal plane, the current study was designed to determine the nature of these errors in the vertical plane. Participants viewed an image containing multiple colonnades aligned on parallel converging lines receding to a vanishing point. They were asked to judge where, in the physical room, the next column should be placed. The results support Todorović in that systematic deviations in the spatial judgments depended on vantage point for both the horizontal and vertical planes. However, there are also marked differences between the two planes. While judgments in both planes failed to compensate adequately for the vantage-point shift, the vertical plane induced greater distortions of the stimulus image itself within each vantage point.

Model for Semantically Rich Point Cloud Data

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

2017-10-01

This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

Measuring Spatial Variability of Vapor Flux to Characterize Vadose-zone VOC Sources: Flow-cell Experiments

DOE PAGES

Mainhagu, Jon; Morrison, C.; Truex, Michael J.; ...

2014-08-05

A method termed vapor-phase tomography has recently been proposed to characterize the distribution of volatile organic contaminant mass in vadose-zone source areas, and to measure associated three-dimensional distributions of local contaminant mass discharge. The method is based on measuring the spatial variability of vapor flux, and thus inherent to its effectiveness is the premise that the magnitudes and temporal variability of vapor concentrations measured at different monitoring points within the interrogated area will be a function of the geospatial positions of the points relative to the source location. A series of flow-cell experiments was conducted to evaluate this premise. Amore » well-defined source zone was created by injection and extraction of a non-reactive gas (SF6). Spatial and temporal concentration distributions obtained from the tests were compared to simulations produced with a mathematical model describing advective and diffusive transport. Tests were conducted to characterize both areal and vertical components of the application. Decreases in concentration over time were observed for monitoring points located on the opposite side of the source zone from the local–extraction point, whereas increases were observed for monitoring points located between the local–extraction point and the source zone. We found that the results illustrate that comparison of temporal concentration profiles obtained at various monitoring points gives a general indication of the source location with respect to the extraction and monitoring points.« less

Analysis of Temporal and Spatial Distributions of Ammonia Nitrogen in the Huaihe River Basin from 1998 to 2014

NASA Astrophysics Data System (ADS)

Xu, J.; Jin, G.; Tang, H.; Li, L.

2016-12-01

To assess the effectiveness of water pollution control measures taken in the Huaihe River Basin (HRB) in China, we analyzed the temporal and spatial distributions of ammonia nitrogen (NH3-N) in the river water from 1998 to 2014 (three Chinese Five-year Plan periods).Analysis of measured NH3-N concentrations from various monitoring stations using the STL (seasonal trend decomposition using loess) method and a modified log-linear model revealed that: (1) The rate of NH3-N concentration reduction over the whole period was 70% 81% in the main stream of Huaihe River, but reached 88% in two major tributaries - the Shaying River and Guo River. (2) The NH3-N concentrations decreased significantly particularly between the tenth Five-year Plan and eleventh Five-year Plan periods in the main stream. In comparison, significant NH3-N reduction occurred over all three Five-year Plan periods in the Shaying and Guo tributaries. The concentration in the first year of a Five-year Plan period tended to much higher than that in the last year of the same period, likely due to the difference in implementing the pollution control measures. (3) The NH3-N concentrations were higher in the spring (fertilization period) and winter (low discharge) than in the summer and autumn. (4) With the implementation of pollution control measures, the contribution rate of NH3-N in the two major tributaries from point sources has decreased from 74% 93% in earlier years to 3% 28% in later years. However, NH3-N input from non-point sources appeared to remain stable and largely depend on runoff. To further reduce the NH3-N concentration in the river, policies and control measures should focus on non-point sources.

Sensitivity of finite helical axis parameters to temporally varying realistic motion utilizing an idealized knee model.

PubMed

Johnson, T S; Andriacchi, T P; Erdman, A G

2004-01-01

Various uses of the screw or helical axis have previously been reported in the literature in an attempt to quantify the complex displacements and coupled rotations of in vivo human knee kinematics. Multiple methods have been used by previous authors to calculate the axis parameters, and it has been theorized that the mathematical stability and accuracy of the finite helical axis (FHA) is highly dependent on experimental variability and rotation increment spacing between axis calculations. Previous research has not addressed the sensitivity of the FHA for true in vivo data collection, as required for gait laboratory analysis. This research presents a controlled series of experiments simulating continuous data collection as utilized in gait analysis to investigate the sensitivity of the three-dimensional finite screw axis parameters of rotation, displacement, orientation and location with regard to time step increment spacing, utilizing two different methods for spatial location. Six-degree-of-freedom motion parameters are measured for an idealized rigid body knee model that is constrained to a planar motion profile for the purposes of error analysis. The kinematic data are collected using a multicamera optoelectronic system combined with an error minimization algorithm known as the point cluster method. Rotation about the screw axis is seen to be repeatable, accurate and time step increment insensitive. Displacement along the axis is highly dependent on time step increment sizing, with smaller rotation angles between calculations producing more accuracy. Orientation of the axis in space is accurate with only a slight filtering effect noticed during motion reversal. Locating the screw axis by a projected point onto the screw axis from the mid-point of the finite displacement is found to be less sensitive to motion reversal than finding the intersection of the axis with a reference plane. A filtering effect of the spatial location parameters was noted for larger time step increments during periods of little or no rotation.

Simultaneous colour visualizations of multiple ALS point cloud attributes for land cover and vegetation analysis

NASA Astrophysics Data System (ADS)

Zlinszky, András; Schroiff, Anke; Otepka, Johannes; Mandlburger, Gottfried; Pfeifer, Norbert

2014-05-01

LIDAR point clouds hold valuable information for land cover and vegetation analysis, not only in the spatial distribution of the points but also in their various attributes. However, LIDAR point clouds are rarely used for visual interpretation, since for most users, the point cloud is difficult to interpret compared to passive optical imagery. Meanwhile, point cloud viewing software is available allowing interactive 3D interpretation, but typically only one attribute at a time. This results in a large number of points with the same colour, crowding the scene and often obscuring detail. We developed a scheme for mapping information from multiple LIDAR point attributes to the Red, Green, and Blue channels of a widely used LIDAR data format, which are otherwise mostly used to add information from imagery to create "photorealistic" point clouds. The possible combinations of parameters are therefore represented in a wide range of colours, but relative differences in individual parameter values of points can be well understood. The visualization was implemented in OPALS software, using a simple and robust batch script, and is viewer independent since the information is stored in the point cloud data file itself. In our case, the following colour channel assignment delivered best results: Echo amplitude in the Red, echo width in the Green and normalized height above a Digital Terrain Model in the Blue channel. With correct parameter scaling (but completely without point classification), points belonging to asphalt and bare soil are dark red, low grassland and crop vegetation are bright red to yellow, shrubs and low trees are green and high trees are blue. Depending on roof material and DTM quality, buildings are shown from red through purple to dark blue. Erroneously high or low points, or points with incorrect amplitude or echo width usually have colours contrasting from terrain or vegetation. This allows efficient visual interpretation of the point cloud in planar, profile and 3D views since it reduces crowding of the scene and delivers intuitive contextual information. The resulting visualization has proved useful for vegetation analysis for habitat mapping, and can also be applied as a first step for point cloud level classification. An interactive demonstration of the visualization script is shown during poster attendance, including the opportunity to view your own point cloud sample files.

Coronal energy distribution and X-ray activity in the small scale magnetic field of the quiet sun

NASA Technical Reports Server (NTRS)

Habbal, S. R.

1992-01-01

The energy distribution in the small-scale magnetic field that pervades the solar surface, and its relationship to X-ray/coronal activity are discussed. The observed emission from the small scale structures, at temperatures characteristic of the chromosphere, transition region and corona, emanates from the boundaries of supergranular cells, within coronal bright points. This emission is characterized by a strong temporal and spatial variability with no definite pattern. The analysis of simultaneous, multiwavelength EUV observations shows that the spatial density of the enhanced as well as variable emission from the small scale structures exhibits a pronounced temperature dependence with significant maxima at 100,000 and 1,000,000 K. Within the limits of the spatial (1-5 arcsec) and temporal (1-5 min) resolution of data available at present, the observed variability in the small scale structure cannot account for the coroal heating of the quiet sun. The characteristics of their emission are more likely to be an indicator of the coronal heating mechanisms.

Spatial and temporal characterizations of water quality in Kuwait Bay.

PubMed

Al-Mutairi, N; Abahussain, A; El-Battay, A

2014-06-15

The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay's coast as well as from Shatt Al-Arab River. Copyright © 2014 Elsevier Ltd. All rights reserved.

Links between global meat trade and organic river pollution

NASA Astrophysics Data System (ADS)

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-04-01

Rising demand of meat boosts livestock farming intensification. Due to international meat trade, the environmental costs of production are becoming increasingly separated from where the meat is consumed. However, little is known about the impact of trade on the environment for both importers and exporters. Combining multi-scale (national, regional and gridded) data, we present a new method to quantify the impacts of international meat trade on global river organic pollution. We computed spatially distributed organic pollution in global river networks with and without meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis indicates high potential savings of livestock population and pollutants production at the global scale due to the international meat trade. The spatially detailed analysis shows that current trade contributes to organic pollution reductions in meat importing regions, especially in rich nations. The deterioration of river water quality, especially in developing regions, points to an urgent need for affordable infrastructure and technology development and wastewater solutions.

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.

Structure analysis of turbulent liquid phase by POD and LSE techniques

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

Munir, S., E-mail: shahzad-munir@comsats.edu.pk; Muthuvalu, M. S.; Siddiqui, M. I.

2014-10-24

In this paper, vortical structures and turbulence characteristics of liquid phase in both single liquid phase and two-phase slug flow in pipes were studied. Two dimensional velocity vector fields of liquid phase were obtained by Particle image velocimetry (PIV). Two cases were considered one single phase liquid flow at 80 l/m and second slug flow by introducing gas at 60 l/m while keeping liquid flow rate same. Proper orthogonal decomposition (POD) and Linear stochastic estimation techniques were used for the extraction of coherent structures and analysis of turbulence in liquid phase for both cases. POD has successfully revealed large energymore » containing structures. The time dependent POD spatial mode coefficients oscillate with high frequency for high mode numbers. The energy distribution of spatial modes was also achieved. LSE has pointed out the coherent structured for both cases and the reconstructed velocity fields are in well agreement with the instantaneous velocity fields.« less

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.