Sample records for spatial point process
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Modeling fixation locations using spatial point processes.
Barthelmé, Simon; Trukenbrod, Hans; Engbert, Ralf; Wichmann, Felix
2013-10-01
Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.
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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.
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Development and evaluation of spatial point process models for epidermal nerve fibers.
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.
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Analysis of Spatial Point Patterns in Nuclear Biology
Weston, David J.; Adams, Niall M.; Russell, Richard A.; Stephens, David A.; Freemont, Paul S.
2012-01-01
There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells. PMID:22615822
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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)...
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Marked point process for modelling seismic activity (case study in Sumatra and Java)
NASA Astrophysics Data System (ADS)
Pratiwi, Hasih; Sulistya Rini, Lia; Wayan Mangku, I.
2018-05-01
Earthquake is a natural phenomenon that is random, irregular in space and time. Until now the forecast of earthquake occurrence at a location is still difficult to be estimated so that the development of earthquake forecast methodology is still carried out both from seismology aspect and stochastic aspect. To explain the random nature phenomena, both in space and time, a point process approach can be used. There are two types of point processes: temporal point process and spatial point process. The temporal point process relates to events observed over time as a sequence of time, whereas the spatial point process describes the location of objects in two or three dimensional spaces. The points on the point process can be labelled with additional information called marks. A marked point process can be considered as a pair (x, m) where x is the point of location and m is the mark attached to the point of that location. This study aims to model marked point process indexed by time on earthquake data in Sumatra Island and Java Island. This model can be used to analyse seismic activity through its intensity function by considering the history process up to time before t. Based on data obtained from U.S. Geological Survey from 1973 to 2017 with magnitude threshold 5, we obtained maximum likelihood estimate for parameters of the intensity function. The estimation of model parameters shows that the seismic activity in Sumatra Island is greater than Java Island.
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Liu, Mei-bing; Chen, Xing-wei; Chen, Ying
2015-07-01
Identification of the critical source areas of non-point source pollution is an important means to control the non-point source pollution within the watershed. In order to further reveal the impact of multiple time scales on the spatial differentiation characteristics of non-point source nitrogen loss, a SWAT model of Shanmei Reservoir watershed was developed. Based on the simulation of total nitrogen (TN) loss intensity of all 38 subbasins, spatial distribution characteristics of nitrogen loss and critical source areas were analyzed at three time scales of yearly average, monthly average and rainstorms flood process, respectively. Furthermore, multiple linear correlation analysis was conducted to analyze the contribution of natural environment and anthropogenic disturbance on nitrogen loss. The results showed that there were significant spatial differences of TN loss in Shanmei Reservoir watershed at different time scales, and the spatial differentiation degree of nitrogen loss was in the order of monthly average > yearly average > rainstorms flood process. TN loss load mainly came from upland Taoxi subbasin, which was identified as the critical source area. At different time scales, land use types (such as farmland and forest) were always the dominant factor affecting the spatial distribution of nitrogen loss, while the effect of precipitation and runoff on the nitrogen loss was only taken in no fertilization month and several processes of storm flood at no fertilization date. This was mainly due to the significant spatial variation of land use and fertilization, as well as the low spatial variability of precipitation and runoff.
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High-Dimensional Bayesian Geostatistics
Banerjee, Sudipto
2017-01-01
With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as “priors” for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has ~ n floating point operations (flops), where n the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings. PMID:29391920
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High-Dimensional Bayesian Geostatistics.
Banerjee, Sudipto
2017-06-01
With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as "priors" for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has ~ n floating point operations (flops), where n the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings.
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Point pattern analysis applied to flood and landslide damage events in Switzerland (1972-2009)
NASA Astrophysics Data System (ADS)
Barbería, Laura; Schulte, Lothar; Carvalho, Filipe; Peña, Juan Carlos
2017-04-01
Damage caused by meteorological and hydrological extreme events depends on many factors, not only on hazard, but also on exposure and vulnerability. In order to reach a better understanding of the relation of these complex factors, their spatial pattern and underlying processes, the spatial dependency between values of damage recorded at sites of different distances can be investigated by point pattern analysis. For the Swiss flood and landslide damage database (1972-2009) first steps of point pattern analysis have been carried out. The most severe events have been selected (severe, very severe and catastrophic, according to GEES classification, a total number of 784 damage points) and Ripley's K-test and L-test have been performed, amongst others. For this purpose, R's library spatstat has been used. The results confirm that the damage points present a statistically significant clustered pattern, which could be connected to prevalence of damages near watercourses and also to rainfall distribution of each event, together with other factors. On the other hand, bivariate analysis shows there is no segregated pattern depending on process type: flood/debris flow vs landslide. This close relation points to a coupling between slope and fluvial processes, connectivity between small-size and middle-size catchments and the influence of spatial distribution of precipitation, temperature (snow melt and snow line) and other predisposing factors such as soil moisture, land-cover and environmental conditions. Therefore, further studies will investigate the relationship between the spatial pattern and one or more covariates, such as elevation, distance from watercourse or land use. The final goal will be to perform a regression model to the data, so that the adjusted model predicts the intensity of the point process as a function of the above mentioned covariates.
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Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates
NASA Astrophysics Data System (ADS)
Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.
2016-10-01
Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.
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NASA Astrophysics Data System (ADS)
Rohmer, J.; Dewez, D.
2014-09-01
Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a cliff face. Yet, this spatial organisation carries essential information about the external processes and the environmental conditions that promote or initiate sea-cliff instabilities. In this article, we use summary statistics of spatial point process theory as a tool to examine the spatial and temporal pattern of a rockfall inventory recorded with repeated terrestrial laser scanning surveys at the chalk coastal cliff site of Mesnil-Val (Normandy, France). Results show that: (1) the spatial density of erosion scars is specifically conditioned alongshore by the distance to an engineered concrete groin, with an exponential-like decreasing trend, and vertically focused both at wave breaker height and on strong lithological contrasts; (2) small erosion scars (10-3-10-2 m3) aggregate in clusters within a radius of 5 to 10 m, which suggests some sort of attraction or focused causative process, and disperse above this critical distance; (3) on the contrary, larger erosion scars (10-2-101 m3) tend to disperse above a radius of 1 to 5 m, possibly due to the spreading of successive failures across the cliff face; (4) large scars significantly occur albeit moderately, where previous large rockfalls have occurred during preceeding winter; (5) this temporal trend is not apparent for small events. In conclusion, this study shows, with a worked example, how spatial point process summary statistics are a tool to test and quantify the significance of geomorphological observation organisation.
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NASA Astrophysics Data System (ADS)
Rohmer, J.; Dewez, T.
2015-02-01
Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a cliff face. Yet, this spatial organisation carries essential information about the external processes and the environmental conditions that promote or initiate sea-cliff instabilities. In this article, we use summary statistics of spatial point process theory as a tool to examine the spatial and temporal pattern of a rockfall inventory recorded with repeated terrestrial laser scanning surveys at the chalk coastal cliff site of Mesnil-Val (Normandy, France). Results show that: (1) the spatial density of erosion scars is specifically conditioned alongshore by the distance to an engineered concrete groyne, with an exponential-like decreasing trend, and vertically focused both at wave breaker height and on strong lithological contrasts; (2) small erosion scars (10-3 to 10-2 m3) aggregate in clusters within a radius of 5 to 10 m, which suggests some sort of attraction or focused causative process, and disperse above this critical distance; (3) on the contrary, larger erosion scars (10-2 to 101 m3) tend to disperse above a radius of 1 to 5 m, possibly due to the spreading of successive failures across the cliff face; (4) large scars significantly occur albeit moderately, where previous large rockfalls have occurred during preceding winter; (5) this temporal trend is not apparent for small events. In conclusion, this study shows, with a worked example, how spatial point process summary statistics are a tool to test and quantify the significance of geomorphological observation organisation.
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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.
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Detecting determinism from point processes.
Andrzejak, Ralph G; Mormann, Florian; Kreuz, Thomas
2014-12-01
The detection of a nonrandom structure from experimental data can be crucial for the classification, understanding, and interpretation of the generating process. We here introduce a rank-based nonlinear predictability score to detect determinism from point process data. Thanks to its modular nature, this approach can be adapted to whatever signature in the data one considers indicative of deterministic structure. After validating our approach using point process signals from deterministic and stochastic model dynamics, we show an application to neuronal spike trains recorded in the brain of an epilepsy patient. While we illustrate our approach in the context of temporal point processes, it can be readily applied to spatial point processes as well.
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Spatial perspectives in state-and-transition models: A missing link to land management?
USDA-ARS?s Scientific Manuscript database
Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...
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Performance analysis of a dual-tree algorithm for computing spatial distance histograms
Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni
2011-01-01
Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753
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Spectrum of classes of point emitters of electromagnetic wave fields.
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.
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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...
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Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.
Renner, Ian W; Warton, David I
2013-03-01
Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.
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NASA Astrophysics Data System (ADS)
Sefton-Nash, E.; Williams, J.-P.; Greenhagen, B. T.; Aye, K.-M.; Paige, D. A.
2017-12-01
An approach is presented to efficiently produce high quality gridded data records from the large, global point-based dataset returned by the Diviner Lunar Radiometer Experiment aboard NASA's Lunar Reconnaissance Orbiter. The need to minimize data volume and processing time in production of science-ready map products is increasingly important with the growth in data volume of planetary datasets. Diviner makes on average >1400 observations per second of radiance that is reflected and emitted from the lunar surface, using 189 detectors divided into 9 spectral channels. Data management and processing bottlenecks are amplified by modeling every observation as a probability distribution function over the field of view, which can increase the required processing time by 2-3 orders of magnitude. Geometric corrections, such as projection of data points onto a digital elevation model, are numerically intensive and therefore it is desirable to perform them only once. Our approach reduces bottlenecks through parallel binning and efficient storage of a pre-processed database of observations. Database construction is via subdivision of a geodesic icosahedral grid, with a spatial resolution that can be tailored to suit the field of view of the observing instrument. Global geodesic grids with high spatial resolution are normally impractically memory intensive. We therefore demonstrate a minimum storage and highly parallel method to bin very large numbers of data points onto such a grid. A database of the pre-processed and binned points is then used for production of mapped data products that is significantly faster than if unprocessed points were used. We explore quality controls in the production of gridded data records by conditional interpolation, allowed only where data density is sufficient. The resultant effects on the spatial continuity and uncertainty in maps of lunar brightness temperatures is illustrated. We identify four binning regimes based on trades between the spatial resolution of the grid, the size of the FOV and the on-target spacing of observations. Our approach may be applicable and beneficial for many existing and future point-based planetary datasets.
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Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis
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
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Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.
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.
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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.
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Spatial pattern analysis of Cu, Zn and Ni and their interpretation in the Campania region (Italy)
NASA Astrophysics Data System (ADS)
Petrik, Attila; Albanese, Stefano; Jordan, Gyozo; Rolandi, Roberto; De Vivo, Benedetto
2017-04-01
The uniquely abundant Campanian topsoil dataset enabled us to perform a spatial pattern analysis on 3 potentially toxic elements of Cu, Zn and Ni. This study is focusing on revealing the spatial texture and distribution of these elements by spatial point pattern and image processing analysis such as lineament density and spatial variability index calculation. The application of these methods on geochemical data provides a new and efficient tool to understand the spatial variation of concentrations and their background/baseline values. The determination and quantification of spatial variability is crucial to understand how fast the change in concentration is in a certain area and what processes might govern the variation. The spatial variability index calculation and image processing analysis including lineament density enables us to delineate homogenous areas and analyse them with respect to lithology and land use. Identification of spatial outliers and their patterns were also investigated by local spatial autocorrelation and image processing analysis including the determination of local minima and maxima points and singularity index analysis. The spatial variability of Cu and Zn reveals the highest zone (Cu: 0.5 MAD, Zn: 0.8-0.9 MAD, Median Deviation Index) along the coast between Campi Flegrei and the Sorrento Peninsula with the vast majority of statistically identified outliers and high-high spatial clustered points. The background/baseline maps of Cu and Zn reveals a moderate to high variability (Cu: 0.3 MAD, Zn: 0.4-0.5 MAD) NW-SE oriented zone including disrupted patches from Bisaccia to Mignano following the alluvial plains of Appenine's rivers. This zone has high abundance of anomaly concentrations identified using singularity analysis and it also has a high density of lineaments. The spatial variability of Ni shows the highest variability zone (0.6-0.7 MAD) around Campi Flegrei where the majority of low outliers are concentrated. The variability of background/baseline map of Ni reveals a shift to the east in case of highest variability zones coinciding with limestone outcrops. The high segmented area between Mignano and Bisaccia partially follows the alluvial plains of Appenine's rivers which seem to be playing a crucial role in the distribution and redistribution pattern of Cu, Zn and Ni in Campania. The high spatial variability zones of the later elements are located in topsoils on volcanoclastic rocks and are mostly related to cultivation and urbanised areas.
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Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.
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.
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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,
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Estimation of Traffic Variables Using Point Processing Techniques
DOT National Transportation Integrated Search
1978-05-01
An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting...
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Dermol, Urška; Kontić, Branko
2011-01-01
The benefits of strategic environmental considerations in the process of siting a repository for low- and intermediate-level radioactive waste (LILW) are presented. The benefits have been explored by analyzing differences between the two site selection processes. One is a so-called official site selection process, which is implemented by the Agency for radwaste management (ARAO); the other is an optimization process suggested by experts working in the area of environmental impact assessment (EIA) and land-use (spatial) planning. The criteria on which the comparison of the results of the two site selection processes has been based are spatial organization, environmental impact, safety in terms of potential exposure of the population to radioactivity released from the repository, and feasibility of the repository from the technical, financial/economic and social point of view (the latter relates to consent by the local community for siting the repository). The site selection processes have been compared with the support of the decision expert system named DEX. The results of the comparison indicate that the sites selected by ARAO meet fewer suitability criteria than those identified by applying strategic environmental considerations in the framework of the optimization process. This result stands when taking into account spatial, environmental, safety and technical feasibility points of view. Acceptability of a site by a local community could not have been tested, since the formal site selection process has not yet been concluded; this remains as an uncertain and open point of the comparison. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Spatial patterns of modern period human-caused fire occurrence in the Missouri Ozark Highlands
Jian Yang; Hong S. Healy; Stephen R. Shifley; Eric J. Gustafson
2007-01-01
The spatial pattern of forest fire locations is important in the study of the dynamics of fire disturbance. In this article we used a spatial point process modeling approach to quantitatively study the effects of land cover, topography, roads, municipalities, ownership, and population density on fire occurrence reported between 1970 and 2002 in the Missouri Ozark...
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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.
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Training site statistics from Landsat and Seasat satellite imagery registered to a common map base
NASA Technical Reports Server (NTRS)
Clark, J.
1981-01-01
Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.
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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
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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.
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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
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Entropy of Movement Outcome in Space-Time.
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.
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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.
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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.
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Monitoring urban subsidence based on SAR lnterferometric point target analysis
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.
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NASA Astrophysics Data System (ADS)
Li, Weiyao; Huang, Guanhua; Xiong, Yunwu
2016-04-01
The complexity of the spatial structure of porous media, randomness of groundwater recharge and discharge (rainfall, runoff, etc.) has led to groundwater movement complexity, physical and chemical interaction between groundwater and porous media cause solute transport in the medium more complicated. An appropriate method to describe the complexity of features is essential when study on solute transport and conversion in porous media. Information entropy could measure uncertainty and disorder, therefore we attempted to investigate complexity, explore the contact between the information entropy and complexity of solute transport in heterogeneous porous media using information entropy theory. Based on Markov theory, two-dimensional stochastic field of hydraulic conductivity (K) was generated by transition probability. Flow and solute transport model were established under four conditions (instantaneous point source, continuous point source, instantaneous line source and continuous line source). The spatial and temporal complexity of solute transport process was characterized and evaluated using spatial moment and information entropy. Results indicated that the entropy increased as the increase of complexity of solute transport process. For the point source, the one-dimensional entropy of solute concentration increased at first and then decreased along X and Y directions. As time increased, entropy peak value basically unchanged, peak position migrated along the flow direction (X direction) and approximately coincided with the centroid position. With the increase of time, spatial variability and complexity of solute concentration increase, which result in the increases of the second-order spatial moment and the two-dimensional entropy. Information entropy of line source was higher than point source. Solute entropy obtained from continuous input was higher than instantaneous input. Due to the increase of average length of lithoface, media continuity increased, flow and solute transport complexity weakened, and the corresponding information entropy also decreased. Longitudinal macro dispersivity declined slightly at early time then rose. Solute spatial and temporal distribution had significant impacts on the information entropy. Information entropy could reflect the change of solute distribution. Information entropy appears a tool to characterize the spatial and temporal complexity of solute migration and provides a reference for future research.
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Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten; Schüz, Joachim; Cardis, Elisabeth; Andersen, Per K
2015-10-15
We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial aggregation of a disease around a source of potential hazard in environmental epidemiology, where now the source is the preferred ear of each phone user. In this context, the spatial distribution is a distribution over a sample of patients rather than over multiple disease cases within one geographical area. We show how the distance relation between tumour and phone can be modelled nonparametrically and, with various parametric functions, how covariates can be included in the model and how to test for the effect of distance. To illustrate the models, we apply them to a subset of the data from the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use. Copyright © 2015 John Wiley & Sons, Ltd.
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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.
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Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models
Phillips, D.L.; Marks, D.G.
1996-01-01
In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.
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Stream Kriging: Incremental and recursive ordinary Kriging over spatiotemporal data streams
NASA Astrophysics Data System (ADS)
Zhong, Xu; Kealy, Allison; Duckham, Matt
2016-05-01
Ordinary Kriging is widely used for geospatial interpolation and estimation. Due to the O (n3) time complexity of solving the system of linear equations, ordinary Kriging for a large set of source points is computationally intensive. Conducting real-time Kriging interpolation over continuously varying spatiotemporal data streams can therefore be especially challenging. This paper develops and tests two new strategies for improving the performance of an ordinary Kriging interpolator adapted to a stream-processing environment. These strategies rely on the expectation that, over time, source data points will frequently refer to the same spatial locations (for example, where static sensor nodes are generating repeated observations of a dynamic field). First, an incremental strategy improves efficiency in cases where a relatively small proportion of previously processed spatial locations are absent from the source points at any given iteration. Second, a recursive strategy improves efficiency in cases where there is substantial set overlap between the sets of spatial locations of source points at the current and previous iterations. These two strategies are evaluated in terms of their computational efficiency in comparison to ordinary Kriging algorithm. The results show that these two strategies can reduce the time taken to perform the interpolation by up to 90%, and approach average-case time complexity of O (n2) when most but not all source points refer to the same locations over time. By combining the approaches developed in this paper with existing heuristic ordinary Kriging algorithms, the conclusions indicate how further efficiency gains could potentially be accrued. The work ultimately contributes to the development of online ordinary Kriging interpolation algorithms, capable of real-time spatial interpolation with large streaming data sets.
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Analyzing linear spatial features in ecology.
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.
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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.
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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.
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Research on photodiode detector-based spatial transient light detection and processing system
NASA Astrophysics Data System (ADS)
Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng
2016-10-01
In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.
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A Practical Decision-Analysis Process for Forest Ecosystem Management
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...
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Using a Virtual Experiment to Analyze Infiltration Process from Point to Grid-cell Size Scale
NASA Astrophysics Data System (ADS)
Barrios, M. I.
2013-12-01
The hydrological science requires the emergence of a consistent theoretical corpus driving the relationships between dominant physical processes at different spatial and temporal scales. However, the strong spatial heterogeneities and non-linearities of these processes make difficult the development of multiscale conceptualizations. Therefore, scaling understanding is a key issue to advance this science. This work is focused on the use of virtual experiments to address the scaling of vertical infiltration from a physically based model at point scale to a simplified physically meaningful modeling approach at grid-cell scale. Numerical simulations have the advantage of deal with a wide range of boundary and initial conditions against field experimentation. The aim of the work was to show the utility of numerical simulations to discover relationships between the hydrological parameters at both scales, and to use this synthetic experience as a media to teach the complex nature of this hydrological process. The Green-Ampt model was used to represent vertical infiltration at point scale; and a conceptual storage model was employed to simulate the infiltration process at the grid-cell scale. Lognormal and beta probability distribution functions were assumed to represent the heterogeneity of soil hydraulic parameters at point scale. The linkages between point scale parameters and the grid-cell scale parameters were established by inverse simulations based on the mass balance equation and the averaging of the flow at the point scale. Results have shown numerical stability issues for particular conditions and have revealed the complex nature of the non-linear relationships between models' parameters at both scales and indicate that the parameterization of point scale processes at the coarser scale is governed by the amplification of non-linear effects. The findings of these simulations have been used by the students to identify potential research questions on scale issues. Moreover, the implementation of this virtual lab improved the ability to understand the rationale of these process and how to transfer the mathematical models to computational representations.
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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.
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Preferential sampling and Bayesian geostatistics: Statistical modeling and examples.
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.
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Follow your nose: Implicit spatial processing within the chemosensory systems.
Wudarczyk, Olga A; Habel, Ute; Turetsky, Bruce I; Gur, Raquel E; Kellermann, Thilo; Schneider, Frank; Moessnang, Carolin
2016-11-01
Although most studies agree that humans cannot smell in stereo, it was recently suggested that olfactory localization is possible when assessed implicitly. In a spatial cueing paradigm, lateralized olfactory cues impaired the detection of congruently presented visual targets, an effect contrary to the typical facilitation observed in other sensory domains. Here, we examined the specificity and the robustness of this finding by studying implicit localization abilities in another chemosensory system and by accounting for possible confounds in a modified paradigm. Sixty participants completed a spatial cueing task along with an explicit localization task, using trigeminal (Experiment 1) and olfactory (Experiment 2) stimuli. A control task was implemented to control for residual somatosensory stimulation (Experiment 3). In the trigeminal experiment, stimuli were localized with high accuracy on the explicit level, while the cueing effect in form of facilitation was limited to response accuracy. In the olfactory experiment, responses were slowed by congruent cues on the implicit level, while no explicit localization was observed. Our results point to the robustness of the olfactory interference effect, corroborating the implicit-explicit dissociation of olfactory localization, and challenging the view that humans lost the ability to extract spatial information from smell. The absence of a similar interference for trigeminal cues suggests distinct implicit spatial processing mechanisms within the chemosensory systems. Moreover, the lack of a typical facilitation effect in the trigeminal domain points to important differences from spatial information processing in other, nonchemosensory domains. The possible mechanisms driving the effects are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Full-frame, programmable hyperspectral imager
DOE Office of Scientific and Technical Information (OSTI.GOV)
Love, Steven P.; Graff, David L.
A programmable, many-band spectral imager based on addressable spatial light modulators (ASLMs), such as micro-mirror-, micro-shutter- or liquid-crystal arrays, is described. Capable of collecting at once, without scanning, a complete two-dimensional spatial image with ASLM spectral processing applied simultaneously to the entire image, the invention employs optical assemblies wherein light from all image points is forced to impinge at the same angle onto the dispersing element, eliminating interplay between spatial position and wavelength. This is achieved, as examples, using telecentric optics to image light at the required constant angle, or with micro-optical array structures, such as micro-lens- or capillary arrays,more » that aim the light on a pixel-by-pixel basis. Light of a given wavelength then emerges from the disperser at the same angle for all image points, is collected at a unique location for simultaneous manipulation by the ASLM, then recombined with other wavelengths to form a final spectrally-processed image.« less
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Statistical characterization of spatial patterns of rainfall cells in extratropical cyclones
NASA Astrophysics Data System (ADS)
Bacchi, Baldassare; Ranzi, Roberto; Borga, Marco
1996-11-01
The assumption of a particular type of distribution of rainfall cells in space is needed for the formulation of several space-time rainfall models. In this study, weather radar-derived rain rate maps are employed to evaluate different types of spatial organization of rainfall cells in storms through the use of distance functions and second-moment measures. In particular the spatial point patterns of the local maxima of rainfall intensity are compared to a completely spatially random (CSR) point process by applying an objective distance measure. For all the analyzed radar maps the CSR assumption is rejected, indicating that at the resolution of the observation considered, rainfall cells are clustered. Therefore a theoretical framework for evaluating and fitting alternative models to the CSR is needed. This paper shows how the "reduced second-moment measure" of the point pattern can be employed to estimate the parameters of a Neyman-Scott model and to evaluate the degree of adequacy to the experimental data. Some limitations of this theoretical framework, and also its effectiveness, in comparison to the use of scaling functions, are discussed.
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Focal Points, Endogenous Processes, and Exogenous Shocks in the Autism Epidemic
ERIC Educational Resources Information Center
Liu, Kayuet; Bearman, Peter S.
2015-01-01
Autism prevalence has increased rapidly in the United States during the past two decades. We have previously shown that the diffusion of information about autism through spatially proximate social relations has contributed significantly to the epidemic. This study expands on this finding by identifying the focal points for interaction that drive…
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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.
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NASA Astrophysics Data System (ADS)
Niwase, Hiroaki; Takada, Naoki; Araki, Hiromitsu; Maeda, Yuki; Fujiwara, Masato; Nakayama, Hirotaka; Kakue, Takashi; Shimobaba, Tomoyoshi; Ito, Tomoyoshi
2016-09-01
Parallel calculations of large-pixel-count computer-generated holograms (CGHs) are suitable for multiple-graphics processing unit (multi-GPU) cluster systems. However, it is not easy for a multi-GPU cluster system to accomplish fast CGH calculations when CGH transfers between PCs are required. In these cases, the CGH transfer between the PCs becomes a bottleneck. Usually, this problem occurs only in multi-GPU cluster systems with a single spatial light modulator. To overcome this problem, we propose a simple method using the InfiniBand network. The computational speed of the proposed method using 13 GPUs (NVIDIA GeForce GTX TITAN X) was more than 3000 times faster than that of a CPU (Intel Core i7 4770) when the number of three-dimensional (3-D) object points exceeded 20,480. In practice, we achieved ˜40 tera floating point operations per second (TFLOPS) when the number of 3-D object points exceeded 40,960. Our proposed method was able to reconstruct a real-time movie of a 3-D object comprising 95,949 points.
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Cultural differences in room size perception
Bülthoff, Heinrich H.; de la Rosa, Stephan; Dodds, Trevor J.
2017-01-01
Cultural differences in spatial perception have been little investigated, which gives rise to the impression that spatial cognitive processes might be universal. Contrary to this idea, we demonstrate cultural differences in spatial volume perception of computer generated rooms between Germans and South Koreans. We used a psychophysical task in which participants had to judge whether a rectangular room was larger or smaller than a square room of reference. We systematically varied the room rectangularity (depth to width aspect ratio) and the viewpoint (middle of the short wall vs. long wall) from which the room was viewed. South Koreans were significantly less biased by room rectangularity and viewpoint than their German counterparts. These results are in line with previous notions of general cognitive processing strategies being more context dependent in East Asian societies than Western ones. We point to the necessity of considering culturally-specific cognitive processing strategies in visual spatial cognition research. PMID:28426729
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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).
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Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.
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.
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The hippocampus and visual perception
Lee, Andy C. H.; Yeung, Lok-Kin; Barense, Morgan D.
2012-01-01
In this review, we will discuss the idea that the hippocampus may be involved in both memory and perception, contrary to theories that posit functional and neuroanatomical segregation of these processes. This suggestion is based on a number of recent neuropsychological and functional neuroimaging studies that have demonstrated that the hippocampus is involved in the visual discrimination of complex spatial scene stimuli. We argue that these findings cannot be explained by long-term memory or working memory processing or, in the case of patient findings, dysfunction beyond the medial temporal lobe (MTL). Instead, these studies point toward a role for the hippocampus in higher-order spatial perception. We suggest that the hippocampus processes complex conjunctions of spatial features, and that it may be more appropriate to consider the representations for which this structure is critical, rather than the cognitive processes that it mediates. PMID:22529794
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Self-Exciting Point Process Models of Civilian Deaths in Iraq
2010-01-01
Tita , 2009), we propose that violence in Iraq arises from a combination of exogenous and en- dogenous effects. Spatial heterogeneity in background...Schoenberg, and Tita (2010) where they analyze burgarly and robbery data in Los Angeles. Related work has also been done 2 in Short et al. (2009) where...Control , 4 , 215–240. Mohler, G. O., Short, M. B., Brantingham, P. J., Schoenberg, F. P., & Tita , G. E. (2010). Self- exciting point process modeling of
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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.
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Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets.
Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O; Gelfand, Alan E
2016-01-01
Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online.
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Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets
Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O.; Gelfand, Alan E.
2018-01-01
Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online. PMID:29720777
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Film characteristics pertinent to coherent optical data processing systems.
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.
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The application of prototype point processes for the summary and description of California wildfires
Nichols, K.; Schoenberg, F.P.; Keeley, J.E.; Bray, A.; Diez, D.
2011-01-01
A method for summarizing repeated realizations of a space-time marked point process, known as prototyping, is discussed and applied to catalogues of wildfires in California. Prototype summaries are constructed for varying time intervals using California wildfire data from 1990 to 2006. Previous work on prototypes for temporal and space-time point processes is extended here to include methods for computing prototypes with marks and the incorporation of prototype summaries into hierarchical clustering algorithms, the latter of which is used to delineate fire seasons in California. Other results include summaries of patterns in the spatial-temporal distribution of wildfires within each wildfire season. ?? 2011 Blackwell Publishing Ltd.
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Advanced analysis of forest fire clustering
NASA Astrophysics Data System (ADS)
Kanevski, Mikhail; Pereira, Mario; Golay, Jean
2017-04-01
Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.
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Spatially explicit models for inference about density in unmarked or partially marked populations
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.
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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
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Focal Points, Endogenous Processes, and Exogenous Shocks in the Autism Epidemic
Liu, Kayuet; Bearman, Peter S.
2014-01-01
Autism prevalence has increased rapidly in the United States during the past two decades. We have previously shown that the diffusion of information about autism through spatially proximate social relations has contributed significantly to the epidemic. This study expands on this finding by identifying the focal points for interaction that drive the proximity effect on subsequent diagnoses. We then consider how diffusion dynamics through interaction at critical focal points, in tandem with exogenous shocks, could have shaped the spatial dynamics of autism in California. We achieve these goals through an empirically calibrated simulation model of the whole population of 3- to 9-year-olds in California. We show that in the absence of interaction at these foci—principally malls and schools—we would not observe an autism epidemic. We also explore the idea that epigenetic changes affecting one generation in the distal past could shape the precise spatial patterns we observe among the next generation. PMID:26166907
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NASA Astrophysics Data System (ADS)
Pappenberger, F.; Beven, K. J.; Frodsham, K.; Matgen, P.
2005-12-01
Flood inundation models play an increasingly important role in assessing flood risk. The growth of 2D inundation models that are intimately related to raster maps of floodplains is occurring at the same time as an increase in the availability of 2D remote data (e.g. SAR images and aerial photographs), against which model performancee can be evaluated. This requires new techniques to be explored in order to evaluate model performance in two dimensional space. In this paper we present a fuzzified pattern matching algorithm which compares favorably to a set of traditional measures. However, we further argue that model calibration has to go beyond the comparison of physical properties and should demonstrate how a weighting towards consequences, such as loss of property, can enhance model focus and prediction. Indeed, it will be necessary to abandon a fully spatial comparison in many scenarios to concentrate the model calibration exercise on specific points such as hospitals, police stations or emergency response centers. It can be shown that such point evaluations lead to significantly different flood hazard maps due to the averaging effect of a spatial performance measure. A strategy to balance the different needs (accuracy at certain spatial points and acceptable spatial performance) has to be based in a public and political decision making process.
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ERIC Educational Resources Information Center
Solan, Harold A.
1987-01-01
This study involving 38 normally achieving fourth and fifth grade children confirmed previous studies indicating that both spatial-simultaneous (in which perceived stimuli are totally available at one point in time) and verbal-successive (information is presented in serial order) cognitive processing are important in normal learning. (DB)
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Prism adaptation in alternately exposed hands.
Redding, Gordon M; Wallace, Benjamin
2013-08-01
We assessed intermanual transfer of the proprioceptive realignment aftereffects of prism adaptation in right-handers by examining alternate target pointing with the two hands for 40 successive trials, 20 with each hand. Adaptation for the right hand was not different as a function of exposure sequence order or postexposure test order, in contrast with adaptation for the left hand. Adaptation was greater for the left hand when the right hand started the alternate pointing than when the sequence of target-pointing movements started with the left hand. Also, the largest left-hand adaptation appeared when that hand was tested first after exposure. Terminal error during exposure varied in cycles for the two hands, converging on zero when the right hand led, but no difference appeared between the two hands when the left hand led. These results suggest that transfer of proprioceptive realignment occurs from the right to the left hand during both exposure and postexposure testing. Such transfer reflects the process of maintaining spatial alignment between the two hands. Normally, the left hand appears to be calibrated with the right-hand spatial map, and when the two hands are misaligned, the left-hand spatial map is realigned with the right-hand spatial map.
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Integration agent-based models and GIS as a virtual urban dynamic laboratory
NASA Astrophysics Data System (ADS)
Chen, Peng; Liu, Miaolong
2007-06-01
Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.
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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.
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Spatially Enabling the Health Sector
Weeramanthri, Tarun Stephen; Woodgate, Peter
2016-01-01
Spatial information describes the physical location of either people or objects, and the measured relationships between them. In this article, we offer the view that greater utilization of spatial information and its related technology, as part of a broader redesign of the architecture of health information at local and national levels, could assist and speed up the process of health reform, which is taking place across the globe in richer and poorer countries alike. In making this point, we describe the impetus for health sector reform, recent developments in spatial information and analytics, and current Australasian spatial health research. We highlight examples of uptake of spatial information by the health sector, as well as missed opportunities. Our recommendations to spatially enable the health sector are applicable to high- and low-resource settings. PMID:27867933
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Spatially Enabling the Health Sector.
Weeramanthri, Tarun Stephen; Woodgate, Peter
2016-01-01
Spatial information describes the physical location of either people or objects, and the measured relationships between them. In this article, we offer the view that greater utilization of spatial information and its related technology, as part of a broader redesign of the architecture of health information at local and national levels, could assist and speed up the process of health reform, which is taking place across the globe in richer and poorer countries alike. In making this point, we describe the impetus for health sector reform, recent developments in spatial information and analytics, and current Australasian spatial health research. We highlight examples of uptake of spatial information by the health sector, as well as missed opportunities. Our recommendations to spatially enable the health sector are applicable to high- and low-resource settings.
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Calibration of stereo rigs based on the backward projection process
NASA Astrophysics Data System (ADS)
Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui; Zhao, Zixin
2016-08-01
High-accuracy 3D measurement based on binocular vision system is heavily dependent on the accurate calibration of two rigidly-fixed cameras. In most traditional calibration methods, stereo parameters are iteratively optimized through the forward imaging process (FIP). However, the results can only guarantee the minimal 2D pixel errors, but not the minimal 3D reconstruction errors. To address this problem, a simple method to calibrate a stereo rig based on the backward projection process (BPP) is proposed. The position of a spatial point can be determined separately from each camera by planar constraints provided by the planar pattern target. Then combined with pre-defined spatial points, intrinsic and extrinsic parameters of the stereo-rig can be optimized by minimizing the total 3D errors of both left and right cameras. An extensive performance study for the method in the presence of image noise and lens distortions is implemented. Experiments conducted on synthetic and real data demonstrate the accuracy and robustness of the proposed method.
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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
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High level language-based robotic control system
NASA Technical Reports Server (NTRS)
Rodriguez, Guillermo (Inventor); Kruetz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)
1994-01-01
This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.
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High level language-based robotic control system
NASA Technical Reports Server (NTRS)
Rodriguez, Guillermo (Inventor); Kreutz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)
1996-01-01
This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.
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Web Service for Positional Quality Assessment: the Wps Tier
NASA Astrophysics Data System (ADS)
Xavier, E. M. A.; Ariza-López, F. J.; Ureña-Cámara, M. A.
2015-08-01
In the field of spatial data every day we have more and more information available, but we still have little or very little information about the quality of spatial data. We consider that the automation of the spatial data quality assessment is a true need for the geomatic sector, and that automation is possible by means of web processing services (WPS), and the application of specific assessment procedures. In this paper we propose and develop a WPS tier centered on the automation of the positional quality assessment. An experiment using the NSSDA positional accuracy method is presented. The experiment involves the uploading by the client of two datasets (reference and evaluation data). The processing is to determine homologous pairs of points (by distance) and calculate the value of positional accuracy under the NSSDA standard. The process generates a small report that is sent to the client. From our experiment, we reached some conclusions on the advantages and disadvantages of WPSs when applied to the automation of spatial data accuracy assessments.
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How number-space relationships are assessed before formal schooling: A taxonomy proposal
Patro, Katarzyna; Nuerk, Hans-Christoph; Cress, Ulrike; Haman, Maciej
2014-01-01
The last years of research on numerical development have provided evidence that spatial-numerical associations (SNA) can be formed independent of formal school training. However, most of these studies used various experimental paradigms that referred to slightly different aspects of number and space processing. This poses a question of whether all SNAs described in the developmental literature can be interpreted as a unitary construct, or whether they are rather examples of different, but related phenomena. Our review aims to provide a starting point for a systematic classification of SNA measures used from infancy to late preschool years, and their underlying representations. We propose to distinguish among four basic SNA categories: (i) cross-dimensional magnitude processing, (ii) associations between spatial and numerical intervals, (iii) associations between cardinalities and spatial directions, (iv) associations between ordinalities and spatial directions. Such systematization allows for identifying similarities and differences between processes and representations that underlie the described measures, and also for assessing the adequacy of using different SNA tasks at different developmental stages. PMID:24860532
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Zhang, Xue-Lei; Feng, Wan-Wan; Zhong, Guo-Min
2011-01-01
A GIS-based 500 m x 500 m soil sampling point arrangement was set on 248 points at Wenshu Town of Yuzhou County in central Henan Province, where the typical Ustic Cambosols locates. By using soil digital data, the spatial database was established, from which, all the needed latitude and longitude data of the sampling points were produced for the field GPS guide. Soil samples (0-20 cm) were collected from 202 points, of which, bulk density measurement were conducted for randomly selected 34 points, and the ten soil property items used as the factors for soil quality assessment, including organic matter, available K, available P, pH, total N, total P, soil texture, cation exchange capacity (CEC), slowly available K, and bulk density, were analyzed for the other points. The soil property items were checked by statistic tools, and then, classified with standard criteria at home and abroad. The factor weight was given by analytic hierarchy process (AHP) method, and the spatial variation of the major 10 soil properties as well as the soil quality classes and their occupied areas were worked out by Kriging interpolation maps. The results showed that the arable Ustic Cambosols in study area was of good quality soil, over 95% of which ranked in good and medium classes and only less than 5% were in poor class.
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Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach
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
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hammond, Glenn Edward; Song, Xuehang; Ye, Ming
A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less
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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.
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Blind deconvolution post-processing of images corrected by adaptive optics
NASA Astrophysics Data System (ADS)
Christou, Julian C.
1995-08-01
Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.
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Statistical and Spatial Analysis of Bathymetric Data for the St. Clair River, 1971-2007
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.
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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.
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Face perception in women with Turner syndrome and its underlying factors.
Anaki, David; Zadikov Mor, Tal; Gepstein, Vardit; Hochberg, Ze'ev
2016-09-01
Turner syndrome (TS) is a chromosomal condition that affects development in females. It is characterized by short stature, ovarian failure and other congenital malformations, due to a partial or complete absence of the sex chromosome. Women with TS frequently suffer from various physical and hormonal dysfunctions, along with impairments in visual-spatial processing and social cognition difficulties. Previous research has also shown difficulties in face and emotion perception. In the current study we examined two questions: First, whether women with TS, that are impaired in face perception, also suffer from deficits in face-specific processes. The second question was whether these face impairments in TS are related to visual-spatial perceptual dysfunctions exhibited by TS individuals, or to impaired social cognition skills. Twenty-six women with TS and 26 control participants were tested on various cognitive and psychological tests to assess visual-spatial perception, face and facial expression perception, and social cognition skills. Results show that women with TS were less accurate in face perception and facial expression processing, yet they exhibited normal face-specific processes (configural and holistic processing). They also showed difficulties in spatial perception and social cognition capacities. Additional analyses revealed that their face perception impairments were related to their deficits in visual-spatial processing. Thus, our results do not support the claim that the impairments in face processing observed in TS are related to difficulties in social cognition. Rather, our data point to the possibility that face perception difficulties in TS stem from visual-spatial impairments and may not be specific to faces. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Fractal analysis of multiscale spatial autocorrelation among point data
De Cola, L.
1991-01-01
The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Abere, Michael J.; Yalisove, Steven M.; Torralva, Ben
2016-04-11
The formation of high spatial frequency laser induced periodic surface structures (HSFL) with period <0.3 λ in GaAs after irradiation with femtosecond laser pulses in air is studied. We have identified a point defect generation mechanism that operates in a specific range of fluences in semiconductors between the band-gap closure and ultrafast-melt thresholds that produces vacancy/interstitial pairs. Stress relaxation, via diffusing defects, forms the 350–400 nm tall and ∼90 nm wide structures through a bifurcation process of lower spatial frequency surface structures. The resulting HSFL are predominately epitaxial single crystals and retain the original GaAs stoichiometry.
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Implementation of MPEG-2 encoder to multiprocessor system using multiple MVPs (TMS320C80)
NASA Astrophysics Data System (ADS)
Kim, HyungSun; Boo, Kenny; Chung, SeokWoo; Choi, Geon Y.; Lee, YongJin; Jeon, JaeHo; Park, Hyun Wook
1997-05-01
This paper presents the efficient algorithm mapping for the real-time MPEG-2 encoding on the KAIST image computing system (KICS), which has a parallel architecture using five multimedia video processors (MVPs). The MVP is a general purpose digital signal processor (DSP) of Texas Instrument. It combines one floating-point processor and four fixed- point DSPs on a single chip. The KICS uses the MVP as a primary processing element (PE). Two PEs form a cluster, and there are two processing clusters in the KICS. Real-time MPEG-2 encoder is implemented through the spatial and the functional partitioning strategies. Encoding process of spatially partitioned half of the video input frame is assigned to ne processing cluster. Two PEs perform the functionally partitioned MPEG-2 encoding tasks in the pipelined operation mode. One PE of a cluster carries out the transform coding part and the other performs the predictive coding part of the MPEG-2 encoding algorithm. One MVP among five MVPs is used for system control and interface with host computer. This paper introduces an implementation of the MPEG-2 algorithm with a parallel processing architecture.
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Development and validation of a short-lag spatial coherence theory for photoacoustic imaging
NASA Astrophysics Data System (ADS)
Graham, Michelle T.; Lediju Bell, Muyinatu A.
2018-02-01
We previously derived spatial coherence theory to be implemented for studying theoretical properties of ShortLag Spatial Coherence (SLSC) beamforming applied to photoacoustic images. In this paper, our newly derived theoretical equation is evaluated to generate SLSC images of a point target and a 1.2 mm diameter target and corresponding lateral profiles. We compared SLSC images simulated solely based on our theory to SLSC images created after beamforming acoustic channel data from k-Wave simulations of 1.2 mm-diameter disc target. This process was repeated for a point target and the full width at half the maximum signal amplitudes were measured to estimate the resolution of each imaging system. Resolution as a function of lag was comparable for the first 10% of the receive aperture (i.e., the short-lag region), after which resolution measurements diverged by a maximum of 1 mm between the two types of simulated images. These results indicate the potential for both simulation methods to be utilized as independent resources to study coherence-based photoacoustic beamformers when imaging point-like targets.
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Multiscale Structure of UXO Site Characterization: Spatial Estimation and Uncertainty Quantification
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ostrouchov, George; Doll, William E.; Beard, Les P.
2009-01-01
Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales. We describe a conceptual site characterization process, the dependence structures available at several scales, and consider their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale and propose a representation for site contamination intensity that takes full account of uncertainty,more » is flexible enough to answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation. The representation is based on point process spatial estimation methods that require modern computational resources for practical application. These methods have provisions for including prior and covariate information.« less
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Amako, Jun; Shinozaki, Yu
2016-07-11
We report on a dual-wavelength diffractive beam splitter designed for use in parallel laser processing. This novel optical element generates two beam arrays of different wavelengths and allows their overlap at the process points on a workpiece. To design the deep surface-relief profile of a splitter using a simulated annealing algorithm, we introduce a heuristic but practical scheme to determine the maximum depth and the number of quantization levels. The designed corrugations were fabricated in a photoresist by maskless grayscale exposure using a high-resolution spatial light modulator. We characterized the photoresist splitter, thereby validating the proposed beam-splitting concept.
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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.
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NASA Technical Reports Server (NTRS)
Wang, Xue-Wen; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Fernandes, Richard; Smith, David E. (Technical Monitor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes at the Southern Study Area (SSA) and Northern Study Area (NSA) Old Black Spruce (OBS) Tower Flux sites, supporting its research into point hydrological processes and the spatial variation of these processes. These data were collected during the 1994 and 1996 field campaigns. Data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the measurements of throughfall, which is the amount of precipitation that fell through the canopy. A nested spatial sampling plan was implemented to determine spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in ASCII text files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
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Strong, James Asa; Elliott, Michael
2017-03-15
The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process. Copyright © 2017 Elsevier Ltd. All rights reserved.
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BOREAS HYD-8 1996 Gravimetric Moss Moisture Data
NASA Technical Reports Server (NTRS)
Fernandes, Richard; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes that were collected at the southern study area-Old Black Spruce (SSA-OBS) Tower Flux site in 1996 to support its research into point hydrological processes and the spatial variation of these processes. Data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the gravimetric moss moisture measurements from July to August 1996. To collect these data, a nested spatial sampling plan was implemented to support research into spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in ASCII text files. The HYD-08 1996 gravimetric moss moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
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NASA Technical Reports Server (NTRS)
Lewis, Mark David (Inventor); Seal, Michael R. (Inventor); Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor)
2007-01-01
Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.
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NASA Technical Reports Server (NTRS)
Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor)
2004-01-01
Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.
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NASA Technical Reports Server (NTRS)
2001-01-01
DATASTAR, Inc., of Picayune, Miss., has taken NASA's award-winning Earth Resources Laboratory Applications (ELAS) software program and evolved it to the point that the company is now providing a unique, spatial imagery service over the Internet. ELAS was developed in the early 80's to process satellite and airborne sensor imagery data of the Earth's surface into readable and useable information. While there are several software packages on the market that allow the manipulation of spatial data into useable products, this is usually a laborious task. The new program, called the DATASTAR Image Processing Exploitation, or DIPX, Delivery Service, is a subscription service available over the Internet that takes the work out of the equation and provides normalized geo-spatial data in the form of decision products.
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Multiple Point Statistics algorithm based on direct sampling and multi-resolution images
NASA Astrophysics Data System (ADS)
Julien, S.; Renard, P.; Chugunova, T.
2017-12-01
Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.
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NASA Technical Reports Server (NTRS)
Miles, J. H.; Wasserbauer, C. A.; Krejsa, E. A.
1983-01-01
Pressure temperature cross spectra are necessary in predicting noise propagation in regions of velocity gradients downstream of combustors if the effect of convective entropy disturbances is included. Pressure temperature cross spectra and coherences were measured at spatially separated points in a combustion rig fueled with hydrogen. Temperature-temperature and pressure-pressure cross spectra and coherences between the spatially separated points as well as temperature and pressure autospectra were measured. These test results were compared with previous results obtained in the same combustion rig using Jet A fuel in order to investigate their dependence on the type of combustion process. The phase relationships are not consistent with a simple source model that assumes that pressure and temperature are in phase at a point in the combustor and at all other points downstream are related to one another by only a time delay due to convection of temperature disturbances. Thus these test results indicate that a more complex model of the source is required.
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NASA Technical Reports Server (NTRS)
Tom, C.; Miller, L. D.; Christenson, J. W.
1978-01-01
A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.
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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.
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The VLITE Post-Processing Pipeline
NASA Astrophysics Data System (ADS)
Richards, Emily E.; Clarke, Tracy; Peters, Wendy; Polisensky, Emil; Kassim, Namir E.
2018-01-01
A post-processing pipeline to adaptively extract and catalog point sources is being developed to enhance the scientific value and accessibility of data products generated by the VLA Low-band Ionosphere and Transient Experiment (VLITE;
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A Data Cleaning Method for Big Trace Data Using Movement Consistency
Tang, Luliang; Zhang, Xia; Li, Qingquan
2018-01-01
Given the popularization of GPS technologies, the massive amount of spatiotemporal GPS traces collected by vehicles are becoming a new kind of big data source for urban geographic information extraction. The growing volume of the dataset, however, creates processing and management difficulties, while the low quality generates uncertainties when investigating human activities. Based on the conception of the error distribution law and position accuracy of the GPS data, we propose in this paper a data cleaning method for this kind of spatial big data using movement consistency. First, a trajectory is partitioned into a set of sub-trajectories using the movement characteristic points. In this process, GPS points indicate that the motion status of the vehicle has transformed from one state into another, and are regarded as the movement characteristic points. Then, GPS data are cleaned based on the similarities of GPS points and the movement consistency model of the sub-trajectory. The movement consistency model is built using the random sample consensus algorithm based on the high spatial consistency of high-quality GPS data. The proposed method is evaluated based on extensive experiments, using GPS trajectories generated by a sample of vehicles over a 7-day period in Wuhan city, China. The results show the effectiveness and efficiency of the proposed method. PMID:29522456
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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.
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Hierarchical species distribution models
Hefley, Trevor J.; Hooten, Mevin B.
2016-01-01
Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
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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.
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Data Processing and Quality Evaluation of a Boat-Based Mobile Laser Scanning System
Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri
2013-01-01
Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0–1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data. PMID:24048340
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Data processing and quality evaluation of a boat-based mobile laser scanning system.
Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri
2013-09-17
Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0-1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data.
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The Design of a High Performance Earth Imagery and Raster Data Management and Processing Platform
NASA Astrophysics Data System (ADS)
Xie, Qingyun
2016-06-01
This paper summarizes the general requirements and specific characteristics of both geospatial raster database management system and raster data processing platform from a domain-specific perspective as well as from a computing point of view. It also discusses the need of tight integration between the database system and the processing system. These requirements resulted in Oracle Spatial GeoRaster, a global scale and high performance earth imagery and raster data management and processing platform. The rationale, design, implementation, and benefits of Oracle Spatial GeoRaster are described. Basically, as a database management system, GeoRaster defines an integrated raster data model, supports image compression, data manipulation, general and spatial indices, content and context based queries and updates, versioning, concurrency, security, replication, standby, backup and recovery, multitenancy, and ETL. It provides high scalability using computer and storage clustering. As a raster data processing platform, GeoRaster provides basic operations, image processing, raster analytics, and data distribution featuring high performance computing (HPC). Specifically, HPC features include locality computing, concurrent processing, parallel processing, and in-memory computing. In addition, the APIs and the plug-in architecture are discussed.
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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.
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Accelerated high-resolution photoacoustic tomography via compressed sensing
NASA Astrophysics Data System (ADS)
Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward
2016-12-01
Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.
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Evaluation and testing of image quality of the Space Solar Extreme Ultraviolet Telescope
NASA Astrophysics Data System (ADS)
Peng, Jilong; Yi, Zhong; Zhou, Shuhong; Yu, Qian; Hou, Yinlong; Wang, Shanshan
2018-01-01
For the space solar extreme ultraviolet telescope, the star point test can not be performed in the x-ray band (19.5nm band) as there is not light source of bright enough. In this paper, the point spread function of the optical system is calculated to evaluate the imaging performance of the telescope system. Combined with the actual processing surface error, such as small grinding head processing and magnetorheological processing, the optical design software Zemax and data analysis software Matlab are used to directly calculate the system point spread function of the space solar extreme ultraviolet telescope. Matlab codes are programmed to generate the required surface error grid data. These surface error data is loaded to the specified surface of the telescope system by using the communication technique of DDE (Dynamic Data Exchange), which is used to connect Zemax and Matlab. As the different processing methods will lead to surface error with different size, distribution and spatial frequency, the impact of imaging is also different. Therefore, the characteristics of the surface error of different machining methods are studied. Combining with its position in the optical system and simulation its influence on the image quality, it is of great significance to reasonably choose the processing technology. Additionally, we have also analyzed the relationship between the surface error and the image quality evaluation. In order to ensure the final processing of the mirror to meet the requirements of the image quality, we should choose one or several methods to evaluate the surface error according to the different spatial frequency characteristics of the surface error.
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Datta, Kaberi; Basak, Trayambak; Varshney, Swati; Sengupta, Shantanu; Sarkar, Sagartirtha
2017-01-30
Myocardial infarction is one of the leading causes of cardiac dysfunction, failure and sudden death. Post infarction cardiac remodeling presents a poor prognosis, with 30%-45% of patients developing heart failure, in a period of 5-25years. Oxidative stress has been labelled as the primary causative factor for cardiac damage during infarction, however, the impact it may have during the process of post infarction remodeling has not been well probed. In this study, we have implemented iTRAQ proteomics to catalogue proteins and functional processes, participating both temporally (early and late phases) and spatially (infarct and remote zones), during post myocardial infarction remodeling of the heart as functions of the differential oxidative stress manifest during the remodeling process. Cardiac metabolism was the dominant network to be affected during infarction and the remodeling time points considered in this study. A distinctive expression pattern of cytoskeletal proteins was also observed with increased remodeling time points. Further, it was found that the cytoskeletal protein Desmin, aggregated in the infarct zone during the remodeling process, mediated by the protease Calpain1. Taken together, all of these data in conjunction may lay the foundation to understand the effects of oxidative stress on the remodeling process and elaborate the mechanism behind the compromised cardiac function observed during post myocardial infarction remodeling. Oxidative stress is the major driving force for cardiac damage during myocardial infarction. However, the impact of oxidative stress on the process of post MI remodeling in conducting the heart towards functional failure has not been well explored. In this study, a spatial and temporal approach was taken to elaborate the major proteins and cellular processes involved in post MI remodeling. Based on level/ intensity of ROS, spatially, infarct and noninfarct zones were chosen for analysis while on the temporal scale, early (30days) and late time points (120days) post MI were included in the study. This design enabled us to delineate the differential protein expression on a spectrum of maximum oxidative stress at infarct zone during MI to minimum oxidative stress at noninfarct zone during late time point post MI. The proteome profiles for each of the study groups when comparatively analysed gave a holistic idea about the dominant cellular processes involved in post MI remodeling such as cardiac metabolism, both for short term and long term remodeling as well as unique processes such as Desmin mediated cytoskeletal remodeling of the infarcted myocardium that are involved in the compromise of cardiac function. Copyright © 2016 Elsevier B.V. All rights reserved.
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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.
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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.
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Evaluation of process errors in bed load sampling using a Dune Model
Gomez, Basil; Troutman, Brent M.
1997-01-01
Reliable estimates of the streamwide bed load discharge obtained using sampling devices are dependent upon good at-a-point knowledge across the full width of the channel. Using field data and information derived from a model that describes the geometric features of a dune train in terms of a spatial process observed at a fixed point in time, we show that sampling errors decrease as the number of samples collected increases, and the number of traverses of the channel over which the samples are collected increases. It also is preferable that bed load sampling be conducted at a pace which allows a number of bed forms to pass through the sampling cross section. The situations we analyze and simulate pertain to moderate transport conditions in small rivers. In such circumstances, bed load sampling schemes typically should involve four or five traverses of a river, and the collection of 20–40 samples at a rate of five or six samples per hour. By ensuring that spatial and temporal variability in the transport process is accounted for, such a sampling design reduces both random and systematic errors and hence minimizes the total error involved in the sampling process.
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Nonrigid mammogram registration using mutual information
NASA Astrophysics Data System (ADS)
Wirth, Michael A.; Narhan, Jay; Gray, Derek W. S.
2002-05-01
Of the papers dealing with the task of mammogram registration, the majority deal with the task by matching corresponding control-points derived from anatomical landmark points. One of the caveats encountered when using pure point-matching techniques is their reliance on accurately extracted anatomical features-points. This paper proposes an innovative approach to matching mammograms which combines the use of a similarity-measure and a point-based spatial transformation. Mutual information is a cost-function used to determine the degree of similarity between the two mammograms. An initial rigid registration is performed to remove global differences and bring the mammograms into approximate alignment. The mammograms are then subdivided into smaller regions and each of the corresponding subimages is matched independently using mutual information. The centroids of each of the matched subimages are then used as corresponding control-point pairs in association with the Thin-Plate Spline radial basis function. The resulting spatial transformation generates a nonrigid match of the mammograms. The technique is illustrated by matching mammograms from the MIAS mammogram database. An experimental comparison is made between mutual information incorporating purely rigid behavior, and that incorporating a more nonrigid behavior. The effectiveness of the registration process is evaluated using image differences.
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Spectral analysis and filtering techniques in digital spatial data processing
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
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Optical ranked-order filtering using threshold decomposition
Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.
1990-01-01
A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.
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Biomechanics of the incudo-malleolar-joint - Experimental investigations for quasi-static loads.
Ihrle, S; Gerig, R; Dobrev, I; Röösli, C; Sim, J H; Huber, A M; Eiber, A
2016-10-01
Under large quasi-static loads, the incudo-malleolar joint (IMJ), connecting the malleus and the incus, is highly mobile. It can be classified as a mechanical filter decoupling large quasi-static motions while transferring small dynamic excitations. This is presumed to be due to the complex geometry of the joint inducing a spatial decoupling between the malleus and incus under large quasi-static loads. Spatial Laser Doppler Vibrometer (LDV) displacement measurements on isolated malleus-incus-complexes (MICs) were performed. With the malleus firmly attached to a probe holder, the incus was excited by applying quasi-static forces at different points. For each force application point the resulting displacement was measured subsequently at different points on the incus. The location of the force application point and the LDV measurement points were calculated in a post-processing step combining the position of the LDV points with geometric data of the MIC. The rigid body motion of the incus was then calculated from the multiple displacement measurements for each force application point. The contact regions of the articular surfaces for different load configurations were calculated by applying the reconstructed motion to the geometry model of the MIC and calculate the minimal distance of the articular surfaces. The reconstructed motion has a complex spatial characteristic and varies for different force application points. The motion changed with increasing load caused by the kinematic guidance of the articular surfaces of the joint. The IMJ permits a relative large rotation around the anterior-posterior axis through the joint when a force is applied at the lenticularis in lateral direction before impeding the motion. This is part of the decoupling of the malleus motion from the incus motion in case of large quasi-static loads. Copyright © 2015 Elsevier B.V. All rights reserved.
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Lamm, Claus; Windischberger, Christian; Moser, Ewald; Bauer, Herbert
2007-07-15
Subjects deciding whether two objects presented at angular disparity are identical or mirror versions of each other usually show response times that linearly increase with the angle between objects. This phenomenon has been termed mental rotation. While there is widespread agreement that parietal cortex plays a dominant role in mental rotation, reports concerning the involvement of motor areas are less consistent. From a theoretical point of view, activation in motor areas suggests that mental rotation relies upon visuo-motor rather than visuo-spatial processing alone. However, the type of information that is processed by motor areas during mental rotation remains unclear. In this study we used event-related fMRI to assess whether activation in parietal and dorsolateral premotor areas (dPM) during mental rotation is distinctively related to processing spatial orientation information. Using a newly developed task paradigm we explicitly separated the processing steps (encoding, mental rotation proper and object matching) required by mental rotation tasks and additionally modulated the amount of spatial orientation information that had to be processed. Our results show that activation in dPM during mental rotation is not strongly modulated by the processing of spatial orientation information, and that activation in dPM areas is strongest during mental rotation proper. The latter finding suggests that dPM is involved in more generalized processes such as visuo-spatial attention and movement anticipation. We propose that solving mental rotation tasks is heavily dependent upon visuo-motor processes and evokes neural processing that may be considered as an implicit simulation of actual object rotation.
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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.
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Chen, Yun; Svenning, Jens-Christian; Wang, Xueying; Cao, Ruofan; Yuan, Zhiliang; Ye, Yongzhong
2018-01-01
The effects of environmental and dispersal processes on macrofungi community assembly remain unclear. Further, it is not well understood if community assembly differs for different functional guilds of macrofungi, e.g., soil and rotten-wood macrofungi. In this study, using 2433 macrofungi sporocarps belonging to 217 species located within a forest dynamics plot in temperate mountain forest (China), we examined the explanatory power of topography, spatial eigenvectors (representing unknown spatial processes, e.g., dispersal), plant community, and light availability for local spatial variation in the macrofungi community through variance partitioning and partial least squares path modeling. We found spatial eigenvectors and light as the most important factors for explaining species richness and composition of macrofungi. Light was negatively correlated with species richness of macrofungi. Furthermore, species richness and composition of soil macrofungi were best explained by light, and species richness and composition of rotten-wood macrofungi were best explained by spatial eigenvectors. Woody plant community structure was not an important factor for species richness and composition of macrofungi. Our findings suggest that spatial processes, perhaps dispersal limitation, and light availability were the most important factors affecting macrofungi community in temperate deciduous broad-leaved forest. Major differences in influencing factors between soil and rotten-wood macrofungi were observed, with light as the major driver for soil macrofungi and unknown spatial processes as the major driver for rotten-wood macrofungi. These findings shed new light to the processes shaping community assembly in macrofungi in temperate deciduous broad-leaved forest and point to the potential importance of both intrinsic dynamics, such as dispersal, and external forcing, such as forest dynamics, via its effect on light availability. PMID:29410660
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Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor
Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki
2015-01-01
This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760
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Spatial interpolation schemes of daily precipitation for hydrologic modeling
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.
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Significance of connectivity and post-wildfire runoff
USDA-ARS?s Scientific Manuscript database
Amplified hillslope soil loss from rain storms following wildfire results from the evolution of runoff and erosion processes across spatial scales. At point to small-plot scales, soil is detached and transported a short distance by rainsplash and sheetflow. Soil transport by water over larger scales...
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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.
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Prototypes and particulars: geometric and experience-dependent spatial categories.
Spencer, John P; Hund, Alycia M
2002-03-01
People use geometric cues to form spatial categories. This study investigated whether people also use the spatial distribution of exemplars. Adults pointed to remembered locations on a tabletop. In Experiment 1, a target was placed in each geometric category, and the location of targets was varied. Adults' responses were biased away from a midline category boundary toward geometric prototypes located at the centers of left and right categories. Experiment 2 showed that prototype effects were not influenced by cross-category interactions. In Experiment 3, subsets of targets were positioned at different locations within each category. When prototype effects were removed, there was a bias toward the center of the exemplar distribution, suggesting that common categorization processes operate across spatial and object domains.
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NASA Technical Reports Server (NTRS)
Bautista, Abigail B.
1994-01-01
Twenty-four observers looked through a pair of 20 diopter wedge prisms and pointed to an image of a target which was displaced vertically from eye level by 6 cm at a distance of 30 cm. Observers pointed 40 times, using only their right hand, and received error-corrective feedback upon termination of each pointing response (terminal visual feedback). At three testing distances, 20, 30, and 40 cm, ten pre-exposure and ten post-exposure pointing responses were recorded for each hand as observers reached to a mirror-viewed target located at eye level. The difference between pre- and post-exposure pointing response (adaptive shift) was compared for both Exposed and Unexposed hands across all three testing distances. The data were assessed according to the results predicted by two alternative models for processing spatial-information: one using angular displacement information and another using linear displacement information. The angular model of spatial mapping best predicted the observer's pointing response for the Exposed hand. Although the angular adaptive shift did not change significantly as a function of distance (F(2,44) = 1.12, n.s.), the linear adaptive shift increased significantly over the three testing distances 02 44) = 4.90 p less than 0.01).
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A spatially collocated sound thrusts a flash into awareness
Aller, Máté; Giani, Anette; Conrad, Verena; Watanabe, Masataka; Noppeney, Uta
2015-01-01
To interact effectively with the environment the brain integrates signals from multiple senses. It is currently unclear to what extent spatial information can be integrated across different senses in the absence of awareness. Combining dynamic continuous flash suppression (CFS) and spatial audiovisual stimulation, the current study investigated whether a sound facilitates a concurrent visual flash to elude flash suppression and enter perceptual awareness depending on audiovisual spatial congruency. Our results demonstrate that a concurrent sound boosts unaware visual signals into perceptual awareness. Critically, this process depended on the spatial congruency of the auditory and visual signals pointing towards low level mechanisms of audiovisual integration. Moreover, the concurrent sound biased the reported location of the flash as a function of flash visibility. The spatial bias of sounds on reported flash location was strongest for flashes that were judged invisible. Our results suggest that multisensory integration is a critical mechanism that enables signals to enter conscious perception. PMID:25774126
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NASA Astrophysics Data System (ADS)
Du, Jia-Wei; Wang, Xuan-Yin; Zhu, Shi-Qiang
2017-10-01
Based on the process by which the spatial depth clue is obtained by a single eye, a monocular stereo vision to measure the depth information of spatial objects was proposed in this paper and a humanoid monocular stereo measuring system with two degrees of freedom was demonstrated. The proposed system can effectively obtain the three-dimensional (3-D) structure of spatial objects of different distances without changing the position of the system and has the advantages of being exquisite, smart, and flexible. The bionic optical imaging system we proposed in a previous paper, named ZJU SY-I, was employed and its vision characteristic was just like the resolution decay of the eye's vision from center to periphery. We simplified the eye's rotation in the eye socket and the coordinated rotation of other organs of the body into two rotations in the orthogonal direction and employed a rotating platform with two rotation degrees of freedom to drive ZJU SY-I. The structure of the proposed system was described in detail. The depth of a single feature point on the spatial object was deduced, as well as its spatial coordination. With the focal length adjustment of ZJU SY-I and the rotation control of the rotation platform, the spatial coordinates of all feature points on the spatial object could be obtained and then the 3-D structure of the spatial object could be reconstructed. The 3-D structure measurement experiments of two spatial objects with different distances and sizes were conducted. Some main factors affecting the measurement accuracy of the proposed system were analyzed and discussed.
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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.
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Spatial and temporal laser pulse design for material processing on ultrafast scales
NASA Astrophysics Data System (ADS)
Stoian, R.; Colombier, J. P.; Mauclair, C.; Cheng, G.; Bhuyan, M. K.; Velpula, P. K.; Srisungsitthisunti, P.
2014-01-01
The spatio-temporal design of ultrafast laser excitation can have a determinant influence on the physical and engineering aspects of laser-matter interactions, with the potential of upgrading laser processing effects. Energy relaxation channels can be synergetically stimulated as the energy delivery rate is synchronized with the material response on ps timescales. Experimental and theoretical loops based on the temporal design of laser irradiation and rapid monitoring of irradiation effects are, therefore, able to predict and determine ideal optimal laser pulse forms for specific ablation objectives. We illustrate this with examples on manipulating the thermodynamic relaxation pathways impacting the ablation products and nanostructuring of bulk and surfaces using longer pulse envelopes. Some of the potential control factors will be pointed out. At the same time the spatial character can dramatically influence the development of laser interaction. We discuss spatial beam engineering examples such as parallel and non-diffractive approaches designed for high-throughput, high-accuracy processing events.
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Texture segmentation: do the processing units on the saliency map increase with eccentricity?
Schade, Ursula; Meinecke, Cristina
2011-01-01
The saliency map is a computational model and has been constructed for simulating human saliency processing, e.g. pop-out target detection (e.g. Itti & Koch, 2000). In this study the spatial structure on the saliency map was investigated. It is proposed that the saliency map is structured into processing units whose size is increasing with retinal eccentricity. In two experiments the distance between a target in the stimulus and an irrelevant structure in the mask was varied systematically. Our findings had two main points. Firstly, in texture segmentation tasks the saliency signals from two texture irregularities interfere, when these irregularities appear within a critical spatial distance. Second, the critical distances increase with target eccentricity. The eccentricity-dependent critical distances can be interpreted as crowding effects. It is assumed that additionally to the target eccentricity, also the strength of a saliency signal can determine the spatial area of its impairing influence. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Kang, Guanlan; Zhou, Xiaolin; Wei, Ping
2015-09-01
The present study investigated the effect of reward expectation and spatial orientation on the processing of emotional facial expressions, using a spatial cue-target paradigm. A colored cue was presented at the left or right side of the central fixation point, with its color indicating the monetary reward stakes of a given trial (incentive vs. non-incentive), followed by the presentation of an emotional facial target (angry vs. neutral) at a cued or un-cued location. Participants were asked to discriminate the emotional expression of the target, with the cue-target stimulus onset asynchrony being 200-300 ms in Experiment 1 and 950-1250 ms in Experiment 2a (without a fixation cue) and Experiment 2b (with a fixation cue), producing a spatial facilitation effect and an inhibition of return effect, respectively. The results of all the experiments revealed faster reaction times in the monetary incentive condition than in the non-incentive condition, demonstrating the effect of reward to facilitate task performance. An interaction between reward expectation and the emotion of the target was evident in all the three experiments, with larger reward effects for angry faces than for neutral faces. This interaction was not affected by spatial orientation. These findings demonstrate that incentive motivation improves task performance and increases sensitivity to angry faces, irrespective of spatial orienting and reorienting processes.
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Velázquez, Eduardo; Escudero, Adrián; de la Cruz, Marcelino
2018-01-01
We assessed the relative importance of dispersal limitation, environmental heterogeneity and their joint effects as determinants of the spatial patterns of 229 species in the moist tropical forest of Barro Colorado Island (Panama). We differentiated five types of species according to their dispersal syndrome; autochorous, anemochorous, and zoochorous species with small, medium-size and large fruits. We characterized the spatial patterns of each species and we checked whether they were best fitted by Inhomogeneous Poisson (IPP), Homogeneous Poisson cluster (HPCP) and Inhomogeneous Poisson cluster processes (IPCP) by means of the Akaike Information Criterion. We also assessed the influence of species’ dispersal mode in the average cluster size. We found that 63% of the species were best fitted by IPCP regardless of their dispersal syndrome, although anemochorous species were best described by HPCP. Our results indicate that spatial patterns of tree species in this forest cannot be explained only by dispersal limitation, but by the joint effects of dispersal limitation and environmental heterogeneity. The absence of relationships between dispersal mode and degree of clustering suggests that several processes modify the original spatial pattern generated by seed dispersal. These findings emphasize the importance of fitting point process models with a different biological meaning when studying the main determinants of spatial structure in plant communities. PMID:29451871
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NASA Astrophysics Data System (ADS)
Li, Jun; Qin, Qiming; Xie, Chao; Zhao, Yue
2012-10-01
The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps.
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One-loop gravitational wave spectrum in de Sitter spacetime
NASA Astrophysics Data System (ADS)
Fröb, Markus B.; Roura, Albert; Verdaguer, Enric
2012-08-01
The two-point function for tensor metric perturbations around de Sitter spacetime including one-loop corrections from massless conformally coupled scalar fields is calculated exactly. We work in the Poincaré patch (with spatially flat sections) and employ dimensional regularization for the renormalization process. Unlike previous studies we obtain the result for arbitrary time separations rather than just equal times. Moreover, in contrast to existing results for tensor perturbations, ours is manifestly invariant with respect to the subgroup of de Sitter isometries corresponding to a simultaneous time translation and rescaling of the spatial coordinates. Having selected the right initial state for the interacting theory via an appropriate iepsilon prescription is crucial for that. Finally, we show that although the two-point function is a well-defined spacetime distribution, the equal-time limit of its spatial Fourier transform is divergent. Therefore, contrary to the well-defined distribution for arbitrary time separations, the power spectrum is strictly speaking ill-defined when loop corrections are included.
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Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.
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.
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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.
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Two spatial memories are not better than one: evidence of exclusivity in memory for object location.
Baguley, Thom; Lansdale, Mark W; Lines, Lorna K; Parkin, Jennifer K
2006-05-01
This paper studies the dynamics of attempting to access two spatial memories simultaneously and its implications for the accuracy of recall. Experiment 1 demonstrates in a range of conditions that two cues pointing to different experiences of the same object location produce little or no higher recall than that observed with a single cue. Experiment 2 confirms this finding in a within-subject design where both cues have previously elicited recall. Experiment 3 shows that these findings are only consistent with a model in which two representations of the same object location are mutually exclusive at both encoding and retrieval, and inconsistent with models that assume information from both representations is available. We propose that these representations quantify directionally specific judgments of location relative to specific anchor points in the stimulus; a format that precludes the parallel processing of like representations. Finally, we consider the apparent paradox of how such representations might contribute to the acquisition of spatial knowledge from multiple experiences of the same stimuli.
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Users as essential contributors to spatial cyberinfrastructures
Poore, Barbara S.
2011-01-01
Current accounts of spatial cyberinfrastructure development tend to overemphasize technologies to the neglect of critical social and cultural issues on which adoption depends. Spatial cyberinfrastructures will have a higher chance of success if users of many types, including nonprofessionals, are made central to the development process. Recent studies in the history of infrastructures reveal key turning points and issues that should be considered in the development of spatial cyberinfrastructure projects. These studies highlight the importance of adopting qualitative research methods to learn how users work with data and digital tools, and how user communities form. The author's empirical research on data sharing networks in the Pacific Northwest salmon crisis at the turn of the 21st century demonstrates that ordinary citizens can contribute critical local knowledge to global databases and should be considered in the design and construction of spatial cyberinfrastructures. PMID:21444825
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Users as essential contributors to spatial cyberinfrastructures.
Poore, Barbara S
2011-04-05
Current accounts of spatial cyberinfrastructure development tend to overemphasize technologies to the neglect of critical social and cultural issues on which adoption depends. Spatial cyberinfrastructures will have a higher chance of success if users of many types, including nonprofessionals, are made central to the development process. Recent studies in the history of infrastructures reveal key turning points and issues that should be considered in the development of spatial cyberinfrastructure projects. These studies highlight the importance of adopting qualitative research methods to learn how users work with data and digital tools, and how user communities form. The author's empirical research on data sharing networks in the Pacific Northwest salmon crisis at the turn of the 21st century demonstrates that ordinary citizens can contribute critical local knowledge to global databases and should be considered in the design and construction of spatial cyberinfrastructures.
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Users as essential contributors to spatial cyberinfrastructures
Poore, B.S.
2011-01-01
Current accounts of spatial cyberinfrastructure development tend to overemphasize technologies to the neglect of critical social and cultural issues on which adoption depends. Spatial cyberinfrastructures will have a higher chance of success if users of many types, including nonprofessionals, are made central to the development process. Recent studies in the history of infrastructures reveal key turning points and issues that should be considered in the development of spatial cyberinfrastructure projects. These studies highlight the importance of adopting qualitative research methods to learn how users work with data and digital tools, and how user communities form. The author's empirical research on data sharing networks in the Pacific Northwest salmon crisis at the turn of the 21st century demonstrates that ordinary citizens can contribute critical local knowledge to global databases and should be considered in the design and construction of spatial cyberinfrastructures.
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Monitoring of dispersed smoke-plume layers by determining locations of the data-point clusters
NASA Astrophysics Data System (ADS)
Kovalev, Vladimir; Wold, Cyle; Petkov, Alexander; Min Hao, Wei
2018-04-01
A modified data-processing technique of the signals recorded by zenith-directed lidar, which operates in smoke-polluted atmosphere, is discussed. The technique is based on simple transformations of the lidar backscatter signal and the determination of the spatial location of the data point clusters. The technique allows more reliable detection of the location of dispersed smoke layering. Examples of typical results obtained with lidar in a smokepolluted atmosphere are presented.
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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.
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BOREAS HYD-8 1994 Gravimetric Moss Moisture Data
NASA Technical Reports Server (NTRS)
Wang, Xuewen; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes that were collected at the Northern Study Area-Old Black Spruce (NSA-OBS) Tower Flux site in 1994 and at Joey Lake, Manitoba, to support its research into point hydrological processes and the spatial variation of these processes. The data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the gravimetric moss moisture measurements from June to September 1994. A nested spatial sampling plan was implemented to support research into spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in tabular ASCII files. The HYD-08 1994 gravimetric moss moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
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Optical ranked-order filtering using threshold decomposition
Allebach, J.P.; Ochoa, E.; Sweeney, D.W.
1987-10-09
A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.
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Fan, Zhencheng; Weng, Yitong; Chen, Guowen; Liao, Hongen
2017-07-01
Three-dimensional (3D) visualization of preoperative and intraoperative medical information becomes more and more important in minimally invasive surgery. We develop a 3D interactive surgical visualization system using mobile spatial information acquisition and autostereoscopic display for surgeons to observe surgical target intuitively. The spatial information of regions of interest (ROIs) is captured by the mobile device and transferred to a server for further image processing. Triangular patches of intraoperative data with texture are calculated with a dimension-reduced triangulation algorithm and a projection-weighted mapping algorithm. A point cloud selection-based warm-start iterative closest point (ICP) algorithm is also developed for fusion of the reconstructed 3D intraoperative image and the preoperative image. The fusion images are rendered for 3D autostereoscopic display using integral videography (IV) technology. Moreover, 3D visualization of medical image corresponding to observer's viewing direction is updated automatically using mutual information registration method. Experimental results show that the spatial position error between the IV-based 3D autostereoscopic fusion image and the actual object was 0.38±0.92mm (n=5). The system can be utilized in telemedicine, operating education, surgical planning, navigation, etc. to acquire spatial information conveniently and display surgical information intuitively. Copyright © 2017 Elsevier Inc. All rights reserved.
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Generalized estimators of avian abundance from count survey data
Royle, J. Andrew
2004-01-01
I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.
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Long-term effects of cannabis on oculomotor function in humans.
Huestegge, L; Radach, R; Kunert, H J
2009-08-01
Cannabis is known to affect human cognitive and visuomotor skills directly after consumption. Some studies even point to rather long-lasting effects, especially after chronic tetrahydrocannabinol (THC) abuse. However, it is still unknown whether long-term effects on basic visual and oculomotor processing may exist. In the present study, the performance of 20 healthy long-term cannabis users without acute THC intoxication and 20 control subjects were examined in four basic visuomotor paradigms to search for specific long-term impairments. Subjects were asked to perform: 1) reflexive saccades to visual targets (prosaccades), including gap and overlap conditions, 2) voluntary antisaccades, 3) memory-guided saccades and 4) double-step saccades. Spatial and temporal parameters of the saccades were subsequently analysed. THC subjects exhibited a significant increase of latency in the prosaccade and antisaccade tasks, as well as prolonged saccade amplitudes in the antisaccade and memory-guided task, compared with the control subjects. The results point to substantial and specific long-term deficits in basic temporal processing of saccades and impaired visuo-spatial working memory. We suggest that these impairments are a major contributor to degraded performance of chronic users in a vital everyday task like visual search, and they might potentially also affect spatial navigation and reading.
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C, N, P export regimes from headwater catchments to downstream reaches
NASA Astrophysics Data System (ADS)
Dupas, R.; Musolff, A.; Jawitz, J. W.; Rao, P. S.; Jaeger, C. G.; Fleckenstein, J. H.; Rode, M.; Borchardt, D.
2017-12-01
Excessive amounts of nutrients and dissolved organic matter in freshwater bodies affect aquatic ecosystems. In this study, the spatial and temporal variability in nitrate (NO3), dissolved organic carbon (DOC) and soluble reactive phosphorus (SRP) was analyzed in the Selke river continuum from headwaters draining 1 - 3 km² catchments to downstream reaches representing spatially integrated signals from 184 - 456 km² catchments (part of TERENO - Terrestrial Environmental Observatories, in Germany). Three headwater catchments were selected as archetypes of the main landscape units (land use x lithology) present in the Selke catchment. Export regimes in headwater catchments were interpreted in terms of NO3, DOC and SRP land-to-stream transfer processes. Headwater signals were subtracted from downstream signals, with the differences interpreted in terms of in-stream processes and contribution of point-source emissions. The seasonal dynamics for NO3 were opposite those of DOC and SRP in all three headwater catchments, and spatial differences also showed NO3 contrasting with DOC and SRP. These dynamics were interpreted as the result of the interplay of hydrological and biogeochemical processes, for which riparian zones were hypothesized to play a determining role. In the two downstream reaches, NO3 was transported almost conservatively, whereas DOC was consumed and produced in the upper and lower river sections, respectively. The natural export regime of SRP in the three headwater catchments mimicked a point-source signal, which may lead to overestimation of domestic contributions in the downstream reaches. Monitoring the river continuum from headwaters to downstream reaches proved effective to investigate jointly land-to-stream and in-stream transport and transformation processes.
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D Reconstruction from Uav-Based Hyperspectral Images
NASA Astrophysics Data System (ADS)
Liu, L.; Xu, L.; Peng, J.
2018-04-01
Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.
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Perception of biological motion from size-invariant body representations.
Lappe, Markus; Wittinghofer, Karin; de Lussanet, Marc H E
2015-01-01
The visual recognition of action is one of the socially most important and computationally demanding capacities of the human visual system. It combines visual shape recognition with complex non-rigid motion perception. Action presented as a point-light animation is a striking visual experience for anyone who sees it for the first time. Information about the shape and posture of the human body is sparse in point-light animations, but it is essential for action recognition. In the posturo-temporal filter model of biological motion perception posture information is picked up by visual neurons tuned to the form of the human body before body motion is calculated. We tested whether point-light stimuli are processed through posture recognition of the human body form by using a typical feature of form recognition, namely size invariance. We constructed a point-light stimulus that can only be perceived through a size-invariant mechanism. This stimulus changes rapidly in size from one image to the next. It thus disrupts continuity of early visuo-spatial properties but maintains continuity of the body posture representation. Despite this massive manipulation at the visuo-spatial level, size-changing point-light figures are spontaneously recognized by naive observers, and support discrimination of human body motion.
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NASA Astrophysics Data System (ADS)
Park, Byeongjin; Sohn, Hoon
2018-04-01
The practicality of laser ultrasonic scanning is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated defect visualization technique is developed to visualize defect with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio of measured ultrasonic responses. The approximate defect boundary is identified by examining the interactions between ultrasonic waves and defect observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and defect can be better identified in the spatial ultrasonic domain. Then, the area inside the identified defect boundary is visualized as defect. The performance of the proposed defect visualization technique is validated through an experiment on a semiconductor chip. The proposed defect visualization technique accelerates the defect visualization process in three aspects: (1) The number of measurements that is necessary for defect visualization is dramatically reduced by a binary search algorithm; (2) The number of averaging that is necessary to achieve a high signal-to-noise ratio is reduced by maintaining the wave propagation distance short; and (3) With the proposed technique, defect can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.
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NASA Astrophysics Data System (ADS)
Benaud, P.; Anderson, K.; Quine, T. A.; James, M. R.; Quinton, J.; Brazier, R. E.
2016-12-01
While total sediment capture can accurately quantify soil loss via water erosion, it isn't practical at the field scale and provides little information on the spatial nature of soil erosion processes. Consequently, high-resolution, remote sensing, point cloud data provide an alternative method for quantifying soil loss. The accessibility of Structure-from-Motion Multi-Stereo View (SfM) and the potential for multi-temporal applications, offers an exciting opportunity to spatially quantify soil erosion. Accordingly, published research provides examples of the successful quantification of large erosion features and events, to centimetre accuracy. Through rigorous control of the camera and image network geometry, the centimetre accuracy achievable at the field scale, can translate to sub-millimetre accuracies within a laboratory environment. Accordingly, this study looks to understand how the ultra-high-resolution spatial information on soil surface topography, derived from SfM, can be integrated with a multi-element sediment tracer to develop a mechanistic understanding of rill and inter-rill erosion, under experimental conditions. A rainfall simulator was used to create three soil surface conditions; compaction and rainsplash, inter-rill erosion, and rill erosion, at two experimental scales (0.15 m2 and 3 m2). Total sediment capture was the primary validation for the experiments, allowing the comparison between structurally and volumetrically derived change, and true soil loss. A Terrestrial Laser Scanner (resolution of ca. 0.8mm) has been employed to assess spatial discrepancies within the SfM data sets and to provide an alternative measure of volumetric change. Preliminary results show the SfM approach used can achieve a ground resolution of less than 0.2 mm per pixel, and a RMSE of less than 0.3 mm. Consequently, it is expected that the ultra-high-resolution SfM point clouds can be utilised to provide a detailed assessment of soil loss via water erosion processes.
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Indexing and retrieving point and region objects
NASA Astrophysics Data System (ADS)
Ibrahim, Azzam T.; Fotouhi, Farshad A.
1996-03-01
R-tree and its variants are examples of spatial data structures for paged-secondary memory. To process a query, these structures require multiple path traversals. In this paper, we present a new image access method, SB+-tree which requires a single path traversal to process a query. Also, SB+-tree will allow commercial databases an access method for spatial objects without a major change, since most commercial databases already support B+-tree as an access method for text data. The SB+-tree can be used for zero and non-zero size data objects. Non-zero size objects are approximated by their minimum bounding rectangles (MBRs). The number of SB+-trees generated is dependent upon the number of dimensions of the approximation of the object. The structure supports efficient spatial operations such as regions-overlap, distance and direction. In this paper, we experimentally and analytically demonstrate the superiority of SB+-tree over R-tree.
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Di Vito, Alessia; Fanfoni, Massimo; Tomellini, Massimo
2010-12-01
Starting from a stochastic two-dimensional process we studied the transformation of points in disks and squares following a protocol according to which at any step the island size increases proportionally to the corresponding Voronoi tessera. Two interaction mechanisms among islands have been dealt with: coalescence and impingement. We studied the evolution of the island density and of the island size distribution functions, in dependence on island collision mechanisms for both Poissonian and correlated spatial distributions of points. The island size distribution functions have been found to be invariant with the fraction of transformed phase for a given stochastic process. The n(Θ) curve describing the island decay has been found to be independent of the shape (apart from high correlation degrees) and interaction mechanism.
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Hemispheric Differences in Attentional Orienting by Social Cues
ERIC Educational Resources Information Center
Greene, Deanna J.; Zaidel, Eran
2011-01-01
Research points to a right hemisphere bias for processing social stimuli. Hemispheric specialization for attention shifts cued by social stimuli, however, has been rarely studied. We examined the capacity of each hemisphere to orient attention in response to social and nonsocial cues using a lateralized spatial cueing paradigm. We compared the…
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NASA Astrophysics Data System (ADS)
Yokoyama, Ryouta; Yagi, Shin-ichi; Tamura, Kiyoshi; Sato, Masakazu
2009-07-01
Ultrahigh speed dynamic elastography has promising potential capabilities in applying clinical diagnosis and therapy of living soft tissues. In order to realize the ultrahigh speed motion tracking at speeds of over thousand frames per second, synthetic aperture (SA) array signal processing technology must be introduced. Furthermore, the overall system performance should overcome the fine quantitative evaluation in accuracy and variance of echo phase changes distributed across a tissue medium. On spatial evaluation of local phase changes caused by pulsed excitation on a tissue phantom, investigation was made with the proposed SA signal system utilizing different virtual point sources that were generated by an array transducer to probe each component of local tissue displacement vectors. The final results derived from the cross-correlation method (CCM) brought about almost the same performance as obtained by the constrained least square method (LSM) extended to successive echo frames. These frames were reconstructed by SA processing after the real-time acquisition triggered by the pulsed irradiation from a point source. The continuous behavior of spatial motion vectors demonstrated the dynamic generation and traveling of the pulsed shear wave at a speed of one thousand frames per second.
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NASA Astrophysics Data System (ADS)
Harrison, T. W.; Polagye, B. L.
2016-02-01
Coastal ecosystems are characterized by spatially and temporally varying hydrodynamics. In marine renewable energy applications, these variations strongly influence project economics and in oceanographic studies, they impact accuracy of biological transport and pollutant dispersion models. While stationary point or profile measurements are relatively straight forward, spatial representativeness of point measurements can be poor due to strong gradients. Moving platforms, such as AUVs or surface vessels, offer better coverage, but suffer from energetic constraints (AUVs) and resolvable scales (vessels). A system of sub-surface, drifting sensor packages is being developed to provide spatially distributed, synoptic data sets of coastal hydrodynamics with meter-scale resolution over a regional extent of a kilometer. Computational investigation has informed system parameters such as drifter size and shape, necessary position accuracy, number of drifters, and deployment methods. A hydrodynamic domain with complex flow features was created using a computational fluid dynamics code. A simple model of drifter dynamics propagate the drifters through the domain in post-processing. System parameters are evaluated relative to their ability to accurately recreate domain hydrodynamics. Implications of these results for an inexpensive, depth-controlled Lagrangian drifter system is presented.
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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.
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Bootstrap percolation on spatial networks
NASA Astrophysics Data System (ADS)
Gao, Jian; Zhou, Tao; Hu, Yanqing
2015-10-01
Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links’ lengths being a power law with tunable exponent. Setting the size of the giant active component as the order parameter, we find a parameter-dependent critical value for the power-law exponent, above which there is a double phase transition, mixed of a second-order phase transition and a hybrid phase transition with two varying critical points, otherwise there is only a second-order phase transition. We further find a parameter-independent critical value around -1, about which the two critical points for the double phase transition are almost constant. To our surprise, this critical value -1 is just equal or very close to the values of many real online social networks, including LiveJournal, HP Labs email network, Belgian mobile phone network, etc. This work helps us in better understanding the self-organization of spatial structure of online social networks, in terms of the effective function for information spreading.
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Probing the degenerate states of V-point singularities.
Ram, B S Bhargava; Sharma, Anurag; Senthilkumaran, Paramasivam
2017-09-15
V-points are polarization singularities in spatially varying linearly polarized optical fields and are characterized by the Poincare-Hopf index η. Each V-point singularity is a superposition of two oppositely signed orbital angular momentum states in two orthogonal spin angular momentum states. Hence, a V-point singularity has zero net angular momentum. V-points with given |η| have the same (amplitude) intensity distribution but have four degenerate polarization distributions. Each of these four degenerate states also produce identical diffraction patterns. Hence to distinguish these degenerate states experimentally, we present in this Letter a method involving a combination of polarization transformation and diffraction. This method also shows the possibility of using polarization singularities in place of phase singularities in optical communication and quantum information processing.
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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.
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Line segment confidence region-based string matching method for map conflation
NASA Astrophysics Data System (ADS)
Huh, Yong; Yang, Sungchul; Ga, Chillo; Yu, Kiyun; Shi, Wenzhong
2013-04-01
In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.
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An analysis of neural receptive field plasticity by point process adaptive filtering
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
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NASA Astrophysics Data System (ADS)
Luo, L.; Fan, M.; Shen, M. Z.
2007-07-01
Atmospheric turbulence greatly limits the spatial resolution of astronomical images acquired by the large ground-based telescope. The record image obtained from telescope was thought as a convolution result of the object function and the point spread function. The statistic relationship of the images measured data, the estimated object and point spread function was in accord with the Bayes conditional probability distribution, and the maximum-likelihood formulation was found. A blind deconvolution approach based on the maximum-likelihood estimation technique with real optical band limitation constraint is presented for removing the effect of atmospheric turbulence on this class images through the minimization of the convolution error function by use of the conjugation gradient optimization algorithm. As a result, the object function and the point spread function could be estimated from a few record images at the same time by the blind deconvolution algorithm. According to the principle of Fourier optics, the relationship between the telescope optical system parameters and the image band constraint in the frequency domain was formulated during the image processing transformation between the spatial domain and the frequency domain. The convergence of the algorithm was increased by use of having the estimated function variable (also is the object function and the point spread function) nonnegative and the point-spread function band limited. Avoiding Fourier transform frequency components beyond the cut off frequency lost during the image processing transformation when the size of the sampled image data, image spatial domain and frequency domain were the same respectively, the detector element (e.g. a pixels in the CCD) should be less than the quarter of the diffraction speckle diameter of the telescope for acquiring the images on the focal plane. The proposed method can easily be applied to the case of wide field-view turbulent-degraded images restoration because of no using the object support constraint in the algorithm. The performance validity of the method is examined by the computer simulation and the restoration of the real Alpha Psc astronomical image data. The results suggest that the blind deconvolution with the real optical band constraint can remove the effect of the atmospheric turbulence on the observed images and the spatial resolution of the object image can arrive at or exceed the diffraction-limited level.
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A stochastic-geometric model of soil variation in Pleistocene patterned ground
NASA Astrophysics Data System (ADS)
Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc
2013-04-01
In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.
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Plasmonic computing of spatial differentiation
NASA Astrophysics Data System (ADS)
Zhu, Tengfeng; Zhou, Yihan; Lou, Yijie; Ye, Hui; Qiu, Min; Ruan, Zhichao; Fan, Shanhui
2017-05-01
Optical analog computing offers high-throughput low-power-consumption operation for specialized computational tasks. Traditionally, optical analog computing in the spatial domain uses a bulky system of lenses and filters. Recent developments in metamaterials enable the miniaturization of such computing elements down to a subwavelength scale. However, the required metamaterial consists of a complex array of meta-atoms, and direct demonstration of image processing is challenging. Here, we show that the interference effects associated with surface plasmon excitations at a single metal-dielectric interface can perform spatial differentiation. And we experimentally demonstrate edge detection of an image without any Fourier lens. This work points to a simple yet powerful mechanism for optical analog computing at the nanoscale.
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Scale Invariance in Lateral Head Scans During Spatial Exploration.
Yadav, Chetan K; Doreswamy, Yoganarasimha
2017-04-14
Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.
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Scale Invariance in Lateral Head Scans During Spatial Exploration
NASA Astrophysics Data System (ADS)
Yadav, Chetan K.; Doreswamy, Yoganarasimha
2017-04-01
Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.
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Point pattern analysis of FIA data
Chris Woodall
2002-01-01
Point pattern analysis is a branch of spatial statistics that quantifies the spatial distribution of points in two-dimensional space. Point pattern analysis was conducted on stand stem-maps from FIA fixed-radius plots to explore point pattern analysis techniques and to determine the ability of pattern descriptions to describe stand attributes. Results indicate that the...
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[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].
Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping
2016-12-01
As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.
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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
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The limits of boundaries: unpacking localization and cognitive mapping relative to a boundary.
Zhou, Ruojing; Mou, Weimin
2018-05-01
Previous research (Zhou, Mou, Journal of Experimental Psychology: Learning, Memory and Cognition 42(8):1316-1323, 2016) showed that learning individual locations relative to a single landmark, compared to learning relative to a boundary, led to more accurate inferences of inter-object spatial relations (cognitive mapping of multiple locations). Following our past findings, the current study investigated whether the larger number of reference points provided by a homogeneous circular boundary, as well as less accessible knowledge of direct spatial relations among the multiple reference points, would lead to less effective cognitive mapping relative to the boundary. Accordingly, we manipulated (a) the number of primary reference points (one segment drawn from a circular boundary, four such segments, vs. the complete boundary) available when participants were localizing four objects sequentially (Experiment 1) and (b) the extendedness of each of the four segments (Experiment 2). The results showed that cognitive mapping was the least accurate in the whole boundary condition. However, expanding each of the four segments did not affect the accuracy of cognitive mapping until the four were connected to form a continuous boundary. These findings indicate that when encoding locations relative to a homogeneous boundary, participants segmented the boundary into differentiated pieces and subsequently chose the most informative local part (i.e., the segment closest in distance to one location) as the primary reference point for a particular location. During this process, direct spatial relations among the reference points were likely not attended to. These findings suggest that people might encode and represent bounded space in a fragmented fashion when localizing within a homogeneous boundary.
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When Do Objects Become Landmarks? A VR Study of the Effect of Task Relevance on Spatial Memory
Han, Xue; Byrne, Patrick; Kahana, Michael; Becker, Suzanna
2012-01-01
We investigated how objects come to serve as landmarks in spatial memory, and more specifically how they form part of an allocentric cognitive map. Participants performing a virtual driving task incidentally learned the layout of a virtual town and locations of objects in that town. They were subsequently tested on their spatial and recognition memory for the objects. To assess whether the objects were encoded allocentrically we examined pointing consistency across tested viewpoints. In three experiments, we found that spatial memory for objects at navigationally relevant locations was more consistent across tested viewpoints, particularly when participants had more limited experience of the environment. When participants’ attention was focused on the appearance of objects, the navigational relevance effect was eliminated, whereas when their attention was focused on objects’ locations, this effect was enhanced, supporting the hypothesis that when objects are processed in the service of navigation, rather than merely being viewed as objects, they engage qualitatively distinct attentional systems and are incorporated into an allocentric spatial representation. The results are consistent with evidence from the neuroimaging literature that when objects are relevant to navigation, they not only engage the ventral “object processing stream”, but also the dorsal stream and medial temporal lobe memory system classically associated with allocentric spatial memory. PMID:22586455
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A quantitative method for determining spatial discriminative capacity.
Zhang, Zheng; Tannan, Vinay; Holden, Jameson K; Dennis, Robert G; Tommerdahl, Mark
2008-03-10
The traditional two-point discrimination (TPD) test, a widely used tactile spatial acuity measure, has been criticized as being imprecise because it is based on subjective criteria and involves a number of non-spatial cues. The results of a recent study showed that as two stimuli were delivered simultaneously, vibrotactile amplitude discrimination became worse when the two stimuli were positioned relatively close together and was significantly degraded when the probes were within a subject's two-point limen. The impairment of amplitude discrimination with decreasing inter-probe distance suggested that the metric of amplitude discrimination could possibly provide a means of objective and quantitative measurement of spatial discrimination capacity. A two alternative forced-choice (2AFC) tracking procedure was used to assess a subject's ability to discriminate the amplitude difference between two stimuli positioned at near-adjacent skin sites. Two 25 Hz flutter stimuli, identical except for a constant difference in amplitude, were delivered simultaneously to the hand dorsum. The stimuli were initially spaced 30 mm apart, and the inter-stimulus distance was modified on a trial-by-trial basis based on the subject's performance of discriminating the stimulus with higher intensity. The experiment was repeated via sequential, rather than simultaneous, delivery of the same vibrotactile stimuli. Results obtained from this study showed that the performance of the amplitude discrimination task was significantly degraded when the stimuli were delivered simultaneously and were near a subject's two-point limen. In contrast, subjects were able to correctly discriminate between the amplitudes of the two stimuli when they were sequentially delivered at all inter-probe distances (including those within the two-point limen), and improved when an adapting stimulus was delivered prior to simultaneously delivered stimuli. Subjects' capacity to discriminate the amplitude difference between two vibrotactile stimulations was degraded as the inter-stimulus distance approached the limit of their two-point spatial discriminative capacity. This degradation of spatial discriminative capacity lessened when an adapting stimulus was used. Performance of the task, as well as improvement on the task with adaptation, would most likely be impaired if the cortical information processing capacity of a subject or subject population were systemically altered, and thus, the methods described could be effective measures for use in clinical or clinical research applications.
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Interferometric at-wavelength flare characterization of EUV optical systems
Naulleau, Patrick P.; Goldberg, Kenneth Alan
2001-01-01
The extreme ultraviolet (EUV) phase-shifting point diffraction interferometer (PS/PDI) provides the high-accuracy wavefront characterization critical to the development of EUV lithography systems. Enhancing the implementation of the PS/PDI can significantly extend its spatial-frequency measurement bandwidth. The enhanced PS/PDI is capable of simultaneously characterizing both wavefront and flare. The enhanced technique employs 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. Using the dual-domain technique in combination with a flare-measurement-optimized mask and an iterative calculation process for removing flare contribution caused by higher order grating diffraction terms, the enhanced PS/PDI can be used to simultaneously measure both figure and flare in optical systems.
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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.
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Spine-fan reconnection. The influence of temporal and spatial variation in the driver
NASA Astrophysics Data System (ADS)
Wyper, P. F.; Jain, R.; Pontin, D. I.
2012-09-01
Context. From observations, the atmosphere of the Sun has been shown to be highly dynamic with perturbations of the magnetic field often lacking temporal or spatial symmetry. Despite this, studies of the spine-fan reconnection mode at 3D nulls have so far focused on the very idealised case with symmetric driving of a fixed spatial extent. Aims: We investigate the spine-fan reconnection process for less idealised cases, focusing on asymmetric driving and drivers with different length scales. We look at the initial current sheet formation and whether the scalings developed in the idealised models are robust in more realistic situations. Methods: The investigation was carried out by numerically solving the resistive compressible 3D magnetohydrodynamic equations in a Cartesian box containing a linear null point. The spine-fan collapse was driven at the null through tangential boundary driving of the spine foot points. Results: We find significant differences in the initial current sheet formation with asymmetric driving. Notable is the displacement of the null point position as a function of driving velocity and resistivity (η). However, the scaling relations developed in the idealised case are found to be robust (albeit at reduced amplitudes) despite this extra complexity. Lastly, the spatial variation is also shown to play an important role in the initial current sheet formation through controlling the displacement of the spine foot points. Conclusions: We conclude that during the early stages of spine-fan reconnection both the temporal and spatial nature of the driving play important roles, with the idealised symmetrically driven case giving a "best case" for the rate of current development and connectivity change. As the most interesting eruptive events occur in relatively short time frames this work clearly shows the need for high temporal and spatial knowledge of the flows for accurate interpretation of the reconnection scenario. Lastly, since the scalings developed in the idealised case remain robust with more complex driving we can be more confident of their use in interpreting reconnection in complex magnetic field structures.
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Drugs at the campsite: Socio-spatial relations and drug use at music festivals.
Dilkes-Frayne, Ella
2016-07-01
Music festivals have received relatively little research attention despite being key sites for alcohol and drug use among young people internationally. Research into music festivals and the social contexts of drug use more generally, has tended to focus on social and cultural processes without sufficient regard for the mediating role of space and spatial processes. Adopting a relational approach to space and the social, from Actor-Network Theory and human geography, I examine how socio-spatial relations are generated in campsites at multiple-day music festivals. The data are drawn from ethnographic observations at music festivals around Melbourne, Australia; interviews with 18-23 year olds; and participant-written diaries. Through the analysis, the campsite is revealed as a space in process, the making of which is bound up in how drug use unfolds. Campsite relations mediate the formation of drug knowledge and norms, informal harm reduction practices, access to and exchange of drugs, and rest and recovery following drug use. Greater attendance to socio-spatial relations affords new insights regarding how festival spaces and their social effects are generated, and how they give rise to particular drug use practices. These findings also point to how festival harm reduction strategies might be enhanced through the promotion of enabling socio-spatial relations. Copyright © 2015 Elsevier B.V. All rights reserved.
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The 14,582 km2 Neuse River Basin in North Carolina was characterized based on a user defined land-cover (LC) classification system developed specifically to support spatially explicit, non-point source nitrogen allocation modeling studies. Data processing incorporated both spect...
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Shi, Yuning; Eissenstat, David M.; He, Yuting; ...
2018-05-12
Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, Yuning; Eissenstat, David M.; He, Yuting
Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less
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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.
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Li, Zhan; Schaefer, Michael; Strahler, Alan; Schaaf, Crystal; Jupp, David
2018-04-06
The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.
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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
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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.
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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.
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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.
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Network based approaches reveal clustering in protein point patterns
NASA Astrophysics Data System (ADS)
Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang
2014-03-01
Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.
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NASA Astrophysics Data System (ADS)
Shaw, Leah B.; Sethna, James P.; Lee, Kelvin H.
2004-08-01
The process of protein synthesis in biological systems resembles a one-dimensional driven lattice gas in which the particles (ribosomes) have spatial extent, covering more than one lattice site. Realistic, nonuniform gene sequences lead to quenched disorder in the particle hopping rates. We study the totally asymmetric exclusion process with large particles and quenched disorder via several mean-field approaches and compare the mean-field results with Monte Carlo simulations. Mean-field equations obtained from the literature are found to be reasonably effective in describing this system. A numerical technique is developed for computing the particle current rapidly. The mean-field approach is extended to include two-point correlations between adjacent sites. The two-point results are found to match Monte Carlo simulations more closely.
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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.
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Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR
NASA Astrophysics Data System (ADS)
Gao, Yang; Zhong, Ruofei; Tang, Tao; Wang, Liuzhao; Liu, Xianlin
2017-08-01
Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings’ information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.
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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.
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Extinction threshold for spatial forest dynamics with height structure.
Garcia-Domingo, Josep L; Saldaña, Joan
2011-05-07
We present a pair-approximation model for spatial forest dynamics defined on a regular lattice. The model assumes three possible states for a lattice site: empty (gap site), occupied by an immature tree, and occupied by a mature tree, and considers three nonlinearities in the dynamics associated to the processes of light interference, gap expansion, and recruitment. We obtain an expression of the basic reproduction number R(0) which, in contrast to the one obtained under the mean-field approach, uses information about the spatial arrangement of individuals close to extinction. Moreover, we analyze the corresponding survival-extinction transition of the forest and the spatial correlations among gaps, immature and mature trees close to this critical point. Predictions of the pair-approximation model are compared with those of a cellular automaton. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Congenital blindness limits allocentric to egocentric switching ability.
Ruggiero, Gennaro; Ruotolo, Francesco; Iachini, Tina
2018-03-01
Many everyday spatial activities require the cooperation or switching between egocentric (subject-to-object) and allocentric (object-to-object) spatial representations. The literature on blind people has reported that the lack of vision (congenital blindness) may limit the capacity to represent allocentric spatial information. However, research has mainly focused on the selective involvement of egocentric or allocentric representations, not the switching between them. Here we investigated the effect of visual deprivation on the ability to switch between spatial frames of reference. To this aim, congenitally blind (long-term visual deprivation), blindfolded sighted (temporary visual deprivation) and sighted (full visual availability) participants were compared on the Ego-Allo switching task. This task assessed the capacity to verbally judge the relative distances between memorized stimuli in switching (from egocentric-to-allocentric: Ego-Allo; from allocentric-to-egocentric: Allo-Ego) and non-switching (only-egocentric: Ego-Ego; only-allocentric: Allo-Allo) conditions. Results showed a difficulty in congenitally blind participants when switching from allocentric to egocentric representations, not when the first anchor point was egocentric. In line with previous results, a deficit in processing allocentric representations in non-switching conditions also emerged. These findings suggest that the allocentric deficit in congenital blindness may determine a difficulty in simultaneously maintaining and combining different spatial representations. This deficit alters the capacity to switch between reference frames specifically when the first anchor point is external and not body-centered.
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NASA Astrophysics Data System (ADS)
Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.
2016-06-01
Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.
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Multispectral multisensor image fusion using wavelet transforms
Lemeshewsky, George P.
1999-01-01
Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.
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Research on large spatial coordinate automatic measuring system based on multilateral method
NASA Astrophysics Data System (ADS)
Miao, Dongjing; Li, Jianshuan; Li, Lianfu; Jiang, Yuanlin; Kang, Yao; He, Mingzhao; Deng, Xiangrui
2015-10-01
To measure the spatial coordinate accurately and efficiently in large size range, a manipulator automatic measurement system which based on multilateral method is developed. This system is divided into two parts: The coordinate measurement subsystem is consists of four laser tracers, and the trajectory generation subsystem is composed by a manipulator and a rail. To ensure that there is no laser beam break during the measurement process, an optimization function is constructed by using the vectors between the laser tracers measuring center and the cat's eye reflector measuring center, then an orientation automatically adjust algorithm for the reflector is proposed, with this algorithm, the laser tracers are always been able to track the reflector during the entire measurement process. Finally, the proposed algorithm is validated by taking the calibration of laser tracker for instance: the actual experiment is conducted in 5m × 3m × 3.2m range, the algorithm is used to plan the orientations of the reflector corresponding to the given 24 points automatically. After improving orientations of some minority points with adverse angles, the final results are used to control the manipulator's motion. During the actual movement, there are no beam break occurs. The result shows that the proposed algorithm help the developed system to measure the spatial coordinates over a large range with efficiency.
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A New Era in Geodesy and Cartography: Implications for Landing Site Operations
NASA Technical Reports Server (NTRS)
Duxbury, T. C.
2001-01-01
The Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) global dataset has ushered in a new era for Mars local and global geodesy and cartography. These data include the global digital terrain model (Digital Terrain Model (DTM) radii), the global digital elevation model (Digital Elevation Model (DEM) elevation with respect to the geoid), and the higher spatial resolution individual MOLA ground tracks. Currently there are about 500,000,000 MOLA points and this number continues to grow as MOLA continues successful operations in orbit about Mars, the combined processing of radiometric X-band Doppler and ranging tracking of MGS together with millions of MOLA orbital crossover points has produced global geodetic and cartographic control having a spatial (latitude/longitude) accuracy of a few meters and a topographic accuracy of less than 1 meter. This means that the position of an individual MOLA point with respect to the center-of-mass of Mars is know to an absolute accuracy of a few meters. The positional accuracy of this point in inertial space over time is controlled by the spin rate uncertainty of Mars which is less than 1 km over 10 years that will be improved significantly with the next landed mission.
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NASA Astrophysics Data System (ADS)
Fricke, Katharina; Baschek, Björn; Jenal, Alexander; Kneer, Caspar; Weber, Immanuel; Bongartz, Jens; Wyrwa, Jens; Schöl, Andreas
2016-10-01
This study presents the results from a combined aerial survey performed with a hexacopter and a gyrocopter over a part of the Elbe estuary near Hamburg, Germany. The survey was conducted by the Federal Institute of Hydrology, Germany, and the Fraunhofer Application Center for Multimodal and Airborne Sensors as well as by a contracted engineering company with the aim to acquire spatial thermal infrared (TIR) data of the Hahnöfer Nebenelbe, a branch of the Elbe estuary. Additionally, RGB and NIR data was captured to facilitate the identification of water surfaces and intertidal mudflats. The temperature distribution of the Elbe estuary affects all biological processes and in consequence the oxygen content, which is a key parameter in water quality. The oxygen levels vary in space between the main fairway and side channels. So far, only point measurements are available for monitoring and calibration/validation of water quality models. To better represent this highly dynamic system with a high spatial and temporal variability, tidal streams, heating and cooling, diffusion and mixing processes, spatially distributed data from several points of time within the tidal cycle are necessary. The data acquisition took place during two tidal cycles over two subsequent days in the summer of 2015. While the piloted gyrocopter covered the whole Hahnöfer Nebenelbe seven times, the unmanned hexacopter covered a smaller section of the branch and tidal mudflats with a higher spatial and temporal resolution (16 coverages of the subarea). The gyrocopter data was acquired with a thermal imaging system and processed and georeferenced using the structure from motion algorithm with GPS information from the gyrocopter and optional ground control points. The hexacopter data was referenced based on ground control points and the GPS and position information of the acquisition system. Both datasets from the gyrocopter and the hexacopter are corrected for the effects of the atmosphere and emissivity of the water surface and compared to in situ measurements, taken during the data acquisition. Of particular interest is the effect of the observation angle on the brightness temperature acquired by the wide angle lenses on the platforms, which is up to 40° at the margins of the imagery. Here, both datasets show deviating temperatures, which are probably not due to actual temperature differences. We will discuss the position accuracy achieved over the water areas, the adaptation of atmospheric and emissivity correction to the observation angle and subsequent improvement of the temperature data. With two datasets of the same research area at different resolutions we will investigate the effects of the acquisition platforms, acquisition system and resolutions on the accuracy of the remotely sensed temperatures as well as their ability to represent temperature patterns of tidal currents and mixing processes.
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Elementary model of severe plastic deformation by KoBo process
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gusak, A.; Storozhuk, N.; Danielewski, M., E-mail: daniel@agh.edu.pl
2014-01-21
Self-consistent model of generation, interaction, and annihilation of point defects in the gradient of oscillating stresses is presented. This model describes the recently suggested method of severe plastic deformation by combination of pressure and oscillating rotations of the die along the billet axis (KoBo process). Model provides the existence of distinct zone of reduced viscosity with sharply increased concentration of point defects. This zone provides the high extrusion velocity. Presented model confirms that the Severe Plastic Deformation (SPD) in KoBo may be treated as non-equilibrium phase transition of abrupt drop of viscosity in rather well defined spatial zone. In thismore » very zone, an intensive lateral rotational movement proceeds together with generation of point defects which in self-organized manner make rotation possible by the decrease of viscosity. The special properties of material under KoBo version of SPD can be described without using the concepts of nonequilibrium grain boundaries, ballistic jumps and amorphization. The model can be extended to include different SPD processes.« less
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Midline Body Actions and Leftward Spatial “Aiming” in Patients with Spatial Neglect
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
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NASA Astrophysics Data System (ADS)
Elkadiri, R.; Momm, H.; Yasarer, L.; Armour, G. L.
2017-12-01
Climatic conditions play a major role in physical processes impacting soil and agrochemicals detachment and transportation from/in agricultural watersheds. In addition, these climatic conditions are projected to significantly vary spatially and temporally in the 21st century, leading to vast uncertainties about the future of sediment and non-point source pollution transport in agricultural watersheds. In this study, we selected the sunflower basin in the lower Mississippi River basin, USA to contribute in the understanding of how climate change affects watershed processes and the transport of pollutant loads. The climate projections used in this study were retrieved from the archive of World Climate Research Programme's (WCRP) Coupled Model Intercomparison Phase 5 (CMIP5) project. The CMIP5 dataset was selected because it contains the most up-to-date spatially downscaled and bias corrected climate projections. A subset of ten GCMs representing a range in projected climate were spatially downscaled for the sunflower watershed. Statistics derived from downscaled GCM output representing the 2011-2040, 2041-2070 and 2071-2100 time periods were used to generate maximum/minimum temperature and precipitation on a daily time step using the USDA Synthetic Weather Generator, SYNTOR. These downscaled climate data were then utilized as inputs to run in the Annualized Agricultural Non-Point Source (AnnAGNPS) pollution watershed model to estimate time series of runoff, sediment, and nutrient loads produced from the watershed. For baseline conditions a validated simulation of the watershed was created and validated using historical data from 2000 until 2015.
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High Resolution Temperature Measurement of Liquid Stainless Steel Using Hyperspectral Imaging
Devesse, Wim; De Baere, Dieter; Guillaume, Patrick
2017-01-01
A contactless temperature measurement system is presented based on a hyperspectral line camera that captures the spectra in the visible and near infrared (VNIR) region of a large set of closely spaced points. The measured spectra are used in a nonlinear least squares optimization routine to calculate a one-dimensional temperature profile with high spatial resolution. Measurements of a liquid melt pool of AISI 316L stainless steel show that the system is able to determine the absolute temperatures with an accuracy of 10%. The measurements are made with a spatial resolution of 12 µm/pixel, justifying its use in applications where high temperature measurements with high spatial detail are desired, such as in the laser material processing and additive manufacturing fields. PMID:28067764
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Andéol, Guillaume; Suied, Clara; Scannella, Sébastien; Dehais, Frédéric
2017-06-01
In a multi-talker situation, spatial separation between talkers reduces cognitive processing load: this is the "spatial release of cognitive load". The present study investigated the role played by the relative levels of the talkers on this spatial release of cognitive load. During the experiment, participants had to report the speech emitted by a target talker in the presence of a concurrent masker talker. The spatial separation (0° and 120° angular distance in azimuth) and the relative levels of the talkers (adverse, intermediate, and favorable target-to-masker ratio) were manipulated. The cognitive load was assessed with a prefrontal functional near-infrared spectroscopy. Data from 14 young normal-hearing listeners revealed that the target-to-masker ratio had a direct impact on the spatial release of cognitive load. Spatial separation significantly reduced the prefrontal activity only for the intermediate target-to-masker ratio and had no effect on prefrontal activity for the favorable and the adverse target-to-masker ratios. Therefore, the relative levels of the talkers might be a key point to determine the spatial release of cognitive load and more specifically the prefrontal activity induced by spatial cues in multi-talker situations.
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NASA Astrophysics Data System (ADS)
Park, Byeongjin; Sohn, Hoon
2017-07-01
Laser ultrasonic scanning, especially full-field wave propagation imaging, is attractive for damage visualization thanks to its noncontact nature, sensitivity to local damage, and high spatial resolution. However, its practicality is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated damage visualization technique is developed to visualize damage with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio (SNR) of measured ultrasonic responses. The approximate damage boundary is identified by examining the interactions between ultrasonic waves and damage observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and damage, such as reflections and transmissions, can be better identified in the spatial ultrasonic domain. Then, the area inside the identified damage boundary is visualized as damage. The performance of the proposed damage visualization technique is validated excusing a numerical simulation performed on an aluminum plate with a notch and experiments performed on an aluminum plate with a crack and a wind turbine blade with delamination. The proposed damage visualization technique accelerates the damage visualization process in three aspects: (1) the number of measurements that is necessary for damage visualization is dramatically reduced by a binary search algorithm; (2) the number of averaging that is necessary to achieve a high SNR is reduced by maintaining the wave propagation distance short; and (3) with the proposed technique, the same damage can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.
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Rapid encoding of relationships between spatially remote motion signals.
Maruya, Kazushi; Holcombe, Alex O; Nishida, Shin'ya
2013-02-06
For visual processing, the temporal correlation of remote local motion signals is a strong cue to detect meaningful large-scale structures in the retinal image, because related points are likely to move together regardless of their spatial separation. While the processing of multi-element motion patterns involved in biological motion and optic flow has been studied intensively, the encoding of simpler pairwise relationships between remote motion signals remains poorly understood. We investigated this process by measuring the temporal rate limit for perceiving the relationship of two motion directions presented at the same time at different spatial locations. Compared to luminance or orientation, motion comparison was more rapid. Performance remained very high even when interstimulus separation was increased up to 100°. Motion comparison also remained rapid regardless of whether the two motion directions were similar to or different from each other. The exception was a dramatic slowing when the elements formed an orthogonal "T," in which two motions do not perceptually group together. Motion presented at task-irrelevant positions did not reduce performance, suggesting that the rapid motion comparison could not be ascribed to global optic flow processing. Our findings reveal the existence and unique nature of specialized processing that encodes long-range relationships between motion signals for quick appreciation of global dynamic scene structure.
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NASA Astrophysics Data System (ADS)
Schmitz, Oliver; van der Perk, Marcel; Karssenberg, Derek; Häring, Tim; Jene, Bernhard
2017-04-01
The modelling of pesticide transport through the soil and estimating its leaching to groundwater is essential for an appropriate environmental risk assessment. Pesticide leaching models commonly used in regulatory processes often lack the capability of providing a comprehensive spatial view, as they are implemented as non-spatial point models or only use a few combinations of representative soils to simulate specific plots. Furthermore, their handling of spatial input and output data and interaction with available Geographical Information Systems tools is limited. Therefore, executing several scenarios simulating and assessing the potential leaching on national or continental scale at high resolution is rather inefficient and prohibits the straightforward identification of areas prone to leaching. We present a new pesticide leaching model component of the PyCatch framework developed in PCRaster Python, an environmental modelling framework tailored to the development of spatio-temporal models (http://www.pcraster.eu). To ensure a feasible computational runtime of large scale models, we implemented an elementary field capacity approach to model soil water. Currently implemented processes are evapotranspiration, advection, dispersion, sorption, degradation and metabolite transformation. Not yet implemented relevant additional processes such as surface runoff, snowmelt, erosion or other lateral flows can be integrated with components already implemented in PyCatch. A preliminary version of the model executes a 20-year simulation of soil water processes for Germany (20 soil layers, 1 km2 spatial resolution, and daily timestep) within half a day using a single CPU. A comparison of the soil moisture and outflow obtained from the PCRaster implementation and PELMO, a commonly used pesticide leaching model, resulted in an R2 of 0.98 for the FOCUS Hamburg scenario. We will further discuss the validation of the pesticide transport processes and show case studies applied to European countries.
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Spatial interferences in the electron transport of heavy-fermion materials
NASA Astrophysics Data System (ADS)
Zhang, Shu-feng; Liu, Yu; Song, Hai-Feng; Yang, Yi-feng
2016-08-01
The scanning tunneling microscopy/spectroscopy and the point contact spectroscopy represent major progress in recent heavy-fermion research. Both have revealed important information on the composite nature of the emergent heavy-electron quasiparticles. However, a detailed and thorough microscopic understanding of the similarities and differences in the underlying physical processes of these techniques is still lacking. Here we study the electron transport in the normal state of the periodic Anderson lattice by using the Keldysh nonequilibrium Green's function technique. In addition to the well-known Fano interference between the conduction and f -electron channels, our results further reveal the effect of spatial interference between different spatial paths at the interface on the differential conductance and their interesting interplay with the band features such as the hybridization gap and the Van Hove singularity. We find that the spatial interference leads to a weighted average in the momentum space for the electron transport and could cause suppression of the electronic band features under certain circumstances. In particular, it reduces the capability of probing the f -electron spectral weight near the edges of the hybridization gap for large interface depending on the Fermi surface of the lead. Our results indicate an intrinsic inefficiency of the point contact spectroscopy in probing the f electrons.
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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 ...
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Inventory of File WAFS_blended_2014102006f06.grib2
) [%] 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
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NASA Technical Reports Server (NTRS)
Berendes, Todd; Sengupta, Sailes K.; Welch, Ron M.; Wielicki, Bruce A.; Navar, Murgesh
1992-01-01
A semiautomated methodology is developed for estimating cumulus cloud base heights on the basis of high spatial resolution Landsat MSS data, using various image-processing techniques to match cloud edges with their corresponding shadow edges. The cloud base height is then estimated by computing the separation distance between the corresponding generalized Hough transform reference points. The differences between the cloud base heights computed by these means and a manual verification technique are of the order of 100 m or less; accuracies of 50-70 m may soon be possible via EOS instruments.
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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.
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Toruño, Tania Y.; Stergiopoulos, Ioannis; Coaker, Gitta
2017-01-01
Plants possess large arsenals of immune receptors capable of recognizing all pathogen classes. To cause disease, pathogenic organisms must be able to overcome physical barriers, suppress or evade immune perception, and derive nutrients from host tissues. Consequently, to facilitate some of these processes, pathogens secrete effector proteins that promote colonization. This review covers recent advances in the field of effector biology, focusing on conserved cellular processes targeted by effectors from diverse pathogens. The ability of effectors to facilitate pathogen entry into the host interior, suppress plant immune perception, and alter host physiology for pathogen benefit is discussed. Pathogens also deploy effectors in a spatial and temporal manner, depending on infection stage. Recent advances have also enhanced our understanding of effectors acting in specific plant organs and tissues. Effectors are excellent cellular probes that facilitate insight into biological processes as well as key points of vulnerability in plant immune signaling networks. PMID:27359369
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Impact of Operating Context on the Use of Structure in Air Traffic Controller Cognitive Processes
NASA Technical Reports Server (NTRS)
Davison, Hayley J.; Histon, Jonathan M.; Ragnarsdottir, Margret Dora; Major, Laura M.; Hansman, R. John
2004-01-01
This paper investigates the influence of structure on air traffic controllers cognitive processes in the TRACON, En Route, and Oceanic environments. Radar data and voice command analyses were conducted to support hypotheses generated through observations and interviews conducted at the various facilities. Three general types of structure-based abstractions (standard flows, groupings, and critical points) have been identified as being used in each context, though the details of their application varied in accordance with the constraints of the particular operational environment. Projection emerged as a key cognitive process aided by the structure-based abstractions, and there appears to be a significant difference between how time-based versus spatial-based projection is performed by controllers. It is recommended that consideration be given to the value provided by the structure-based abstractions to the controller as well as to maintain consistency between the type (time or spatial) of information support provided to the controller.
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Using stochastic models to incorporate spatial and temporal variability [Exercise 14
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,...
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ERIC Educational Resources Information Center
Wood, Pamela L.; Quitadamo, Ian J.; DePaepe, James L.; Loverro, Ian
2007-01-01
The WebQuest is a four-step process integrated at appropriate points in the Animal Studies unit. Through the WebQuest, students create a series of habitat maps that build on the knowledge gained from conducting the various activities of the unit. The quest concludes with an evaluation using the WebQuest rubric and an oral presentation of a final…
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Quantifying evenly distributed states in exclusion and nonexclusion processes
NASA Astrophysics Data System (ADS)
Binder, Benjamin J.; Landman, Kerry A.
2011-04-01
Spatial-point data sets, generated from a wide range of physical systems and mathematical models, can be analyzed by counting the number of objects in equally sized bins. We find that the bin counts are related to the Pólya distribution. New measures are developed which indicate whether or not a spatial data set, generated from an exclusion process, is at its most evenly distributed state, the complete spatial randomness (CSR) state. To this end, we define an index in terms of the variance between the bin counts. Limiting values of the index are determined when objects have access to the entire domain and when there are subregions of the domain that are inaccessible to objects. Using three case studies (Lagrangian fluid particles in chaotic laminar flows, cellular automata agents in discrete models, and biological cells within colonies), we calculate the indexes and verify that our theoretical CSR limit accurately predicts the state of the system. These measures should prove useful in many biological applications.
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Banerjee, Chiranjib; Westberg, Michael; Breitenbach, Thomas; Bregnhøj, Mikkel; Ogilby, Peter R
2017-06-06
The oxidation of lipids is an important phenomenon with ramifications for disciplines that range from food science to cell biology. The development and characterization of tools and techniques to monitor lipid oxidation are thus relevant. Of particular significance in this regard are tools that facilitate the study of oxidations at interfaces in heterogeneous samples (e.g., oil-in-water emulsions, cell membranes). In this article, we establish a proof-of-principle for methods to initiate and then monitor such oxidations with high spatial resolution. The experiments were performed using oil-in-water emulsions of polyunsaturated fatty acids (PUFAs) prepared from cod liver oil. We produced singlet oxygen at a point near the oil-water interface of a given PUFA droplet in a spatially localized two-photon photosensitized process. We then followed the oxidation reactions initiated by this process with the fluorescence-based imaging technique of structured illumination microscopy (SIM). We conclude that the approach reported herein has attributes well-suited to the study of lipid oxidation in heterogeneous samples.
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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.
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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.
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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.
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Mapping extent and change in surface mines within the United States for 2001 to 2006
Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.; Parker, Owen P.
2016-01-01
A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi-automated procedure to map the country's mining footprint (30-m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate-to-large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km2 of surface mines were mapped. The footprint increased to 9,181 km2 in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall-to-wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country.
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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.
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Tree species exhibit complex patterns of distribution in bottomland hardwood forests
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...
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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.
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The use of embodied self-rotation for visual and spatial perspective-taking
Surtees, Andrew; Apperly, Ian; Samson, Dana
2013-01-01
Previous research has shown that calculating if something is to someone’s left or right involves a simulative process recruiting representations of our own body in imagining ourselves in the position of the other person (Kessler and Rutherford, 2010). We compared left and right judgements from another’s spatial position (spatial perspective judgements) to judgements of how a numeral appeared from another’s point of view (visual perspective judgements). Experiment 1 confirmed that these visual and spatial perspective judgements involved a process of rotation as they became more difficult with angular disparity between the self and other. There was evidence of some difference between the two, but both showed a linear pattern. Experiment 2 went a step further in showing that these judgements used embodied self rotations, as their difficulty was also dependent on the current position of the self within the world. This effect was significantly stronger in spatial perspective-taking, but was present in both cases. We conclude that embodied self-rotations, through which we actively imagine ourselves assuming someone else’s position in the world can subserve not only reasoning about where objects are in relation to someone else but also how the objects in their environment appear to them. PMID:24204334
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Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama
Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.
2008-01-01
Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.
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Evaluation of terrestrial photogrammetric point clouds derived from thermal imagery
NASA Astrophysics Data System (ADS)
Metcalf, Jeremy P.; Olsen, Richard C.
2016-05-01
Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.
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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.
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A task-irrelevant stimulus attribute affects perception and short-term memory
Huang, Jie; Kahana, Michael J.; Sekuler, Robert
2010-01-01
Selective attention protects cognition against intrusions of task-irrelevant stimulus attributes. This protective function was tested in coordinated psychophysical and memory experiments. Stimuli were superimposed, horizontally and vertically oriented gratings of varying spatial frequency; only one orientation was task relevant. Experiment 1 demonstrated that a task-irrelevant spatial frequency interfered with visual discrimination of the task-relevant spatial frequency. Experiment 2 adopted a two-item Sternberg task, using stimuli that had been scaled to neutralize interference at the level of vision. Despite being visually neutralized, the task-irrelevant attribute strongly influenced recognition accuracy and associated reaction times (RTs). This effect was sharply tuned, with the task-irrelevant spatial frequency having an impact only when the task-relevant spatial frequencies of the probe and study items were highly similar to one another. Model-based analyses of judgment accuracy and RT distributional properties converged on the point that the irrelevant orientation operates at an early stage in memory processing, not at a later one that supports decision making. PMID:19933454
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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
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Spatial-frequency dependent binocular imbalance in amblyopia
Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C.; Bex, Peter J.
2015-01-01
While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy. PMID:26603125
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Spatial-frequency dependent binocular imbalance in amblyopia.
Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C; Bex, Peter J
2015-11-25
While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy.
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Li, Kevin; Vandermeer, John H; Perfecto, Ivette
2016-05-01
Spatial patterns in ecology can be described as reflective of environmental heterogeneity (exogenous), or emergent from dynamic relationships between interacting species (endogenous), but few empirical studies focus on the combination. The spatial distribution of the nests of Azteca sericeasur, a keystone tropical arboreal ant, is thought to form endogenous spatial patterns among the shade trees of a coffee plantation through self-regulating interactions with controlling agents (i.e. natural enemies). Using inhomogeneous point process models, we found evidence for both types of processes in the spatial distribution of A. sericeasur. Each year's nest distribution was determined mainly by a density-dependent relationship with the previous year's lagged nest density; but using a novel application of a Thomas cluster process to account for the effects of nest clustering, we found that nest distribution also correlated significantly with tree density in the later years of the study. This coincided with the initiation of agricultural intensification and tree felling on the coffee farm. The emergence of this significant exogenous effect, along with the changing character of the density-dependent effect of lagged nest density, provides clues to the mechanism behind a unique phenomenon observed in the plot, that of an increase in nest population despite resource limitation in nest sites. Our results have implications in coffee agroecological management, as this system provides important biocontrol ecosystem services. Further research is needed, however, to understand the effective scales at which these relationships occur.
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Multi-Point Measurements to Characterize Radiation Belt Electron Precipitation Loss
NASA Astrophysics Data System (ADS)
Blum, L. W.
2017-12-01
Multipoint measurements in the inner magnetosphere allow the spatial and temporal evolution of various particle populations and wave modes to be disentangled. To better characterize and quantify radiation belt precipitation loss, we utilize multi-point measurements both to study precipitating electrons directly as well as the potential drivers of this loss process. Magnetically conjugate CubeSat and balloon measurements are combined to estimate of the temporal and spatial characteristics of dusk-side precipitation features and quantify loss due to these events. To then understand the drivers of precipitation events, and what determines their spatial structure, we utilize measurements from the dual Van Allen Probes to estimate spatial and temporal scales of various wave modes in the inner magnetosphere, and compare these to precipitation characteristics. The structure, timing, and spatial extent of waves are compared to those of MeV electron precipitation during a few individual events to determine when and where EMIC waves cause radiation belt electron precipitation. Magnetically conjugate measurements provide observational support of the theoretical picture of duskside interaction of EMIC waves and MeV electrons leading to radiation belt loss. Finally, understanding the drivers controlling the spatial scales of wave activity in the inner magnetosphere is critical for uncovering the underlying physics behind the wave generation as well as for better predicting where and when waves will be present. Again using multipoint measurements from the Van Allen Probes, we estimate the spatial and temporal extents and evolution of plasma structures and their gradients in the inner magnetosphere, to better understand the drivers of magnetospheric wave characteristic scales. In particular, we focus on EMIC waves and the plasma parameters important for their growth, namely cold plasma density and cool and warm ion density, anisotropy, and composition.
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da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina
2015-01-01
Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150
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Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response
NASA Astrophysics Data System (ADS)
Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.
2016-06-01
Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.
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NASA Astrophysics Data System (ADS)
Grochocka, M.
2013-12-01
Mobile laser scanning is dynamically developing measurement technology, which is becoming increasingly widespread in acquiring three-dimensional spatial information. Continuous technical progress based on the use of new tools, technology development, and thus the use of existing resources in a better way, reveals new horizons of extensive use of MLS technology. Mobile laser scanning system is usually used for mapping linear objects, and in particular the inventory of roads, railways, bridges, shorelines, shafts, tunnels, and even geometrically complex urban spaces. The measurement is done from the perspective of use of the object, however, does not interfere with the possibilities of movement and work. This paper presents the initial results of the segmentation data acquired by the MLS. The data used in this work was obtained as part of an inventory measurement infrastructure railway line. Measurement of point clouds was carried out using a profile scanners installed on the railway platform. To process the data, the tools of 'open source' Point Cloud Library was used. These tools allow to use templates of programming libraries. PCL is an open, independent project, operating on a large scale for processing 2D/3D image and point clouds. Software PCL is released under the terms of the BSD license (Berkeley Software Distribution License), which means it is a free for commercial and research use. The article presents a number of issues related to the use of this software and its capabilities. Segmentation data is based on applying the templates library pcl_ segmentation, which contains the segmentation algorithms to separate clusters. These algorithms are best suited to the processing point clouds, consisting of a number of spatially isolated regions. Template library performs the extraction of the cluster based on the fit of the model by the consensus method samples for various parametric models (planes, cylinders, spheres, lines, etc.). Most of the mathematical operation is carried out on the basis of Eigen library, a set of templates for linear algebra.
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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.
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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.
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Geostatistics and spatial analysis in biological anthropology.
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.
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NASA Astrophysics Data System (ADS)
Rasera, L. G.; Mariethoz, G.; Lane, S. N.
2017-12-01
Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.
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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.
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New approaches for calculating Moran's index of spatial autocorrelation.
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.
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Characterizing Spatial Organization of Cell Surface Receptors in Human Breast Cancer with STORM
NASA Astrophysics Data System (ADS)
Lyall, Evan; Chapman, Matthew R.; Sohn, Lydia L.
2012-02-01
Regulation and control of complex biological functions are dependent upon spatial organization of biological structures at many different length scales. For instance Eph receptors and their ephrin ligands bind when opposing cells come into contact during development, resulting in spatial organizational changes on the nanometer scale that lead to changes on the macro scale, in a process known as organ morphogenesis. One technique able to probe this important spatial organization at both the nanometer and micrometer length scales, including at cell-cell junctions, is stochastic optical reconstruction microscopy (STORM). STORM is a technique that localizes individual fluorophores based on the centroids of their point spread functions and then reconstructs a composite image to produce super resolved structure. We have applied STORM to study spatial organization of the cell surface of human breast cancer cells, specifically the organization of tyrosine kinase receptors and chemokine receptors. A better characterization of spatial organization of breast cancer cell surface proteins is necessary to fully understand the tumorigenisis pathways in the most common malignancy in United States women.
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An ArcGIS approach to include tectonic structures in point data regionalization.
Darsow, Andreas; Schafmeister, Maria-Theresia; Hofmann, Thilo
2009-01-01
Point data derived from drilling logs must often be regionalized. However, aquifers may show discontinuous surface structures, such as the offset of an aquitard caused by tectonic faults. One main challenge has been to incorporate these structures into the regionalization process of point data. We combined ordinary kriging and inverse distance weighted (IDW) interpolation to account for neotectonic structures in the regionalization process. The study area chosen to test this approach is the largest porous aquifer in Austria. It consists of three basins formed by neotectonic events and delimited by steep faults with a vertical offset of the aquitard up to 70 m within very short distances. First, ordinary kriging was used to incorporate the characteristic spatial variability of the aquitard location by means of a variogram. The tectonic faults could be included into the regionalization process by using breaklines with buffer zones. All data points inside the buffer were deleted. Last, IDW was performed, resulting in an aquitard map representing the discontinuous surface structures. This approach enables one to account for such surfaces using the standard software package ArcGIS; therefore, it could be adopted in many practical applications.
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Separation processes during binary monotectic alloy production
NASA Technical Reports Server (NTRS)
Frazier, D. O.; Facemire, B. R.; Kaukler, W. F.; Witherow, W. K.; Fanning, U.
1984-01-01
Observation of microgravity solidification processes indicates that outside of sedimentation, at least two other important effects can separate the phases: critical-point wetting and spreading; and thermal migration of second-phase droplets due to interfacial tension gradients. It is difficult to study these surface tension effects while in a unit gravity field. In order to investigate the processes occurring over a temperature range, i.e., between a consolute point and the monotectic temperature, it is necessary to use a low-gravity environment. The MSFC drop tube (and tower), the ballistic trajectory KC-135 airplane, and the Space Shuttle are ideal facilities to aid formation and testing of hypotheses. Much of the early work in this area focuses on transparent materials so that process dynamics may be studied by optical techniques such as photography for viewing macro-processes; holography for studying diffusional growth; spinodal decomposition and coalescence; ellipsometry for surface wetting and spreading effects; and interferometry and spectroscopy for small-scale spatial resolution of concentration profiles.
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Paavilainen, Petri; Illi, Janne; Moisseinen, Nella; Niinisalo, Maija; Ojala, Karita; Reinikainen, Johanna; Vainio, Lari
2016-06-01
The task-irrelevant spatial location of a cue stimulus affects the processing of a subsequent target. This "Posner effect" has been explained by an exogenous attention shift to the spatial location of the cue, improving perceptual processing of the target. We studied whether the left/right location of task-irrelevant and uninformative tones produces cueing effects on the processing of visual targets. Tones were presented randomly from left or right. In the first condition, the subsequent visual target, requiring response either with the left or right hand, was presented peripherally to left or right. In the second condition, the target was a centrally presented left/right-pointing arrow, indicating the response hand. In the third condition, the tone and the central arrow were presented simultaneously. Data were recorded on compatible (the tone location and the response hand were the same) and incompatible trials. Reaction times were longer on incompatible than on compatible trials. The results of the second and third conditions are difficult to explain with the attention-shift model emphasizing improved perceptual processing in the cued location, as the central target did not require any location-based processing. Consequently, as an alternative explanation they suggest response priming in the hand corresponding to the spatial location of the tone. Simultaneous lateralized readiness potential (LRP) recordings were consistent with the behavioral data, the tone cues eliciting on incompatible trials a fast preparation for the incorrect response and on compatible trials preparation for the correct response. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Mahmoudabadi, H.; Briggs, G.
2016-12-01
Gridded data sets, such as geoid models or datum shift grids, are commonly used in coordinate transformation algorithms. Grid files typically contain known or measured values at regular fixed intervals. The process of computing a value at an unknown location from the values in the grid data set is called "interpolation". Generally, interpolation methods predict a value at a given point by computing a weighted average of the known values in the neighborhood of the point. Geostatistical Kriging is a widely used interpolation method for irregular networks. Kriging interpolation first analyzes the spatial structure of the input data, then generates a general model to describe spatial dependencies. This model is used to calculate values at unsampled locations by finding direction, shape, size, and weight of neighborhood points. Because it is based on a linear formulation for the best estimation, Kriging it the optimal interpolation method in statistical terms. The Kriging interpolation algorithm produces an unbiased prediction, as well as the ability to calculate the spatial distribution of uncertainty, allowing you to estimate the errors in an interpolation for any particular point. Kriging is not widely used in geospatial applications today, especially applications that run on low power devices or deal with large data files. This is due to the computational power and memory requirements of standard Kriging techniques. In this paper, improvements are introduced in directional kriging implementation by taking advantage of the structure of the grid files. The regular spacing of points simplifies finding the neighborhood points and computing their pairwise distances, reducing the the complexity and improving the execution time of the Kriging algorithm. Also, the proposed method iteratively loads small portion of interest areas in different directions to reduce the amount of required memory. This makes the technique feasible on almost any computer processor. Comparison between kriging and other standard interpolation methods demonstrated more accurate estimations in less denser data files.
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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.
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Campos, Jennifer L.; Siegle, Joshua H.; Mohler, Betty J.; Bülthoff, Heinrich H.; Loomis, Jack M.
2009-01-01
Background The extent to which actual movements and imagined movements maintain a shared internal representation has been a matter of much scientific debate. Of the studies examining such questions, few have directly compared actual full-body movements to imagined movements through space. Here we used a novel continuous pointing method to a) provide a more detailed characterization of self-motion perception during actual walking and b) compare the pattern of responding during actual walking to that which occurs during imagined walking. Methodology/Principal Findings This continuous pointing method requires participants to view a target and continuously point towards it as they walk, or imagine walking past it along a straight, forward trajectory. By measuring changes in the pointing direction of the arm, we were able to determine participants' perceived/imagined location at each moment during the trajectory and, hence, perceived/imagined self-velocity during the entire movement. The specific pattern of pointing behaviour that was revealed during sighted walking was also observed during blind walking. Specifically, a peak in arm azimuth velocity was observed upon target passage and a strong correlation was observed between arm azimuth velocity and pointing elevation. Importantly, this characteristic pattern of pointing was not consistently observed during imagined self-motion. Conclusions/Significance Overall, the spatial updating processes that occur during actual self-motion were not evidenced during imagined movement. Because of the rich description of self-motion perception afforded by continuous pointing, this method is expected to have significant implications for several research areas, including those related to motor imagery and spatial cognition and to applied fields for which mental practice techniques are common (e.g. rehabilitation and athletics). PMID:19907655
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NASA Astrophysics Data System (ADS)
Lindley, S. J.; Walsh, T.
There are many modelling methods dedicated to the estimation of spatial patterns in pollutant concentrations, each with their distinctive advantages and disadvantages. The derivation of a surface of air quality values from monitoring data alone requires the conversion of point-based data from a limited number of monitoring stations to a continuous surface using interpolation. Since interpolation techniques involve the estimation of data at un-sampled points based on calculated relationships between data measured at a number of known sample points, they are subject to some uncertainty, both in terms of the values estimated and their spatial distribution. These uncertainties, which are incorporated into many empirical and semi-empirical mapping methodologies, could be recognised in any further usage of the data and also in the assessment of the extent of an exceedence of an air quality standard and the degree of exposure this may represent. There is a wide range of available interpolation techniques and the differences in the characteristics of these result in variations in the output surfaces estimated from the same set of input points. The work presented in this paper provides an examination of uncertainties through the application of a number of interpolation techniques available in standard GIS packages to a case study nitrogen dioxide data set for the Greater Manchester conurbation in northern England. The implications of the use of different techniques are discussed through application to hourly concentrations during an air quality episode and annual average concentrations in 2001. Patterns of concentrations demonstrate considerable differences in the estimated spatial pattern of maxima as the combined effects of chemical processes, topography and meteorology. In the case of air quality episodes, the considerable spatial variability of concentrations results in large uncertainties in the surfaces produced but these uncertainties vary widely from area to area. In view of the uncertainties with classical techniques research is ongoing to develop alternative methods which should in time help improve the suite of tools available to air quality managers.
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Designing efficient surveys: spatial arrangement of sample points for detection of invasive species
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...
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NASA Astrophysics Data System (ADS)
Liu, W. C.; Wu, B.
2018-04-01
High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.
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Spatially distributed effects of mental exhaustion on resting-state FMRI networks.
Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer
2014-01-01
Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.
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Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.
2006-01-01
There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.
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Ma, Zhenling; Wu, Xiaoliang; Yan, Li; Xu, Zhenliang
2017-01-26
With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important means to acquire geospatial information. This paper explores geometric processing using satellite imagery without ground control points (GCPs). The outcome of spatial triangulation is introduced for geo-positioning as repeated observation. Results from combining block adjustment with non-oriented new images indicate the feasibility of geometric positioning with the repeated observation. GCPs are a must when high accuracy is demanded in conventional block adjustment; the accuracy of direct georeferencing with repeated observation without GCPs is superior to conventional forward intersection and even approximate to conventional block adjustment with GCPs. The conclusion is drawn that taking the existing oriented imagery as repeated observation enhances the effective utilization of previous spatial triangulation achievement, which makes the breakthrough for repeated observation to improve accuracy by increasing the base-height ratio and redundant observation. Georeferencing tests using data from multiple sensors and platforms with the repeated observation will be carried out in the follow-up research.
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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.
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Retinal image quality and visual stimuli processing by simulation of partial eye cataract
NASA Astrophysics Data System (ADS)
Ozolinsh, Maris; Danilenko, Olga; Zavjalova, Varvara
2016-10-01
Visual stimuli were demonstrated on a 4.3'' mobile phone screen inside a "Virtual Reality" adapter that allowed separation of the left and right eye visual fields. Contrast of the retina image thus can be controlled by the image on the phone screen and parallel to that at appropriate geometry by the AC voltage applied to scattering PDLC cell inside the adapter. Such optical pathway separation allows to demonstrate to both eyes spatially variant images, that after visual binocular fusion acquire their characteristic indications. As visual stimuli we used grey and different color (two opponent components to vision - red-green in L*a*b* color space) spatially periodical stimuli for left and right eyes; and with spatial content that by addition or subtraction resulted as clockwise or counter clockwise slanted Gabor gratings. We performed computer modeling with numerical addition or subtraction of signals similar to processing in brain via stimuli input decomposition in luminance and color opponency components. It revealed the dependence of the perception psychophysical equilibrium point between clockwise or counter clockwise perception of summation on one eye image contrast and color saturation, and on the strength of the retinal aftereffects. Existence of a psychophysical equilibrium point in perception of summation is only in the presence of a prior adaptation to a slanted periodical grating and at the appropriate slant orientation of adaptation grating and/or at appropriate spatial grating pattern phase according to grating nods. Actual observer perception experiments when one eye images were deteriorated by simulated cataract approved the shift of mentioned psychophysical equilibrium point on the degree of artificial cataract. We analyzed also the mobile devices stimuli emission spectra paying attention to areas sensitive to macula pigments absorption spectral maxima and blue areas where the intense irradiation can cause in abnormalities in periodic melatonin regeneration and deviations in regular circadian rhythms. Therefore participants in vision studies using "Virtual Reality" appliances with fixed vision fields and emitting a spike liked spectral bands (on basis of OLED and AMOLED diodes) different from spectra of ambient illuminators should be accordingly warned about potential health risks.
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Streak camera based SLR receiver for two color atmospheric measurements
NASA Technical Reports Server (NTRS)
Varghese, Thomas K.; Clarke, Christopher; Oldham, Thomas; Selden, Michael
1993-01-01
To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.
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Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land
NASA Astrophysics Data System (ADS)
Silasari, Rasmiaditya; Blöschl, Günter
2014-05-01
Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.
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Probabilistic cluster labeling of imagery data
NASA Technical Reports Server (NTRS)
Chittineni, C. B. (Principal Investigator)
1980-01-01
The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented.
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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.
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NASA Astrophysics Data System (ADS)
Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.
2013-12-01
In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.
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Privacy protection versus cluster detection in spatial epidemiology.
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.
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Doubly stochastic Poisson process models for precipitation at fine time-scales
NASA Astrophysics Data System (ADS)
Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao
2012-09-01
This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.
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NASA Astrophysics Data System (ADS)
Hübner, R.; Heller, K.; Günther, T.; Kleber, A.
2015-01-01
Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.
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A scrutiny of heterogeneity at the TCE Source Area BioREmediation (SABRE) test site
NASA Astrophysics Data System (ADS)
Rivett, M.; Wealthall, G. P.; Mcmillan, L. A.; Zeeb, P.
2015-12-01
A scrutiny of heterogeneity at the UK's Source Area BioREmediation (SABRE) test site is presented to better understand how spatial heterogeneity in subsurface properties and process occurrence may constrain performance of enhanced in-situ bioremediation (EISB). The industrial site contained a 25 to 45 year old trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) that was exceptionally well monitored via a network of multilevel samplers and high resolution core sampling. Moreover, monitoring was conducted within a 3-sided sheet-pile cell that allowed a controlled streamtube of flow to be drawn through the source zone by an extraction well. We primarily focus on the longitudinal transect of monitoring along the length of the cell that provides a 200 groundwater point sample slice along the streamtube of flow through the DNAPL source zone. TCE dechlorination is shown to be significant throughout the cell domain, but spatially heterogeneous in occurrence and progress of dechlorination to lesser chlorinated ethenes - it is this heterogeneity in dechlorination that we primarily scrutinise. We illustrate the diagnostic use of the relative occurrence of TCE parent and daughter compounds to confirm: dechlorination in close proximity to DNAPL and enhanced during the bioremediation; persistent layers of DNAPL into which gradients of dechlorination products are evident; fast flowpaths through the source zone where dechlorination is less evident; and, the importance of underpinning flow regime understanding on EISB performance. Still, even with such spatial detail, there remains uncertainty over the dataset interpretation. These includes poor closure of mass balance along the cell length for the multilevel sampler based monitoring and points to needs to still understand lateral flows (even in the constrained cell), even greater spatial resolution of point monitoring and potentially, not easily proven, ethene degradation loss.
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Point process statistics in atom probe tomography.
Philippe, T; Duguay, S; Grancher, G; Blavette, D
2013-09-01
We present a review of spatial point processes as statistical models that we have designed for the analysis and treatment of atom probe tomography (APT) data. As a major advantage, these methods do not require sampling. The mean distance to nearest neighbour is an attractive approach to exhibit a non-random atomic distribution. A χ(2) test based on distance distributions to nearest neighbour has been developed to detect deviation from randomness. Best-fit methods based on first nearest neighbour distance (1 NN method) and pair correlation function are presented and compared to assess the chemical composition of tiny clusters. Delaunay tessellation for cluster selection has been also illustrated. These statistical tools have been applied to APT experiments on microelectronics materials. Copyright © 2012 Elsevier B.V. All rights reserved.
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Spatial dependence of extreme rainfall
NASA Astrophysics Data System (ADS)
Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri
2017-05-01
This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.
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Spatial ecology of refuge selection by an herbivore under risk of predation
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.
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Modeling spatially-varying landscape change points in species occurrence thresholds
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.
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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.
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Stelzenmüller, V; Diekmann, R; Bastardie, F; Schulze, T; Berkenhagen, J; Kloppmann, M; Krause, G; Pogoda, B; Buck, B H; Kraus, G
2016-12-01
Worldwide the renewable energy sector is expanding at sea to address increasing demands. Recently the race for space in heavily used areas such as the North Sea triggered the proposal of co-locating other activities such as aquaculture or fisheries with passive gears in offshore wind farms (OWFs). Our interdisciplinary approach combined a quantification of spatial overlap of activities by using Vessel Monitoring System and logbook data with a stakeholder consultation to conclude and verify on the actual feasibility of co-location. In the German Exclusive Economic Zone (EEZ) of the North Sea up to 90% of Danish and 40% of German annual gillnet fleet landings of plaice overlapped with areas where OWFs are developed. Our results indicated further that the international gillnet fishery could lose up to 50% in landings within the North Sea German EEZ when OWF areas are closed entirely for fisheries. No spatial overlap was found for UK potters targeting brown crab in the German EEZ. We further identified a number of key issues and obstacles that to date hinder an actual implementation of co-location as a measure in the marine spatial planning process: defining the legal base; implementation of safety regulations; delineation of minimum requirements for fishing vessels such as capacities, quotas, technical equipment; implementation of a licensing process; and scoping for financial subsidies to set up business. The stakeholder consultation verified the scientific findings and highlighted that all those points need to be addressed in a planning process. In the German EEZ we have shown that the socio-economic importance of spatial overlap varies within planning boundaries. Therefore we recommend an interdisciplinary bottom-up approach when scoping for suitable areas of co-location. Hence, an informed marine spatial planning process requires comprehensive and spatial explicit socio-economic viability studies factoring in also ecological effects of OWFs on target species. Copyright © 2016 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim
2009-02-01
Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.
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Wavelength dependence in radio-wave scattering and specular-point theory
NASA Technical Reports Server (NTRS)
Tyler, G. L.
1976-01-01
Radio-wave scattering from natural surfaces contains a strong quasispecular component that at fixed wavelengths is consistent with specular-point theory, but often has a strong wavelength dependence that is not predicted by physical optics calculations under the usual limitations of specular-point models. Wavelength dependence can be introduced by a physical approximation that preserves the specular-point assumptions with respect to the radii of curvature of a fictitious, effective scattering surface obtained by smoothing the actual surface. A uniform low-pass filter model of the scattering process yields explicit results for the effective surface roughness versus wavelength. Interpretation of experimental results from planetary surfaces indicates that the asymptotic surface height spectral densities fall at least as fast as an inverse cube of spatial frequency. Asymptotic spectral densities for Mars and portions of the lunar surface evidently decrease more rapidly.
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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.
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NASA Astrophysics Data System (ADS)
Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe
2018-06-01
In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.
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Spatial Rack Drives Pitch Configurations: Essence and Content
NASA Astrophysics Data System (ADS)
Abadjieva, Emilia; Abadjiev, Valentin; Naganawa, Akihiro
2018-03-01
The practical realization of all types of mechanical motions converters is preceded by solving the task of their kinematic synthesis. In this way, the determination of the optimal values of the constant geometrical parameters of the chosen structure of the created mechanical system is achieved. The searched result is a guarantee of the preliminary defined kinematic characteristics of the synthesized transmission and in the first place, to guarantee the law of motions transformation. The kinematic synthesis of mechanical transmissions is based on adequate mathematical modelling of the process of motions transformation and on the object, realizing this transformation. Basic primitives of the mathematical models for synthesis upon a pitch contact point are geometric and kinematic pitch configurations. Their dimensions and mutual position in space are the input parameters for the processes of design and elaboration of the synthesized mechanical device. The study presented here is a brief review of the theory of pitch configurations. It is an independent scientific branch of the spatial gearing theory (theory of hyperboloid gears). On this basis, the essence and content of the corresponding primitives, applicable to the synthesis of spatial rack drives, are defined.
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Modes of Visual Recognition and Perceptually Relevant Sketch-based Coding for Images
NASA Technical Reports Server (NTRS)
Jobson, Daniel J.
1991-01-01
A review of visual recognition studies is used to define two levels of information requirements. These two levels are related to two primary subdivisions of the spatial frequency domain of images and reflect two distinct different physical properties of arbitrary scenes. In particular, pathologies in recognition due to cerebral dysfunction point to a more complete split into two major types of processing: high spatial frequency edge based recognition vs. low spatial frequency lightness (and color) based recognition. The former is more central and general while the latter is more specific and is necessary for certain special tasks. The two modes of recognition can also be distinguished on the basis of physical scene properties: the highly localized edges associated with reflectance and sharp topographic transitions vs. smooth topographic undulation. The extreme case of heavily abstracted images is pursued to gain an understanding of the minimal information required to support both modes of recognition. Here the intention is to define the semantic core of transmission. This central core of processing can then be fleshed out with additional image information and coding and rendering techniques.
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NASA Astrophysics Data System (ADS)
Hughes, N. P.; Perry, C. C.; Williams, R. J. P.; Watt, F.; Grime, G. W.
1988-03-01
Proton-induced X-ray emission (PIXE) combined with the Oxford scanning proton microprobe (SPM) was used to investigate the abundance and spatial distribution of inorganic elements in mineralising stinging emergences from the leaf of the Common Stinging Nettle, Urtica dioica L. Elemental maps and point analytical data were collected for emergences at two stages of maturity. In all emergences calcium and silicon were spatially organised and present at high concentration. The inorganic elements K, P, S and Mn were also spatially organised during mineralisation, but at maturity these elements were present only at background levels and then showed no specific localisation. The observed changes in the inorganic content of the emergences are obviously related to the mineralisation processes. The possible biochemical significance of the distribution of the elements is discussed.
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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.
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Self-Similar Spin Images for Point Cloud Matching
NASA Astrophysics Data System (ADS)
Pulido, Daniel
The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.
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Resolving ability and image discretization in the visual system.
Shelepin, Yu E; Bondarko, V M
2004-02-01
Psychophysiological studies were performed to measure the spatial threshold for resolution of two "points" and the thresholds for discriminating their orientations depending on the distance between the two points. Data were compared with the scattering of the "point" by the eye's optics, the packing density of cones in the fovea, and the characteristics of the receptive fields of ganglion cells in the foveal area of the retina and neurons in the corresponding projection zones of the primary visual cortex. The effective zone was shown to have to contain a scattering function for several receptors, as this allowed preliminary blurring of the image by the eye's optics to decrease the subsequent (at the level of receptors) discretization noise created by a matrix of receptors. The concordance of these parameters supports the optical operation of the spatial elements of the neural network determining the resolving ability of the visual system at different levels of visual information processing. It is suggested that the special geometry of the receptive fields of neurons in the striate cortex, which are concordant with the statistics of natural scenes, results in a further increase in the signal:noise ratio.
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D Data Acquisition Based on Opencv for Close-Range Photogrammetry Applications
NASA Astrophysics Data System (ADS)
Jurjević, L.; Gašparović, M.
2017-05-01
Development of the technology in the area of the cameras, computers and algorithms for 3D the reconstruction of the objects from the images resulted in the increased popularity of the photogrammetry. Algorithms for the 3D model reconstruction are so advanced that almost anyone can make a 3D model of photographed object. The main goal of this paper is to examine the possibility of obtaining 3D data for the purposes of the close-range photogrammetry applications, based on the open source technologies. All steps of obtaining 3D point cloud are covered in this paper. Special attention is given to the camera calibration, for which two-step process of calibration is used. Both, presented algorithm and accuracy of the point cloud are tested by calculating the spatial difference between referent and produced point clouds. During algorithm testing, robustness and swiftness of obtaining 3D data is noted, and certainly usage of this and similar algorithms has a lot of potential in the real-time application. That is the reason why this research can find its application in the architecture, spatial planning, protection of cultural heritage, forensic, mechanical engineering, traffic management, medicine and other sciences.
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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.
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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.
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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
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LWIR hyperspectral micro-imager for detection of trace explosive particles
NASA Astrophysics Data System (ADS)
Bingham, Adam L.; Lucey, Paul G.; Akagi, Jason T.; Hinrichs, John L.; Knobbe, Edward T.
2014-05-01
Chemical micro-imaging is a powerful tool for the detection and identification of analytes of interest against a cluttered background (i.e. trace explosive particles left behind in a fingerprint). While a variety of groups have demonstrated the efficacy of Raman instruments for these applications, point by point or line by line acquisition of a targeted field of view (FOV) is a time consuming process if it is to be accomplished with useful spatial resolutions. Spectrum Photonics has developed and demonstrated a prototype system utilizing long wave infrared hyperspectral microscopy, which enables the simultaneous collection of LWIR reflectance spectra from 8-14 μm in a 30 x 7 mm FOV with 30 μm spatial resolution in 30 s. An overview of the uncooled Sagnac-based LWIR HSM system will be given, emphasizing the benefits of this approach. Laboratory Hyperspectral data collected from custom mixtures and fingerprint residues is shown, focusing on the ability of the LWIR chemical micro-imager to detect chemicals of interest out of a cluttered background.
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NASA Astrophysics Data System (ADS)
Corwin, Ivan; Dimitrov, Evgeni
2018-05-01
We consider the ASEP and the stochastic six vertex model started with step initial data. After a long time, T, it is known that the one-point height function fluctuations for these systems are of order T 1/3. We prove the KPZ prediction of T 2/3 scaling in space. Namely, we prove tightness (and Brownian absolute continuity of all subsequential limits) as T goes to infinity of the height function with spatial coordinate scaled by T 2/3 and fluctuations scaled by T 1/3. The starting point for proving these results is a connection discovered recently by Borodin-Bufetov-Wheeler between the stochastic six vertex height function and the Hall-Littlewood process (a certain measure on plane partitions). Interpreting this process as a line ensemble with a Gibbsian resampling invariance, we show that the one-point tightness of the top curve can be propagated to the tightness of the entire curve.
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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.
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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.
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Moving to higher ground: The dynamic field theory and the dynamics of visual cognition
Johnson, Jeffrey S.; Spencer, John P.; Schöner, Gregor
2009-01-01
In the present report, we describe a new dynamic field theory that captures the dynamics of visuo-spatial cognition. This theory grew out of the dynamic systems approach to motor control and development, and is grounded in neural principles. The initial application of dynamic field theory to issues in visuo-spatial cognition extended concepts of the motor approach to decision making in a sensori-motor context, and, more recently, to the dynamics of spatial cognition. Here we extend these concepts still further to address topics in visual cognition, including visual working memory for non-spatial object properties, the processes that underlie change detection, and the ‘binding problem’ in vision. In each case, we demonstrate that the general principles of the dynamic field approach can unify findings in the literature and generate novel predictions. We contend that the application of these concepts to visual cognition avoids the pitfalls of reductionist approaches in cognitive science, and points toward a formal integration of brains, bodies, and behavior. PMID:19173013
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In situ analysis of the organic framework in the prismatic layer of mollusc shell.
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.
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Sex differences in the weighting of metric and categorical information in spatial location memory.
Holden, Mark P; Duff-Canning, Sarah J; Hampson, Elizabeth
2015-01-01
According to the Category Adjustment model, remembering a spatial location involves the Bayesian combination of fine-grained and categorical information about that location, with each cue weighted by its relative certainty. However, individuals may differ in terms of their certainty about each cue, resulting in estimates that rely more or less on metric or categorical representations. To date, though, very little research has examined individual differences in the relative weighting of these cues in spatial location memory. Here, we address this gap in the literature. Participants were asked to recall point locations in uniform geometric shapes and in photographs of complex, natural scenes. Error patterns were analyzed for evidence of a sex difference in the relative use of metric and categorical information. As predicted, women placed relatively more emphasis on categorical cues, while men relied more heavily on metric information. Location reproduction tasks showed a similar effect, implying that the sex difference arises early in spatial processing, possibly during encoding.
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Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido
2015-02-01
In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications. Copyright © 2014 Elsevier Inc. All rights reserved.
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Privacy Protection Versus Cluster Detection in Spatial Epidemiology
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
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Klopp, Christine; Garcia, Carlos; Schulman, Allan H; Ward, Christopher P; Tartar, Jaime L
2012-01-01
Spatial learning is shown to be influenced by acute stress in both human and other animals. However, the intricacies of this relationship are unclear. Based on prior findings we hypothesized that compared to a control condition, a social stress condition would not affect spatial learning performance despite elevated biochemical markers of stress. The present study tested the effects of social stress in human males and females on a subsequent spatial learning task. Social stress induction consisted of evaluative stress (the Trier Social Stress Test, TSST) compared to a placebo social stress. Compared to the placebo condition, the TSST resulted in significantly elevated cortisol and alpha amylase levels at multiple time points following stress induction. In accord, cognitive appraisal measures also showed that participants in the TSST group experienced greater perceived stress compared to the placebo group. However, there were no group differences in performance on a spatial learning task. Our findings suggest that unlike physiological stress, social stress does not result in alterations in spatial learning in humans. It is possible that moderate social evaluative stress in humans works to prevent acute stress-mediated alterations in hippocampal learning processes..
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Shiels, Keri; Hawk, Larry W; Lysczek, Cynthia L; Tannock, Rosemary; Pelham, William E; Spencer, Sarah V; Gangloff, Brian P; Waschbusch, Daniel A
2008-08-01
Working memory is one of several putative core neurocognitive processes in attention-deficit/hyperactivity disorder (ADHD). The present work seeks to determine whether visual-spatial working memory is sensitive to motivational incentives, a laboratory analogue of behavioral treatment. Participants were 21 children (ages 7-10) with a diagnosis of ADHD-combined type. Participants completed a computerized spatial span task designed to assess storage of visual-spatial information (forward span) and manipulation of the stored information (backward span). The spatial span task was completed twice on the same day, once with a performance-based incentive (trial-wise feedback and points redeemable for prizes) and once without incentives. Participants performed significantly better on the backward span when rewarded for correct responses, compared to the no incentive condition. However, incentives had no effect on performance during the forward span. These findings may suggest the use of motivational incentives improved manipulation, but not storage, of visual-spatial information among children with ADHD. Possible explanations for the differential incentive effects are discussed, including the possibility that incentives prevented a vigilance decrement as task difficulty and time on task increased.
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New Approaches for Calculating Moran’s Index of Spatial Autocorrelation
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
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Fernández-Guisuraga, José Manuel; Sanz-Ablanedo, Enoc; Suárez-Seoane, Susana; Calvo, Leonor
2018-02-14
This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas.
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Shi, Xun; Miller, Stephanie; Mwenda, Kevin; Onda, Akikazu; Reese, Judy; Onega, Tracy; Gui, Jiang; Karagas, Margret; Demidenko, Eugene; Moeschler, John
2013-09-06
Limited by data availability, most disease maps in the literature are for relatively large and subjectively-defined areal units, which are subject to problems associated with polygon maps. High resolution maps based on objective spatial units are needed to more precisely detect associations between disease and environmental factors. We propose to use a Restricted and Controlled Monte Carlo (RCMC) process to disaggregate polygon-level location data to achieve mapping aggregate data at an approximated individual level. RCMC assigns a random point location to a polygon-level location, in which the randomization is restricted by the polygon and controlled by the background (e.g., population at risk). RCMC allows analytical processes designed for individual data to be applied, and generates high-resolution raster maps. We applied RCMC to the town-level birth defect data for New Hampshire and generated raster maps at the resolution of 100 m. Besides the map of significance of birth defect risk represented by p-value, the output also includes a map of spatial uncertainty and a map of hot spots. RCMC is an effective method to disaggregate aggregate data. An RCMC-based disease mapping maximizes the use of available spatial information, and explicitly estimates the spatial uncertainty resulting from aggregation.
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2018-01-01
This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas. PMID:29443914
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Spatial release from masking based on binaural processing for up to six maskers
Yost, William A.
2017-01-01
Spatial Release from Masking (SRM) was measured for identification of a female target word spoken in the presence of male masker words. Target words from a single loudspeaker located at midline were presented when two, four, or six masker words were presented either from the same source as the target or from spatially separated masker sources. All masker words were presented from loudspeakers located symmetrically around the centered target source in the front azimuth hemifield. Three masking conditions were employed: speech-in-speech masking (involving both informational and energetic masking), speech-in-noise masking (involving energetic masking), and filtered speech-in-filtered speech masking (involving informational masking). Psychophysical results were summarized as three-point psychometric functions relating proportion of correct word identification to target-to-masker ratio (in decibels) for both the co-located and spatially separated target and masker sources cases. SRM was then calculated by comparing the slopes and intercepts of these functions. SRM decreased as the number of symmetrically placed masker sources increased from two to six. This decrease was independent of the type of masking, with almost no SRM measured for six masker sources. These results suggest that when SRM is dependent primarily on binaural processing, SRM is effectively limited to fewer than six sound sources. PMID:28372135
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Diffraction patterns in Fresnel approximation of periodic objects for a colorimeter of two apertures
NASA Astrophysics Data System (ADS)
Cortes-Reynoso, Jose-German R.; Suarez-Romero, Jose G.; Hurtado-Ramos, Juan B.; Tepichin-Rodriguez, Eduardo; Solorio-Leyva, Juan Carlos
2004-10-01
In this work, we present a study of Fresnel diffraction of periodic structures in an optical system of two apertures. This system of two apertures was used successfully for measuring color in textile samples solving the problems of illumination and directionality that present current commercial equipments. However, the system is sensible to the spatial frequency of the periodic sample"s area enclosed in its optical field of view. The study of Fresnel diffraction allows us to establish criteria for geometrical parameters of measurements in order to assure invariance in angular rotations and spatial positions. In this work, we use the theory of partial coherence to calculate the diffraction through two continuous apertures. In the calculation process, we use the concept of point-spread function of the system for partial coherence, in this way we avoid complicated statistical processes commonly used in the partial coherence theory.
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Ozone production process in pulsed positive dielectric barrier discharge
NASA Astrophysics Data System (ADS)
Ono, Ryo; Oda, Tetsuji
2007-01-01
The ozone production process in a pulsed positive dielectric barrier discharge (DBD) is studied by measuring the spatial distribution of ozone density using a two-dimensional laser absorption method. DBD occurs in a 6 mm point-to-plane gap with a 1 mm-thick glass plate placed on the plane electrode. First, the propagation of DBD is observed using a short-gated ICCD camera. It is shown that DBD develops in three phases: primary streamer, secondary streamer and surface discharge phases. Next, the spatial distribution of ozone density is measured. It is shown that ozone is mostly produced in the secondary streamer and surface discharge, while only a small amount of ozone is produced in the primary streamer. The rate coefficient of the ozone production reaction, O + O2 + M → O3 + M, is estimated to be 2.5 × 10-34 cm6 s-1.
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NASA Astrophysics Data System (ADS)
Piermattei, Livia; Bozzi, Carlo Alberto; Mancini, Adriano; Tassetti, Anna Nora; Karel, Wilfried; Pfeifer, Norbert
2017-04-01
Unmanned aerial vehicles (UAVs) in combination with consumer grade cameras have become standard tools for photogrammetric applications and surveying. The recent generation of multispectral, cost-efficient and lightweight cameras has fostered a breakthrough in the practical application of UAVs for precision agriculture. For this application, multispectral cameras typically use Green, Red, Red-Edge (RE) and Near Infrared (NIR) wavebands to capture both visible and invisible images of crops and vegetation. These bands are very effective for deriving characteristics like soil productivity, plant health and overall growth. However, the quality of results is affected by the sensor architecture, the spatial and spectral resolutions, the pattern of image collection, and the processing of the multispectral images. In particular, collecting data with multiple sensors requires an accurate spatial co-registration of the various UAV image datasets. Multispectral processed data in precision agriculture are mainly presented as orthorectified mosaics used to export information maps and vegetation indices. This work aims to investigate the acquisition parameters and processing approaches of this new type of image data in order to generate orthoimages using different sensors and UAV platforms. Within our experimental area we placed a grid of artificial targets, whose position was determined with differential global positioning system (dGPS) measurements. Targets were used as ground control points to georeference the images and as checkpoints to verify the accuracy of the georeferenced mosaics. The primary aim is to present a method for the spatial co-registration of visible, Red-Edge, and NIR image sets. To demonstrate the applicability and accuracy of our methodology, multi-sensor datasets were collected over the same area and approximately at the same time using the fixed-wing UAV senseFly "eBee". The images were acquired with the camera Canon S110 RGB, the multispectral cameras Canon S110 NIR and S110 RE and with the multi-camera system Parrot Sequoia, which is composed of single-band cameras (Green, Red, Red Edge, NIR and RGB). Imagery from each sensor was georeferenced and mosaicked with the commercial software Agisoft PhotoScan Pro and different approaches for image orientation were compared. To assess the overall spatial accuracy of each dataset the root mean square error was computed between check point coordinates measured with dGPS and coordinates retrieved from georeferenced image mosaics. Additionally, image datasets from different UAV platforms (i.e. DJI Phantom 4Pro, DJI Phantom 3 professional, and DJI Inspire 1 Pro) were acquired over the same area and the spatial accuracy of the orthoimages was evaluated.
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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.
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NASA Astrophysics Data System (ADS)
Lan, Hengxing; Derek Martin, C.; Lim, C. H.
2007-02-01
Geographic information system (GIS) modeling is used in combination with three-dimensional (3D) rockfall process modeling to assess rockfall hazards. A GIS extension, RockFall Analyst (RA), which is capable of effectively handling large amounts of geospatial information relative to rockfall behaviors, has been developed in ArcGIS using ArcObjects and C#. The 3D rockfall model considers dynamic processes on a cell plane basis. It uses inputs of distributed parameters in terms of raster and polygon features created in GIS. Two major components are included in RA: particle-based rockfall process modeling and geostatistics-based rockfall raster modeling. Rockfall process simulation results, 3D rockfall trajectories and their velocity features either for point seeders or polyline seeders are stored in 3D shape files. Distributed raster modeling, based on 3D rockfall trajectories and a spatial geostatistical technique, represents the distribution of spatial frequency, the flying and/or bouncing height, and the kinetic energy of falling rocks. A distribution of rockfall hazard can be created by taking these rockfall characteristics into account. A barrier analysis tool is also provided in RA to aid barrier design. An application of these modeling techniques to a case study is provided. The RA has been tested in ArcGIS 8.2, 8.3, 9.0 and 9.1.
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Updating visual memory across eye movements for ocular and arm motor control.
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.
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Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012
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
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Keep an eye on your hands: on the role of visual mechanisms in processing of haptic space
Zuidhoek, Sander; Noordzij, Matthijs L.; Kappers, Astrid M. L.
2008-01-01
The present paper reviews research on a haptic orientation processing. Central is a task in which a test bar has to be set parallel to a reference bar at another location. Introducing a delay between inspecting the reference bar and setting the test bar leads to a surprising improvement. Moreover, offering visual background information also elevates performance. Interestingly, (congenitally) blind individuals do not or to a weaker extent show the improvement with time, while in parallel to this, they appear to benefit less from spatial imagery processing. Together this strongly points to an important role for visual processing mechanisms in the perception of haptic inputs. PMID:18196305
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Development of Γ-ray tracking detectors
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.
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The community ecology of pathogens: coinfection, coexistence and community composition.
Seabloom, Eric W; Borer, Elizabeth T; Gross, Kevin; Kendig, Amy E; Lacroix, Christelle; Mitchell, Charles E; Mordecai, Erin A; Power, Alison G
2015-04-01
Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host-pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two-pathogen susceptible-infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species-diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology. © 2015 John Wiley & Sons Ltd/CNRS.
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Dorazio, Robert M.
2012-01-01
Several models have been developed to predict the geographic distribution of a species by combining measurements of covariates of occurrence at locations where the species is known to be present with measurements of the same covariates at other locations where species occurrence status (presence or absence) is unknown. In the absence of species detection errors, spatial point-process models and binary-regression models for case-augmented surveys provide consistent estimators of a species’ geographic distribution without prior knowledge of species prevalence. In addition, these regression models can be modified to produce estimators of species abundance that are asymptotically equivalent to those of the spatial point-process models. However, if species presence locations are subject to detection errors, neither class of models provides a consistent estimator of covariate effects unless the covariates of species abundance are distinct and independently distributed from the covariates of species detection probability. These analytical results are illustrated using simulation studies of data sets that contain a wide range of presence-only sample sizes. Analyses of presence-only data of three avian species observed in a survey of landbirds in western Montana and northern Idaho are compared with site-occupancy analyses of detections and nondetections of these species.
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Sun, Zhishen; Liu, Guoqiang; Guo, Liang; Xia, Hui; Wang, Xinli
2016-04-29
As two of the new biological electrical impedance tomography (EIT), magneto-acoustic tomography (MAT) and magneto-acousto-electrical tomography (MAET) achieve both the high contrast property of EIT and the high spatial resolution property of sonography through combining EIT and sonography. As both MAT and MAET contain a uniform magnetic field, vibration and electrical current density, there is a secondary process both in MAT and in MAET, which is MAET and MAT respectively. To analyze the effect of the secondary process on mass point vibration velocity (MPVV) propagation in MAT and MAET. By analyzing the total force to the sample, the wave equations of MPVV in MAT and MAET - when the secondary processes were considered - were derived. The expression of the attenuation constant in the wave number was derived in the case that the mass point vibration velocity propagates in the form of cylindrical wave and plane wave. Attenuations of propagation of the MPVV in several samples were quantified. Attenuations of the MPVV after propagating for 1 mm in copper or aluminum foil, and for 5 cm in gel phantom or biological soft tissue were less than 1%. Attenuations of the MPVV in MAT and MAET due to the secondary processes are relatively minor, and effects of the secondary processes on MPVV propagation in MAT and MAET can be ignored.
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Dong, Junzi; Colburn, H. Steven
2016-01-01
In multisource, “cocktail party” sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural time differences (ITDs) are well understood in precortical areas, how such information is reused and transformed in higher cortical regions to represent segregated sound sources is not clear. We present a computational model describing a hypothesized neural network that spans spatial cue detection areas and the cortex. This network is based on recent physiological findings that cortical neurons selectively encode target stimuli in the presence of competing maskers based on source locations (Maddox et al., 2012). We demonstrate that key features of cortical responses can be generated by the model network, which exploits spatial interactions between inputs via lateral inhibition, enabling the spatial separation of target and interfering sources while allowing monitoring of a broader acoustic space when there is no competition. We present the model network along with testable experimental paradigms as a starting point for understanding the transformation and organization of spatial information from midbrain to cortex. This network is then extended to suggest engineering solutions that may be useful for hearing-assistive devices in solving the cocktail party problem. PMID:26866056
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Dong, Junzi; Colburn, H Steven; Sen, Kamal
2016-01-01
In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural time differences (ITDs) are well understood in precortical areas, how such information is reused and transformed in higher cortical regions to represent segregated sound sources is not clear. We present a computational model describing a hypothesized neural network that spans spatial cue detection areas and the cortex. This network is based on recent physiological findings that cortical neurons selectively encode target stimuli in the presence of competing maskers based on source locations (Maddox et al., 2012). We demonstrate that key features of cortical responses can be generated by the model network, which exploits spatial interactions between inputs via lateral inhibition, enabling the spatial separation of target and interfering sources while allowing monitoring of a broader acoustic space when there is no competition. We present the model network along with testable experimental paradigms as a starting point for understanding the transformation and organization of spatial information from midbrain to cortex. This network is then extended to suggest engineering solutions that may be useful for hearing-assistive devices in solving the cocktail party problem.
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Topological data analysis of contagion maps for examining spreading processes on networks.
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.
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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.
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Managing distance and covariate information with point-based clustering.
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.
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Establishing a Geologic Baseline Of Cape Canaveral's Natural Landscape: Black Point Drive
NASA Technical Reports Server (NTRS)
Parkinson, Randall W.
2001-01-01
The goal of this project is to identify the process responsible for the formation of geomorphic features in the Black Point Drive area of Merritt Island National Wildlife Refuge/Kennedy Space Center (MINWR/KSC), northwest Cape Canaveral. This study confirms the principal landscape components (geomorphology) of Black Point Drive reflect interaction between surficial sediments deposited in association with late-Quaternary sea-level highstands and the chemical evolution of late-Cenozoic subsurface limestone formations. The Black Point Drive landscape consists of an undulatory mesic terrain which dips westward into myriad circular and channel-like depression marshes and lakes. This geomorphic gradient may reflect: (1) spatial distinctions in the elevation, character or age of buried (pre-Miocene) limestone formations, (2) dissolution history of late-Quaternary coquina and/or (3) thickness of unconsolidated surface sediment. More detailed evaluation of subsurface data will be necessary before this uncertainty can be resolved.
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Establishing A Geologic Baseline of Cape Canaveral''s Natural Landscape: Black Point Drive
NASA Technical Reports Server (NTRS)
Parkinson, Randall W.
2002-01-01
The goal of this project is to identify the process responsible for the formation of geomorphic features in the Black Point Drive area of Merritt Island National Wildlife Refuge/Kennedy Space Center (MINWR/KSC), northwest Cape Canaveral. This study confirms the principal landscape components (geomorphology) of Black Point Drive reflect interaction between surficial sediments deposited in association with late-Quaternary sea-level highstands and the chemical evolution of late-Cenozoic sub-surface limestone formations. The Black Point Drive landscape consists of an undulatory mesic terrain which dips westward into myriad circular and channel-like depression marshes and lakes. This geomorphic gradient may reflect: (1) spatial distinctions in the elevation, character or age of buried (pre-Miocene) limestone formations, (2) dissolution history of late-Quaternary coquina and/or (3) thickness of unconsolidated surface sediment. More detailed evaluation of subsurface data will be necessary before this uncertain0 can be resolved.
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Can Retinal Ganglion Cell Dipoles Seed Iso-Orientation Domains in the Visual Cortex?
Schottdorf, Manuel; Eglen, Stephen J.; Wolf, Fred; Keil, Wolfgang
2014-01-01
It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex. PMID:24475081
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Can retinal ganglion cell dipoles seed iso-orientation domains in the visual cortex?
Schottdorf, Manuel; Eglen, Stephen J; Wolf, Fred; Keil, Wolfgang
2014-01-01
It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex.
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Sex differences in components of imagined perspective transformation.
Gardner, Mark R; Sorhus, Ingrid; Edmonds, Caroline J; Potts, Rosalind
2012-05-01
Little research to date has examined whether sex differences in spatial ability extend to the mental self rotation involved in taking on a third party perspective. This question was addressed in the present study by assessing components of imagined perspective transformations in twenty men and twenty women. Participants made speeded left-right judgements about the hand in which an object was held by front- and back- facing schematic human figures in an "own body transformation task." Response times were longer when the figure did not share the same spatial orientation as the participant, and were substantially longer than those made for a control task requiring left-right judgements about the same stimuli from the participant's own point of view. A sex difference in imagined perspective transformation favouring males was found to be restricted to the speed of imagined self rotation, and was not observed for components indexing readiness to take a third party point of view, nor in left-right confusion. These findings indicate that the range of spatial abilities for which a sex difference has been established should be extended to include imagined perspective transformations. They also suggest that imagined perspective transformations may not draw upon those empathic social-emotional perspective taking processes for which females show an advantage. Copyright © 2012 Elsevier B.V. All rights reserved.
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Aging and the intrusion superiority effect in visuo-spatial working memory.
Cornoldi, Cesare; Bassani, Chiara; Berto, Rita; Mammarella, Nicola
2007-01-01
This study investigated the active component of visuo-spatial working memory (VSWM) in younger and older adults testing the hypotheses that elderly individuals have a poorer performance than younger ones and that errors in active VSWM tasks depend, at least partially, on difficulties in avoiding intrusions (i.e., avoiding already activated information). In two experiments, participants were presented with sequences of matrices on which three positions were pointed out sequentially: their task was to process all the positions but indicate only the final position of each sequence. Results showed a poorer performance in the elderly compared to the younger group and a higher number of intrusion (errors due to activated but irrelevant positions) rather than invention (errors consisting of pointing out a position never indicated by the experiementer) errors. The number of errors increased when a concurrent task was introduced (Experiment 1) and it was affected by different patterns of matrices (Experiment 2). In general, results show that elderly people have an impaired VSWM and produce a large number of errors due to inhibition failures. However, both the younger and the older adults' visuo-spatial working memory was affected by the presence of activated irrelevant information, the reduction of the available resources, and task constraints.
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Geographic distribution of HIV stigma among women of childbearing age in rural Kenya
Akullian, Adam; Kohler, Pamela; Kinuthia, John; Laserson, Kayla; Mills, Lisa A.; Okanda, John; Olilo, George; Ombok, Maurice; Odhiambo, Frank; Rao, Deepa; Wakefield, Jonathan; John-Stewart, Grace
2015-01-01
Objective(s) HIV stigma is considered to be a major driver of the HIV/AIDS pandemic, yet there is a limited understanding of its occurrence. We describe the geographic patterns of two forms of HIV stigma in a cross-sectional sample of women of childbearing age from western Kenya: internalized stigma (associated with shame) and externalized stigma (associated with blame). Design Geographic studies of HIV stigma provide a first step in generating hypotheses regarding potential community-level causes of stigma and may lead to more effective community-level interventions. Methods Spatial regression using generalized additive models and point pattern analyses using K-functions were used to assess the spatial scale(s) at which each form of HIV stigma clusters, and to assess whether the spatial clustering of each stigma indicator was present after adjustment for individual-level characteristics. Results There was evidence that externalized stigma (blame) was geographically heterogeneous across the study area, even after controlling for individual-level factors (P=0.01). In contrast, there was less evidence (P=0.70) of spatial trend or clustering of internalized stigma (shame). Conclusion Our results may point to differences in the underlying social processes motivating each form of HIV stigma. Externalized stigma may be driven more by cultural beliefs disseminated within communities, whereas internalized stigma may be the result of individual-level characteristics outside the domain of community influence. These data may inform community-level interventions to decrease HIV-related stigma, and thus impact the HIV epidemic. PMID:24835356
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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
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Spatial transformation abilities and their relation to later mathematics performance.
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.
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Heat tracing to determine spatial patterns of hyporheic exchange across a river transect
NASA Astrophysics Data System (ADS)
Lu, Chengpeng; Chen, Shuai; Zhang, Ying; Su, Xiaoru; Chen, Guohao
2017-09-01
Significant spatial variability of water fluxes may exist at the water-sediment interface in river channels and has great influence on a variety of water issues. Understanding the complicated flow systems controlling the flux exchanges along an entire river is often limited due to averaging of parameters or the small number of discrete point measurements usually used. This study investigated the spatial pattern of the hyporheic flux exchange across a river transect in China, using the heat tracing approach. This was done with measurements of temperature at high spatial resolution during a 64-h monitoring period and using the data to identify the spatial pattern of the hyporheic exchange flux with the aid of a one-dimensional conduction-advection-dispersion model (VFLUX). The threshold of neutral exchange was considered as 126 L m-2 d-1 in this study and the heat tracing results showed that the change patterns of vertical hyporheic flux varied with buried depth along the river transect; however, the hyporheic flux was not simply controlled by the streambed hydraulic conductivity and water depth in the river transect. Also, lateral flow dominated the hyporheic process within the shallow high-permeability streambed, while the vertical flow was dominant in the deep low-permeability streambed. The spatial pattern of hyporheic exchange across the river transect was naturally controlled by the heterogeneity of the streambed and the bedform of the stream cross-section. Consequently, a two-dimensional conceptual illustration of the hyporheic process across the river transect is proposed, which could be applicable to river transects of similar conditions.
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Small convolution kernels for high-fidelity image restoration
NASA Technical Reports Server (NTRS)
Reichenbach, Stephen E.; Park, Stephen K.
1991-01-01
An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.
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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.
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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
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The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass
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
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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.
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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.
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Dorazio, Robert; Karanth, K. Ullas
2017-01-01
MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.
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Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations
NASA Technical Reports Server (NTRS)
Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.
2000-01-01
Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.
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A Context-sensitive Approach to Anonymizing Spatial Surveillance Data: Impact on Outbreak Detection
Cassa, Christopher A.; Grannis, Shaun J.; Overhage, J. Marc; Mandl, Kenneth D.
2006-01-01
Objective: The use of spatially based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health data sets by transposing their spatial locations through a process informed by the underlying population density. Further, we measure the impact of the skew on detection of spatial clustering as measured by a spatial scanning statistic. Design: Cases were emergency department (ED) visits for respiratory illness. Baseline ED visit data were injected with artificially created clusters ranging in magnitude, shape, and location. The geocoded locations were then transformed using a de-identification algorithm that accounts for the local underlying population density. Measurements: A total of 12,600 separate weeks of case data with artificially created clusters were combined with control data and the impact on detection of spatial clustering identified by a spatial scan statistic was measured. Results: The anonymization algorithm produced an expected skew of cases that resulted in high values of data set k-anonymity. De-identification that moves points an average distance of 0.25 km lowers the spatial cluster detection sensitivity by less than 4% and lowers the detection specificity less than 1%. Conclusion: A population-density–based Gaussian spatial blurring markedly decreases the ability to identify individuals in a data set while only slightly decreasing the performance of a standardly used outbreak detection tool. These findings suggest new approaches to anonymizing data for spatial epidemiology and surveillance. PMID:16357353
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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.
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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.
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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.
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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.
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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.
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Parafoveal letter-position coding in reading.
Snell, Joshua; Bertrand, Daisy; Grainger, Jonathan
2018-05-01
The masked-priming lexical decision task has been the paradigm of choice for investigating how readers code for letter identity and position. Insight into the temporal integration of information between prime and target words has pointed out, among other things, that readers do not code for the absolute position of letters. This conception has spurred various accounts of the word recognition process, but the results at present do not favor one account in particular. Thus, employing a new strategy, the present study moves out of the arena of temporal- and into the arena of spatial information integration. We present two lexical decision experiments that tested how the processing of six-letter target words is influenced by simultaneously presented flanking stimuli (each stimulus was presented for 150 ms). We manipulated the orthographic relatedness between the targets and flankers, in terms of both letter identity (same/different letters based on the target's outer/inner letters) and letter position (intact/reversed order of letters and of flankers, contiguous/noncontiguous flankers). Target processing was strongly facilitated by same-letter flankers, and this facilitatory effect was modulated by both letter/flanker order and contiguity. However, when the flankers consisted of the target's inner-positioned letters alone, letter order no longer mattered. These findings suggest that readers may code for the relative position of letters using words' edges as spatial points of reference. We conclude that the flanker paradigm provides a fruitful means to investigate letter-position coding in the fovea and parafovea.
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Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information
NASA Astrophysics Data System (ADS)
Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.
2015-10-01
The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.
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NASA Astrophysics Data System (ADS)
Benaud, Pia; Anderson, Karen; Quine, Timothy; James, Mike; Quinton, John; Brazier, Richard E.
2017-04-01
The accessibility of Structure-from-Motion Multi-Stereo View (SfM) and the potential for multi-temporal applications, offers an exciting opportunity to quantify soil erosion spatially. Accordingly, published research provides examples of the successful quantification of large erosion features and events, to centimetre accuracy. Through rigorous control of the camera and image network geometry, the centimetre accuracy achievable at the field scale, can translate to sub-millimetre accuracies within a laboratory environment. The broad aim of this study, therefore, was to understand how ultra-high-resolution spatial information on soil surface topography, derived from SfM, can be utilised to develop a spatially explicit, mechanistic understanding of rill and inter-rill erosion, under experimental conditions. A rainfall simulator was used to create three soil surface conditions; compaction and rainsplash erosion, inter-rill erosion, and rill erosion. Total sediment capture was the primary validation for the experiments, allowing the comparison between structurally and volumetrically derived change, and true soil loss. A Terrestrial Laser Scanner (resolution of ca. 0.8mm) was employed to assess spatial discrepancies within the SfM datasets and to provide an alternative measure of volumetric change. The body of work will present the workflow that has been developed for the laboratory-scale studies and provide information on the importance of DTM resolution for volumetric calculations of soil loss, under different soil surface conditions. To-date, using the methodology presented, point clouds with ca. 3.38 x 107 points per m2, and RMSE values of 0.17 to 0.43 mm (relative precision 1:2023-5117), were constructed. Preliminary results suggest a decrease in DTM resolution from 0.5 to 10 mm does not result in a significant change in volumetric calculations (p = 0.088), while affording a 24-fold decrease in processing times, but may impact negatively on mechanistic understanding of patterns of erosion. It is argued that the approach can be an invaluable tool for the spatially-explicit evaluation of soil erosion models.
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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.
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Spatial Distribution of the Coefficient of Variation for the Paleo-Earthquakes in Japan
NASA Astrophysics Data System (ADS)
Nomura, S.; Ogata, Y.
2015-12-01
Renewal processes, point prccesses in which intervals between consecutive events are independently and identically distributed, are frequently used to describe this repeating earthquake mechanism and forecast the next earthquakes. However, one of the difficulties in applying recurrent earthquake models is the scarcity of the historical data. Most studied fault segments have few, or only one observed earthquake that often have poorly constrained historic and/or radiocarbon ages. The maximum likelihood estimate from such a small data set can have a large bias and error, which tends to yield high probability for the next event in a very short time span when the recurrence intervals have similar lengths. On the other hand, recurrence intervals at a fault depend on the long-term slip rate caused by the tectonic motion in average. In addition, recurrence times are also fluctuated by nearby earthquakes or fault activities which encourage or discourage surrounding seismicity. These factors have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus, this paper introduces a spatial structure on the key parameters of renewal processes for recurrent earthquakes and estimates it by using spatial statistics. Spatial variation of mean and variance parameters of recurrence times are estimated in Bayesian framework and the next earthquakes are forecasted by Bayesian predictive distributions. The proposal model is applied for recurrent earthquake catalog in Japan and its result is compared with the current forecast adopted by the Earthquake Research Committee of Japan.
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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/
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NASA Astrophysics Data System (ADS)
Burkholder, E. F.
2016-12-01
One way to address challenges of replacing NAD 83, NGVD 88 and IGLD 85 is to exploit the characteristics of 3-D digital spatial data. This presentation describes the 3-D global spatial data model (GSDM) which accommodates rigorous scientific endeavors while simultaneously supporting a local flat-earth view of the world. The GSDM is based upon the assumption of a single origin for 3-D spatial data and uses rules of solid geometry for manipulating spatial data components. This approach exploits the characteristics of 3-D digital spatial data and preserves the quality of geodetic measurements while providing spatial data users the option of working with rectangular flat-earth components and computational procedures for local applications. This flexibility is provided by using a bidirectional rotation matrix that allows any 3-D vector to be used in a geodetic reference frame for high-end applications and/or the local frame for flat-earth users. The GSDM is viewed as compatible with the datum products being developed by NGS and provides for unambiguous exchange of 3-D spatial data between disciplines and users worldwide. Three geometrical models will be summarized - geodetic, map projection, and 3-D. Geodetic computations are performed on an ellipsoid and are without equal in providing rigorous coordinate values for latitude, longitude, and ellipsoid height. Members of the user community have, for generations, sought ways to "flatten the world" to accommodate a flat-earth view and to avoid the complexity of working on an ellipsoid. Map projections have been defined for a wide variety of applications and remain very useful for visualizing spatial data. But, the GSDM supports computations based on 3-D components that have not been distorted in a 2-D map projection. The GSDM does not invalidate either geodesy or cartographic computational processes but provides a geometrically correct view of any point cloud from any point selected by the user. As a bonus, the GSDM also defines spatial data accuracy and includes procedures for establishing, tracking and using spatial data accuracy - increasingly important in many applications but especially relevant given development of procedures for tracking drones (primarily absolute) and intelligent vehicles (primarily relative).
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Role of Alpha-Band Oscillations in Spatial Updating across Whole Body Motion
Gutteling, Tjerk P.; Medendorp, W. P.
2016-01-01
When moving around in the world, we have to keep track of important locations in our surroundings. In this process, called spatial updating, we must estimate our body motion and correct representations of memorized spatial locations in accordance with this motion. While the behavioral characteristics of spatial updating across whole body motion have been studied in detail, its neural implementation lacks detailed study. Here we use electroencephalography (EEG) to distinguish various spectral components of this process. Subjects gazed at a central body-fixed point in otherwise complete darkness, while a target was briefly flashed, either left or right from this point. Subjects had to remember the location of this target as either moving along with the body or remaining fixed in the world while being translated sideways on a passive motion platform. After the motion, subjects had to indicate the remembered target location in the instructed reference frame using a mouse response. While the body motion, as detected by the vestibular system, should not affect the representation of body-fixed targets, it should interact with the representation of a world-centered target to update its location relative to the body. We show that the initial presentation of the visual target induced a reduction of alpha band power in contralateral parieto-occipital areas, which evolved to a sustained increase during the subsequent memory period. Motion of the body led to a reduction of alpha band power in central parietal areas extending to lateral parieto-temporal areas, irrespective of whether the targets had to be memorized relative to world or body. When updating a world-fixed target, its internal representation shifts hemispheres, only when subjects’ behavioral responses suggested an update across the body midline. Our results suggest that parietal cortex is involved in both self-motion estimation and the selective application of this motion information to maintaining target locations as fixed in the world or fixed to the body. PMID:27199882
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Quesada, Jose Antonio; Melchor, Inmaculada; Nolasco, Andreu
2017-05-26
The analysis of spatio-temporal patterns of disease or death in urban areas has been developed mainly from the ecological studies approach. These designs may have some limitations like the ecological fallacy and instability with few cases. The objective of this study was to apply the point process methodology, as a complement to that of aggregated data, to study HIV/AIDS mortality in men in the city of Alicante (Spain). A case-control study in residents in the city during the period 2004-2011 was designed. Cases were men who died from HIV/AIDS and controls represented the general population, matched by age to cases. The risk surfaces of death over the city were estimated using the log-risk function of intensities, and we contrasted their temporal variations over the two periods. High risk significant areas of death by HIV/AIDS, which coincide with the most deprived areas in the city, were detected. Significant spatial change of the areas at risk between the periods studied was not detected. The point process methodology is a useful tool to analyse the patterns of death by HIV/AIDS in urban areas.
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NASA Technical Reports Server (NTRS)
Weaver, Johnathan M.
1993-01-01
A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.
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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.
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Comparable Rest-related Promotion of Spatial Memory Consolidation in Younger and Older Adults
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
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X-ray Point Source Populations in Spiral and Elliptical Galaxies
NASA Astrophysics Data System (ADS)
Colbert, E.; Heckman, T.; Weaver, K.; Strickland, D.
2002-01-01
The hard-X-ray luminosity of non-active galaxies has been known to be fairly well correlated with the total blue luminosity since the days of the Einstein satellite. However, the origin of this hard component was not well understood. Some possibilities that were considered included X-ray binaries, extended upscattered far-infrared light via the inverse-Compton process, extended hot 107 K gas (especially in ellipitical galaxies), or even an active nucleus. Chandra images of normal, elliptical and starburst galaxies now show that a significant amount of the total hard X-ray emission comes from individual point sources. We present here spatial and spectral analyses of the point sources in a small sample of Chandra obervations of starburst galaxies, and compare with Chandra point source analyses from comparison galaxies (elliptical, Seyfert and normal galaxies). We discuss possible relationships between the number and total hard luminosity of the X-ray point sources and various measures of the galaxy star formation rate, and discuss possible options for the numerous compact sources that are observed.
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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.
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A Secondary Spatial Analysis of Gun Violence near Boston Schools: a Public Health Approach.
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.
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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...
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[A landscape ecological approach for urban non-point source pollution control].
Guo, Qinghai; Ma, Keming; Zhao, Jingzhu; Yang, Liu; Yin, Chengqing
2005-05-01
Urban non-point source pollution is a new problem appeared with the speeding development of urbanization. The particularity of urban land use and the increase of impervious surface area make urban non-point source pollution differ from agricultural non-point source pollution, and more difficult to control. Best Management Practices (BMPs) are the effective practices commonly applied in controlling urban non-point source pollution, mainly adopting local repairing practices to control the pollutants in surface runoff. Because of the close relationship between urban land use patterns and non-point source pollution, it would be rational to combine the landscape ecological planning with local BMPs to control the urban non-point source pollution, which needs, firstly, analyzing and evaluating the influence of landscape structure on water-bodies, pollution sources and pollutant removal processes to define the relationships between landscape spatial pattern and non-point source pollution and to decide the key polluted fields, and secondly, adjusting inherent landscape structures or/and joining new landscape factors to form new landscape pattern, and combining landscape planning and management through applying BMPs into planning to improve urban landscape heterogeneity and to control urban non-point source pollution.
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NASA Astrophysics Data System (ADS)
Irving, D. H.; Rasheed, M.; O'Doherty, N.
2010-12-01
The efficient storage, retrieval and interactive use of subsurface data present great challenges in geodata management. Data volumes are typically massive, complex and poorly indexed with inadequate metadata. Derived geomodels and interpretations are often tightly bound in application-centric and proprietary formats; open standards for long-term stewardship are poorly developed. Consequently current data storage is a combination of: complex Logical Data Models (LDMs) based on file storage formats; 2D GIS tree-based indexing of spatial data; and translations of serialised memory-based storage techniques into disk-based storage. Whilst adequate for working at the mesoscale over a short timeframes, these approaches all possess technical and operational shortcomings: data model complexity; anisotropy of access; scalability to large and complex datasets; and weak implementation and integration of metadata. High performance hardware such as parallelised storage and Relational Database Management System (RDBMS) have long been exploited in many solutions but the underlying data structure must provide commensurate efficiencies to allow multi-user, multi-application and near-realtime data interaction. We present an open Spatially-Registered Data Structure (SRDS) built on Massively Parallel Processing (MPP) database architecture implemented by a ANSI SQL 2008 compliant RDBMS. We propose a LDM comprising a 3D Earth model that is decomposed such that each increasing Level of Detail (LoD) is achieved by recursively halving the bin size until it is less than the error in each spatial dimension for that data point. The value of an attribute at that point is stored as a property of that point and at that LoD. It is key to the numerical efficiency of the SRDS that it is under-pinned by a power-of-two relationship thus precluding the need for computationally intensive floating point arithmetic. Our approach employed a tightly clustered MPP array with small clusters of storage, processors and memory communicating over a high-speed network inter-connect. This is a shared-nothing architecture where resources are managed within each cluster unlike most other RDBMSs. Data are accessed on this architecture by their primary index values which utilises the hashing algorithm for point-to-point access. The hashing algorithm’s main role is the efficient distribution of data across the clusters based on the primary index. In this study we used 3D seismic volumes, 2D seismic profiles and borehole logs to demonstrate application in both (x,y,TWT) and (x,y,z)-space. In the SRDS the primary index is a composite column index of (x,y) to avoid invoking time-consuming full table scans as is the case in tree-based systems. This means that data access is isotropic. A query for data in a specified spatial range permits retrieval recursively by point-to-point queries within each nested LoD yielding true linear performance up to the Petabyte scale with hardware scaling presenting the primary limiting factor. Our architecture and LDM promotes: realtime interaction with massive data volumes; streaming of result sets and server-rendered 2D/3D imagery; rigorous workflow control and auditing; and in-database algorithms run directly against data as a HPC cloud service.
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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)
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NASA Astrophysics Data System (ADS)
Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.
2015-12-01
Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.
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Image Processing, Coding, and Compression with Multiple-Point Impulse Response Functions.
NASA Astrophysics Data System (ADS)
Stossel, Bryan Joseph
1995-01-01
Aspects of image processing, coding, and compression with multiple-point impulse response functions are investigated. Topics considered include characterization of the corresponding random-walk transfer function, image recovery for images degraded by the multiple-point impulse response, and the application of the blur function to image coding and compression. It is found that although the zeros of the real and imaginary parts of the random-walk transfer function occur in continuous, closed contours, the zeros of the transfer function occur at isolated spatial frequencies. Theoretical calculations of the average number of zeros per area are in excellent agreement with experimental results obtained from computer counts of the zeros. The average number of zeros per area is proportional to the standard deviations of the real part of the transfer function as well as the first partial derivatives. Statistical parameters of the transfer function are calculated including the mean, variance, and correlation functions for the real and imaginary parts of the transfer function and their corresponding first partial derivatives. These calculations verify the assumptions required in the derivation of the expression for the average number of zeros. Interesting results are found for the correlations of the real and imaginary parts of the transfer function and their first partial derivatives. The isolated nature of the zeros in the transfer function and its characteristics at high spatial frequencies result in largely reduced reconstruction artifacts and excellent reconstructions are obtained for distributions of impulses consisting of 25 to 150 impulses. The multiple-point impulse response obscures original scenes beyond recognition. This property is important for secure transmission of data on many communication systems. The multiple-point impulse response enables the decoding and restoration of the original scene with very little distortion. Images prefiltered by the random-walk transfer function yield greater compression ratios than are obtained for the original scene. The multiple-point impulse response decreases the bit rate approximately 40-70% and affords near distortion-free reconstructions. Due to the lossy nature of transform-based compression algorithms, noise reduction measures must be incorporated to yield acceptable reconstructions after decompression.
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Mapping malaria risk among children in Côte d'Ivoire using Bayesian geo-statistical models.
Raso, Giovanna; Schur, Nadine; Utzinger, Jürg; Koudou, Benjamin G; Tchicaya, Emile S; Rohner, Fabian; N'goran, Eliézer K; Silué, Kigbafori D; Matthys, Barbara; Assi, Serge; Tanner, Marcel; Vounatsou, Penelope
2012-05-09
In Côte d'Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged <16 years in Côte d'Ivoire at high spatial resolution. Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d'Ivoire, focusing on children aged <16 years. The period from 1988 to 2007 was covered. A suite of Bayesian geo-statistical logistic regression models was fitted to analyse malaria risk. Non-spatial models with and without exchangeable random effect parameters were compared to stationary and non-stationary spatial models. Non-stationarity was modelled assuming that the underlying spatial process is a mixture of separate stationary processes in each ecological zone. The best fitting model based on the deviance information criterion was used to predict Plasmodium spp. infection risk for entire Côte d'Ivoire, including uncertainty. Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged <16 years were extracted. Most data points (n = 182, 77.4%) were collected between 2000 and 2007. A Bayesian non-stationary regression model showed the best fit with annualized rainfall and maximum land surface temperature identified as significant environmental covariates. This model was used to predict malaria infection risk at non-sampled locations. High-risk areas were mainly found in the north-central and western area, while relatively low-risk areas were located in the north at the country border, in the north-east, in the south-east around Abidjan, and in the central-west between two high prevalence areas. The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d'Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation.
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Mapping malaria risk among children in Côte d’Ivoire using Bayesian geo-statistical models
2012-01-01
Background In Côte d’Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged <16 years in Côte d’Ivoire at high spatial resolution. Methods Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d’Ivoire, focusing on children aged <16 years. The period from 1988 to 2007 was covered. A suite of Bayesian geo-statistical logistic regression models was fitted to analyse malaria risk. Non-spatial models with and without exchangeable random effect parameters were compared to stationary and non-stationary spatial models. Non-stationarity was modelled assuming that the underlying spatial process is a mixture of separate stationary processes in each ecological zone. The best fitting model based on the deviance information criterion was used to predict Plasmodium spp. infection risk for entire Côte d’Ivoire, including uncertainty. Results Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged <16 years were extracted. Most data points (n = 182, 77.4%) were collected between 2000 and 2007. A Bayesian non-stationary regression model showed the best fit with annualized rainfall and maximum land surface temperature identified as significant environmental covariates. This model was used to predict malaria infection risk at non-sampled locations. High-risk areas were mainly found in the north-central and western area, while relatively low-risk areas were located in the north at the country border, in the north-east, in the south-east around Abidjan, and in the central-west between two high prevalence areas. Conclusion The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d’Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation. PMID:22571469
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The promise of cyborg intelligence.
Brown, Michael F; Brown, Alexander A
2017-03-01
Yu et al. (2016) demonstrated that algorithms designed to find efficient routes in standard mazes can be integrated with the natural processes controlling rat navigation and spatial choices, and they pointed out the promise of such "cyborg intelligence" for biorobotic applications. Here, we briefly describe Yu et al.'s work, explore its relevance to the study of comparative cognition, and indicate how work involving cyborg intelligence would benefit from interdisciplinary collaboration between behavioral scientists and engineers.
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Real-Time Processing of Pressure-Sensitive Paint Images
2006-12-01
intermediate or final data to the hard disk in 3D grid format. In addition to the pressure or pressure coefficient at every grid point, the saved file may...occurs. Nevertheless, to achieve an accurate mapping between 2D image coordinates and 3D spatial coordinates, additional parameters must be introduced. A...improved mapping between the 2D and 3D coordinates. In a more sophisticated approach, additional terms corresponding to specific deformation modes
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Systems Reliability Framework for Surface Water Sustainability and Risk Management
NASA Astrophysics Data System (ADS)
Myers, J. R.; Yeghiazarian, L.
2016-12-01
With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability. With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability.
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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.
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Spatial resolution in visual memory.
Ben-Shalom, Asaf; Ganel, Tzvi
2015-04-01
Representations in visual short-term memory are considered to contain relatively elaborated information on object structure. Conversely, representations in earlier stages of the visual hierarchy are thought to be dominated by a sensory-based, feed-forward buildup of information. In four experiments, we compared the spatial resolution of different object properties between two points in time along the processing hierarchy in visual short-term memory. Subjects were asked either to estimate the distance between objects or to estimate the size of one of the objects' features under two experimental conditions, of either a short or a long delay period between the presentation of the target stimulus and the probe. When different objects were referred to, similar spatial resolution was found for the two delay periods, suggesting that initial processing stages are sensitive to object-based properties. Conversely, superior resolution was found for the short, as compared with the long, delay when features were referred to. These findings suggest that initial representations in visual memory are hybrid in that they allow fine-grained resolution for object features alongside normal visual sensitivity to the segregation between objects. The findings are also discussed in reference to the distinction made in earlier studies between visual short-term memory and iconic memory.
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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
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Structure-from-motion approach for characterization of bioerosion patterns using UAV imagery.
Genchi, Sibila A; Vitale, Alejandro J; Perillo, Gerardo M E; Delrieux, Claudio A
2015-02-04
The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features.
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Structure-from-Motion Approach for Characterization of Bioerosion Patterns Using UAV Imagery
Genchi, Sibila A.; Vitale, Alejandro J.; Perillo, Gerardo M. E.; Delrieux, Claudio A.
2015-01-01
The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features. PMID:25658392
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NASA Astrophysics Data System (ADS)
Yakimov, E. B.; Polyakov, A. Y.; Smirnov, N. B.; Shchemerov, I. V.; Yang, Jiancheng; Ren, F.; Yang, Gwangseok; Kim, Jihyun; Pearton, S. J.
2018-05-01
The spatial distribution of electron-hole pair generation in β-Ga2O3 as a function of scanning electron microscope (SEM) beam energy has been calculated by a Monte Carlo method. This spatial distribution is then used to obtain the diffusion length of charge carriers in high-quality epitaxial Ga2O3 films from the dependence of the electron beam induced current (EBIC) collection efficiency on the accelerating voltage of a SEM. The experimental results show, contrary to earlier theory, that holes are mobile in β-Ga2O3 and to a large extent determine the diffusion length of charge carriers. Diffusion lengths in the range 350-400 nm are determined for the as-grown Ga2O3, while processes like exposing the samples to proton irradiation essentially halve this value, showing the role of point defects in controlling minority carrier transport. The pitfalls related to using other popular EBIC-based methods assuming a point-like excitation function are demonstrated. Since the point defect type and the concentration in currently available Ga2O3 are dependent on the growth method and the doping concentration, accurate methods of diffusion length determination are critical to obtain quantitative comparisons of material quality.
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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.
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Influence of different natural physical fields on biological processes
NASA Astrophysics Data System (ADS)
Mashinsky, A. L.
2001-01-01
In space flight conditions gravity, magnetic, and electrical fields as well as ionizing radiation change both in size, and in direction. This causes disruptions in the conduct of some physical processes, chemical reactions, and metabolism in living organisms. In these conditions organisms of different phylogenetic level change their metabolic reactions undergo changes such as disturbances in ionic exchange both in lower and in higher plants, changes in cell morphology for example, gyrosity in Proteus ( Proteus vulgaris), spatial disorientation in coleoptiles of Wheat ( Triticum aestivum) and Pea ( Pisum sativum) seedlings, mutational changes in Crepis ( Crepis capillaris) and Arabidopsis ( Arabidopsis thaliana) seedling. It has been found that even in the absence of gravity, gravireceptors determining spatial orientation in higher plants under terrestrial conditions are formed in the course of ontogenesis. Under weightlessness this system does not function and spatial orientation is determined by the light flux gradient or by the action of some other factors. Peculiarities of the formation of the gravireceptor apparatus in higher plants, amphibians, fish, and birds under space flight conditions have been observed. It has been found that the system in which responses were accompanied by phase transition have proven to be gravity-sensitive under microgravity conditions. Such reactions include also the process of photosynthesis which is the main energy production process in plants. In view of the established effects of microgravity and different natural physical fields on biological processes, it has been shown that these processes change due to the absence of initially rigid determination. The established biological effect of physical fields influence on biological processes in organisms is the starting point for elucidating the role of gravity and evolutionary development of various organisms on Earth.
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Aryal, Arjun; Brooks, Benjamin A.; Reid, Mark E.; Bawden, Gerald W.; Pawlak, Geno
2012-01-01
Acquiring spatially continuous ground-surface displacement fields from Terrestrial Laser Scanners (TLS) will allow better understanding of the physical processes governing landslide motion at detailed spatial and temporal scales. Problems arise, however, when estimating continuous displacement fields from TLS point-clouds because reflecting points from sequential scans of moving ground are not defined uniquely, thus repeat TLS surveys typically do not track individual reflectors. Here, we implemented the cross-correlation-based Particle Image Velocimetry (PIV) method to derive a surface deformation field using TLS point-cloud data. We estimated associated errors using the shape of the cross-correlation function and tested the method's performance with synthetic displacements applied to a TLS point cloud. We applied the method to the toe of the episodically active Cleveland Corral Landslide in northern California using TLS data acquired in June 2005–January 2007 and January–May 2010. Estimated displacements ranged from decimeters to several meters and they agreed well with independent measurements at better than 9% root mean squared (RMS) error. For each of the time periods, the method provided a smooth, nearly continuous displacement field that coincides with independently mapped boundaries of the slide and permits further kinematic and mechanical inference. For the 2010 data set, for instance, the PIV-derived displacement field identified a diffuse zone of displacement that preceded by over a month the development of a new lateral shear zone. Additionally, the upslope and downslope displacement gradients delineated by the dense PIV field elucidated the non-rigid behavior of the slide.
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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.
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NASA Astrophysics Data System (ADS)
Wollheim, W. M.; Mulukutla, G.; Cook, C.; Carey, R. O.
2014-12-01
Biogeochemical conditions throughout aquatic landscapes are spatially varied and temporally dynamic due to interactions of upstream land use, climate, hydrologic responses, and internal aquatic processes. One of the key goals in aquatic ecosystem ecology is to parse the upstream influences of terrestrial and aquatic processes on local conditions, which becomes progressively more difficult as watershed size increases and as processes are altered by diverse human activities. Simultaneous deployments of high frequency, in situ aquatic sensors for multiple constituents (e.g. NO3-N, CDOM, turbidity, conductivity, D.O., water temperature, along with flow) offer a new approach for understanding patterns along the aquatic continuum. For this talk, we explore strategies for deployments within single watersheds to improve understanding of terrestrial and aquatic processes. We address applications regarding mobilization of non-point nutrient sources across temporal scales, interactions with land use and watershed size, and the importance of aquatic processes. We also explore ways in which simultaneous sensor deployments can be designed to improve parameterization and testing of river network biogeochemical models. We will provide several specific examples using conductivity, nitrate and carbon from ongoing sensor deployments in New England, USA. We expect that improved deployments of sensors and sensor networks will benefit the management of critical freshwater resources.
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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.
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Snapshot science: new research possibilities facilitated by spatially dense data sets in limnology
NASA Astrophysics Data System (ADS)
Stanley, E. H.; Loken, L. C.; Crawford, J.; Butitta, V.; Schramm, P.
2017-12-01
The recent increase in availability of high frequency sensors is transforming the study of inland aquatic ecosystems, allowing the detection of rare or difficult-to-capture events, revealing previously unappreciated temporal dynamics, and providing rich data sets that can be used to calibrate or inform process-based models in ways that have not previously been possible. Yet sensor deployment is typically a 1-D practice, so insights are tempered by device placement. Limnologists have long known that there can be substantial spatial variability in physical, chemical, and biological features within water bodies, but in most cases, logistical difficulties limit our ability to quantify this heterogeneity. Recent improvements in remote sensing are helping to overcome this deficit for a subset of variables. Alternatively, devices such as the Fast Limnology Automated Measurement platform that deploy sensors on watercraft can be used to quickly generate spatially-rich data sets. This expanded capacity leads to new questions about what can be seen and learned about underlying processes. Surveys of multiple Wisconsin lakes reveal both homogeneity and heterogeneity among sites and variables, indicating that the limnological tradition of sampling at a single fixed point is unlikely to represent the entire lake area. Initial inferences drawn from surface water maps include identification of biogeochemical hotspots or areas of elevated loading. At a more sophisticated level, evaluation of changes in spatial structure among sites or dates is commonly used to infer process by landscape ecologists, and these same practices can now be applied to lakes and rivers. For example, a recent study documented significant changes in spatial variance and the magnitude of spatial autocorrelation of phycocyanin prior to the onset of a cyanobacterial bloom. This may provide information on population growth dynamics of cyanobacteria, and be used as early warnings of impending algal blooms. As the application of aquatic mapping tools expands in limnology, both by themselves and complemented by Lagrangian and traditional measurement approaches, we expect that the questions and insights they provide will again expand and shift our understanding of pattern and process in inland waters.
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NASA Astrophysics Data System (ADS)
Riihimaki, L. D.; Comstock, J. M.; Luke, E.; Thorsen, T. J.; Fu, Q.
2017-07-01
To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.
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Research of GIS-services applicability for solution of spatial analysis tasks.
NASA Astrophysics Data System (ADS)
Terekhin, D. A.; Botygin, I. A.; Sherstneva, A. I.; Sherstnev, V. S.
2017-01-01
Experiments for working out the areas of applying various gis-services in the tasks of spatial analysis are discussed in this paper. Google Maps, Yandex Maps, Microsoft SQL Server are used as services of spatial analysis. All services have shown a comparable speed of analyzing the spatial data when carrying out elemental spatial requests (building up the buffer zone of a point object) as well as the preferences of Microsoft SQL Server in operating with more complicated spatial requests. When building up elemental spatial requests, internet-services show higher efficiency due to cliental data handling with JavaScript-subprograms. A weak point of public internet-services is an impossibility to handle data on a server side and a barren variety of spatial analysis functions. Microsoft SQL Server offers a large variety of functions needed for spatial analysis on the server side. The authors conclude that when solving practical problems, the capabilities of internet-services used in building up routes and completing other functions with spatial analysis with Microsoft SQL Server should be involved.
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Topological Schemas of Memory Spaces.
Babichev, Andrey; Dabaghian, Yuri A
2018-01-01
Hippocampal cognitive map-a neuronal representation of the spatial environment-is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework-the memory space-that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as "networks of interconnections among the representations of events," have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature-a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure.
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Topological Schemas of Memory Spaces
Babichev, Andrey; Dabaghian, Yuri A.
2018-01-01
Hippocampal cognitive map—a neuronal representation of the spatial environment—is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework—the memory space—that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as “networks of interconnections among the representations of events,” have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature—a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure. PMID:29740306
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Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei
2016-10-01
Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.
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Point process models for localization and interdependence of punctate cellular structures.
Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F
2016-07-01
Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.
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A graph signal filtering-based approach for detection of different edge types on airborne lidar data
NASA Astrophysics Data System (ADS)
Bayram, Eda; Vural, Elif; Alatan, Aydin
2017-10-01
Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.
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Smith, Cindy J.; Dong, Liang F.; Wilson, John; Stott, Andrew; Osborn, A. Mark; Nedwell, David B.
2015-01-01
This research investigated spatial-temporal variation in benthic bacterial community structure, rates of denitrification and dissimilatory nitrate reduction to ammonium (DNRA) processes and abundances of corresponding genes and transcripts at three sites—the estuary-head, mid-estuary and the estuary mouth (EM) along the nitrate gradient of the Colne estuary over an annual cycle. Denitrification rates declined down the estuary, while DNRA rates were higher at the estuary head and middle than the EM. In four out of the six 2-monthly time-points, rates of DNRA were greater than denitrification at each site. Abundance of gene markers for nitrate-reduction (nitrate reductase narG and napA), denitrification (nitrite reductase nirS) and DNRA (DNRA nitrite reductase nrfA) declined along the estuary with significant relationships between denitrification and nirS abundance, and DNRA and nrfA abundance. Spatially, rates of denitrification, DNRA and corresponding functional gene abundances decreased along the estuary. However, temporal correlations between rate processes and functional gene and transcript abundances were not observed. PMID:26082763
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NASA Astrophysics Data System (ADS)
Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.
2003-04-01
Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.
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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.
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Brian R Miranda; Brian R Sturtevant; Susan I Stewart; Roger B. Hammer
2012-01-01
Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression...
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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…
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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.
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Computer graphic visualization of orbiter lower surface boundary-layer transition
NASA Technical Reports Server (NTRS)
Throckmorton, D. A.; Hartung, L. C.
1984-01-01
Computer graphic techniques are applied to the processing of Shuttle Orbiter flight data in order to create a visual presentation of the extent and movement of the boundary-layer transition front over the orbiter lower surface during entry. Flight-measured surface temperature-time histories define the onset and completion of the boundary-layer transition process at any measurement location. The locus of points which define the spatial position of the boundary-layer transition front on the orbiter planform is plotted at each discrete time for which flight data are available. Displaying these images sequentially in real-time results in an animated simulation of the in-flight boundary-layer transition process.
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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.
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Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000
NASA Astrophysics Data System (ADS)
Reba, Meredith; Reitsma, Femke; Seto, Karen C.
2016-06-01
How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends.
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Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000
Reba, Meredith; Reitsma, Femke; Seto, Karen C.
2016-01-01
How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends. PMID:27271481
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EPA Office of Water (OW): 2002 SPARROW Total NP (Catchments)
SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling tool with output that allows the user to interpret water quality monitoring data at the regional and sub-regional scale. The model relates in-stream water-quality measurements to spatially referenced characteristics of watersheds, including pollutant sources and environmental factors that affect rates of pollutant delivery to streams from the land and aquatic, in-stream processing . The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and non-point (or ??diffuse??) sources on land to rivers and through the stream and river network. SPARROW estimates contaminant concentrations, loads (or ??mass,?? which is the product of concentration and streamflow), and yields in streams (mass of nitrogen and of phosphorus entering a stream per acre of land). It empirically estimates the origin and fate of contaminants in streams and receiving bodies, and quantifies uncertainties in model predictions. The model predictions are illustrated through detailed maps that provide information about contaminant loadings and source contributions at multiple scales for specific stream reaches, basins, or other geographic areas.
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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.
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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.
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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
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NASA Astrophysics Data System (ADS)
Pillosu, F. M.; Hewson, T.; Mazzetti, C.
2017-12-01
Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (<2 days) and become prohibitively expensive at global scale. ECMWF/EFAS/GLOFAS have developed a novel, cost-effective and physically-based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will illustrate for ecPR 1) system calibration, 2) operational implementation, 3) long-term verification, 4) future developments, and 5) early ideas for the application of ecPR outputs in hydrological models.
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NASA Astrophysics Data System (ADS)
Comas, Carles; del Castillo, Jorge; Voltas, Jordi; Ferrio, Juan Pedro
2013-04-01
The stable isotope composition of xylem water reflects has been used to assess inter-specific differences in uptake patterns, revealing synergistic and competition processes in the use of water resources (see e.g. Dawson et al. 1993). However, there is a lack of detailed studies on spatial and temporal variability of inter- and intra-specific competition within forest stands. In this context, the aim of this work was to compare the isotope composition of xylem water (δ18O , δ2H) in two common Mediterranean tree species, Quercus ilex L. and Pinus halepensis Mill, in order to understand their water uptake patterns throughout the growing season. In addition, we analyze the spatial variability of xylem water, to get insight into inter-specific strategies employed to cope with drought and the interaction between the individuals. Our first hypothesis was that both species used different strategies to cope with drought by uptaking water at different depths; and our second hypothesis was that individual trees would behave in different manner according to the distance to their neighbours as well as to whether the neighbour is from one species or the other. The study was performed in a mixed stand where both species are nearly co-dominant, adding up to a total of 33 oaks and 77 pines (plot area= 893 m2). We sampled sun-exposed branches of each tree six times over the growing season, and extracted the xylem water with a cryogenic trap. The isotopic composition of the water was determined using a Picarro Water Analizer L2130-i. Tree mapping for spatial analysis was done using a high resolution GPS technology (Trimble GeoExplorer 6000). For the spatial analysis, we used the pair-correlation function to study intra-specific tree configuration and the bivariate pair correlation function to analyse the inter-specific spatial configurations (Stoyan et al 1995). Moreover, the isotopic composition of xylem water was assumed to be a mark associated to each tree and analysed as a marked point pattern. Preliminary results showed significant differences between species, but only during drought periods, confirming our first hypothesis. For example, in late-summer and early-autumn, the values for Q. Ilex (δ18O= -4.9 ±0.3 permille, δ2H=-53.5±1.2 permille) were significantly lower than for P. halepensis (δ18O= -1.1±0.2 permille, δ2H = -27.8±0.8 permille), pointing to the use of deeper soil layers by Q. ilex. On the other hand, point process analyses showed intra-specific interactions, whereas inter-specific interactions were not detected. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively. References Dawson TE et al. 1993. In: Ehleringer JR, Hall AE, Farquhar GD (eds) Stable isotopes and plant carbon-water relations. Academic Press, Inc. IPCC. 2007 Climate Change 2007: The Physical Science Basis. Cambridge UP. Stoyan D et al. 1995. Stochastic Geometry and its Applications. Wiley&Sons.
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Selective influence of prior allocentric knowledge on the kinesthetic learning of a path.
Lafon, Matthieu; Vidal, Manuel; Berthoz, Alain
2009-04-01
Spatial cognition studies have described two main cognitive strategies involved in the memorization of traveled paths in human navigation. One of these strategies uses the action-based memory (egocentric) of the traveled route or paths, which involves kinesthetic memory, optic flow, and episodic memory, whereas the other strategy privileges a survey memory of cartographic type (allocentric). Most studies have dealt with these two strategies separately, but none has tried to show the interaction between them in spite of the fact that we commonly use a map to imagine our journey and then proceed using egocentric navigation. An interesting question is therefore: how does prior allocentric knowledge of the environment affect the egocentric, purely kinesthetic navigation processes involved in human navigation? We designed an experiment in which blindfolded subjects had first to walk and memorize a path with kinesthetic cues only. They had previously been shown a map of the path, which was either correct or distorted (consistent shrinking or growing). The latter transformations were studied in order to observe what influence a distorted prior knowledge could have on spatial mechanisms. After having completed the first learning travel along the path, they had to perform several spatial tasks during the testing phase: (1) pointing towards the origin and (2) to specific points encountered along the path, (3) a free locomotor reproduction, and (4) a drawing of the memorized path. The results showed that prior cartographic knowledge influences the paths drawn and the spatial inference capacity, whereas neither locomotor reproduction nor spatial updating was disturbed. Our results strongly support the notion that (1) there are two independent neural bases underlying these mechanisms: a map-like representation allowing allocentric spatial inferences, and a kinesthetic memory of self-motion in space; and (2) a common use of, or a switching between, these two strategies is possible. Nevertheless, allocentric representations can emerge from the experience of kinesthetic cues alone.
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Multiplicity of the 660-km discontinuity beneath the Izu-Bonin area
NASA Astrophysics Data System (ADS)
Zhou, Yuan-Ze; Yu, Xiang-Wei; Yang, Hui; Zang, Shao-Xian
2012-05-01
The relatively simple subducting slab geometry in the Izu-Bonin region provides a valuable opportunity to study the multiplicity of the 660-km discontinuity and the related response of the subducting slab on the discontinuity. Vertical short-period recordings of deep events with simple direct P phases beneath the Izu-Bonin region were retrieved from two seismic networks in the western USA and were used to study the structure of the 660-km discontinuity. After careful selection and pre-processing, 23 events from the networks, forming 32 pairs of event-network records, were processed. Related vespagrams were produced using the N-th root slant stack method for detecting weak down-going SdP phases that were inverted to the related conversion points. From depth histograms and the spatial distribution of the conversion points, there were three clear interfaces at depths of 670, 710 and 730 km. These interfaces were depressed approximately 20-30 km in the northern region. In the southern region, only two layers were identified in the depth histograms, and no obvious layered structure could be observed from the distribution of the conversion points.
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An Automated Road Roughness Detection from Mobile Laser Scanning Data
NASA Astrophysics Data System (ADS)
Kumar, P.; Angelats, E.
2017-05-01
Rough roads influence the safety of the road users as accident rate increases with increasing unevenness of the road surface. Road roughness regions are required to be efficiently detected and located in order to ensure their maintenance. Mobile Laser Scanning (MLS) systems provide a rapid and cost-effective alternative by providing accurate and dense point cloud data along route corridor. In this paper, an automated algorithm is presented for detecting road roughness from MLS data. The presented algorithm is based on interpolating smooth intensity raster surface from LiDAR point cloud data using point thinning process. The interpolated surface is further processed using morphological and multi-level Otsu thresholding operations to identify candidate road roughness regions. The candidate regions are finally filtered based on spatial density and standard deviation of elevation criteria to detect the roughness along the road surface. The test results of road roughness detection algorithm on two road sections are presented. The developed approach can be used to provide comprehensive information to road authorities in order to schedule maintenance and ensure maximum safety conditions for road users.
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Mislocalization of tactile stimuli applied to the trunk in spatial neglect.
Rousseaux, Marc; Sauer, Angéline; Saj, Arnaud; Bernati, Thérèse; Honoré, Jacques
2013-01-01
In patients with spatial neglect, body perception and representation are impaired - especially the projection of the anterior body midline in anterior space (the subjective "straight ahead"). However, data on more lateral body parts and the posterior body surface are scarce. We explored deviations of the perception of different body points located to the left or right of the midline and on the anterior and posterior body surfaces, and their lesion correlates in right hemisphere stroke patients. Nine patients with neglect (diagnosed with paper and pencil and behavioural tests) were compared with six non-neglect patients and 13 healthy controls. The subjects had to use a mannequin to designate the body location that had been stimulated by a blunt pencil tip. Four horizontally arranged series of locations were traced on the anterior and posterior body surfaces at shoulder and navel levels. Each horizontal series comprised five equidistant test points, from left to right and corresponded to eleven labelled points on the mannequin. Patient errors were confronted to their anatomic lesions (MRI). We found a significant (p ≤ .05) rightward deviation of the left-side points and midpoint and a significant leftward deviation of the right-most point in neglect patients. Non-neglect patients and control subjects designated all the test points accurately. The body side (anterior or posterior) and the line (shoulder or navel) did not influence performance. Controls showed a definite reduction in variability for the midline points, which disappeared in neglect patients who showed a severe global increase of this variability. Errors depended on lesions centred on the intraparietal sulcus. These observations were compatible with a complex bias in body perception-representation extending to various lateral body points, with a left to right gradient. The right parietal cortex likely participates in processing such information. Copyright © 2013 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Chen, Nan
2018-03-01
Conversion of points or lines from vector to grid format, or vice versa, is the first operation required for most spatial analysis. Conversion, however, usually causes the location of points or lines to change, which influences the reliability of the results of spatial analysis or even results in analysis errors. The purpose of this paper is to evaluate the change of the location of points and lines during conversion using the concepts of probability and entropy. This paper shows that when a vector point is converted to a grid point, the vector point may be outside or inside the grid point. This paper deduces a formula for computing the probability that the vector point is inside the grid point. It was found that the probability increased with the side length of the grid and with the variances of the coordinates of the vector point. In addition, the location entropy of points and lines are defined in this paper. Formulae for computing the change of the location entropy during conversion are deduced. The probability mentioned above and the change of location entropy may be used to evaluate the location reliability of points and lines in Geographic Information Systems and may be used to choose an appropriate range of the side length of grids before conversion. The results of this study may help scientists and users to avoid mistakes caused by the change of location during conversion as well as in spatial decision and analysis.
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3D hierarchical spatial representation and memory of multimodal sensory data
NASA Astrophysics Data System (ADS)
Khosla, Deepak; Dow, Paul A.; Huber, David J.
2009-04-01
This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.
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Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes
NASA Astrophysics Data System (ADS)
Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian
2014-05-01
Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.
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Passaiacquaa, Paola; Belmont, Patrick; Staley, Dennis M.; Simley, Jeffery; Arrowsmith, J. Ramon; Bode, Collin A.; Crosby, Christopher; DeLong, Stephen; Glenn, Nancy; Kelly, Sara; Lague, Dimitri; Sangireddy, Harish; Schaffrath, Keelin; Tarboton, David; Wasklewicz, Thad; Wheaton, Joseph
2015-01-01
The study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data.In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT.
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NASA Astrophysics Data System (ADS)
Lopez, Benjamin; Baran, Nicole; Bourgine, Bernard
2015-03-01
The European Water Framework Directive (WFD) asks Member States to identify trends in contaminant concentrations in groundwater and to take measures to reach a good chemical status by 2015. In this study, carried out in a large hydrological basin (95,300 km2), an innovative procedure is described for the assessment of recent trends in groundwater nitrate concentrations both at sampling point and regional scales. Temporal variograms of piezometric and nitrate concentration time series are automatically calculated and fitted in order to classify groundwater according to their temporal pattern. These results are then coupled with aquifer lithology to map spatial units within which the modes of diffuse transport of contaminants towards groundwater are assumed to be the same at all points. These spatial units are suitable for evaluating regional trends. The stability over time of the time series is tested based on the cumulative sum principle, to determine the time period during which the trend should be sought. The Mann-Kendall and Regional-Kendall nonparametric tests for monotonic trends, coupled with the Sen-slope test, are applied to the periods following the point breaks thus determined at both the sampling point or regional scales. This novel procedure is robust and enables rapid processing of large databases of raw data. It would therefore be useful for managing groundwater quality in compliance with the aims of the WFD.
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Dumont, Julie R.; Amin, Eman; Wright, Nicholas F.; Dillingham, Christopher M.; Aggleton, John P.
2015-01-01
The present study sought to understand how the hippocampus and anterior thalamic nuclei are conjointly required for spatial learning by examining the impact of cutting a major tract (the fornix) that interconnects these two sites. The initial experiments examined the consequences of fornix lesions in rats on spatial biconditional discrimination learning. The rationale arose from previous findings showing that fornix lesions spare the learning of spatial biconditional tasks, despite the same task being highly sensitive to both hippocampal and anterior thalamic nuclei lesions. In the present study, fornix lesions only delayed acquisition of the spatial biconditional task, pointing to additional contributions from non-fornical routes linking the hippocampus with the anterior thalamic nuclei. The same fornix lesions spared the learning of an analogous nonspatial biconditional task that used local contextual cues. Subsequent tests, including T-maze place alternation, place learning in a cross-maze, and a go/no-go place discrimination, highlighted the impact of fornix lesions when distal spatial information is used flexibly to guide behaviour. The final experiment examined the ability to learn incidentally the spatial features of a square water-maze that had differently patterned walls. Fornix lesions disrupted performance but did not stop the rats from distinguishing the various corners of the maze. Overall, the results indicate that interconnections between the hippocampus and anterior thalamus, via the fornix, help to resolve problems with flexible spatial and temporal cues, but the results also signal the importance of additional, non-fornical contributions to hippocampal-anterior thalamic spatial processing, particularly for problems with more stable spatial solutions. PMID:25453745
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Ulrich, Craig; Hubbard, Susan S.; Florsheim, Joan; Rosenberry, Donald O.; Borglin, Sharon; Trotta, Marcus; Seymour, Donald
2015-01-01
An experimental field study was performed to investigate riverbed clogging processes and associated monitoring approaches near a dam-controlled riverbank filtration facility in Northern California. Motivated by previous studies at the site that indicated riverbed clogging plays an important role in the performance of the riverbank filtration system, we investigated the spatiotemporal variability and nature of the clogging. In particular, we investigated whether the clogging was due to abiotic or biotic mechanisms. A secondary aspect of the study was the testing of different methods to monitor riverbed clogging and related processes, such as seepage. Monitoring was conducted using both point-based approaches and spatially extensive geophysical approaches, including: grain-size analysis, temperature sensing, electrical resistivity tomography, seepage meters, microbial analysis, and cryocoring, along two transects. The point monitoring measurements suggested a substantial increase in riverbed biomass (2 orders of magnitude) after the dam was raised compared to the small increase (∼2%) in fine-grained sediment. These changes were concomitant with decreased seepage. The decreased seepage eventually led to the development of an unsaturated zone beneath the riverbed, which further decreased infiltration capacity. Comparison of our time-lapse grain-size and biomass datasets suggested that biotic processes played a greater role in clogging than did abiotic processes. Cryocoring and autonomous temperature loggers were most useful for locally monitoring clogging agents, while electrical resistivity data were useful for interpreting the spatial extent of a pumping-induced unsaturated zone that developed beneath the riverbed after riverbed clogging was initiated. The improved understanding of spatiotemporally variable riverbed clogging and monitoring approaches is expected to be useful for optimizing the riverbank filtration system operations.
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Min-Cut Based Segmentation of Airborne LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
Ural, S.; Shan, J.
2012-07-01
Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance parameter does not strongly conform to the natural structure of the points. Including shape information within the energy function by assigning costs based on the local properties may help to achieve a better representation for segmentation.
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Mapping the global depth to bedrock for land surface modelling
NASA Astrophysics Data System (ADS)
Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.
2017-12-01
Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.
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Mapping the global depth to bedrock for land surface modeling
NASA Astrophysics Data System (ADS)
Shangguan, Wei; Hengl, Tomislav; Mendes de Jesus, Jorge; Yuan, Hua; Dai, Yongjiu
2017-03-01
Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.
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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
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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.
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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.
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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.
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Spatial Sampling of Weather Data for Regional Crop Yield Simulations
NASA Technical Reports Server (NTRS)
Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;
2016-01-01
Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.
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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.
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Mark Spencer; Kevin O' Hara
2006-01-01
Phytophthora ramorum is a major source of tanoak (Lithocarpus densiflorus) mortality in the tanoak/redwood (Sequoia sempervirens) forests of central California. This study presents a spatial analysis of the spread of the disease using second-order point pattern and GIS analyses. Our data set includes four plots...
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Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.
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).
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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.
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Exploratory Spatial Analysis of in vitro Respiratory Syncytial Virus Co-infections
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
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Spatializing Critical Education: Progress and Cautions
ERIC Educational Resources Information Center
Ferrare, Joseph J.; Apple, Michael W.
2010-01-01
Recently critical scholars have shown a renewed interest in spatial relations in educational contexts. In this essay we use selections from Gulson and Symes's edited volume "Spatial theories of education" as a point of departure to examine what spatial analysis can contribute to the critical education traditions. We argue that, when done…
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Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.
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.
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Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders
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. PMID:27902724
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NASA Astrophysics Data System (ADS)
Yang, DeSen; Zhu, ZhongRui
2012-12-01
This work investigates the direction-of-arrival (DOA) estimation for a uniform circular acoustic Vector-Sensor Array (UCAVSA) mounted around a cylindrical baffle. The total pressure field and the total particle velocity field near the surface of the cylindrical baffle are analyzed theoretically by applying the method of spatial Fourier transform. Then the so-called modal vector-sensor array signal processing algorithm, which is based on the decomposed wavefield representations, for the UCAVSA mounted around the cylindrical baffle is proposed. Simulation and experimental results show that the UCAVSA mounted around the cylindrical baffle has distinct advantages over the same manifold of traditional uniform circular pressure-sensor array (UCPSA). It is pointed out that the acoustic Vector-Sensor (AVS) could be used under the condition of the cylindrical baffle and that the UCAVSA mounted around the cylindrical baffle could also combine the anti-noise performance of the AVS with spatial resolution performance of array system by means of modal vector-sensor array signal processing algorithms.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lerm, S.; Kleyboecker, A.; Miethling-Graff, R.
2012-03-15
Highlights: Black-Right-Pointing-Pointer Two types of methanogens are necessary to respond successfully to perturbation. Black-Right-Pointing-Pointer Diversity of methanogens correlates with the VFA concentration and methane yield. Black-Right-Pointing-Pointer Aggregates indicate tight spatial relationship between minerals and microorganisms. - Abstract: Microbial community diversity in two thermophilic laboratory-scale and three full-scale anaerobic co-digesters was analysed by genetic profiling based on PCR-amplified partial 16S rRNA genes. In parallel operated laboratory reactors a stepwise increase of the organic loading rate (OLR) resulted in a decrease of methane production and an accumulation of volatile fatty acids (VFAs). However, almost threefold different OLRs were necessary to inhibit themore » gas production in the reactors. During stable reactor performance, no significant differences in the bacterial community structures were detected, except for in the archaeal communities. Sequencing of archaeal PCR products revealed a dominance of the acetoclastic methanogen Methanosarcina thermophila, while hydrogenotrophic methanogens were of minor importance and differed additionally in their abundance between reactors. As a consequence of the perturbation, changes in bacterial and archaeal populations were observed. After organic overload, hydrogenotrophic methanogens (Methanospirillum hungatei and Methanoculleus receptaculi) became more dominant, especially in the reactor attributed by a higher OLR capacity. In addition, aggregates composed of mineral and organic layers formed during organic overload and indicated tight spatial relationships between minerals and microbial processes that may support de-acidification processes in over-acidified sludge. Comparative analyses of mesophilic stationary phase full-scale reactors additionally indicated a correlation between the diversity of methanogens and the VFA concentration combined with the methane yield. This study demonstrates that the coexistence of two types of methanogens, i.e. hydrogenotrophic and acetoclastic methanogens is necessary to respond successfully to perturbation and leads to stable process performance.« less
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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.
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Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis.
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.
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Forest fire spatial pattern analysis in Galicia (NW Spain).
Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W
2013-10-15
Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Fluvial process and the establishment of bottomland trees
Scott, Michael L.; Friedman, Jonathan M.; Auble, Gregor T.
1996-01-01
The relation between streamflow and establishment of bottomland trees is conditioned by the dominant fluvial process or processes acting along a stream. For successful establishment, cottonwoods, poplars, and willows require bare, moist surfaces protected from disturbance. Channel narrowing, channel meandering, and flood deposition promote different spatial and temporal patterns of establishment. During channel narrowing, the site requirements are met on portions of the bed abandoned by the stream, and establishment is associated with a period of low flow lasting one to several years. During channel meandering, the requirements are met on point bars following moderate or higher peak flows. Following flood deposition, the requirements are met on flood deposits ;high above the channel bed. Flood deposition can occur along most streams, but where a channel is constrained by a narrow valley, this process may be the only mechanism that can produce a bare, moist surface high enough to be safe from future disturbance. Because of differences in local bedrock, tributary influence, or geologic history, two nearby reaches of the same stream may be dominated by different fluvial processes and have different spatial and temporal patterns of trees. We illustrate this phenomenon with examples from forests of plains cottonwood (Populus deltoides ssp. monilifera) along meandering and constrained reaches of the Missouri River in Montana.
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NASA Astrophysics Data System (ADS)
Schrön, Martin; Köhli, Markus; Scheiffele, Lena; Iwema, Joost; Bogena, Heye R.; Lv, Ling; Martini, Edoardo; Baroni, Gabriele; Rosolem, Rafael; Weimar, Jannis; Mai, Juliane; Cuntz, Matthias; Rebmann, Corinna; Oswald, Sascha E.; Dietrich, Peter; Schmidt, Ulrich; Zacharias, Steffen
2017-10-01
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
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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.
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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.
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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.
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NASA Astrophysics Data System (ADS)
Kay, J. E.; Hansen, G.; Gillespie, A.; Pettit, E.
2002-12-01
Relating cryosphere change to climate change requires estimation of radiative fluxes on snow-covered surfaces. The distribution of, and relationship between, snow-pack properties that affect radiative balance can be estimated with high-resolution remote-sensing data. MODIS/ASTER airborne simulator (MASTER) data were collected at Mt. Rainier to reveal spatial patterns of, and correlations between, snow contaminant content, grain size, and temperature. The visible and near-infrared (VNIR: 11 bands, 0.4-1.0 μm) and the short-wave infrared (SWIR: 14 bands, 1.6-2.4 μm) data are processed to bi-directional reflectance (BDR) and albedo, by removing atmospheric effects and by normalizing to Solar irradiance and incidence angle. VNIR BDR and albedo are used as a proxy for snow contaminant content. Physical and optical grain size are estimated by comparing SWIR BDR and albedo to modeled and measured spectra, and ground-truth measurements. The thermal infrared data (TIR: 10 bands, 8-13 μm) are processed to temperature by removing emissivity and atmospheric effects. In combination, the VNIR, SWIR, and TIR data reveal a distinct pattern of contaminants, grain size, and temperature related to a recent snowfall and the end-of-the-summer melting season. At lower elevations, the surface accumulation of dirty lag deposits resulted in snow with very low visible albedo (20-30 %), large physical and optical grain radii (500-1500 μm, 200 μm), and temperatures near the melting point. At higher elevations, the recent snowfall left snow with low contaminant content, and a higher visible albedo (60-90 %). However, a region near the summit with smaller physical and optical grain radii (400 μm, 100 μm), and temperatures below the melting point, is distinguished from a middle elevation region with grain sizes and temperatures similar to the lower region. Contaminants reduce VNIR albedo and significantly enhance absorption of incoming solar radiation. The spatial correlation between temperature and grain size supports the idea that rapid, destructive metamorphism occurs when snow temperatures are at the melting point.
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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.
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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.
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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.
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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.
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Human body motion capture from multi-image video sequences
NASA Astrophysics Data System (ADS)
D'Apuzzo, Nicola
2003-01-01
In this paper is presented a method to capture the motion of the human body from multi image video sequences without using markers. The process is composed of five steps: acquisition of video sequences, calibration of the system, surface measurement of the human body for each frame, 3-D surface tracking and tracking of key points. The image acquisition system is currently composed of three synchronized progressive scan CCD cameras and a frame grabber which acquires a sequence of triplet images. Self calibration methods are applied to gain exterior orientation of the cameras, the parameters of internal orientation and the parameters modeling the lens distortion. From the video sequences, two kinds of 3-D information are extracted: a three-dimensional surface measurement of the visible parts of the body for each triplet and 3-D trajectories of points on the body. The approach for surface measurement is based on multi-image matching, using the adaptive least squares method. A full automatic matching process determines a dense set of corresponding points in the triplets. The 3-D coordinates of the matched points are then computed by forward ray intersection using the orientation and calibration data of the cameras. The tracking process is also based on least squares matching techniques. Its basic idea is to track triplets of corresponding points in the three images through the sequence and compute their 3-D trajectories. The spatial correspondences between the three images at the same time and the temporal correspondences between subsequent frames are determined with a least squares matching algorithm. The results of the tracking process are the coordinates of a point in the three images through the sequence, thus the 3-D trajectory is determined by computing the 3-D coordinates of the point at each time step by forward ray intersection. Velocities and accelerations are also computed. The advantage of this tracking process is twofold: it can track natural points, without using markers; and it can track local surfaces on the human body. In the last case, the tracking process is applied to all the points matched in the region of interest. The result can be seen as a vector field of trajectories (position, velocity and acceleration). The last step of the process is the definition of selected key points of the human body. A key point is a 3-D region defined in the vector field of trajectories, whose size can vary and whose position is defined by its center of gravity. The key points are tracked in a simple way: the position at the next time step is established by the mean value of the displacement of all the trajectories inside its region. The tracked key points lead to a final result comparable to the conventional motion capture systems: 3-D trajectories of key points which can be afterwards analyzed and used for animation or medical purposes.
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Effects of input uncertainty on cross-scale crop modeling
NASA Astrophysics Data System (ADS)
Waha, Katharina; Huth, Neil; Carberry, Peter
2014-05-01
The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.
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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
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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.
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NASA Astrophysics Data System (ADS)
Sanskrityayn, Abhishek; Suk, Heejun; Kumar, Naveen
2017-04-01
In this study, analytical solutions of one-dimensional pollutant transport originating from instantaneous and continuous point sources were developed in groundwater and riverine flow using both Green's Function Method (GFM) and pertinent coordinate transformation method. Dispersion coefficient and flow velocity are considered spatially and temporally dependent. The spatial dependence of the velocity is linear, non-homogeneous and that of dispersion coefficient is square of that of velocity, while the temporal dependence is considered linear, exponentially and asymptotically decelerating and accelerating. Our proposed analytical solutions are derived for three different situations depending on variations of dispersion coefficient and velocity, respectively which can represent real physical processes occurring in groundwater and riverine systems. First case refers to steady solute transport situation in steady flow in which dispersion coefficient and velocity are only spatially dependent. The second case represents transient solute transport in steady flow in which dispersion coefficient is spatially and temporally dependent while the velocity is spatially dependent. Finally, the third case indicates transient solute transport in unsteady flow in which both dispersion coefficient and velocity are spatially and temporally dependent. The present paper demonstrates the concentration distribution behavior from a point source in realistically occurring flow domains of hydrological systems including groundwater and riverine water in which the dispersivity of pollutant's mass is affected by heterogeneity of the medium as well as by other factors like velocity fluctuations, while velocity is influenced by water table slope and recharge rate. Such capabilities give the proposed method's superiority about application of various hydrological problems to be solved over other previously existing analytical solutions. Especially, to author's knowledge, any other solution doesn't exist for both spatially and temporally variations of dispersion coefficient and velocity. In this study, the existing analytical solutions from previous widely known studies are used for comparison as validation tools to verify the proposed analytical solution as well as the numerical code of the Two-Dimensional Subsurface Flow, Fate and Transport of Microbes and Chemicals (2DFATMIC) code and the developed 1D finite difference code (FDM). All such solutions show perfect match with the respective proposed solutions.
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Phencyclidine Discoordinates Hippocampal Network Activity But Not Place Fields
Kao, Hsin-Yi; Kenney, Jana; Kelemen, Eduard
2017-01-01
We used the psychotomimetic phencyclidine (PCP) to investigate the relationships among cognitive behavior, coordinated neural network function, and information processing within the hippocampus place cell system. We report in rats that PCP (5 mg/kg, i.p.) impairs a well learned, hippocampus-dependent place avoidance behavior in rats that requires cognitive control even when PCP is injected directly into dorsal hippocampus. PCP increases 60–100 Hz medium-freguency gamma oscillations in hippocampus CA1 and these increases correlate with the cognitive impairment caused by systemic PCP administration. PCP discoordinates theta-modulated medium-frequency and slow gamma oscillations in CA1 LFPs such that medium-frequency gamma oscillations become more theta-organized than slow gamma oscillations. CA1 place cell firing fields are preserved under PCP, but the drug discoordinates the subsecond temporal organization of discharge among place cells. This discoordination causes place cell ensemble representations of a familiar space to cease resembling pre-PCP representations despite preserved place fields. These findings point to the cognitive impairments caused by PCP arising from neural discoordination. PCP disrupts the timing of discharge with respect to the subsecond timescales of theta and gamma oscillations in the LFP. Because these oscillations arise from local inhibitory synaptic activity, these findings point to excitation–inhibition discoordination as the root of PCP-induced cognitive impairment. SIGNIFICANCE STATEMENT Hippocampal neural discharge is temporally coordinated on timescales of theta and gamma oscillations in the LFP and the discharge of a subset of pyramidal neurons called “place cells” is spatially organized such that discharge is restricted to locations called a cell's “place field.” Because this temporal coordination and spatial discharge organization is thought to represent spatial knowledge, we used the psychotomimetic phencyclidine (PCP) to disrupt cognitive behavior and assess the importance of neural coordination and place fields for spatial cognition. PCP impaired the judicious use of spatial information and discoordinated hippocampal discharge without disrupting firing fields. These findings dissociate place fields from spatial cognitive behavior and suggest that hippocampus discharge coordination is crucial to spatial cognition. PMID:29118102
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Spatially explicit spectral analysis of point clouds and geospatial data
Buscombe, Daniel D.
2015-01-01
The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.
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Hu, Yue-Hua; Kitching, Roger L.; Lan, Guo-Yu; Zhang, Jiao-Lin; Sha, Li-Qing; Cao, Min
2014-01-01
We have investigated the processes of community assembly using size classes of trees. Specifically our work examined (1) whether point process models incorporating an effect of size-class produce more realistic summary outcomes than do models without this effect; (2) which of three selected models incorporating, respectively environmental effects, dispersal and the joint-effect of both of these, is most useful in explaining species-area relationships (SARs) and point dispersion patterns. For this evaluation we used tree species data from the 50-ha forest dynamics plot in Barro Colorado Island, Panama and the comparable 20 ha plot at Bubeng, Southwest China. Our results demonstrated that incorporating an size-class effect dramatically improved the SAR estimation at both the plots when the dispersal only model was used. The joint effect model produced similar improvement but only for the 50-ha plot in Panama. The point patterns results were not improved by incorporation of size-class effects using any of the three models. Our results indicate that dispersal is likely to be a key process determining both SARs and point patterns. The environment-only model and joint-effects model were effective at the species level and the community level, respectively. We conclude that it is critical to use multiple summary characteristics when modelling spatial patterns at the species and community levels if a comprehensive understanding of the ecological processes that shape species’ distributions is sought; without this results may have inherent biases. By influencing dispersal, the effect of size-class contributes to species assembly and enhances our understanding of species coexistence. PMID:25251538
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Recovering the fine structures in solar images
NASA Technical Reports Server (NTRS)
Karovska, Margarita; Habbal, S. R.; Golub, L.; Deluca, E.; Hudson, Hugh S.
1994-01-01
Several examples of the capability of the blind iterative deconvolution (BID) technique to recover the real point spread function, when limited a priori information is available about its characteristics. To demonstrate the potential of image post-processing for probing the fine scale and temporal variability of the solar atmosphere, the BID technique is applied to different samples of solar observations from space. The BID technique was originally proposed for correction of the effects of atmospheric turbulence on optical images. The processed images provide a detailed view of the spatial structure of the solar atmosphere at different heights in regions with different large-scale magnetic field structures.
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NASA Astrophysics Data System (ADS)
James, Mike R.; Robson, Stuart; d'Oleire-Oltmanns, Sebastian; Niethammer, Uwe
2016-04-01
Structure-from-motion (SfM) algorithms are greatly facilitating the production of detailed topographic models based on images collected by unmanned aerial vehicles (UAVs). However, SfM-based software does not generally provide the rigorous photogrammetric analysis required to fully understand survey quality. Consequently, error related to problems in control point data or the distribution of control points can remain undiscovered. Even if these errors are not large in magnitude, they can be systematic, and thus have strong implications for the use of products such as digital elevation models (DEMs) and orthophotos. Here, we develop a Monte Carlo approach to (1) improve the accuracy of products when SfM-based processing is used and (2) reduce the associated field effort by identifying suitable lower density deployments of ground control points. The method highlights over-parameterisation during camera self-calibration and provides enhanced insight into control point performance when rigorous error metrics are not available. Processing was implemented using commonly-used SfM-based software (Agisoft PhotoScan), which we augment with semi-automated and automated GCPs image measurement. We apply the Monte Carlo method to two contrasting case studies - an erosion gully survey (Taurodont, Morocco) carried out with an fixed-wing UAV, and an active landslide survey (Super-Sauze, France), acquired using a manually controlled quadcopter. The results highlight the differences in the control requirements for the two sites, and we explore the implications for future surveys. We illustrate DEM sensitivity to critical processing parameters and show how the use of appropriate parameter values increases DEM repeatability and reduces the spatial variability of error due to processing artefacts.
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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.
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Perceived Ownership of Avatars Influences Visual Perspective Taking
Böffel, Christian; Müsseler, Jochen
2018-01-01
Modern computer-based applications often require the user to interact with avatars. Depending on the task at hand, spatial dissociation between the orientations of the user and the avatars might arise. As a consequence, the user has to adopt the avatar’s perspective and identify herself/himself with the avatar, possibly changing the user’s self-representation in the process. The present study aims to identify the conditions that benefit this change of perspective with objective performance measures and subjective self-estimations by integrating the idea of avatar-ownership into the cognitive phenomenon of spatial compatibility. Two different instructions were used to manipulate a user’s perceived ownership of an avatar in otherwise identical situations. Users with the high-ownership instruction reported higher levels of perceived ownership of the avatar and showed larger spatial compatibility effects from the avatar’s point of view in comparison to the low ownership instruction. This supports the hypothesis that perceived ownership benefits perspective taking. PMID:29887816
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Visuospatial deficits in schizophrenia: central executive and memory subsystems impairments.
Leiderman, Eduardo A; Strejilevich, Sergio A
2004-06-01
Object and spatial visual working memory are impaired in schizophrenic patients. It is not clear if the impairments reside in each memory subsystem alone or also in the central executive component that coordinates these processes. In order to elucidate which memory component is impaired, we developed a paradigm with single spatial and object working memory tasks and dual ones with two different delays (5 and 30 s). Fifteen schizophrenic patients and 14 control subjects performed these tests. Schizophrenic patients had a poorer performance compared to normal controls in all tasks and in all time delays. Both schizophrenics and controls performed significantly worse in the object task than in the spatial task. The performance was even worse in the dual task compared to the singles ones in schizophrenic patients but not in controls. These data suggest that visuospatial performance deficits in schizophrenia are due to both visuospatial memory subsystems impairments and central executive ones. The pattern of deficits observed points to a codification or evocation deficit and not to a maintenance one.
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Rodo, Christophe; Sargolini, Francesca; Save, Etienne
2017-03-01
The entorhinal-hippocampal circuitry has been suggested to play an important role in episodic memory but the contribution of the entorhinal cortex remains elusive. Predominant theories propose that the medial entorhinal cortex (MEC) processes spatial information whereas the lateral entorhinal cortex (LEC) processes non spatial information. A recent study using an object exploration task has suggested that the involvement of the MEC and LEC spatial and non-spatial information processing could be modulated by the amount of information to be processed, i.e. environmental complexity. To address this hypothesis we used an object exploration task in which rats with excitotoxic lesions of the MEC and LEC had to detect spatial and non-spatial novelty among a set of objects and we varied environmental complexity by decreasing the number of objects or amount of object diversity. Reducing diversity resulted in restored ability to process spatial and non-spatial information in MEC and LEC groups, respectively. Reducing the number of objects yielded restored ability to process non-spatial information in the LEC group but not the ability to process spatial information in the MEC group. The findings indicate that the MEC and LEC are not strictly necessary for spatial and non-spatial processing but that their involvement depends on the complexity of the information to be processed. Copyright © 2016 Elsevier B.V. All rights reserved.
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Reduced vision selectively impairs spatial updating in fall-prone older adults.
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.
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Using Imaging Methods to Interrogate Radiation-Induced Cell Signaling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shankaran, Harish; Weber, Thomas J.; Freiin von Neubeck, Claere H.
2012-04-01
There is increasing emphasis on the use of systems biology approaches to define radiation induced responses in cells and tissues. Such approaches frequently rely on global screening using various high throughput 'omics' platforms. Although these methods are ideal for obtaining an unbiased overview of cellular responses, they often cannot reflect the inherent heterogeneity of the system or provide detailed spatial information. Additionally, performing such studies with multiple sampling time points can be prohibitively expensive. Imaging provides a complementary method with high spatial and temporal resolution capable of following the dynamics of signaling processes. In this review, we utilize specific examplesmore » to illustrate how imaging approaches have furthered our understanding of radiation induced cellular signaling. Particular emphasis is placed on protein co-localization, and oscillatory and transient signaling dynamics.« less
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Thermal responses in a coronal loop maintained by wave heating mechanisms
NASA Astrophysics Data System (ADS)
Matsumoto, Takuma
2018-05-01
A full 3-dimensional compressible magnetohydrodynamic (MHD) simulation is conducted to investigate the thermal responses of a coronal loop to the dynamic dissipation processes of MHD waves. When the foot points of the loop are randomly and continuously forced, the MHD waves become excited and propagate upward. Then, 1-MK temperature corona is produced naturally as the wave energy dissipates. The excited wave packets become non-linear just above the magnetic canopy, and the wave energy cascades into smaller spatial scales. Moreover, collisions between counter-propagating Alfvén wave packets increase the heating rate, resulting in impulsive temperature increases. Our model demonstrates that the heating events in the wave-heated loops can be nanoflare-like in the sense that they are spatially localized and temporally intermittent.
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Martarelli, Corinna S; Mast, Fred W; Hartmann, Matthias
2017-01-01
Time is grounded in various ways, and previous studies point to a "mental time line" with past associated with the left, and future with the right side. In this study, we investigated whether spontaneous eye movements on a blank screen would follow a mental timeline during encoding, free recall, and recognition of past and future items. In all three stages of processing, gaze position was more rightward during future items compared to past items. Moreover, horizontal gaze position during encoding predicted horizontal gaze position during free recall and recognition. We conclude that mental time line and the stored gaze position during encoding assist memory retrieval of past versus future items. Our findings highlight the spatial nature of temporal representations.
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Parameters influencing focalization spot in time reversal of acoustic waves
NASA Astrophysics Data System (ADS)
Zophoniasson, Harald; Bolzmacher, Christian; Hafez, Moustafa
2015-05-01
Time reversal is an approach that can be used to focus acoustic waves in a particular location on a surface, allowing a multitouch tactile feedback interaction. The spatial resolution in this case depends on several parameters, such as geometrical parameters, frequency used and material properties, described by the Lamb wave theory. This paper highlights the impact of frequency, geometrical parameters such as plate thickness and transducer's surface on the focused spot dimensions. In this paper a study of the influence of the plate's thickness and the frequency bandwidth used in the focusing process is presented. It is also shown that the dimension of the piezoelectric diaphragms used has little influence on the spatial resolution. Resonant behavior of the plate and its implication on focus point dimension and focalization contrast were investigated.
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Oscillations and waves in a spatially distributed system with a 1/f spectrum
NASA Astrophysics Data System (ADS)
Koverda, V. P.; Skokov, V. N.
2018-02-01
A spatially distributed system with a 1/f power spectrum is described by two nonlinear stochastic equations. Conditions for the formation of auto-oscillations have been found using numerical methods. The formation of a 1/f and 1/k spectrum simultaneously with the formation and motion of waves under the action of white noise has been demonstrated. The large extreme fluctuations with 1/f and 1/k spectra correspond to the maximum entropy, which points to the stability of such processes. It is shown that on the background of formation and motion of waves at an external periodic action there appears spatio-temporal stochastic resonance, at which one can observe the expansion of the region of periodic pulsations under the action of white noise.
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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.
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Advances in Domain Connectivity for Overset Grids Using the X-Rays Approach
NASA Technical Reports Server (NTRS)
Chan, William M.; Kim, Noah; Pandya, Shishir A.
2012-01-01
Advances in automation and robustness of the X-rays approach to domain connectivity for overset grids are presented. Given the surface definition for each component that makes up a complex configuration, the determination of hole points with appropriate hole boundaries is automatically and efficiently performed. Improvements made to the original X-rays approach for identifying the minimum hole include an automated closure scheme for hole-cutters with open boundaries, automatic determination of grid points to be considered for blanking by each hole-cutter, and an adaptive X-ray map to economically handle components in close proximity. Furthermore, an automated spatially varying offset of the hole boundary from the minimum hole is achieved using a dual wall-distance function and an orphan point removal iteration process. Results using the new scheme are presented for a number of static and relative motion test cases on a variety of aerospace applications.
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A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring
NASA Astrophysics Data System (ADS)
Xiao, F.
2018-04-01
In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.
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Compression of auditory space during forward self-motion.
Teramoto, Wataru; Sakamoto, Shuichi; Furune, Fumimasa; Gyoba, Jiro; Suzuki, Yôiti
2012-01-01
Spatial inputs from the auditory periphery can be changed with movements of the head or whole body relative to the sound source. Nevertheless, humans can perceive a stable auditory environment and appropriately react to a sound source. This suggests that the inputs are reinterpreted in the brain, while being integrated with information on the movements. Little is known, however, about how these movements modulate auditory perceptual processing. Here, we investigate the effect of the linear acceleration on auditory space representation. Participants were passively transported forward/backward at constant accelerations using a robotic wheelchair. An array of loudspeakers was aligned parallel to the motion direction along a wall to the right of the listener. A short noise burst was presented during the self-motion from one of the loudspeakers when the listener's physical coronal plane reached the location of one of the speakers (null point). In Experiments 1 and 2, the participants indicated which direction the sound was presented, forward or backward relative to their subjective coronal plane. The results showed that the sound position aligned with the subjective coronal plane was displaced ahead of the null point only during forward self-motion and that the magnitude of the displacement increased with increasing the acceleration. Experiment 3 investigated the structure of the auditory space in the traveling direction during forward self-motion. The sounds were presented at various distances from the null point. The participants indicated the perceived sound location by pointing a rod. All the sounds that were actually located in the traveling direction were perceived as being biased towards the null point. These results suggest a distortion of the auditory space in the direction of movement during forward self-motion. The underlying mechanism might involve anticipatory spatial shifts in the auditory receptive field locations driven by afferent signals from vestibular system.
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NASA Astrophysics Data System (ADS)
Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.
2016-12-01
Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.
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Integration Of 3D Geographic Information System (GIS) For Effective Waste Management Practice
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rood, G.J.; Hecox, G.R.
2006-07-01
Soil remediation in response to the presence of residual radioactivity resulting from past MED/AEC activities is currently in progress under the Formerly Utilized Sites Remedial Action Program near the St. Louis, MO airport. During GY05, approximately 92,000 cubic meters (120,000 cubic yards) of radioactive soil was excavated, packaged and transported via rail for disposal at U.S. Ecology or Envirocare of Utah, LLC. To facilitate the management of excavation/transportation/disposal activities, a 3D GIS was developed for the site that was used to estimate the in-situ radionuclide activities, activities in excavation block areas, and shipping activities using a sum-of ratio (SOR) methodmore » for combining various radionuclide compounds into applicable transportation and disposal SOR values. The 3D GIS was developed starting with the SOR values for the approximately 900 samples from 90 borings. These values were processed into a three-dimensional (3D) point grid using kriging with nominal grid spacing of 1.5 by 1.5 meter horizontal by 0.3 meter vertical. The final grid, clipped to the area and soil interval above the planned base of excavation, consisted of 210,000 individual points. Standard GIS volumetric and spatial join procedures were used to calculate the volume of soil represented by each grid point, the base of excavation, depth below ground surface, elevation, surface elevation and SOR values for each point in the final grid. To create the maps needed for management, the point grid results were spatially joined to each excavation area in 0.9 meter (3 foot) depth intervals and the average SOR and total volumes were calculations. The final maps were color-coded for easy identification of areas above the specific transportation or disposal criteria. (authors)« less
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NASA Astrophysics Data System (ADS)
Montereali, R. M.; Bonfigli, F.; Menchini, F.; Vincenti, M. A.
2012-08-01
Broad-band light-emitting radiation-induced F2 and F3+ electronic point defects, which are stable and laser-active at room temperature in lithium fluoride crystals and films, are used in dosimeters, tuneable color-center lasers, broad-band miniaturized light sources and novel radiation imaging detectors. A brief review of their photoemission properties is presented, and their behavior at liquid nitrogen temperatures is discussed. Some experimental data from optical spectroscopy and fluorescence microscopy of these radiation-induced point defects in LiF crystals and thin films are used to obtain information about the coloration curves, the efficiency of point defect formation, the effects of photo-bleaching processes, etc. Control of the local formation, stabilization, and transformation of radiation-induced light-emitting defect centers is crucial for the development of optically active micro-components and nanostructures. Some of the advantages of low temperature measurements for novel confocal laser scanning fluorescence microscopy techniques, widely used for spatial mapping of these point defects through the optical reading of their visible photoluminescence, are highlighted.
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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.
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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.
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Huang, Jinliang; Huang, Yaling; Zhang, Zhenyu
2014-01-01
Surface water samples of baseflow were collected from 20 headwater sub-watersheds which were classified into three types of watersheds (natural, urban and agricultural) in the flood, dry and transition seasons during three consecutive years (2010–2012) within a coastal watershed of Southeast China. Integrating spatial statistics with multivariate statistical techniques, river water quality variations and their interactions with natural and anthropogenic controls were examined to identify the causal factors and underlying mechanisms governing spatiotemporal patterns of water quality. Anthropogenic input related to industrial effluents and domestic wastewater, agricultural activities associated with the precipitation-induced surface runoff, and natural weathering process were identified as the potential important factors to drive the seasonal variations in stream water quality for the transition, flood and dry seasons, respectively. All water quality indicators except SRP had the highest mean concentrations in the dry and transition seasons. Anthropogenic activities and watershed characteristics led to the spatial variations in stream water quality in three types of watersheds. Concentrations of NH4 +-N, SRP, K+, CODMn, and Cl− were generally highest in urban watersheds. NO3 –N Concentration was generally highest in agricultural watersheds. Mg2+ concentration in natural watersheds was significantly higher than that in agricultural watersheds. Spatial autocorrelations analysis showed similar levels of water pollution between the neighboring sub-watersheds exhibited in the dry and transition seasons while non-point source pollution contributed to the significant variations in water quality between neighboring sub-watersheds. Spatial regression analysis showed anthropogenic controls played critical roles in variations of water quality in the JRW. Management implications were further discussed for water resource management. This research demonstrates that the coupled effects of natural and anthropogenic controls involved in watershed processes, contribute to the seasonal and spatial variation of headwater stream water quality in a coastal watershed with high spatial variability and intensive anthropogenic activities. PMID:24618771
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A spatial model to aggregate point-source and nonpoint-source water-quality data for large areas
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.
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NASA Astrophysics Data System (ADS)
Zeyliger, Anatoly; Ermolaeva, Olga
2014-05-01
Efficiency of water use for the irrigation purposes is connected to the variety of circumstances, factors and processes appearing along the transportation path of water from its sources to the root zone of the plant. Water efficiency of agricultural irrigation is connected with variety of circumstances, the impacts and the processes occurring during the transportation of water from water sources to plant root zone. Agrohydrological processes occur directly at the irrigated field, these processes linked to the infiltration of the applied water subsequent redistribution of the infiltrated water within the root zone. One of them are agrohydrological processes occurring directly on an irrigated field, connected with infiltration of water applied for irrigation to the soil, and the subsequent redistribution of infiltrated water in the root zone. These processes have the strongly pronounced spatial character depending on the one hand from a spatial variation of some hydrological characteristics of soils, and from other hand with distribution of volume of irrigation water on a surface of the area of an irrigated field closely linked with irrigation technology used. The combination of water application parameters with agrohydrological characteristics of soils and agricultural vegetation in each point at the surface of an irrigated field leads to formation of a vector field of intensity of irrigation water. In an ideal situation, such velocity field on a soil surface should represent uniform set of vertically directed collinear vectors. Thus values of these vectors should be equal to infiltration intensities of water inflows on a soil surface. In soil profile the field of formed intensities of a water flow should lead to formation in it of a water storage accessible to root system of irrigated crops. In practice this ideal scheme undergoes a lot of changes. These changes have the different nature, the reasons of occurrence and degree of influence on the processes connected with formation of water flow and water storage. The major changes are formed as a result of imposing of the intensity fields on a soil surface and its field capillary infiltration rate. Excess of the first intensity over the second in each point of soil surface leads to formation of a layer of intensity of water not infiltrated in soil. Thus generate the new field of vectors of intensity which can consist of vertically directed vector of speed of evaporation, a quasi horizontal vector of intensity of a surface water flow and quasi vertical vector of intensity of a preferential flow directed downwards. Principal cause of excess of irrigation water application intensity over capillary infiltration rate can be on the one hand spatial non-uniformity of irrigation water application, and with other spatial variability of capillary infiltration rate, connected with spatial variability of water storage in the top layers of soil. As a result the spatial redistribution of irrigation water over irrigated filed forms distortions of ideal model of irrigation water storage in root zone of soil profile. The major differences consist in increasing of water storage in the depressions of a relief of an irrigated field and accordingly in their reduction on elevated zones of a relief, as well as losses of irrigation water outside of boundaries of a root zone of an irrigated field, in vertical, and horizontal directions. One of key parameters characterizing interaction between irrigation technology and soil state an irrigated field are intensity of water application, intensity and volume of a capillary infiltration, the water storage in root zone at the moment of infiltration starting and a topography of an irrigated field. Fnalyzing of spatial links between these characteristics a special research had been carried out on irrigated by sprinkler machine called Fregate at alfalfa field during the summer of 2012. This research carried out at experimental farm of the research institute VolgNIIGiM situated at a left bank of Volga River of Saratov Region of Russia (N51.384650°, E46.055890°). The digital elevation model of soil surface has been created, as well as monitoring of spatial water storage with EM 38 device and of a biomass were carried out. Layers of corresponding spatial data have been created and analyzed. The carried out analysis of spatial regresses has shown presence of links between productivity of a biomass of a alfalfa, water storage and topography. The obtained results shows the significance to include spatial characteristics of the topography and water storage to the irrigation models, as well as adaptation of sprinkler technology to allow differentiate the volume and rate of the applied water within the field. Special attention should be done to quantify relationships between uniform technology of water application by sprinkler and spatial nonuniformity of moisture storage (zoning of high soil moisture in depressions) in soil and as consequence of infiltration capacity.
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NASA Astrophysics Data System (ADS)
Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping
2017-10-01
A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3.9 and 6.5 °C for 2050s and 2080s relative to 1990s in Ontario, respectively; Cooling degree days and hot days will significantly increase over southern Ontario and heating degree days and cold days will significantly decrease in northern Ontario. Annual total precipitation will increase over Ontario and heavy precipitation events will increase as well. These results are consistent with conclusions in many other studies in the literature.
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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.
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Preliminary surficial geologic map database of the Amboy 30 x 60 minute quadrangle, California
Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.
2006-01-01
The surficial geologic map database of the Amboy 30x60 minute quadrangle presents characteristics of surficial materials for an area approximately 5,000 km2 in the eastern Mojave Desert of California. This map consists of new surficial mapping conducted between 2000 and 2005, as well as compilations of previous surficial mapping. Surficial geology units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects occurring post-deposition, and, where appropriate, the lithologic nature of the material. The physical properties recorded in the database focus on those that drive hydrologic, biologic, and physical processes such as particle size distribution (PSD) and bulk density. This version of the database is distributed with point data representing locations of samples for both laboratory determined physical properties and semi-quantitative field-based information. Future publications will include the field and laboratory data as well as maps of distributed physical properties across the landscape tied to physical process models where appropriate. The database is distributed in three parts: documentation, spatial map-based data, and printable map graphics of the database. Documentation includes this file, which provides a discussion of the surficial geology and describes the format and content of the map data, a database 'readme' file, which describes the database contents, and FGDC metadata for the spatial map information. Spatial data are distributed as Arc/Info coverage in ESRI interchange (e00) format, or as tabular data in the form of DBF3-file (.DBF) file formats. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files, and are appropriate for representing a view of the spatial database at the mapped scale.
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NASA Astrophysics Data System (ADS)
El Alem, A.
2016-12-01
Harmful algal bloom (HAB) causes negative impacts to other organisms by producing natural toxins, mechanical damage to other micro-organisms, or simply by degrading waters quality. Contaminated waters could expose several billions of population to serious intoxications problems. Traditionally, HAB monitoring is made with standard methods limited to a restricted network of sampling points. However, rapid evolution of HABs makes it difficult to monitor their variation in time and space, threating then public safety. Daily monitoring is then the best way to control and to mitigate their harmful effect upon population, particularly for sources feeding cities. Recently, an approach for estimating chlorophyll-a (Chl-a) concentration, as a proxy of HAB presence, in inland waters based MODIS imagery downscaled to 250 meters spatial resolution was developed. Statistical evaluation of the developed approach highlighted the accuracy of Chl-a estimate with a R2 = 0.98, a relative RMSE of 15%, a relative BIAS of -2%, and a relative NASH of 0.95. Temporal resolution of MODIS sensor allows then a daily monitoring of HAB spatial distribution for inland waters of more than 2.25 Km2 of surface. Groupe-Hemisphere, a company specialized in environmental and sustainable planning in Quebec, has shown a great interest to the developed approach. Given the complexity of the preprocessing (geometric and atmospheric corrections as well as downscaling spatial resolution) and processing (Chl-a estimate) of images, a standalone application under the MATLAB's GUI environment was developed. The application allows an automated process for all preprocessing and processing steps. Outputs produced by the application for end users, many of whom may be decision makers or policy makers in the public and private sectors, allows a near-real time monitoring of water quality for a more efficient management.
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A scoping review of spatial cluster analysis techniques for point-event data.
Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott
2013-05-01
Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.