Automatic enhancement of skin fluorescence localization due to refractive index matching

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2004-07-01

Fluorescence diagnostic techniques are notable amongst many other optical methods, as they offer high sensitivity and non-invasive measurements of tissue properties. However, a combination of multiple scattering and physical heterogeneity of biological tissues hampers the interpretation of the fluorescence measurements. The analyses of the spatial distribution of endogenous and exogenous fluorophores excitations within tissues and their contribution to the detected signal localization are essential for many applications. We have developed a novel Monte Carlo technique that gives a graphical perception of how the excitation and fluorescence detected signal are localized in tissues. Our model takes into account spatial distribution of fluorophores and their quantum yields. We demonstrate that matching of the refractive indices of ambient medium and topical skin layer improves spatial localization of the detected fluorescence signal within the tissue. This result is consistent with the recent conclusion that administering biocompatible agents results in higher image contrast.

Spatial variation of volcanic rock geochemistry in the Virunga Volcanic Province: Statistical analysis of an integrated database

NASA Astrophysics Data System (ADS)

Barette, Florian; Poppe, Sam; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2017-10-01

We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.

On the analysis of time-of-flight spin-echo modulated dark-field imaging data

NASA Astrophysics Data System (ADS)

Sales, Morten; Plomp, Jeroen; Bouwman, Wim G.; Tremsin, Anton S.; Habicht, Klaus; Strobl, Markus

2017-06-01

Spin-Echo Modulated Small Angle Neutron Scattering with spatial resolution, i.e. quantitative Spin-Echo Dark Field Imaging, is an emerging technique coupling neutron imaging with spatially resolved quantitative small angle scattering information. However, the currently achieved relatively large modulation periods of the order of millimeters are superimposed to the images of the samples. So far this required an independent reduction and analyses of the image and scattering information encoded in the measured data and is involving extensive curve fitting routines. Apart from requiring a priori decisions potentially limiting the information content that is extractable also a straightforward judgment of the data quality and information content is hindered. In contrast we propose a significantly simplified routine directly applied to the measured data, which does not only allow an immediate first assessment of data quality and delaying decisions on potentially information content limiting further reduction steps to a later and better informed state, but also, as results suggest, generally better analyses. In addition the method enables to drop the spatial resolution detector requirement for non-spatially resolved Spin-Echo Modulated Small Angle Neutron Scattering.

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

PubMed

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

2013-10-15

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

Near-infrared hyperspectral imaging for quality analysis of agricultural and food products

NASA Astrophysics Data System (ADS)

Singh, C. B.; Jayas, D. S.; Paliwal, J.; White, N. D. G.

2010-04-01

Agricultural and food processing industries are always looking to implement real-time quality monitoring techniques as a part of good manufacturing practices (GMPs) to ensure high-quality and safety of their products. Near-infrared (NIR) hyperspectral imaging is gaining popularity as a powerful non-destructive tool for quality analysis of several agricultural and food products. This technique has the ability to analyse spectral data in a spatially resolved manner (i.e., each pixel in the image has its own spectrum) by applying both conventional image processing and chemometric tools used in spectral analyses. Hyperspectral imaging technique has demonstrated potential in detecting defects and contaminants in meats, fruits, cereals, and processed food products. This paper discusses the methodology of hyperspectral imaging in terms of hardware, software, calibration, data acquisition and compression, and development of prediction and classification algorithms and it presents a thorough review of the current applications of hyperspectral imaging in the analyses of agricultural and food products.

40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

Code of Federal Regulations, 2011 CFR

2011-07-01

... sufficient spatial and temporal coverage are available. c. It would be advantageous to categorize the various... control strategies. These are referred to as refined models. c. The use of screening techniques followed... location of the source in question and its expected impacts. c. In all regulatory analyses, especially if...

Improved analyses using function datasets and statistical modeling

Treesearch

John S. Hogland; Nathaniel M. Anderson

2014-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space and have limited statistical functionality and machine learning algorithms. To address this issue, we developed a new modeling framework using C# and ArcObjects and integrated that framework...

Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

PubMed Central

Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

2017-01-01

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia. PMID:28348512

Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

PubMed

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Describing spatial pattern in stream networks: A practical approach

USGS Publications Warehouse

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

2005-01-01

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

A geostatistical approach for describing spatial pattern in stream networks

USGS Publications Warehouse

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

2005-01-01

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

Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state–space models

PubMed Central

Polansky, Leo; Kilian, Werner; Wittemyer, George

2015-01-01

Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State–space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. PMID:25808888

Spatial analysis to identify hotspots of prevalence of schizophrenia.

PubMed

Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis

2008-10-01

The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.

Function modeling: improved raster analysis through delayed reading and function raster datasets

Treesearch

John S. Hogland; Nathaniel M. Anderson; J .Greg Jones

2013-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Mapping Tamarix: New techniques for field measurements, spatial modeling and remote sensing

NASA Astrophysics Data System (ADS)

Evangelista, Paul H.

Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Remote high-definition rotating video enables fast spatial survey of marine underwater macrofauna and habitats.

PubMed

Pelletier, Dominique; Leleu, Kévin; Mallet, Delphine; Mou-Tham, Gérard; Hervé, Gilles; Boureau, Matthieu; Guilpart, Nicolas

2012-01-01

Observing spatial and temporal variations of marine biodiversity from non-destructive techniques is central for understanding ecosystem resilience, and for monitoring and assessing conservation strategies, e.g. Marine Protected Areas. Observations are generally obtained through Underwater Visual Censuses (UVC) conducted by divers. The problems inherent to the presence of divers have been discussed in several papers. Video techniques are increasingly used for observing underwater macrofauna and habitat. Most video techniques that do not need the presence of a diver use baited remote systems. In this paper, we present an original video technique which relies on a remote unbaited rotating remote system including a high definition camera. The system is set on the sea floor to record images. These are then analysed at the office to quantify biotic and abiotic sea bottom cover, and to identify and count fish species and other species like marine turtles. The technique was extensively tested in a highly diversified coral reef ecosystem in the South Lagoon of New Caledonia, based on a protocol covering both protected and unprotected areas in major lagoon habitats. The technique enabled to detect and identify a large number of species, and in particular fished species, which were not disturbed by the system. Habitat could easily be investigated through the images. A large number of observations could be carried out per day at sea. This study showed the strong potential of this non obtrusive technique for observing both macrofauna and habitat. It offers a unique spatial coverage and can be implemented at sea at a reasonable cost by non-expert staff. As such, this technique is particularly interesting for investigating and monitoring coastal biodiversity in the light of current conservation challenges and increasing monitoring needs.

Spatial analysis of malaria in Anhui province, China

PubMed Central

Zhang, Wenyi; Wang, Liping; Fang, Liqun; Ma, Jiaqi; Xu, Youfu; Jiang, Jiafu; Hui, Fengming; Wang, Jianjun; Liang, Song; Yang, Hong; Cao, Wuchun

2008-01-01

Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. PMID:18847489

Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS Raster Utility coding library

Treesearch

John S. Hogland; Nathaniel M. Anderson

2015-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that...

Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS raster utility coding library

Treesearch

John S. Hogland; Nathaniel M. Anderson

2015-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...

Refining Windows and Frames: Visions toward Integration in the Discipline(s) of Communication. Part II.

ERIC Educational Resources Information Center

Burke, Ken

1998-01-01

Detailed analyses are made of the concepts of window (seemingly deep spatial renderings) and frame (flatter, more technique-conscious structures) as they apply to a wide variety of visual media and communicative purposes. Special cases of each of these are detailed, along with their applications in cinema history to a range of realist, formalist,…

Evaluating uncertainty in predicting spatially variable representative elementary scales in fractured aquifers, with application to Turkey Creek Basin, Colorado

USGS Publications Warehouse

Wellman, Tristan P.; Poeter, Eileen P.

2006-01-01

Computational limitations and sparse field data often mandate use of continuum representation for modeling hydrologic processes in large‐scale fractured aquifers. Selecting appropriate element size is of primary importance because continuum approximation is not valid for all scales. The traditional approach is to select elements by identifying a single representative elementary scale (RES) for the region of interest. Recent advances indicate RES may be spatially variable, prompting unanswered questions regarding the ability of sparse data to spatially resolve continuum equivalents in fractured aquifers. We address this uncertainty of estimating RES using two techniques. In one technique we employ data‐conditioned realizations generated by sequential Gaussian simulation. For the other we develop a new approach using conditioned random walks and nonparametric bootstrapping (CRWN). We evaluate the effectiveness of each method under three fracture densities, three data sets, and two groups of RES analysis parameters. In sum, 18 separate RES analyses are evaluated, which indicate RES magnitudes may be reasonably bounded using uncertainty analysis, even for limited data sets and complex fracture structure. In addition, we conduct a field study to estimate RES magnitudes and resulting uncertainty for Turkey Creek Basin, a crystalline fractured rock aquifer located 30 km southwest of Denver, Colorado. Analyses indicate RES does not correlate to rock type or local relief in several instances but is generally lower within incised creek valleys and higher along mountain fronts. Results of this study suggest that (1) CRWN is an effective and computationally efficient method to estimate uncertainty, (2) RES predictions are well constrained using uncertainty analysis, and (3) for aquifers such as Turkey Creek Basin, spatial variability of RES is significant and complex.

Using GIS Mapping to Target Public Health Interventions: Examining Birth Outcomes Across GIS Techniques.

PubMed

MacQuillan, E L; Curtis, A B; Baker, K M; Paul, R; Back, Y O

2017-08-01

With advances in spatial analysis techniques, there has been a trend in recent public health research to assess the contribution of area-level factors to health disparity for a number of outcomes, including births. Although it is widely accepted that health disparity is best addressed by targeted, evidence-based and data-driven community efforts, and despite national and local focus in the U.S. to reduce infant mortality and improve maternal-child health, there is little work exploring how choice of scale and specific GIS visualization technique may alter the perception of analyses focused on health disparity in birth outcomes. Retrospective cohort study. Spatial analysis of individual-level vital records data for low birthweight and preterm births born to black women from 2007 to 2012 in one mid-sized Midwest city using different geographic information systems (GIS) visualization techniques [geocoded address records were aggregated at two levels of scale and additionally mapped using kernel density estimation (KDE)]. GIS analyses in this study support our hypothesis that choice of geographic scale (neighborhood or census tract) for aggregated birth data can alter programmatic decision-making. Results indicate that the relative merits of aggregated visualization or the use of KDE technique depend on the scale of intervention. The KDE map proved useful in targeting specific areas for interventions in cities with smaller populations and larger census tracts, where they allow for greater specificity in identifying intervention areas. When public health programmers seek to inform intervention placement in highly populated areas, however, aggregated data at the census tract level may be preferred, since it requires lower investments in terms of time and cartographic skill and, unlike neighborhood, census tracts are standardized in that they become smaller as the population density of an area increases.

Spatial variability of soil available phosphorous and potassium at three different soils located in Pannonian Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Đurđević, Boris

2017-04-01

Information on spatial distribution of soil nutrients in agroecosystems is critical for improving productivity and reducing environmental pressures in intensive farmed soils. In this context, spatial prediction of soil properties should be accurate. In this study we analyse 704 data of soil available phosphorus (AP) and potassium (AK); the data derive from soil samples collected across three arable fields in Baranja region (Croatia) in correspondence of different soil types: Cambisols (169 samples), Chernozems (131 samples) and Gleysoils (404 samples). The samples are collected in a regular sampling grid (distance 225 x 225 m). Several geostatistical techniques (Inverse Distance to a Weight (IDW) with the power of 1, 2 and 3; Radial Basis Functions (RBF) - Inverse Multiquadratic (IMT), Multiquadratic (MTQ), Completely Regularized Spline (CRS), Spline with Tension (SPT) and Thin Plate Spline (TPS); and Local Polynomial (LP) with the power of 1 and 2; two geostatistical techniques -Ordinary Kriging - OK and Simple Kriging - SK) were tested in order to evaluate the most accurate spatial variability maps using criteria of lowest RMSE during cross validation technique. Soil parameters varied considerably throughout the studied fields and their coefficient of variations ranged from 31.4% to 37.7% and from 19.3% to 27.1% for soil AP and AK, respectively. The experimental variograms indicate a moderate spatial dependence for AP and strong spatial dependence for all three locations. The best spatial predictor for AP at Chernozem field was Simple kriging (RMSE=61.711), and for AK inverse multiquadratic (RMSE=44.689). The least accurate technique was Thin plate spline (AP) and Inverse distance to a weight with a power of 1 (AK). Radial basis function models (Spline with Tension for AP at Gleysoil and Cambisol and Completely Regularized Spline for AK at Gleysol) were the best predictors, while Thin Plate Spline models were the least accurate in all three cases. The best interpolator for AK at Cambisol was the local polynomial with the power of 2 (RMSE=33.943), while the least accurate was Thin Plate Spline (RMSE=39.572).

A spatial model with pulsed releases to compare strategies for the sterile insect technique applied to the mosquito Aedes aegypti.

PubMed

Oléron Evans, Thomas P; Bishop, Steven R

2014-08-01

We present a simple mathematical model to replicate the key features of the sterile insect technique (SIT) for controlling pest species, with particular reference to the mosquito Aedes aegypti, the main vector of dengue fever. The model differs from the majority of those studied previously in that it is simultaneously spatially explicit and involves pulsed, rather than continuous, sterile insect releases. The spatially uniform equilibria of the model are identified and analysed. Simulations are performed to analyse the impact of varying the number of release sites, the interval between pulsed releases and the overall volume of sterile insect releases on the effectiveness of SIT programmes. Results show that, given a fixed volume of available sterile insects, increasing the number of release sites and the frequency of releases increases the effectiveness of SIT programmes. It is also observed that programmes may become completely ineffective if the interval between pulsed releases is greater that a certain threshold value and that, beyond a certain point, increasing the overall volume of sterile insects released does not improve the effectiveness of SIT. It is also noted that insect dispersal drives a rapid recolonisation of areas in which the species has been eradicated and we argue that understanding the density dependent mortality of released insects is necessary to develop efficient, cost-effective SIT programmes. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

PubMed Central

Chaix, Basile; Leyland, Alastair H; Sabel, Clive E; Chauvin, Pierre; Råstam, Lennart; Kristersson, Håkan; Merlo, Juan

2006-01-01

Study objective Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. PMID:16614334

Analysing magnetism using scanning SQUID microscopy.

PubMed

Reith, P; Renshaw Wang, X; Hilgenkamp, H

2017-12-01

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last few decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength, and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape, and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.

Analysing magnetism using scanning SQUID microscopy

NASA Astrophysics Data System (ADS)

Reith, P.; Renshaw Wang, X.; Hilgenkamp, H.

2017-12-01

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last few decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength, and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape, and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.

Analysing child mortality in Nigeria with geoadditive discrete-time survival models.

PubMed

Adebayo, Samson B; Fahrmeir, Ludwig

2005-03-15

Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and health variables but they also vary considerably across regions and districts. In this paper, we analysed child mortality in Nigeria with flexible geoadditive discrete-time survival models. This class of models allows us to measure small-area district-specific spatial effects simultaneously with possibly non-linear or time-varying effects of other factors. Inference is fully Bayesian and uses computationally efficient Markov chain Monte Carlo (MCMC) simulation techniques. The application is based on the 1999 Nigeria Demographic and Health Survey. Our method assesses effects at a high level of temporal and spatial resolution not available with traditional parametric models, and the results provide some evidence on how to reduce child mortality by improving socio-economic and public health conditions. Copyright (c) 2004 John Wiley & Sons, Ltd.

Desertification in the south Junggar Basin, 2000-2009: Part I. Spatial analysis and indicator retrieval

NASA Astrophysics Data System (ADS)

Jiang, Miao; Lin, Yi

2018-07-01

Desertification is a serious environmental problem that threatens ecological balance and society sustainability, and pursuit of efficient techniques for its monitoring is always highlighted. Compared to in-situ investigation, remote sensing (RS) has proved to be an efficient solution plan, particularly for large covers, whereas previous RS-based studies mostly focused on proposal and validation of various indicators for different scenarios. To comprehensively reflect desertification and project its trend, this study attempted to develop a new comprehensive RS information model, with the scenario for test deployed at the south Junggar Basin, China in the last decade (2000-2009). The premise of establishing such a model, however, is not simple, involving selection of RS images with appropriate spatial resolutions and uniform retrievals of indicators with high accuracies. To handle these fundamental problems, this Part I compared the merits and faults of MODIS and TM images in desertification characterization, by making spatial analyses including land cover patch- and pixel-scale analyses and land attribute semi-variance and scale-agreement analyses. After the MODIS images with the resolution of 250 m were identified to be the appropriate choice, multiple representative indicators including NDVI, fraction of vegetation cover, land surface temperature, albedo and soil moisture that relate to different aspects of desertification processes were uniformly retrieved by using their individual effective algorithms and downscaling. Tests showed the spatial analyses did help in ensuring the premise of the whole study and the retrievals of indicators were reliable. The contributions are of fundamental implications for improving RS-based desertification analysis and have created a firm foundation for developing a RS information model in Part II.

Aspects of decision support in water management--example Berlin and Potsdam (Germany) I--spatially differentiated evaluation.

PubMed

Simon, Ute; Brüggemann, Rainer; Pudenz, Stefan

2004-04-01

Decisions about sustainable development demand spatially differentiated evaluations. As an example, we demonstrate the evaluation of water management strategies in the cities of Berlin and Potsdam (Germany) with respect to their ecological effects in 14 sections of the surface water system. Two decision support systems were compared, namely PROMETHEE, which is designed to obtain a clear decision (linear ranking), and Hasse Diagram Technique (HDT), normally providing more than one favourable solution (partial order). By PROMETHEE, the spatial differentiation had unwanted effects on the result, negating the stakeholders determined weighting of indicators. Therefore, the stakeholder can barely benefit from the convenience of obtaining a clear decision (linear ranking). In contrast, the result obtained by HDT was not influenced by spatial differentiation. Furthermore, HDT provided helpful tools to analyse the evaluation result, such as the concept of antagonistic indicators to discover conflicts in the evaluation process.

Analysis of spatial and temporal rainfall trends in Sicily during the 1921-2012 period

NASA Astrophysics Data System (ADS)

Liuzzo, Lorena; Bono, Enrico; Sammartano, Vincenzo; Freni, Gabriele

2016-10-01

Precipitation patterns worldwide are changing under the effects of global warming. The impacts of these changes could dramatically affect the hydrological cycle and, consequently, the availability of water resources. In order to improve the quality and reliability of forecasting models, it is important to analyse historical precipitation data to account for possible future changes. For these reasons, a large number of studies have recently been carried out with the aim of investigating the existence of statistically significant trends in precipitation at different spatial and temporal scales. In this paper, the existence of statistically significant trends in rainfall from observational datasets, which were measured by 245 rain gauges over Sicily (Italy) during the 1921-2012 period, was investigated. Annual, seasonal and monthly time series were examined using the Mann-Kendall non-parametric statistical test to detect statistically significant trends at local and regional scales, and their significance levels were assessed. Prior to the application of the Mann-Kendall test, the historical dataset was completed using a geostatistical spatial interpolation technique, the residual ordinary kriging, and then processed to remove the influence of serial correlation on the test results, applying the procedure of trend-free pre-whitening. Once the trends at each site were identified, the spatial patterns of the detected trends were examined using spatial interpolation techniques. Furthermore, focusing on the 30 years from 1981 to 2012, the trend analysis was repeated with the aim of detecting short-term trends or possible changes in the direction of the trends. Finally, the effect of climate change on the seasonal distribution of rainfall during the year was investigated by analysing the trend in the precipitation concentration index. The application of the Mann-Kendall test to the rainfall data provided evidence of a general decrease in precipitation in Sicily during the 1921-2012 period. Downward trends frequently occurred during the autumn and winter months. However, an increase in total annual precipitation was detected during the period from 1981 to 2012.

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

NASA Astrophysics Data System (ADS)

Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

2015-04-01

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

Siderophile Element Profile Measurements in Iron Meteorites Using Laser Ablation ICP-MS

NASA Technical Reports Server (NTRS)

Watson, H. C.; Watson, E. B.; McDonough, W. F.

2005-01-01

Understanding the behaviour of siderophile elements during cooling of iron meteorites can lead to insight into the general thermal histories of the meteorites as well as their respective parent bodies. Traditionally trace element analyses in meteorites have been done using techniques that only measure the average concentration in each phase. With these methods, all of the spatial information with respect to the distribution of an element within one phase is lost. Measuring concentration profiles of trace elements in meteorites is now possible, with the advent of high-resolution analytical techniques such as laser ablation, inductively coupled plasma mass spectrometry (LA-ICP-MS) with spatial resolution <20 microns. [e.g. 1,2] and secondary ion mass spectrometry [3]. These profiles can give more insight into both the partitioning and diffusive behavior of siderophile elements in metal systems relevant to iron meteorites, as well as parent body cooling rates.

Spatial and Temporal scales of time-averaged 700 MB height anomalies

NASA Technical Reports Server (NTRS)

Gutzler, D.

1981-01-01

The monthly and seasonal forecasting technique is based to a large extent on the extrapolation of trends in the positions of the centers of time averaged geopotential height anomalies. The complete forecasted height pattern is subsequently drawn around the forecasted anomaly centers. The efficacy of this technique was tested and time series of observed monthly mean and 5 day mean 700 mb geopotential heights were examined. Autocorrelation statistics are generated to document the tendency for persistence of anomalies. These statistics are compared to a red noise hypothesis to check for evidence of possible preferred time scales of persistence. Space-time spectral analyses at middle latitudes are checked for evidence of periodicities which could be associated with predictable month-to-month trends. A local measure of the average spatial scale of anomalies is devised for guidance in the completion of the anomaly pattern around the forecasted centers.

Comparison of Multivariate Spatial Dependence Structures of DPIL and Flowmeter Hydraulic Conductivity Data Sets at the MADE Site

NASA Astrophysics Data System (ADS)

Xiao, B.; Haslauer, C. P.; Bohling, G. C.; Bárdossy, A.

2017-12-01

The spatial arrangement of hydraulic conductivity (K) determines water flow and solute transport behaviour in groundwater systems. This presentation demonstrates three advances over commonly used geostatistical methods by integrating measurements from novel measurement techniques and novel multivariate non-Gaussian dependence models: The spatial dependence structure of K was analysed using both data sets of K. Previously encountered similarities were confirmed in low-dimensional dependence. These similarities become less stringent and deviate more from symmetric Gaussian dependence in dimensions larger than two. Measurements of small and large K values are more uncertain than medium K values due to decreased sensitivity of the measurement devices at both ends of the K scale. Nevertheless, these measurements contain useful information that we include in the estimation of the marginal distribution and the spatial dependence structure as ``censored measurements'' that are estimated jointly without the common assumption of independence. The spatial dependence structure of the two data sets and their cross-covariances are used to infer the spatial dependence and the amount of the bias between the two data sets. By doing so, one spatial model for K is constructed that is used for simulation and that reflects the characteristics of both measurement techniques. The concept of the presented methodology is to use all available information for the estimation of a stochastic model of the primary parameter (K) at the highly heterogeneous Macrodispersion Experiment (MADE) site. The primary parameter has been measured by two independent measurement techniques whose sets of locations do not overlap. This site offers the unique opportunity of large quantities of measurements of K (31123 direct push injection logging based measurements and 2611 flowmeter based measurements). This improved dependence structure of K will be included into the estimated non-Gaussian dependence models and is expected to reproduce observed solute concentrations at the site better than existing dependence models of K.

Dark matter constraints from a joint analysis of dwarf Spheroidal galaxy observations with VERITAS

DOE PAGES

Archambault, S.; Archer, A.; Benbow, W.; ...

2017-04-05

We present constraints on the annihilation cross section of weakly interacting massive particles dark matter based on the joint statistical analysis of four dwarf galaxies with VERITAS. These results are derived from an optimized photon weighting statistical technique that improves on standard imaging atmospheric Cherenkov telescope (IACT) analyses by utilizing the spectral and spatial properties of individual photon events.

Unlocking the spatial inversion of large scanning magnetic microscopy datasets

NASA Astrophysics Data System (ADS)

Myre, J. M.; Lascu, I.; Andrade Lima, E.; Feinberg, J. M.; Saar, M. O.; Weiss, B. P.

2013-12-01

Modern scanning magnetic microscopy provides the ability to perform high-resolution, ultra-high sensitivity moment magnetometry, with spatial resolutions better than 10^-4 m and magnetic moments as weak as 10^-16 Am^2. These microscopy capabilities have enhanced numerous magnetic studies, including investigations of the paleointensity of the Earth's magnetic field, shock magnetization and demagnetization of impacts, magnetostratigraphy, the magnetic record in speleothems, and the records of ancient core dynamos of planetary bodies. A common component among many studies utilizing scanning magnetic microscopy is solving an inverse problem to determine the non-negative magnitude of the magnetic moments that produce the measured component of the magnetic field. The two most frequently used methods to solve this inverse problem are classic fast Fourier techniques in the frequency domain and non-negative least squares (NNLS) methods in the spatial domain. Although Fourier techniques are extremely fast, they typically violate non-negativity and it is difficult to implement constraints associated with the space domain. NNLS methods do not violate non-negativity, but have typically been computation time prohibitive for samples of practical size or resolution. Existing NNLS methods use multiple techniques to attain tractable computation. To reduce computation time in the past, typically sample size or scan resolution would have to be reduced. Similarly, multiple inversions of smaller sample subdivisions can be performed, although this frequently results in undesirable artifacts at subdivision boundaries. Dipole interactions can also be filtered to only compute interactions above a threshold which enables the use of sparse methods through artificial sparsity. To improve upon existing spatial domain techniques, we present the application of the TNT algorithm, named TNT as it is a "dynamite" non-negative least squares algorithm which enhances the performance and accuracy of spatial domain inversions. We show that the TNT algorithm reduces the execution time of spatial domain inversions from months to hours and that inverse solution accuracy is improved as the TNT algorithm naturally produces solutions with small norms. Using sIRM and NRM measures of multiple synthetic and natural samples we show that the capabilities of the TNT algorithm allow very large samples to be inverted without the need for alternative techniques to make the problems tractable. Ultimately, the TNT algorithm enables accurate spatial domain analysis of scanning magnetic microscopy data on an accelerated time scale that renders spatial domain analyses tractable for numerous studies, including searches for the best fit of unidirectional magnetization direction and high-resolution step-wise magnetization and demagnetization.

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

PubMed

Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex

2018-02-27

"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

The statistical geoportal and the ``cartographic added value'' - creation of the spatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Fiedukowicz, Anna; Gasiorowski, Jedrzej; Kowalski, Paweł; Olszewski, Robert; Pillich-Kolipinska, Agata

2012-11-01

The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge. Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here. Szeroki dostep do danych zródłowych publikowanych w licznych serwisach internetowych sprawia, iz współczesnie problemem jest nie pozyskanie informacji, lecz umiejetne przekształcenie jej w uzyteczna wiedze. Kartograficzna metoda badan, która od wielu lat słuzy temu celowi w odniesieniu do danych przestrzennych, zyskuje dzis nowe oblicze - pozwala na wykonywanie złozonych analiz dzieki wykorzystaniu intensywnego rozwoju technologii informatycznych. Znaczaca wiekszosc zastosowan metod analitycznych tzw. eksploracyjnej analizy danych (data mining) i ich "wzbogacania” (data enrichment) dotyczy jednakze danych nieprzestrzennych. Wykorzystanie tych metod do analizy danych o charakterze przestrzennym, w tym danych statystycznych, i zapewnienie dostepu do nich w formie dedykowanych usług przyczyniłoby sie, zdaniem Autorów, do przetworzenia infrastruktury informacji przestrzennej (Spatial InformationInfrastructure - SII) w infrastrukture wiedzy przestrzennej (Spatial Knowledge Infrastructure - SKI). Rozwojowi SKI mógłby słuzyc geoportal statystyczny, którego propozycje funkcjonalnosci, obejmujace zarówno analize jak i wizualizacje danych, zarysowano w artykule. Zaprezentowano tez przykłady analiz statystycznych (ANOVA, regresja z uwzglednieniem sasiedztwa przestrzennego), mozliwych do zaimplementowania w takim portalu, a które mogłyby sie przyczynic do wytworzenia "kartograficznej wartosci dodanej”.

A Compact, Solid-State UV (266 nm) Laser System Capable of Burst-Mode Operation for Laser Ablation Desorption Processing

NASA Technical Reports Server (NTRS)

Arevalo, Ricardo, Jr.; Coyle, Barry; Paulios, Demetrios; Stysley, Paul; Feng, Steve; Getty, Stephanie; Binkerhoff, William

2015-01-01

Compared to wet chemistry and pyrolysis techniques, in situ laser-based methods of chemical analysis provide an ideal way to characterize precious planetary materials without requiring extensive sample processing. In particular, laser desorption and ablation techniques allow for rapid, reproducible and robust data acquisition over a wide mass range, plus: Quantitative, spatially-resolved measurements of elemental and molecular (organic and inorganic) abundances; Low analytical blanks and limits-of-detection ( ng g-1); and, the destruction of minimal quantities of sample ( g) compared to traditional solution and/or pyrolysis analyses (mg).

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

PubMed

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

2013-05-01

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

Bioimaging of cells and tissues using accelerator-based sources.

PubMed

Petibois, Cyril; Cestelli Guidi, Mariangela

2008-07-01

A variety of techniques exist that provide chemical information in the form of a spatially resolved image: electron microprobe analysis, nuclear microprobe analysis, synchrotron radiation microprobe analysis, secondary ion mass spectrometry, and confocal fluorescence microscopy. Linear (LINAC) and circular (synchrotrons) particle accelerators have been constructed worldwide to provide to the scientific community unprecedented analytical performances. Now, these facilities match at least one of the three analytical features required for the biological field: (1) a sufficient spatial resolution for single cell (< 1 mum) or tissue (<1 mm) analyses, (2) a temporal resolution to follow molecular dynamics, and (3) a sensitivity in the micromolar to nanomolar range, thus allowing true investigations on biological dynamics. Third-generation synchrotrons now offer the opportunity of bioanalytical measurements at nanometer resolutions with incredible sensitivity. Linear accelerators are more specialized in their physical features but may exceed synchrotron performances. All these techniques have become irreplaceable tools for developing knowledge in biology. This review highlights the pros and cons of the most popular techniques that have been implemented on accelerator-based sources to address analytical issues on biological specimens.

An explicit approach to detecting and characterizing submersed aquatic vegetation using a single-beam digital echosounder

NASA Astrophysics Data System (ADS)

Sabol, Bruce M.

2005-09-01

There has been a longstanding need for an objective and cost-effective technique to detect, characterize, and quantify submersed aquatic vegetation at spatial scales between direct physical sampling and remote aerial-based imaging. Acoustic-based approaches for doing so are reviewed and an explicit approach, using a narrow, single-beam echosounder, is described in detail. This heuristic algorithm is based on the spatial distribution of a thresholded signal generated from a high-frequency, narrow-beam echosounder operated in a vertical orientation from a survey boat. The physical basis, rationale, and implementation of this algorithm are described, and data documenting performance are presented. Using this technique, it is possible to generate orders of magnitude more data than would be available using previous techniques with a comparable level of effort. Thus, new analysis and interpretation approaches are called for which can make full use of these data. Several analyses' examples are shown for environmental effects application studies. Current operational window and performance limitations are identified and thoughts on potential processing approaches to improve performance are discussed.

Analysis of Trace Siderophile Elements at High Spatial Resolution Using Laser Ablation ICP-MS

NASA Astrophysics Data System (ADS)

Campbell, A. J.; Humayun, M.

2006-05-01

Laser ablation inductively coupled plasma mass spectometry is an increasingly important method of performing spatially resolved trace element analyses. Over the last several years we have applied this technique to measure siderophile element distributions at the ppm level in a variety of natural and synthetic samples, especially metallic phases in meteorites and experimental run products intended for trace element partitioning studies. These samples frequently require trace element analyses to be made at a finer spatial resolution (25 microns or better) than is frequently attained using LA-ICP-MS. In this presentation we review analytical protocols that were developed to optimize the LA-ICP-MS measurements for high spatial resolution. Particular attention is paid to the trade-offs involving sensitivity, ablation pit depth and diameter, background levels, and number of elements measured. To maximize signal/background ratios and avoid difficulties associated with ablating to depths greater than the ablation pit diameter, measurement involved integration of rapidly varying, transient but well-behaved signals. The abundances of platinum group elements and other siderophile elements in ferrous metals were calibrated against well-characterized standards, including iron meteorites and NIST certified steels. The calibrations can be set against the known abundance of an independently determined element, but normalization to 100 percent can also be employed, and was more useful in many circumstances. Evaluation of uncertainties incorporated counting statistics as well as a measure of instrumental uncertainty, determined by replicate analyses of the standards. These methods have led to a number of insights into the formation and chemical processing of metal in the early solar system.

`spup' - An R Package for Analysis of Spatial Uncertainty Propagation and Application to Trace Gas Emission Simulations

NASA Astrophysics Data System (ADS)

Sawicka, K.; Breuer, L.; Houska, T.; Santabarbara Ruiz, I.; Heuvelink, G. B. M.

2016-12-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Advances in uncertainty propagation analysis and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the `spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo techniques, as well as several uncertainty visualization functions. Here we will demonstrate that the 'spup' package is an effective and easy-to-use tool to be applied even in a very complex study case, and that it can be used in multi-disciplinary research and model-based decision support. As an example, we use the ecological LandscapeDNDC model to analyse propagation of uncertainties associated with spatial variability of the model driving forces such as rainfall, nitrogen deposition and fertilizer inputs. The uncertainty propagation is analysed for the prediction of emissions of N2O and CO2 for a German low mountainous, agriculturally developed catchment. The study tests the effect of spatial correlations on spatially aggregated model outputs, and could serve as an advice for developing best management practices and model improvement strategies.

Crossover between two- and three-dimensional turbulence in spatial mixing layers

NASA Astrophysics Data System (ADS)

Biancofiore, Luca

2016-11-01

We investigate how the domain depth affects the turbulent behaviour in spatially developing mixing layers by means of large-eddy simulations (LES) based on a spectral vanishing viscosity technique. Analyses of spectra of the vertical velocity, of Lumley's diagrams, of the turbulent kinetic energy and of the vortex stretching show that a two-dimensional behaviour of the turbulence is promoted in spatial mixing layers by constricting the fluid motion in one direction. This finding is in agreement with previous works on turbulent systems constrained by a geometric anisotropy, pioneered by Smith, Chasnov & Waleffe. We observe that the growth of the momentum thickness along the streamwise direction is damped in a confined domain. A full two-dimensional turbulent behaviour is observed when the momentum thickness is of the same order of magnitude as the confining scale.

Influence of spatial beam inhomogeneities on the parameters of a petawatt laser system based on multi-stage parametric amplification

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

Frolov, S A; Trunov, V I; Pestryakov, Efim V

2013-05-31

We have developed a technique for investigating the evolution of spatial inhomogeneities in high-power laser systems based on multi-stage parametric amplification. A linearised model of the inhomogeneity development is first devised for parametric amplification with the small-scale self-focusing taken into account. It is shown that the application of this model gives the results consistent (with high accuracy and in a wide range of inhomogeneity parameters) with the calculation without approximations. Using the linearised model, we have analysed the development of spatial inhomogeneities in a petawatt laser system based on multi-stage parametric amplification, developed at the Institute of Laser Physics, Siberianmore » Branch of the Russian Academy of Sciences (ILP SB RAS). (control of laser radiation parameters)« less

OdorMapComparer: an application for quantitative analyses and comparisons of fMRI brain odor maps.

PubMed

Liu, Nian; Xu, Fuqiang; Miller, Perry L; Shepherd, Gordon M

2007-01-01

Brain odor maps are reconstructed flat images that describe the spatial activity patterns in the glomerular layer of the olfactory bulbs in animals exposed to different odor stimuli. We have developed a software application, OdorMapComparer, to carry out quantitative analyses and comparisons of the fMRI odor maps. This application is an open-source window program that first loads two odor map images being compared. It allows image transformations including scaling, flipping, rotating, and warping so that the two images can be appropriately aligned to each other. It performs simple subtraction, addition, and average of signals in the two images. It also provides comparative statistics including the normalized correlation (NC) and spatial correlation coefficient. Experimental studies showed that the rodent fMRI odor maps for aliphatic aldehydes displayed spatial activity patterns that are similar in gross outlines but somewhat different in specific subregions. Analyses with OdorMapComparer indicate that the similarity between odor maps decreases with increasing difference in the length of carbon chains. For example, the map of butanal is more closely related to that of pentanal (with a NC = 0.617) than to that of octanal (NC = 0.082), which is consistent with animal behavioral studies. The study also indicates that fMRI odor maps are statistically odor-specific and repeatable across both the intra- and intersubject trials. OdorMapComparer thus provides a tool for quantitative, statistical analyses and comparisons of fMRI odor maps in a fashion that is integrated with the overall odor mapping techniques.

Two modified symplectic partitioned Runge-Kutta methods for solving the elastic wave equation

NASA Astrophysics Data System (ADS)

Su, Bo; Tuo, Xianguo; Xu, Ling

2017-08-01

Based on a modified strategy, two modified symplectic partitioned Runge-Kutta (PRK) methods are proposed for the temporal discretization of the elastic wave equation. The two symplectic schemes are similar in form but are different in nature. After the spatial discretization of the elastic wave equation, the ordinary Hamiltonian formulation for the elastic wave equation is presented. The PRK scheme is then applied for time integration. An additional term associated with spatial discretization is inserted into the different stages of the PRK scheme. Theoretical analyses are conducted to evaluate the numerical dispersion and stability of the two novel PRK methods. A finite difference method is used to approximate the spatial derivatives since the two schemes are independent of the spatial discretization technique used. The numerical solutions computed by the two new schemes are compared with those computed by a conventional symplectic PRK. The numerical results, which verify the new method, are superior to those generated by traditional conventional methods in seismic wave modeling.

Spatiotemporal characterization of ultrashort optical vortex pulses

NASA Astrophysics Data System (ADS)

Miranda, Miguel; Kotur, Marija; Rudawski, Piotr; Guo, Chen; Harth, Anne; L'Huillier, Anne; Arnold, Cord L.

2017-12-01

We use a spiral phase plate to generate few-cycle optical vortices from an ultrafast titanium:sapphire oscillator and characterize them in the spatiotemporal domain with a recently introduced technique based on spatially resolved Fourier transform spectrometry. The performance of this simple approach to the generation of optical vortices is analysed from a wavelength-dependent perspective as well as in the spatiotemporal domain, allowing us to characterize ultrashort vortex pulses in space, frequency and time.

Reducing multi-sensor data to a single time course that reveals experimental effects

PubMed Central

2013-01-01

Background Multi-sensor technologies such as EEG, MEG, and ECoG result in high-dimensional data sets. Given the high temporal resolution of such techniques, scientific questions very often focus on the time-course of an experimental effect. In many studies, researchers focus on a single sensor or the average over a subset of sensors covering a “region of interest” (ROI). However, single-sensor or ROI analyses ignore the fact that the spatial focus of activity is constantly changing, and fail to make full use of the information distributed over the sensor array. Methods We describe a technique that exploits the optimality and simplicity of matched spatial filters in order to reduce experimental effects in multivariate time series data to a single time course. Each (multi-sensor) time sample of each trial is replaced with its projection onto a spatial filter that is matched to an observed experimental effect, estimated from the remaining trials (Effect-Matched Spatial filtering, or EMS filtering). The resulting set of time courses (one per trial) can be used to reveal the temporal evolution of an experimental effect, which distinguishes this approach from techniques that reveal the temporal evolution of an anatomical source or region of interest. Results We illustrate the technique with data from a dual-task experiment and use it to track the temporal evolution of brain activity during the psychological refractory period. We demonstrate its effectiveness in separating the means of two experimental conditions, and in significantly improving the signal-to-noise ratio at the single-trial level. It is fast to compute and results in readily-interpretable time courses and topographies. The technique can be applied to any data-analysis question that can be posed independently at each sensor, and we provide one example, using linear regression, that highlights the versatility of the technique. Conclusion The approach described here combines established techniques in a way that strikes a balance between power, simplicity, speed of processing, and interpretability. We have used it to provide a direct view of parallel and serial processes in the human brain that previously could only be measured indirectly. An implementation of the technique in MatLab is freely available via the internet. PMID:24125590

Photorefractive detection of tagged photons in ultrasound modulated optical tomography of thick biological tissues.

PubMed

Ramaz, F; Forget, B; Atlan, M; Boccara, A C; Gross, M; Delaye, P; Roosen, G

2004-11-01

We present a new and simple method to obtain ultrasound modulated optical tomography images in thick biological tissues with the use of a photorefractive crystal. The technique offers the advantage of spatially adapting the output speckle wavefront by analysing the signal diffracted by the interference pattern between this output field and a reference beam, recorded inside the photorefractive crystal. Averaging out due to random phases of the speckle grains vanishes, and we can use a fast single photodetector to measure the ultrasound modulated optical contrast. This technique offers a promising way to make direct measurements within the decorrelation time scale of living tissues.

An evaluation of semi-automated methods for collecting ecosystem-level data in temperate marine systems.

PubMed

Griffin, Kingsley J; Hedge, Luke H; González-Rivero, Manuel; Hoegh-Guldberg, Ove I; Johnston, Emma L

2017-07-01

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m 2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.

Realistic micromechanical modeling and simulation of two-phase heterogeneous materials

NASA Astrophysics Data System (ADS)

Sreeranganathan, Arun

This dissertation research focuses on micromechanical modeling and simulations of two-phase heterogeneous materials exhibiting anisotropic and non-uniform microstructures with long-range spatial correlations. Completed work involves development of methodologies for realistic micromechanical analyses of materials using a combination of stereological techniques, two- and three-dimensional digital image processing, and finite element based modeling tools. The methodologies are developed via its applications to two technologically important material systems, namely, discontinuously reinforced aluminum composites containing silicon carbide particles as reinforcement, and boron modified titanium alloys containing in situ formed titanium boride whiskers. Microstructural attributes such as the shape, size, volume fraction, and spatial distribution of the reinforcement phase in these materials were incorporated in the models without any simplifying assumptions. Instrumented indentation was used to determine the constitutive properties of individual microstructural phases. Micromechanical analyses were performed using realistic 2D and 3D models and the results were compared with experimental data. Results indicated that 2D models fail to capture the deformation behavior of these materials and 3D analyses are required for realistic simulations. The effect of clustering of silicon carbide particles and associated porosity on the mechanical response of discontinuously reinforced aluminum composites was investigated using 3D models. Parametric studies were carried out using computer simulated microstructures incorporating realistic microstructural attributes. The intrinsic merit of this research is the development and integration of the required enabling techniques and methodologies for representation, modeling, and simulations of complex geometry of microstructures in two- and three-dimensional space facilitating better understanding of the effects of microstructural geometry on the mechanical behavior of materials.

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

A New Approach to X-ray Analysis of SNRs

NASA Astrophysics Data System (ADS)

Frank, Kari A.; Burrows, David; Dwarkadas, Vikram

2016-06-01

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to XMM-Newton observations of SNR RCW 103 and Tycho. SPI is a Bayesian modeling process that fits a population of gas blobs (”smoothed particles”) such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. The analyses of RCW 103 and Tycho are part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.

Integration of fisheries into marine spatial planning: Quo vadis?

NASA Astrophysics Data System (ADS)

Janßen, Holger; Bastardie, Francois; Eero, Margit; Hamon, Katell G.; Hinrichsen, Hans-Harald; Marchal, Paul; Nielsen, J. Rasmus; Le Pape, Olivier; Schulze, Torsten; Simons, Sarah; Teal, Lorna R.; Tidd, Alex

2018-02-01

The relationship between fisheries and marine spatial planning (MSP) is still widely unsettled. While several scientific studies highlight the strong relation between fisheries and MSP, as well as ways in which fisheries could be included in MSP, the actual integration of fisheries into MSP often fails. In this article, we review the state of the art and latest progress in research on various challenges in the integration of fisheries into MSP. The reviewed studies address a wide range of integration challenges, starting with techniques to analyse where fishermen actually fish, assessing the drivers for fishermen's behaviour, seasonal dynamics and long-term spatial changes of commercial fish species under various anthropogenic pressures along their successive life stages, the effects of spatial competition on fisheries and projections on those spaces that might become important fishing areas in the future, and finally, examining how fisheries could benefit from MSP. This paper gives an overview of the latest developments on concepts, tools, and methods. It becomes apparent that the spatial and temporal dynamics of fish and fisheries, as well as the definition of spatial preferences, remain major challenges, but that an integration of fisheries is already possible today.

Spatially resolved synchrotron radiation induced X-ray fluorescence analyses of rare Rembrandt silverpoint drawings

NASA Astrophysics Data System (ADS)

Reiche, I.; Radtke, M.; Berger, A.; Görner, W.; Merchel, S.; Riesemeier, H.; Bevers, H.

2006-05-01

New analyses of a series of very rare silverpoint drawings that were executed by Rembrandt Harmensz. van Rijn (1606 1669) which are kept today in the Kupferstichkabinett (Museum of Prints and Drawings) of the State Museums of Berlin are reported here. Analysis of these drawings requires particular attention because the study has to be fully non-destructive and extremely sensitive. The metal alloy on the paper does not exceed some hundreds of μg/cm2. Therefore, synchrotron radiation induced X-ray fluorescence (SR-XRF) is together with external micro-proton-induced X-ray emission the only well-suited method for the analyses of metalpoint drawings. In some primary work, about 25 German and Flemish metalpoint drawings were investigated using spatially resolved SR-XRF analysis at the BAMline at BESSY. This study enlarges the existing French German database of metalpoint drawings dating from the 15th and 16th centuries, as these Rembrandt drawings originate from the 17th century where this graphical technique was even rarer and already obsolete. It also illustrates how SR-XRF analysis can reinforce art historical assumptions on the dating of drawings and their connection.

Characterization of the ionosphere above the Murchison Radio Observatory using the Murchison Widefield Array

NASA Astrophysics Data System (ADS)

Jordan, C. H.; Murray, S.; Trott, C. M.; Wayth, R. B.; Mitchell, D. A.; Rahimi, M.; Pindor, B.; Procopio, P.; Morgan, J.

2017-11-01

We detail new techniques for analysing ionospheric activity, using Epoch of Reionization data sets obtained with the Murchison Widefield Array, calibrated by the `real-time system' (RTS). Using the high spatial- and temporal-resolution information of the ionosphere provided by the RTS calibration solutions over 19 nights of observing, we find four distinct types of ionospheric activity, and have developed a metric to provide an `at a glance' value for data quality under differing ionospheric conditions. For each ionospheric type, we analyse variations of this metric as we reduce the number of pierce points, revealing that a modest number of pierce points is required to identify the intensity of ionospheric activity; it is possible to calibrate in real-time, providing continuous information of the phase screen. We also analyse temporal correlations, determine diffractive scales, examine the relative fractions of time occupied by various types of ionospheric activity and detail a method to reconstruct the total electron content responsible for the ionospheric data we observe. These techniques have been developed to be instrument agnostic, useful for application on LOw Frequency ARray and Square Kilometre Array-Low.

Multielement geochemistry identifies the spatial pattern of soil and sediment contamination in an urban parkland, Western Australia.

PubMed

Rate, Andrew W

2018-06-15

Urban environments are dynamic and highly heterogeneous, and multiple additions of potential contaminants are likely on timescales which are short relative to natural processes. The likely sources and location of soil or sediment contamination in urban environment should therefore be detectable using multielement geochemical composition combined with rigorously applied multivariate statistical techniques. Soil, wetland sediment, and street dust was sampled along intersecting transects in Robertson Park in metropolitan Perth, Western Australia. Samples were analysed for near-total concentrations of multiple elements (including Cd, Ce, Co, Cr, Cu, Fe, Gd, La, Mn, Nd, Ni, Pb, Y, and Zn), as well as pH, and electrical conductivity. Samples at some locations within Robertson Park had high concentrations of potentially toxic elements (Pb above Health Investigation Limits; As, Ba, Cu, Mn, Ni, Pb, V, and Zn above Ecological Investigation Limits). However, these concentrations carry low risk due to the main land use as recreational open space, the low proportion of samples exceeding guideline values, and a tendency for the highest concentrations to be located within the less accessible wetland basin. The different spatial distributions of different groups of contaminants was consistent with different inputs of contaminants related to changes in land use and technology over the history of the site. Multivariate statistical analyses reinforced the spatial information, with principal component analysis identifying geochemical associations of elements which were also spatially related. A multivariate linear discriminant model was able to discriminate samples into a-priori types, and could predict sample type with 84% accuracy based on multielement composition. The findings suggest substantial advantages of characterising a site using multielement and multivariate analyses, an approach which could benefit investigations of other sites of concern. Copyright © 2018 Elsevier B.V. All rights reserved.

Phase coupling and synchrony in the spatiotemporal dynamics of muskrat and mink populations across Canada

PubMed Central

Haydon, D. T.; Stenseth, N. C.; Boyce, M. S.; Greenwood, P. E.

2001-01-01

Population ecologists have traditionally focused on the patterns and causes of population variation in the temporal domain for which a substantial body of practical analytic techniques have been developed. More recently, numerous studies have documented how populations may fluctuate synchronously over large spatial areas; analyses of such spatially extended time-series have started to provide additional clues regarding the causes of these population fluctuations and explanations for their synchronous occurrence. Here, we report on the development of a phase-based method for identifying coupling between temporally coincident but spatially distributed cyclic time-series, which we apply to the numbers of muskrat and mink recorded at 81 locations across Canada. The analysis reveals remarkable parallel clines in the strength of coupling between proximate populations of both species—declining from west to east—together with a corresponding increase in observed synchrony between these populations the further east they are located. PMID:11606729

Managing Spatial Selections With Contextual Snapshots

PubMed Central

Mindek, P; Gröller, M E; Bruckner, S

2014-01-01

Spatial selections are a ubiquitous concept in visualization. By localizing particular features, they can be analysed and compared in different views. However, the semantics of such selections often depend on specific parameter settings and it can be difficult to reconstruct them without additional information. In this paper, we present the concept of contextual snapshots as an effective means for managing spatial selections in visualized data. The selections are automatically associated with the context in which they have been created. Contextual snapshots can also be used as the basis for interactive integrated and linked views, which enable in-place investigation and comparison of multiple visual representations of data. Our approach is implemented as a flexible toolkit with well-defined interfaces for integration into existing systems. We demonstrate the power and generality of our techniques by applying them to several distinct scenarios such as the visualization of simulation data, the analysis of historical documents and the display of anatomical data. PMID:25821284

Insights into a spatially embedded social network from a large-scale snowball sample

NASA Astrophysics Data System (ADS)

Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

2011-12-01

Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

Ultrasonic Evaluation and Imaging

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

Crawford, Susan L.; Anderson, Michael T.; Diaz, Aaron A.

2015-10-01

Ultrasonic evaluation of materials for material characterization and flaw detection is as simple as manually moving a single-element probe across a speci-men and looking at an oscilloscope display in real time or as complex as automatically (under computer control) scanning a phased-array probe across a specimen and collecting encoded data for immediate or off-line data analyses. The reliability of the results in the second technique is greatly increased because of a higher density of measurements per scanned area and measurements that can be more precisely related to the specimen geometry. This chapter will briefly discuss applications of the collection ofmore » spatially encoded data and focus primarily on the off-line analyses in the form of data imaging. Pacific Northwest National Laboratory (PNNL) has been involved with as-sessing and advancing the reliability of inservice inspections of nuclear power plant components for over 35 years. Modern ultrasonic imaging techniques such as the synthetic aperture focusing technique (SAFT), phased-array (PA) technolo-gy and sound field mapping have undergone considerable improvements to effec-tively assess and better understand material constraints.« less

Long-term vegetation activity trends in the Iberian Peninsula and The Balearic Islands using high spatial resolution NOAA-AVHRR data (1981 - 2015).

NASA Astrophysics Data System (ADS)

Martin-Hernandez, Natalia; Vicente-Serrano, Sergio; Azorin-Molina, Cesar; Begueria-Portugues, Santiago; Reig-Gracia, Fergus; Zabalza-Martínez, Javier

2017-04-01

We have analysed trends in the Normalized Difference Vegetation Index (NDVI) in the Iberian Peninsula and The Balearic Islands over the period 1981 - 2015 using a new high resolution data set from the entire available NOAA - AVHRR images (IBERIAN NDVI dataset). After a complete processing including geocoding, calibration, cloud removal, topographic correction and temporal filtering, we obtained bi-weekly time series. To assess the accuracy of the new IBERIAN NDVI time-series, we have compared temporal variability and trends of NDVI series with those results reported by GIMMS 3g and MODIS (MOD13A3) NDVI datasets. In general, the IBERIAN NDVI showed high reliability with these two products but showing higher spatial resolution than the GIMMS dataset and covering two more decades than the MODIS dataset. Using the IBERIAN NDVI dataset, we analysed NDVI trends by means of the non-parametric Mann-Kendall test and Theil-Sen slope estimator. In average, vegetation trends in the study area show an increase over the last decades. However, there are local spatial differences: the main increase has been recorded in humid regions of the north of the Iberian Peninsula. The statistical techniques allow finding abrupt and gradual changes in different land cover types during the analysed period. These changes are related with human activity due to land transformations (from dry to irrigated land), land abandonment and forest recovery.

Applications of spatial statistical network models to stream data

USGS Publications Warehouse

Isaak, Daniel J.; Peterson, Erin E.; Ver Hoef, Jay M.; Wenger, Seth J.; Falke, Jeffrey A.; Torgersen, Christian E.; Sowder, Colin; Steel, E. Ashley; Fortin, Marie-Josée; Jordan, Chris E.; Ruesch, Aaron S.; Som, Nicholas; Monestiez, Pascal

2014-01-01

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012.

PubMed

Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993-2012. Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ(2) = 15.17, d.f.  = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas.

Spatial and Temporal Patterns of Locally-Acquired Dengue Transmission in Northern Queensland, Australia, 1993–2012

PubMed Central

Naish, Suchithra; Dale, Pat; Mackenzie, John S.; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Background Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012. Methods Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Conclusions Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas. PMID:24691549

Arctic sea ice albedo - A comparison of two satellite-derived data sets

NASA Technical Reports Server (NTRS)

Schweiger, Axel J.; Serreze, Mark C.; Key, Jeffrey R.

1993-01-01

Spatial patterns of mean monthly surface albedo for May, June, and July, derived from DMSP Operational Line Scan (OLS) satellite imagery are compared with surface albedos derived from the International Satellite Cloud Climatology Program (ISCCP) monthly data set. Spatial patterns obtained by the two techniques are in general agreement, especially for June and July. Nevertheless, systematic differences in albedo of 0.05 - 0.10 are noted which are most likely related to uncertainties in the simple parameterizations used in the DMSP analyses, problems in the ISCCP cloud-clearing algorithm and other modeling simplifications. However, with respect to the eventual goal of developing a reliable automated retrieval algorithm for compiling a long-term albedo data base, these initial comparisons are very encouraging.

Spatio-temporal surveillance of water based infectious disease (malaria) in Rawalpindi, Pakistan using geostatistical modeling techniques.

PubMed

Ahmad, Sheikh Saeed; Aziz, Neelam; Butt, Amna; Shabbir, Rabia; Erum, Summra

2015-09-01

One of the features of medical geography that has made it so useful in health research is statistical spatial analysis, which enables the quantification and qualification of health events. The main objective of this research was to study the spatial distribution patterns of malaria in Rawalpindi district using spatial statistical techniques to identify the hot spots and the possible risk factor. Spatial statistical analyses were done in ArcGIS, and satellite images for land use classification were processed in ERDAS Imagine. Four hundred and fifty water samples were also collected from the study area to identify the presence or absence of any microbial contamination. The results of this study indicated that malaria incidence varied according to geographical location, with eco-climatic condition and showing significant positive spatial autocorrelation. Hotspots or location of clusters were identified using Getis-Ord Gi* statistic. Significant clustering of malaria incidence occurred in rural central part of the study area including Gujar Khan, Kaller Syedan, and some part of Kahuta and Rawalpindi Tehsil. Ordinary least square (OLS) regression analysis was conducted to analyze the relationship of risk factors with the disease cases. Relationship of different land cover with the disease cases indicated that malaria was more related with agriculture, low vegetation, and water class. Temporal variation of malaria cases showed significant positive association with the meteorological variables including average monthly rainfall and temperature. The results of the study further suggested that water supply and sewage system and solid waste collection system needs a serious attention to prevent any outbreak in the study area.

Paleohydrologic techniques used to define the spatial occurrence of floods

USGS Publications Warehouse

Jarrett, R.D.

1990-01-01

Defining the cause and spatial characteristics of floods may be difficult because of limited streamflow and precipitation data. New paleohydrologic techniques that incorporate information from geomorphic, sedimentologic, and botanic studies provide important supplemental information to define homogeneous hydrologic regions. These techniques also help to define the spatial structure of rainstorms and floods and improve regional flood-frequency estimates. The occurrence and the non-occurrence of paleohydrologic evidence of floods, such as flood bars, alluvial fans, and tree scars, provide valuable hydrologic information. The paleohydrologic research to define the spatial characteristics of floods improves the understanding of flood hydrometeorology. This research was used to define the areal extent and contributing drainage area of flash floods in Colorado. Also, paleohydrologic evidence was used to define the spatial boundaries for the Colorado foothills region in terms of the meteorologic cause of flooding and elevation. In general, above 2300 m, peak flows are caused by snowmelt. Below 2300 m, peak flows primarily are caused by rainfall. The foothills region has an upper elevation limit of about 2300 m and a lower elevation limit of about 1500 m. Regional flood-frequency estimates that incorporate the paleohydrologic information indicate that the Big Thompson River flash flood of 1976 had a recurrence interval of approximately 10,000 years. This contrasts markedly with 100 to 300 years determined by using conventional hydrologic analyses. Flood-discharge estimates based on rainfall-runoff methods in the foothills of Colorado result in larger values than those estimated with regional flood-frequency relations, which are based on long-term streamflow data. Preliminary hydrologic and paleohydrologic research indicates that intense rainfall does not occur at higher elevations in other Rocky Mountain states and that the highest elevations for rainfall-producing floods vary by latitude. The study results have implications for floodplain management and design of hydraulic structures in the mountains of Colorado and other Rocky Mountain States. ?? 1990.

Does spatial location matter? Traditional therapy utilisation among the general population in a Ghanaian rural and urban setting.

PubMed

Gyasi, Razak Mohammed; Asante, Felix; Segbefia, Alexander Yao; Abass, Kabila; Mensah, Charlotte Monica; Siaw, Lawrencia Pokuah; Eshun, Gabriel; Adjei, Prince Osei-Wusu

2015-06-01

Despite the recognition for rising consumption rate of traditional medicine (TRM) in health and spatio-medical literature in the global scale, the impact of location in traditional therapy use has been explored least in Ghana. This paper analysed the role of spatial variation in TRM use in Kumasi Metropolis and Sekyere South District of Ashanti Region, Ghana. A retrospective cross-sectional and place-based survey was conducted in a representative sample (N=324) selected through systematic random sampling technique. Structured interviewer-administered questionnaires were espoused as the main research instruments. Data were analysed with Pearson's Chi-square and Fisher's exact tests from the Predictive Analytics Software (PASW) version 17.0. The study found that over 86% reported TRM use. Whilst majority (59.1%) of the respondents had used TRM two or more times within the last 12 months, biologically-based therapies and energy healing were common forms of TRM accessed. Although, the use of TRM did not vary (p>0.05), knowledge about TRM, modalities of TRM and the sources of TRM differed significantly across geographically demarcated rural and urban splits (p<0.005). The study advances our understanding of the spatial dimensions as regards TRM utilisation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Geographical Text Analysis: A new approach to understanding nineteenth-century mortality.

PubMed

Porter, Catherine; Atkinson, Paul; Gregory, Ian

2015-11-01

This paper uses a combination of Geographic Information Systems (GIS) and corpus linguistic analysis to extract and analyse disease related keywords from the Registrar-General's Decennial Supplements. Combined with known mortality figures, this provides, for the first time, a spatial picture of the relationship between the Registrar-General's discussion of disease and deaths in England and Wales in the nineteenth and early twentieth centuries. Techniques such as collocation, density analysis, the Hierarchical Regional Settlement matrix and regression analysis are employed to extract and analyse the data resulting in new insight into the relationship between the Registrar-General's published texts and the changing mortality patterns during this time. Copyright © 2015 Elsevier Ltd. All rights reserved.

Statistical analyses of the results of 25 years of beach litter surveys on the south-eastern North Sea coast.

PubMed

Schulz, Marcus; Clemens, Thomas; Förster, Harald; Harder, Thorsten; Fleet, David; Gaus, Silvia; Grave, Christel; Flegel, Imme; Schrey, Eckart; Hartwig, Eike

2015-08-01

In the North Sea, the amount of litter present in the marine environment represents a severe environmental problem. In order to assess the magnitude of the problem and measure changes in abundance, the results of two beach litter monitoring programmes were compared and analysed for long-term trends applying multivariate techniques. Total beach litter pollution was persistently high. Spatial differences in litter abundance made it difficult to identify long-term trends: Partly more than 8000 litter items year(-1) were recorded on a 100 m long survey site on the island of Scharhörn, while the survey site on the beach on the island of Amrum revealed abundances lower by two orders of magnitude. Beach litter was dominated by plastic with mean proportions of 52%-91% of total beach litter. Non-parametric time series analyses detected many significant trends, which, however, did not show any systematic spatial patterns. Cluster analyses partly led to groupings of beaches according to their expositions to sources of litter, wind and currents. Surveys in short intervals of one to two weeks were found to give higher annual sums of beach litter than the quarterly surveys of the OSPAR method. Surveys at regular intervals of four weeks to five months would make monitoring results more reliable. Copyright © 2015 Elsevier Ltd. All rights reserved.

230Th-U dating of surficial deposits using the ion microprobe (SHRIMP-RG): A microstratigraphic perspective

USGS Publications Warehouse

Maher, K.; Wooden, J.L.; Paces, J.B.; Miller, D.M.

2007-01-01

We used the sensitive high-resolution ion microprobe reverse-geometry (SHRIMP-RG) to date pedogenic opal using the 230Th-U system. Due to the high-spatial resolution of an ion microprobe (typically 30 ??m), regions of pure opal within a sample can be targeted and detrital material can be avoided. In addition, because the technique is non-destructive, the sample can be preserved for other types of analyses including electron microprobe or other stable isotope or trace element ion microprobe measurements. The technique is limited to material with U concentrations greater than ???50 ppm. However, the high spatial resolution, small sample requirements, and the ability to avoid detrital material make this technique a suitable technique for dating many Pleistocene deposits formed in semi-arid environments. To determine the versatility of the method, samples from several different deposits were analyzed, including silica-rich pebble coatings from pedogenic carbonate horizons, a siliceous sinter deposit, and opaline silica deposited as a spring mound. U concentrations for 30-??m-diameter spots ranged from 50 to 1000 ppm in these types of materials. The 230Th/232Th activity ratios also ranged from ???100 to 106, eliminating the need for detrital Th corrections that reduce the precision of traditional U-Th ages for many milligram- and larger-sized samples. In pedogenic material, layers of high-U opal (ca. 500 ppm) are commonly juxtaposed next to layers of calcite with much lower U concentrations (1-2 ppm). If these types of samples are not analyzed using a technique with the appropriate spatial resolution, the ages may be strongly biased towards the age of the opal. Comparison with standard TIMS (Thermal Ionization Mass Spectrometry) measurements from separate microdrilled samples suggests that although the analytical precision of the ion microprobe (SHRIMP-RG) measurements is less than TIMS, the high spatial resolution results in better accuracy in the age determination for finely layered or complex deposits. The ion microprobe approach also may be useful for pre-screening samples to determine the age and degree of post-depositional alteration, analyzing finely layered samples or samples with complex growth histories, and obtaining simultaneous measurements of trace elements.

Are visual cue masking and removal techniques equivalent for studying perceptual skills in sport?

PubMed

Mecheri, Sami; Gillet, Eric; Thouvarecq, Regis; Leroy, David

2011-01-01

The spatial-occlusion paradigm makes use of two techniques (masking and removing visual cues) to provide information about the anticipatory cues used by viewers. The visual scene resulting from the removal technique appears to be incongruous, but the assumed equivalence of these two techniques is spreading. The present study was designed to address this issue by combining eye-movement recording with the two types of occlusion (removal versus masking) in a tennis serve-return task. Response accuracy and decision onsets were analysed. The results indicated that subjects had longer reaction times under the removal condition, with an identical proportion of correct responses. Also, the removal technique caused the subjects to rely on atypical search patterns. Our findings suggest that, when the removal technique was used, viewers were unable to systematically count on stored memories to help them accomplish the interception task. The persistent failure to question some of the assumptions about the removal technique in applied visual research is highlighted, and suggestions for continued use of the masking technique are advanced.

A modeling approach for aerosol optical depth analysis during forest fire events

NASA Astrophysics Data System (ADS)

Aube, Martin P.; O'Neill, Normand T.; Royer, Alain; Lavoue, David

2004-10-01

Measurements of aerosol optical depth (AOD) are important indicators of aerosol particle behavior. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as DDV (Dense Dark Vegetation) based inversion algorithms which yield AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new assimilation methodology that links AOD measurements and the predictions of a particulate matter Transport Model. This modelling package (AODSEM V2.0 for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution may be tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important and robust parameter. We applied this methodology to a significant smoke event that occurred over the eastern part of North America in July 2002.

Non-Destructive Study of Bulk Crystallinity and Elemental Composition of Natural Gold Single Crystal Samples by Energy-Resolved Neutron Imaging

PubMed Central

Tremsin, Anton S.; Rakovan, John; Shinohara, Takenao; Kockelmann, Winfried; Losko, Adrian S.; Vogel, Sven C.

2017-01-01

Energy-resolved neutron imaging enables non-destructive analyses of bulk structure and elemental composition, which can be resolved with high spatial resolution at bright pulsed spallation neutron sources due to recent developments and improvements of neutron counting detectors. This technique, suitable for many applications, is demonstrated here with a specific study of ~5–10 mm thick natural gold samples. Through the analysis of neutron absorption resonances the spatial distribution of palladium (with average elemental concentration of ~0.4 atom% and ~5 atom%) is mapped within the gold samples. At the same time, the analysis of coherent neutron scattering in the thermal and cold energy regimes reveals which samples have a single-crystalline bulk structure through the entire sample volume. A spatially resolved analysis is possible because neutron transmission spectra are measured simultaneously on each detector pixel in the epithermal, thermal and cold energy ranges. With a pixel size of 55 μm and a detector-area of 512 by 512 pixels, a total of 262,144 neutron transmission spectra are measured concurrently. The results of our experiments indicate that high resolution energy-resolved neutron imaging is a very attractive analytical technique in cases where other conventional non-destructive methods are ineffective due to sample opacity. PMID:28102285

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

NASA Technical Reports Server (NTRS)

Schieldge, John

2000-01-01

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Recent Advances in the Measurement of Arsenic, Cadmium, and Mercury in Rice and Other Foods

PubMed Central

Punshon, Tracy

2015-01-01

Trace element analysis of foods is of increasing importance because of raised consumer awareness and the need to evaluate and establish regulatory guidelines for toxic trace metals and metalloids. This paper reviews recent advances in the analysis of trace elements in food, including challenges, state-of-the art methods, and use of spatially resolved techniques for localizing the distribution of As and Hg within rice grains. Total elemental analysis of foods is relatively well-established but the push for ever lower detection limits requires that methods be robust from potential matrix interferences which can be particularly severe for food. Inductively coupled plasma mass spectrometry (ICP-MS) is the method of choice, allowing for multi-element and highly sensitive analyses. For arsenic, speciation analysis is necessary because the inorganic forms are more likely to be subject to regulatory limits. Chromatographic techniques coupled to ICP-MS are most often used for arsenic speciation and a range of methods now exist for a variety of different arsenic species in different food matrices. Speciation and spatial analysis of foods, especially rice, can also be achieved with synchrotron techniques. Sensitive analytical techniques and methodological advances provide robust methods for the assessment of several metals in animal and plant-based foods, in particular for arsenic, cadmium and mercury in rice and arsenic speciation in foodstuffs. PMID:25938012

Comparing apples with apples: Using spatially distributed time series of monitoring data for model evaluation

NASA Astrophysics Data System (ADS)

Solazzo, E.; Galmarini, S.

2015-07-01

A more sensible use of monitoring data for the evaluation and development of regional-scale atmospheric models is proposed. The motivation stems from observing current practices in this realm where the quality of monitoring data is seldom questioned and model-to-data deviation is uniquely attributed to model deficiency. Efforts are spent to quantify the uncertainty intrinsic to the measurement process, but aspects connected to model evaluation and development have recently emerged that remain obscure, such as the spatial representativeness and the homogeneity of signals subjects of our investigation. By using time series of hourly records of ozone for a whole year (2006) collected by the European AirBase network the area of representativeness is firstly analysed showing, for similar class of stations (urban, suburban, rural), large heterogeneity and high sensitivity to the density of the network and to the noise of the signal, suggesting the mere station classification to be not a suitable candidate to help select the pool of stations used in model evaluation. Therefore a novel, more robust technique is developed based on the spatial properties of the associativity of the spectral components of the ozone time series, in an attempt to determine the level of homogeneity. The spatial structure of the associativity among stations is informative of the spatial representativeness of that specific component and automatically tells about spatial anisotropy. Time series of ozone data from North American networks have also been analysed to support the methodology. We find that the low energy components (especially the intra-day signal) suffer from a too strong influence of country-level network set-up in Europe, and different networks in North America, showing spatial heterogeneity exactly at the administrative border that separates countries in Europe and at areas separating different networks in North America. For model evaluation purposes these elements should be treated as purely stochastic and discarded, while retaining the portion of the signal useful to the evaluation process. Trans-boundary discontinuity of the intra-day signal along with cross-network grouping has been found to be predominant. Skills of fifteen regional chemical-transport modelling systems have been assessed in light of this result, finding an improved accuracy of up to 5% when the intra-day signal is removed with respect to the case where all components are analysed.

Airborne laser scanning for forest health status assessment and radiative transfer modelling

NASA Astrophysics Data System (ADS)

Novotny, Jan; Zemek, Frantisek; Pikl, Miroslav; Janoutova, Ruzena

2013-04-01

Structural parameters of forest stands/ecosystems are an important complementary source of information to spectral signatures obtained from airborne imaging spectroscopy when quantitative assessment of forest stands are in the focus, such as estimation of forest biomass, biochemical properties (e.g. chlorophyll /water content), etc. The parameterization of radiative transfer (RT) models used in latter case requires three-dimensional spatial distribution of green foliage and woody biomass. Airborne LiDAR data acquired over forest sites bears these kinds of 3D information. The main objective of the study was to compare the results from several approaches to interpolation of digital elevation model (DEM) and digital surface model (DSM). We worked with airborne LiDAR data with different density (TopEye Mk II 1,064nm instrument, 1-5 points/m2) acquired over the Norway spruce forests situated in the Beskydy Mountains, the Czech Republic. Three different interpolation algorithms with increasing complexity were tested: i/Nearest neighbour approach implemented in the BCAL software package (Idaho Univ.); ii/Averaging and linear interpolation techniques used in the OPALS software (Vienna Univ. of Technology); iii/Active contour technique implemented in the TreeVis software (Univ. of Freiburg). We defined two spatial resolutions for the resulting coupled raster DEMs and DSMs outputs: 0.4 m and 1 m, calculated by each algorithm. The grids correspond to the same spatial resolutions of hyperspectral imagery data for which the DEMs were used in a/geometrical correction and b/building a complex tree models for radiative transfer modelling. We applied two types of analyses when comparing between results from the different interpolations/raster resolution: 1/calculated DEM or DSM between themselves; 2/comparison with field data: DEM with measurements from referential GPS, DSM - field tree alometric measurements, where tree height was calculated as DSM-DEM. The results of the analyses show that: 1/averaging techniques tend to underestimate the tree height and the generated surface does not follow the first LiDAR echoes both for 1 m and 0.4 m pixel size; 2/we did not find any significant difference between tree heights calculated by nearest neighbour algorithm and the active contour technique for 1 m pixel output but the difference increased with finer resolution (0.4 m); 3/the accuracy of the DEMs calculated by tested algorithms is similar.

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California.

PubMed

Liévanos, Raoul S

2018-04-16

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

PubMed Central

2018-01-01

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California. PMID:29659481

Descriptive epidemiology of typhoid fever during an epidemic in Harare, Zimbabwe, 2012.

PubMed

Polonsky, Jonathan A; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J

2014-01-01

Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range.

What are we ‘tweeting’ about obesity? Mapping tweets with Topic Modeling and Geographic Information System

PubMed Central

Ghosh, Debarchana (Debs); Guha, Rajarshi

2014-01-01

Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are ‘food deserts’, ‘fast food’, and ‘childhood obesity’. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as ‘childhood obesity and schools’, ‘obesity prevention’, and ‘obesity and food habits’ are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets. PMID:25126022

Descriptive Epidemiology of Typhoid Fever during an Epidemic in Harare, Zimbabwe, 2012

PubMed Central

Polonsky, Jonathan A.; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J.

2014-01-01

Background Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. Methods A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. Principal Findings We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. Conclusions This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range. PMID:25486292

What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System.

PubMed

Ghosh, Debarchana Debs; Guha, Rajarshi

2013-01-01

Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are 'food deserts', 'fast food', and 'childhood obesity'. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as 'childhood obesity and schools', 'obesity prevention', and 'obesity and food habits' are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets.

Feasibility study of imaging spectroscopy to monitor the quality of online welding.

PubMed

Mirapeix, Jesús; García-Allende, P Beatriz; Cobo, Adolfo; Conde, Olga M; López-Higuera, José M

2009-08-20

An online welding quality system based on the use of imaging spectroscopy is proposed and discussed. Plasma optical spectroscopy has already been successfully applied in this context by establishing a direct correlation between some spectroscopic parameters, e.g., the plasma electronic temperature and the resulting seam quality. Given that the use of the so-called hyperspectral devices provides both spatial and spectral information, we propose their use for the particular case of arc welding quality monitoring in an attempt to determine whether this technique would be suitable for this industrial situation. Experimental welding tests are presented, and the ability of the proposed solution to identify simulated defects is proved. Detailed spatial analyses suggest that this additional dimension can be used to improve the performance of the entire system.

Airborne hyperspectral imaging for the detection of powdery mildew in wheat

NASA Astrophysics Data System (ADS)

Franke, Jonas; Mewes, Thorsten; Menz, Gunter

2008-08-01

Plant stresses, in particular fungal diseases, show a high variability in spatial and temporal dimension with respect to their impact on the host. Recent "Precision Agriculture"-techniques allow for a spatially and temporally adjusted pest control that might reduce the amount of cost-intensive and ecologically harmful agrochemicals. Conventional stressdetection techniques such as random monitoring do not meet demands of such optimally placed management actions. The prerequisite is an accurate sensor-based detection of stress symptoms. The present study focuses on a remotely sensed detection of the fungal disease powdery mildew (Blumeria graminis) in wheat, Europe's main crop. In a field experiment, the potential of hyperspectral data for an early detection of stress symptoms was tested. A sophisticated endmember selection procedure was used and, additionally, a linear spectral mixture model was applied to a pixel spectrum with known characteristics, in order to derive an endmember representing 100% powdery mildew-infected wheat. Regression analyses of matched fraction estimates of this endmember and in-field-observed powdery mildew severities showed promising results (r=0.82 and r2=0.67).

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

PubMed

Moerel, Michelle; De Martino, Federico; Kemper, Valentin G; Schmitter, Sebastian; Vu, An T; Uğurbil, Kâmil; Formisano, Elia; Yacoub, Essa

2018-01-01

Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T 2 * weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T 2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T 2 * weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T 2 * weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency preference and selectivity for the GE-EPI dataset, but not for the 3D GRASE dataset. Thus, a T 2 weighted acquisition is recommended if high specificity in tonotopic maps is required. In conclusion, different fMRI acquisitions were better suited for different analyses. It is therefore critical that any sequence parameter optimization considers the eventual intended fMRI analyses and the nature of the neuroscience questions being asked. Copyright © 2017 Elsevier Inc. All rights reserved.

Levelling VS. InSAR in Urban Underground Construction Monitoring. Case of la Sagrera Railway Station (barcelona, Spain).

NASA Astrophysics Data System (ADS)

Vázquez-Suñé, E.; Serrano-Juan, A.; Pujades, E.; Crosetto, M.

2016-12-01

Construction processes require monitoring to ensure safety and to control the new and existing structures. The most accurate and spread monitoring method to measure displacements is levelling, a point-like surveying technique that tipically allows for tens of discrete in-situ sub-millimetric measures per squared kilometer. Another emerging technique for mapping soil deformation is the Interferometric Synthetic Aperture Radar (InSAR), which is based on SAR images acquired from orbiting satellites. This remote sensing technique can provide better spatial point density than levelling, more extensive spatial coverage and cheaper acquisitions. This paper analyses, compares and discusses levelling and InSAR measurements when they are used to measure the soil deformation induced by the dewatering associated to underground constructions in urban areas. To do so, an experiment was performed in the future railway station of La Sagrera, Barcelona (Spain), in which levelling and InSAR were used to accurately quantify ground deformation by dewatering. Results showed that soil displacements measured by levelling and InSAR were not always consisting. InSAR measurements were more accurate with respect the soil deformation produced by the dewatering while levelling was really useful to determine the real impact of the construction on the nearby buildings.

A review of spatio-temporal modelling of quadrat count data with application to striga occurrence in a pearl millet field

NASA Astrophysics Data System (ADS)

Hess, Dale; van Lieshout, Marie-Colette; Payne, Bill; Stein, Alfred

This paper describes how spatial statistical techniques may be used to analyse weed occurrence in tropical fields. Quadrat counts of weed numbers are available over a series of years, as well as data on explanatory variables, and the aim is to smooth the data and assess spatial and temporal trends. We review a range of models for correlated count data. As an illustration, we consider data on striga infestation of a 60 × 24 m 2 millet field in Niger collected from 1985 until 1991, modelled by independent Poisson counts and a prior auto regression term enforcing spatial coherence. The smoothed fields show the presence of a seed bank, the estimated model parameters indicate a decay in the striga numbers over time, as well as a clear correlation with the amount of rainfall in 15 consecutive days following the sowing date. Such results could contribute to precision agriculture as a guide to more cost-effective striga control strategies.

Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder.

PubMed

Landin-Romero, Ramón; Canales-Rodríguez, Erick J; Kumfor, Fiona; Moreno-Alcázar, Ana; Madre, Mercè; Maristany, Teresa; Pomarol-Clotet, Edith; Amann, Benedikt L

2017-01-01

The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques. Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity. At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle. The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders.

Crystallography of refractory metal nuggets in carbonaceous chondrites: A transmission Kikuchi diffraction approach

NASA Astrophysics Data System (ADS)

Daly, Luke; Bland, Phil A.; Dyl, Kathryn A.; Forman, Lucy V.; Saxey, David W.; Reddy, Steven M.; Fougerouse, Denis; Rickard, William D. A.; Trimby, Patrick W.; Moody, Steve; Yang, Limei; Liu, Hongwei; Ringer, Simon P.; Saunders, Martin; Piazolo, Sandra

2017-11-01

Transmission Kikuchi diffraction (TKD) is a relatively new technique that is currently being developed for geological sample analysis. This technique utilises the transmission capabilities of a scanning electron microscope (SEM) to rapidly and accurately map the crystallographic and geochemical features of an electron transparent sample. TKD uses a similar methodology to traditional electron backscatter diffraction (EBSD), but is capable of achieving a much higher spatial resolution (5-10 nm) (Trimby, 2012; Trimby et al., 2014). Here we apply TKD to refractory metal nuggets (RMNs) which are micrometre to sub-micrometre metal alloys composed of highly siderophile elements (HSEs) found in primitive carbonaceous chondrite meteorites. TKD allows us to analyse RMNs in situ, enabling the characterisation of nanometre-scale variations in chemistry and crystallography, whilst preserving their spatial and crystallographic context. This provides a complete representation of each RMN, permitting detailed interpretation of their formation history. We present TKD analysis of five transmission electron microscopy (TEM) lamellae containing RMNs coupled with EBSD and TEM analyses. These analyses revealed textures and relationships not previously observed in RMNs. These textures indicate some RMNs experienced annealing, forming twins. Some RMNs also acted as nucleation centres, and formed immiscible metal-silicate fluids. In fact, each RMN analysed in this study had different crystallographic textures. These RMNs also had heterogeneous compositions, even between RMNs contained within the same inclusion, host phase and even separated by only a few nanometres. Some RMNs are also affected by secondary processes at low temperature causing exsolution of molybdenite. However, most RMNs had crystallographic textures indicating that the RMN formed prior to their host inclusion. TKD analyses reveal most RMNs have been affected by processing in the protoplanetary disk. Despite this alteration, RMNs still preserve primary crystallographic textures and heterogeneous chemical signatures. This heterogeneity in crystallographic relationships, which mostly suggest that RMNs pre-date their host, is consistent with the idea that there is not a dominant RMN forming process. Each RMN has experienced a complex history, supporting the suggestion of Daly et al. (2017), that RMNs may preserve a diverse pre-solar chemical signature inherited from the Giant Molecular Cloud.

A generic method for improving the spatial interoperability of medical and ecological databases.

PubMed

Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M

2017-10-03

The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

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

PubMed

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

2016-01-01

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

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

New Homogeneous Standards by Atomic Layer Deposition for Synchrotron X-ray Fluorescence and Absorption Spectroscopies.

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

Butterworth, A.L.; Becker, N.; Gainsforth, Z.

2012-03-13

Quantification of synchrotron XRF analyses is typically done through comparisons with measurements on the NIST SRM 1832/1833 thin film standards. Unfortunately, these standards are inhomogeneous on small scales at the tens of percent level. We are synthesizing new homogeneous multilayer standards using the Atomic Layer Deposition technique and characterizing them using multiple analytical methods, including ellipsometry, Rutherford Back Scattering at Evans Analytical, Synchrotron X-ray Fluorescence (SXRF) at Advanced Photon Source (APS) Beamline 13-ID, Synchrotron X-ray Absorption Spectroscopy (XAS) at Advanced Light Source (ALS) Beamlines 11.0.2 and 5.3.2.1 and by electron microscopy techniques. Our motivation for developing much-needed cross-calibration of synchrotronmore » techniques is borne from coordinated analyses of particles captured in the aerogel of the NASA Stardust Interstellar Dust Collector (SIDC). The Stardust Interstellar Dust Preliminary Examination (ISPE) team have characterized three sub-nanogram, {approx}1{micro}m-sized fragments considered as candidates to be the first contemporary interstellar dust ever collected, based on their chemistries and trajectories. The candidates were analyzed in small wedges of aerogel in which they were extracted from the larger collector, using high sensitivity, high spatial resolution >3 keV synchrotron x-ray fluorescence spectroscopy (SXRF) and <2 keV synchrotron x-ray transmission microscopy (STXM) during Stardust ISPE. The ISPE synchrotron techniques have complementary capabilities. Hard X-ray SXRF is sensitive to sub-fg mass of elements Z {ge} 20 (calcium) and has a spatial resolution as low as 90nm. X-ray Diffraction data were collected simultaneously with SXRF data. Soft X-ray STXM at ALS beamline 11.0.2 can detect fg-mass of most elements, including cosmochemically important oxygen, magnesium, aluminum and silicon, which are invisible to SXRF in this application. ALS beamline 11.0.2 has spatial resolution better than 25 nm. Limiting factors for Stardust STXM analyses were self-imposed limits of photon dose due to radiation damage concerns, and significant attenuation of <1500 eV X-rays by {approx}80{micro}m thick, {approx}25 mg/cm{sup 3} density silica aerogel capture medium. In practice, the ISPE team characterized the major, light elements using STXM (O, Mg, Al, Si) and the heavier minor and trace elements using SXRF. The two data sets overlapped only with minor Fe and Ni ({approx}1% mass abundance), providing few quantitative cross-checks. New improved standards for cross calibration are essential for consortium-based analyses of Stardust interstellar and cometary particles, IDPs. Indeed, they have far reaching application across the whole synchrotron-based analytical community. We have synthesized three ALD multilayers simultaneously on silicon nitride membranes and silicon and characterized them using RBS (on Si), XRF (on Si{sub 3}N{sub 4}) and STXM/XAS (holey Si{sub 3}N{sub 4}). The systems we have started to work with are Al-Zn-Fe and Y-Mg-Er. We have found these ALD multi-layers to be uniform at {micro}m- to nm scales, and have found excellent consistency between four analytical techniques so far. The ALD films can also be used as a standard for e-beam instruments, eg., TEM EELS or EDX. After some early issues with the consistency of coatings to the back-side of the membrane windows, we are confident to be able to show multi-analytical agreement to within 10%. As the precision improves, we can use the new standards to verify or improve the tabulated cross-sections.« less

New approach to estimating variability in visual field data using an image processing technique.

PubMed Central

Crabb, D P; Edgar, D F; Fitzke, F W; McNaught, A I; Wynn, H P

1995-01-01

AIMS--A new framework for evaluating pointwise sensitivity variation in computerised visual field data is demonstrated. METHODS--A measure of local spatial variability (LSV) is generated using an image processing technique. Fifty five eyes from a sample of normal and glaucomatous subjects, examined on the Humphrey field analyser (HFA), were used to illustrate the method. RESULTS--Significant correlation between LSV and conventional estimates--namely, HFA pattern standard deviation and short term fluctuation, were found. CONCLUSION--LSV is not dependent on normals' reference data or repeated threshold determinations, thus potentially reducing test time. Also, the illustrated pointwise maps of LSV could provide a method for identifying areas of fluctuation commonly found in early glaucomatous field loss. PMID:7703196

An analysis of tree mortality using high resolution remotely-sensed data for mixed-conifer forests in San Diego county

NASA Astrophysics Data System (ADS)

Freeman, Mary Pyott

ABSTRACT An Analysis of Tree Mortality Using High Resolution Remotely-Sensed Data for Mixed-Conifer Forests in San Diego County by Mary Pyott Freeman The montane mixed-conifer forests of San Diego County are currently experiencing extensive tree mortality, which is defined as dieback where whole stands are affected. This mortality is likely the result of the complex interaction of many variables, such as altered fire regimes, climatic conditions such as drought, as well as forest pathogens and past management strategies. Conifer tree mortality and its spatial pattern and change over time were examined in three components. In component 1, two remote sensing approaches were compared for their effectiveness in delineating dead trees, a spatial contextual approach and an OBIA (object based image analysis) approach, utilizing various dates and spatial resolutions of airborne image data. For each approach transforms and masking techniques were explored, which were found to improve classifications, and an object-based assessment approach was tested. In component 2, dead tree maps produced by the most effective techniques derived from component 1 were utilized for point pattern and vector analyses to further understand spatio-temporal changes in tree mortality for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Results indicate that conifer mortality was significantly clustered, increased substantially between 2002 and 2005, and was non-random with respect to tree species and diameter class sizes. In component 3, multiple environmental variables were used in Generalized Linear Model (GLM-logistic regression) and decision tree classifier model development, revealing the importance of climate and topographic factors such as precipitation and elevation, in being able to predict areas of high risk for tree mortality. The results from this study highlight the importance of multi-scale spatial as well as temporal analyses, in order to understand mixed-conifer forest structure, dynamics, and processes of decline, which can lead to more sustainable management of forests with continued natural and anthropogenic disturbance.

Observed SWE trends and climate analysis for Northwest Pacific North America: validation for future projection of SWE using the CRCM and VIC

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Bronaugh, D.; Rodenhuis, D.

2008-12-01

Observational databases of snow water equivalent (SWE) have been collected from Alaska, western US states and the Canadian provinces of British Columbia, Alberta, Saskatchewan, and territories of NWT, and the Yukon. These databases were initially validated to remove inconsistencies and errors in the station records, dates or the geographic co-ordinates of the station. The cleaned data was then analysed for historical (1950 to 2006) trend using emerging techniques for trend detection based on (first of the month) estimates for January to June. Analysis of SWE showed spatial variability in the count of records across the six month time period, and this study illustrated differences between Canadian and US (or the north and south) collection. Two different data sets (one gridded and one station) were then used to analyse April 1st records, for which there was the greatest spatial spread of station records for analysis with climate information. Initial results show spatial variability (in both magnitude and direction of trend) for trend results, and climate correlations and principal components indicate different drivers of change in SWE across the western US, Canada and north to Alaska. These results will be used to validate future predictions of SWE that are being undertaken using the Canadian Regional Climate Model (CRCM) and the Variable Infiltration Capacity (VIC) hydrologic model for Western Northern America (CRCM) and British Columbia (VIC).

Understanding relationships between morphology and ecosystem structure in a shallow tidal basins of Venice lagoon

NASA Astrophysics Data System (ADS)

Giuseppina Persichillo, Maria; Taramelli, Andrea; Valentini, Emiliana; Filipponi, Federico; Meisina, Claudia; Zucca, Francesco

2014-05-01

Coastal wetlands represent complex ecosystems prone to continue fluctuation of their internal equilibrium. They are valuable natural resources characterized by the continue interactions between geomorphological and biological components. Their adaptation to changing conditions is highly dependent on the rate and extent of spatial and temporal processes and their responses are still poorly understood. According to this, the vulnerability assessment to natural and human made hazard have became fundamental to analyse the resilience of these areas, their ability to cope with the impacts from externally driven forces or the efforts needed to minimize the impacts (Gitay et al., 2011). The objective of this research is to develop a comprehensive and replicable method through the application of Multi-Source data analysis, based on the integration of Earth Observation data and field survey, to analyse a shallow tidal basin of salt marshes, located in the northern part of the Venice lagoon. The study site is characterised by relatively elevated areas colonized by halophytic vegetation, and tidal flats, with not vegetated areas, characterized by lower elevations. Sub-pixel processing techniques (Spectral Mixing Analysis - SMA) were used to analyse the spatial distribution of both vegetation and sediments typology. Furthermore the classifications were assayed in terms of spatial (Power law) and temporal (Empirical Orthogonal Functions) patterns, in order to find the main characteristics of the aforementioned spatial trends and their variation over time. The principal aim is to study the spatio-temporal evolution of this coastal wetland area, in order to indentify tipping points, namely thresholds, beyond which the system reaches critical state and the main climatic, hydrodynamic and morphological variables that may influence and increase this behaviour. This research represents a new approach to study the geomorphological processes and to improve the management and conservation planning for coastal areas. Reference: Gitay H., Finlayson C.M. and Davidson N.(2011) - A Framework for assessing the vulnerability of wetlands to climate change, Ramsar Technical Report No. 5, 1-18.

The ground subsidence anomaly investigation around Ambala, India by InSAR and spatial analyses: Why and how the Ambala city behaves as the most significant subsidence region in the Northwest India?

NASA Astrophysics Data System (ADS)

Kim, J.; Lin, S. Y.; Tsai, Y.; Singh, S.; Singh, T.

2017-12-01

A large ground deformation which may be caused by a significant groundwater depletion of the Northwest India Aquifer has been successfully observed throughout space geodesy techniques (Tsai et al, 2016). Employing advanced time-series ScanSAR InSAR analysis and Gravity Recovery and Climate Experiment (GRACE) satellites data, it revealed 400-km wide huge ground deformation in and around Haryana. It was further notified that the Ambala city located in northern Haryana district shown the most significant ground subsidence with maximum cumulative deformation up to 0.2 meters within 3 years in contrast to the nearby cities such as Patiala and Chandigarh that did not present similar subsidence. In this study, we investigated the details of "Ambala Anomaly" employing advanced time-series InSAR and spatial analyses together with local geology and anthropogenic contexts and tried to identify the factors causing such a highly unique ground deformation pattern. To explore the pattern and trend of Ambala' subsidence, we integrated the time-series deformation results of both ascending L-band PALSAR-1 (Phased Array type L-band Synthetic Aperture Radar) from 2007/1 to 2011/1 and descending C-band ASAR (Advanced Synthetic Aperture Radar) from 2008/9 to 2010/8 to process the 3D decomposition, expecting to reveal the asymmetric movement of the surface. In addition. The spatial analyses incorporating detected ground deformations and local economical/social factors were then applied for the interpretation of "Ambala Anomaly". The detailed interrelationship of driving factors of the "Ambala Anomaly" and the spatial pattern of corresponding ground subsidence will be further demonstrated. After all, we determined the uniqueness of Ambala subsidence possibly be driven by both anthropogenic behaviors including the rapid growth rate of population and constructing of industrial centers as well as the natural geological characteristics and sediment deposition.

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Qiu, Hong-lie

1998-01-01

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Assessing SaTScan ability to detect space-time clusters in wildfires

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Pereira, Mário; Caramelo, Liliana; Vega Orozco, Carmen; Kanevski, Mikhail

2013-04-01

Besides classical cluster analysis techniques which are able to analyse spatial and temporal data, SaTScan software analyses space-time data using the spatial, temporal or space-time scan statistics. This software requires the spatial coordinates of the fire, but since in the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011) the location of each fire is the parish where the ignition occurs, the fire spatial coordinates were considered as coordinates of the centroid of the parishes. Moreover, in general, the northern region is characterized by a large number of small parishes while the southern comprises parish much larger. The objectives of this study are: (i) to test the ability of SaTScan to detect the correct space-time clusters, in what respects to spatial and temporal location and size; and, (ii) to evaluate the effect of the dimensions of the parishes and of aggregating all fires occurred in a parish in a single point. Results obtained with a synthetic database where clusters were artificially created with different densities, in different regions of the country and with different sizes and durations, allow to conclude: the ability of SaTScan to correctly identify the clusters (location, shape and spatial and temporal dimension); and objectively assess the influence of the size of the parishes and windows used in space-time detection. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

USGS Publications Warehouse

Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

2012-01-01

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

Resolution, the key to unlocking granite petrogenesis using zircon U-Pb - Lu-Hf studies

NASA Astrophysics Data System (ADS)

Tapster, Simon; Horstwood, Matthew; Roberts, Nick M. W.; Deady, Eimear; Shail, Robin

2017-04-01

Coarse-scale understanding of crustal evolution and source contributions to igneous systems has been drastically enhanced by coupled zircon U-Pb and Lu-Hf data sets. These are now common place and potentially offer advantages over whole-rock analyses by resolving heterogeneous source components in the complex crystal cargos of single hand-samples. However, the application of coupled zircon U-Pb and Lu-Hf studies to address detailed petrogenetic questions faces a crisis of resolution - On the one hand, micro-beam analytical techniques have high spatial resolution, capable of interrogating crystals with complex growth histories. Yet, the >1-2% temporal resolution of these techniques places a fundamental limitation on their utility for developing petrogenetic models. This limitation in data interpretation arises from timescales of crystal recycling or changes in source evolution that are often shorter than the U-Pb analytical precision. Conversely, high-precision CA-ID-TIMS U-Pb analysis of single whole zircons and solution MC-ICP-MS Lu-Hf isotopes of column washes (Hf masses equating to ca. 10-50 ng) have much greater temporal resolution (<0.1%), yet lack the spatial resolution to deal with complex crystal growth. Analyses homogenize any heterogeneity within the zircon and convolute the petrogenetic model. A balance must be struck between spatial and temporal resolution to address petrogenetic issues. Here, we demonstrate that micro-sampling of complex xenocryst-rich zircon crystals (e.g. <40 µm zircon tips) from the granitic post-Variscan Cornubian Batholith (SW England), in tandem with low-common Pb blank CA-ID-TIMS U-Pb chemistry, permits the analysis of zircon volumes that approach those of LA-ICPMS analyses, whilst simultaneously retaining the majority of the temporal resolution associated with the CA-ID-TIMS U-Pb technique. The low volume of zircon within these analyses may only provide <5 ng Hf, and therefore gaining useful precision from Lu-Hf isotopes is beyond the scope of typical solution MC-ICP-MS techniques. However, we demonstrate that an uncertainty level of ca. 1 ɛHf can be achieved with as little as 0.4 ng Hf through the use of low-volume solution introduction methods - thus bridging the gap in resolving power between in-situ and isotope dilution coupled zircon U-Pb - Lu-Hf studies. We demonstrate the potential of this approach to unravel intra- and inter-sample heterogeneity and address models for granite genesis using a new regional data set for 21 samples encompassing all major granite types within the Early Permian Cornubian Batholith (SW England). The data provide a refined chronological framework for magma source evolution over 20 Myrs of crust-mantle melt extraction and upper crustal batholith construction. The resulting petrogenetic model will also be evaluated through the lens of low- temporal resolution commonly employed in granitic zircon U-Pb - Lu-Hf studies in order to highlight the enhanced insights into geological processes gained though our approach. The current limitations to data interpretation and directions of future research will be discussed.

Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model.

PubMed

Brunker, K; Hampson, K; Horton, D L; Biek, R

2012-12-01

Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

Grating-based tomography applications in biomedical engineering

NASA Astrophysics Data System (ADS)

Schulz, Georg; Thalmann, Peter; Khimchenko, Anna; Müller, Bert

2017-10-01

For the investigation of soft tissues or tissues consisting of soft and hard tissues on the microscopic level, hard X-ray phase tomography has become one of the most suitable imaging techniques. Besides other phase contrast methods grating interferometry has the advantage of higher sensitivity than inline methods and the quantitative results. One disadvantage of the conventional double-grating setup (XDGI) compared to inline methods is the limitation of the spatial resolution. This limitation can be overcome by removing the analyser grating resulting in a single-grating setup (XSGI). In order to verify the performance of XSGI concerning contrast and spatial resolution, a quantitative comparison of XSGI and XDGI tomograms of a human nerve was performed. Both techniques provide sufficient contrast to allow for the distinction of tissue types. The spatial resolution of the two-fold binned XSGI data set is improved by a factor of two in comparison to XDGI which underlies its performance in tomography of soft tissues. Another application for grating-based X-ray phase tomography is the simultaneous visualization of soft and hard tissues of a plaque-containing coronary artery. The simultaneous visualization of both tissues is important for the segmentation of the lumen. The segmented data can be used for flow simulations in order to obtain information about the three-dimensional wall shear stress distribution needed for the optimization of mechano-sensitive nanocontainers used for drug delivery.

Nanometer-resolved chemical analyses of femtosecond laser-induced periodic surface structures on titanium

NASA Astrophysics Data System (ADS)

Kirner, Sabrina V.; Wirth, Thomas; Sturm, Heinz; Krüger, Jörg; Bonse, Jörn

2017-09-01

The chemical characteristics of two different types of laser-induced periodic surface structures (LIPSS), so-called high and low spatial frequency LIPSS (HSFL and LSFL), formed upon irradiation of titanium surfaces by multiple femtosecond laser pulses in air (30 fs, 790 nm, 1 kHz), are analyzed by various optical and electron beam based surface analytical techniques, including micro-Raman spectroscopy, energy dispersive X-ray analysis, X-ray photoelectron spectroscopy, and Auger electron spectroscopy. The latter method was employed in a high-resolution mode being capable of spatially resolving even the smallest HSFL structures featuring spatial periods below 100 nm. In combination with an ion sputtering technique, depths-resolved chemical information of superficial oxidation processes was obtained, revealing characteristic differences between the two different types of LIPSS. Our results indicate that a few tens of nanometer shallow HSFL are formed on top of a ˜150 nm thick graded superficial oxide layer without sharp interfaces, consisting of amorphous TiO2 and partially crystallized Ti2O3. The larger LSFL structures with periods close to the irradiation wavelength originate from the laser-interaction with metallic titanium. They are covered by a ˜200 nm thick amorphous oxide layer, which consists mainly of TiO2 (at the surface) and other titanium oxide species of lower oxidation states underneath.

Evaluation of C60 secondary ion mass spectrometry for the chemical analysis and imaging of fingerprints.

PubMed

Sisco, Edward; Demoranville, Leonard T; Gillen, Greg

2013-09-10

The feasibility of using C60(+) cluster primary ion bombardment secondary ion mass spectrometry (C60(+) SIMS) for the analysis of the chemical composition of fingerprints is evaluated. It was found that C60(+) SIMS could be used to detect and image the spatial localization of a number of sebaceous and eccrine components in fingerprints. These analyses were also found to not be hindered by the use of common latent print powder development techniques. Finally, the ability to monitor the depth distribution of fingerprint constituents was found to be possible - a capability which has not been shown using other chemical imaging techniques. This paper illustrates a number of strengths and potential weaknesses of C60(+) SIMS as an additional or complimentary technique for the chemical analysis of fingerprints. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Approximation of Confidence Limits on Sample Semivariograms From Single Realizations of Spatially Correlated Random Fields

NASA Astrophysics Data System (ADS)

Shafer, J. M.; Varljen, M. D.

1990-08-01

A fundamental requirement for geostatistical analyses of spatially correlated environmental data is the estimation of the sample semivariogram to characterize spatial correlation. Selecting an underlying theoretical semivariogram based on the sample semivariogram is an extremely important and difficult task that is subject to a great deal of uncertainty. Current standard practice does not involve consideration of the confidence associated with semivariogram estimates, largely because classical statistical theory does not provide the capability to construct confidence limits from single realizations of correlated data, and multiple realizations of environmental fields are not found in nature. The jackknife method is a nonparametric statistical technique for parameter estimation that may be used to estimate the semivariogram. When used in connection with standard confidence procedures, it allows for the calculation of closely approximate confidence limits on the semivariogram from single realizations of spatially correlated data. The accuracy and validity of this technique was verified using a Monte Carlo simulation approach which enabled confidence limits about the semivariogram estimate to be calculated from many synthetically generated realizations of a random field with a known correlation structure. The synthetically derived confidence limits were then compared to jackknife estimates from single realizations with favorable results. Finally, the methodology for applying the jackknife method to a real-world problem and an example of the utility of semivariogram confidence limits were demonstrated by constructing confidence limits on seasonal sample variograms of nitrate-nitrogen concentrations in shallow groundwater in an approximately 12-mi2 (˜30 km2) region in northern Illinois. In this application, the confidence limits on sample semivariograms from different time periods were used to evaluate the significance of temporal change in spatial correlation. This capability is quite important as it can indicate when a spatially optimized monitoring network would need to be reevaluated and thus lead to more robust monitoring strategies.

Image processing techniques revealing the relationship between the field-measured ambient gamma dose equivalent rate and geological conditions at a granitic area, Velence Mountains, Hungary

NASA Astrophysics Data System (ADS)

Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba

2017-04-01

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies

PubMed Central

2018-01-01

ABSTRACT Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. This study develops population models to depict the spatial distribution of people who have a heightened crime risk for burglaries and robberies. The data used in the study include: Census data as source data for the existing population, Twitter geo-located data, and locations of schools as ancillary data to redistribute the source data more accurately in the space, and finally gridded population and crime data to evaluate the derived population models. To create the models, a density-weighted areal interpolation technique was used that disaggregates the source data in smaller spatial units considering the spatial distribution of the ancillary data. The models were evaluated with validation data that assess the interpolation error and spatial statistics that examine their relationship with the crime types. Our approach derived population models of a finer resolution that can assist in more precise spatial crime analyses and also provide accurate information about crime rates to the public. PMID:29887766

Spatial analysis of the distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) and losses in maize crop productivity using geostatistics.

PubMed

Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M

2008-01-01

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.

Spatial-temporal and cancer risk assessment of selected hazardous air pollutants in Seattle.

PubMed

Wu, Chang-fu; Liu, L-J Sally; Cullen, Alison; Westberg, Hal; Williamson, John

2011-01-01

In the Seattle Air Toxics Monitoring Pilot Program, we measured 15 hazardous air pollutants (HAPs) at 6 sites for more than a year between 2000 and 2002. Spatial-temporal variations were evaluated with random-effects models and principal component analyses. The potential health risks were further estimated based on the monitored data, with the incorporation of the bootstrapping technique for the uncertainty analysis. It is found that the temporal variability was generally higher than the spatial variability for most air toxics. The highest temporal variability was observed for tetrachloroethylene (70% temporal vs. 34% spatial variability). Nevertheless, most air toxics still exhibited significant spatial variations, even after accounting for the temporal effects. These results suggest that it would require operating multiple air toxics monitoring sites over a significant period of time with proper monitoring frequency to better evaluate population exposure to HAPs. The median values of the estimated inhalation cancer risks ranged between 4.3 × 10⁻⁵ and 6.0 × 10⁻⁵, with the 5th and 95th percentile levels exceeding the 1 in a million level. VOCs as a whole contributed over 80% of the risk among the HAPs measured and arsenic contributed most substantially to the overall risk associated with metals. Copyright © 2010 Elsevier Ltd. All rights reserved.

Patterned-string tasks: relation between fine motor skills and visual-spatial abilities in parrots.

PubMed

Krasheninnikova, Anastasia

2013-01-01

String-pulling and patterned-string tasks are often used to analyse perceptual and cognitive abilities in animals. In addition, the paradigm can be used to test the interrelation between visual-spatial and motor performance. Two Australian parrot species, the galah (Eolophus roseicapilla) and the cockatiel (Nymphicus hollandicus), forage on the ground, but only the galah uses its feet to manipulate food. I used a set of string pulling and patterned-string tasks to test whether usage of the feet during foraging is a prerequisite for solving the vertical string pulling problem. Indeed, the two species used techniques that clearly differed in the extent of beak-foot coordination but did not differ in terms of their success in solving the string pulling task. However, when the visual-spatial skills of the subjects were tested, the galahs outperformed the cockatiels. This supports the hypothesis that the fine motor skills needed for advanced beak-foot coordination may be interrelated with certain visual-spatial abilities needed for solving patterned-string tasks. This pattern was also found within each of the two species on the individual level: higher motor abilities positively correlated with performance in patterned-string tasks. This is the first evidence of an interrelation between visual-spatial and motor abilities in non-mammalian animals.

PHOTONICS AND NANOTECHNOLOGY Laser generation of nanostructures on the surface and in the bulk of solids

NASA Astrophysics Data System (ADS)

Bityurin, N. M.

2010-12-01

This paper considers nanostructuring of solid surfaces by nano-optical techniques, primarily by laser particle nanolithography. Threshold processes are examined that can be used for laser structuring of solid surfaces, with particular attention to laser swelling of materials. Fundamental spatial resolution issues in three-dimensional (3D) laser nanostructuring are analysed with application to laser nanopolymerisation and 3D optical information recording. The formation of nanostructures in the bulk of solids due to their structural instability under irradiation is exemplified by photoinduced formation of nanocomposites.

In situ electrostatic characterisation of ion beams in the region of ion acceleration

NASA Astrophysics Data System (ADS)

Bennet, Alexander; Charles, Christine; Boswell, Rod

2018-02-01

In situ and ex situ techniques have been used to measure directional ion beams created by a sharp axial potential drop in low pressure expanding plasmas. Although Retarding Field Energy Analysers (RFEAs) are the most convenient technique to measure the ion velocities and plasma potentials along with the plasma density, they are bulky and are contained in a grounded shield that may perturb the electric potential profile of the expanding plasma. In principle, ex situ techniques produce a more reliable measurement and Laser Induced Fluorescence spectroscopy (LIF) has previously been used to characterise the spatial velocity profile of ion beams in the same region of acceleration for a range of pressures. Here, satisfactory agreement between the ion velocity profiles measured by LIF and RFEA techniques has allowed the RFEA method to be confidently used to probe the ion beam characteristics in the regions of high gradients in plasma density and DC electric fields which have previously proven difficult.

A Local to National Scale Catchment Model Simulation Framework for Hydrological Predictions and Impact Assessments Under Uncertainty

NASA Astrophysics Data System (ADS)

Freer, Jim; Coxon, Gemma; Quinn, Niall; Dunne, Toby; Lane, Rosie; Bates, Paul; Wagener, Thorsten; Woods, Ross; Neal, Jeff; Howden, Nicholas; Musuuza, Jude

2017-04-01

There is a huge challenge in developing hydrological model structures that can be used for hypothesis testing, prediction, impact assessment and risk analyses over a wide range of spatial scales. There are many reasons why this is the case, from computational demands, to how we define and characterize different features and pathway connectivities in the landscape, that differ depending on the objectives of the study. However there is certainly a need more than ever to explore the trade-offs between the complexity of modelling applied (i.e. spatial discretization, levels of process representation, complexity of landscape representation) compared to the benefits realized in terms of predictive capability and robustness of these predictions during hydrological extremes and during change. Furthermore, there is a further balance, particularly associated with prediction uncertainties, in that it is not desirable to have modelling systems that are too complex compared to the observed data that would ever be available to apply them. This is particularly the case when models are applied to quantify national impact assessments, especially if these are based on validation assessments from smaller more detailed case studies. Therefore the hydrological community needs modelling tools and approaches that enable these trade-offs to be explored and to understand the level of representation needed in models to be 'fit-for-purpose' for a given application. This paper presents a catchment scale national modelling framework based on Dynamic-TOPMODEL specifically setup to fulfil these aims. A key component of the modelling framework is it's structural flexibility, as is the ability to assess model outputs using Monte Carlo simulation techniques. The model build has been automated to work at any spatial scale to the national scale, and within that to control the level of spatial discretisation and connectivity of locally accounted landscape elements in the form of hydrological response units (HRU's). This allows for the explicit consideration of spatial rainfall fields, landscape, soils and geological attributes and the spatial connectivity of hydrological flow pathways to explore what level of modelling complexity we need for different prediction problems. We shall present this framework and show how it can be used in flood and drought risk analyses as well as include attributes and features within the landscape to explore societal and climate impacts effectively within an uncertainty analyses framework.

Graffiti for science - erosion painting reveals spatially variable erosivity of sediment-laden flows

NASA Astrophysics Data System (ADS)

Beer, Alexander R.; Kirchner, James W.; Turowski, Jens M.

2016-12-01

Spatially distributed detection of bedrock erosion is a long-standing challenge. Here we show how the spatial distribution of surface erosion can be visualized and analysed by observing the erosion of paint from natural bedrock surfaces. If the paint is evenly applied, it creates a surface with relatively uniform erodibility, such that spatial variability in the erosion of the paint reflects variations in the erosivity of the flow and its entrained sediment. In a proof-of-concept study, this approach provided direct visual verification that sediment impacts were focused on upstream-facing surfaces in a natural bedrock gorge. Further, erosion painting demonstrated strong cross-stream variations in bedrock erosion, even in the relatively narrow (5 m wide) gorge that we studied. The left side of the gorge experienced high sediment throughput with abundant lateral erosion on the painted wall up to 80 cm above the bed, but the right side of the gorge only showed a narrow erosion band 15-40 cm above the bed, likely due to deposited sediment shielding the lower part of the wall. This erosion pattern therefore reveals spatial stream bed aggradation that occurs during flood events in this channel. The erosion painting method provides a simple technique for mapping sediment impact intensities and qualitatively observing spatially distributed erosion in bedrock stream reaches. It can potentially find wide application in both laboratory and field studies.

Using Electromagnetic Induction Technique to Detect Hydropedological Dynamics: Principles and Applications

NASA Astrophysics Data System (ADS)

Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry

2014-05-01

Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.

Soil Sampling Techniques For Alabama Grain Fields

NASA Technical Reports Server (NTRS)

Thompson, A. N.; Shaw, J. N.; Mask, P. L.; Touchton, J. T.; Rickman, D.

2003-01-01

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

RECOVERY ACT: MULTIMODAL IMAGING FOR SOLAR CELL MICROCRACK DETECTION

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

Janice Hudgings; Lawrence Domash

2012-02-08

Undetected microcracks in solar cells are a principal cause of failure in service due to subsequent weather exposure, mechanical flexing or diurnal temperature cycles. Existing methods have not been able to detect cracks early enough in the production cycle to prevent inadvertent shipment to customers. This program, sponsored under the DOE Photovoltaic Supply Chain and Cross-Cutting Technologies program, studied the feasibility of quantifying surface micro-discontinuities by use of a novel technique, thermoreflectance imaging, to detect surface temperature gradients with very high spatial resolution, in combination with a suite of conventional imaging methods such as electroluminescence. The project carried out laboratorymore » tests together with computational image analyses using sample solar cells with known defects supplied by industry sources or DOE National Labs. Quantitative comparisons between the effectiveness of the new technique and conventional methods were determined in terms of the smallest detectable crack. Also the robustness of the new technique for reliable microcrack detection was determined at various stages of processing such as before and after antireflectance treatments. An overall assessment is that the new technique compares favorably with existing methods such as lock-in thermography or ultrasonics. The project was 100% completed in Sept, 2010. A detailed report of key findings from this program was published as: Q.Zhou, X.Hu, K.Al-Hemyari, K.McCarthy, L.Domash and J.Hudgings, High spatial resolution characterization of silicon solar cells using thermoreflectance imaging, J. Appl. Phys, 110, 053108 (2011).« less

Direct shear mapping - a new weak lensing tool

NASA Astrophysics Data System (ADS)

de Burgh-Day, C. O.; Taylor, E. N.; Webster, R. L.; Hopkins, A. M.

2015-08-01

We have developed a new technique called direct shear mapping (DSM) to measure gravitational lensing shear directly from observations of a single background source. The technique assumes the velocity map of an unlensed, stably rotating galaxy will be rotationally symmetric. Lensing distorts the velocity map making it asymmetric. The degree of lensing can be inferred by determining the transformation required to restore axisymmetry. This technique is in contrast to traditional weak lensing methods, which require averaging an ensemble of background galaxy ellipticity measurements, to obtain a single shear measurement. We have tested the efficacy of our fitting algorithm with a suite of systematic tests on simulated data. We demonstrate that we are in principle able to measure shears as small as 0.01. In practice, we have fitted for the shear in very low redshift (and hence unlensed) velocity maps, and have obtained null result with an error of ±0.01. This high-sensitivity results from analysing spatially resolved spectroscopic images (i.e. 3D data cubes), including not just shape information (as in traditional weak lensing measurements) but velocity information as well. Spirals and rotating ellipticals are ideal targets for this new technique. Data from any large Integral Field Unit (IFU) or radio telescope is suitable, or indeed any instrument with spatially resolved spectroscopy such as the Sydney-Australian-Astronomical Observatory Multi-Object Integral Field Spectrograph (SAMI), the Atacama Large Millimeter/submillimeter Array (ALMA), the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) and the Square Kilometer Array (SKA).

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Classification of Volcanic Eruptions on Io and Earth Using Low-Resolution Remote Sensing Data

NASA Technical Reports Server (NTRS)

Davies, A. G.; Keszthelyi, L. P.

2005-01-01

Two bodies in the Solar System exhibit high-temperature active volcanism: Earth and Io. While there are important differences in the eruptions on Earth and Io, in low-spatial-resolution data (corresponding to the bulk of available and foreseeable data of Io), similar styles of effusive and explosive volcanism yield similar thermal flux densities. For example, a square metre of an active pahoehoe flow on Io looks very similar to a square metre of an active pahoehoe flow on Earth. If, from observed thermal emission as a function of wavelength and change in thermal emission with time, the eruption style of an ionian volcano can be constrained, estimates of volumetric fluxes can be made and compared with terrestrial volcanoes using techniques derived for analysing terrestrial remotely-sensed data. In this way we find that ionian volcanoes fundamentally differ from their terrestrial counterparts only in areal extent, with Io volcanoes covering larger areas, with higher volumetric flux. Io outbursts eruptions have enormous implied volumetric fluxes, and may scale with terrestrial flood basalt eruptions. Even with the low-spatial resolution data available it is possible to sometimes constrain and classify eruption style both on Io and Earth from the integrated thermal emission spectrum. Plotting 2 and 5 m fluxes reveals the evolution of individual eruptions of different styles, as well as the relative intensity of eruptions, allowing comparison to be made from individual eruptions on both planets. Analyses like this can be used for interpretation of low-resolution data until the next mission to the jovian system. For a number of Io volcanoes (including Pele, Prometheus, Amirani, Zamama, Culann, Tohil and Tvashtar) we do have high/moderate resolution imagery to aid determination of eruption mode from analyses based only on low spatial-resolution data.

Preserving subject variability in group fMRI analysis: performance evaluation of GICA vs. IVA

PubMed Central

Michael, Andrew M.; Anderson, Mathew; Miller, Robyn L.; Adalı, Tülay; Calhoun, Vince D.

2014-01-01

Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent interest in resting state fMRI data with potentially higher degree of subject variability makes the evaluation of the above techniques important. In this paper we compare component estimation accuracies of GICA and an improved version of IVA using simulated fMRI datasets. We systematically change the degree of inter-subject spatial variability of components and evaluate estimation accuracy over all spatial maps (SMs) and time courses (TCs) of the decomposition. Our results indicate the following: (1) at low levels of SM variability or when just one SM is varied, both GICA and IVA perform well, (2) at higher levels of SM variability or when more than one SMs are varied, IVA continues to perform well but GICA yields SM estimates that are composites of other SMs with errors in TCs, (3) both GICA and IVA remove spatial correlations of overlapping SMs and introduce artificial correlations in their TCs, (4) if number of SMs is over estimated, IVA continues to perform well but GICA introduces artifacts in the varying and extra SMs with artificial correlations in the TCs of extra components, and (5) in the absence or presence of SMs unique to one subject, GICA produces errors in TCs and IVA estimates are accurate. In summary, our simulation experiments (both simplistic and realistic) and our holistic analyses approach indicate that IVA produces results that are closer to ground truth and thereby better preserves subject variability. The improved version of IVA is now packaged into the GIFT toolbox (http://mialab.mrn.org/software/gift). PMID:25018704

Evidence for localised HIV related micro-epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio-temporal analysis of changing mortality patterns (2007-2010).

PubMed

Mee, Paul; Collinson, Mark A; Madhavan, Sangeetha; Root, Elisabeth Dowling; Tollman, Stephen M; Byass, Peter; Kahn, Kathleen

2014-06-01

In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north-eastern South Africa. Previous studies have identified localised concentrated HIV related sub-epidemics and recommended that micro-level analyses be carried out in order to direct focused interventions. Data from an ongoing health and socio-demographic surveillance study was used in the analysis. The follow-up was divided into two periods, 2007-2008 and 2009-2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause-specific mortality hotspots. Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV-related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period. This study shows the value of conducting high resolution spatial analyses in order to understand how local micro-epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions.

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

PubMed

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

2004-11-01

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

Spatial pattern and temporal trend of mortality due to tuberculosis 10

PubMed Central

de Queiroz, Ana Angélica Rêgo; Berra, Thaís Zamboni; Garcia, Maria Concebida da Cunha; Popolin, Marcela Paschoal; Belchior, Aylana de Souza; Yamamura, Mellina; dos Santos, Danielle Talita; Arroyo, Luiz Henrique; Arcêncio, Ricardo Alexandre

2018-01-01

ABSTRACT Objectives: To describe the epidemiological profile of mortality due to tuberculosis (TB), to analyze the spatial pattern of these deaths and to investigate the temporal trend in mortality due to tuberculosis in Northeast Brazil. Methods: An ecological study based on secondary mortality data. Deaths due to TB were included in the study. Descriptive statistics were calculated and gross mortality rates were estimated and smoothed by the Local Empirical Bayesian Method. Prais-Winsten’s regression was used to analyze the temporal trend in the TB mortality coefficients. The Kernel density technique was used to analyze the spatial distribution of TB mortality. Results: Tuberculosis was implicated in 236 deaths. The burden of tuberculosis deaths was higher amongst males, single people and people of mixed ethnicity, and the mean age at death was 51 years. TB deaths were clustered in the East, West and North health districts, and the tuberculosis mortality coefficient remained stable throughout the study period. Conclusions: Analyses of the spatial pattern and temporal trend in mortality revealed that certain areas have higher TB mortality rates, and should therefore be prioritized in public health interventions targeting the disease. PMID:29742272

Monitoring Building Deformation with InSAR: Experiments and Validation.

PubMed

Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

2016-12-20

Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

Comparison of different spatial transformations applied to EEG data: A case study of error processing.

PubMed

Cohen, Michael X

2015-09-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.

Improved spatial resolution in PET scanners using sampling techniques

PubMed Central

Surti, Suleman; Scheuermann, Ryan; Werner, Matthew E.; Karp, Joel S.

2009-01-01

Increased focus towards improved detector spatial resolution in PET has led to the use of smaller crystals in some form of light sharing detector design. In this work we evaluate two sampling techniques that can be applied during calibrations for pixelated detector designs in order to improve the reconstructed spatial resolution. The inter-crystal positioning technique utilizes sub-sampling in the crystal flood map to better sample the Compton scatter events in the detector. The Compton scatter rejection technique, on the other hand, rejects those events that are located further from individual crystal centers in the flood map. We performed Monte Carlo simulations followed by measurements on two whole-body scanners for point source data. The simulations and measurements were performed for scanners using scintillators with Zeff ranging from 46.9 to 63 for LaBr3 and LYSO, respectively. Our results show that near the center of the scanner, inter-crystal positioning technique leads to a gain of about 0.5-mm in reconstructed spatial resolution (FWHM) for both scanner designs. In a small animal LYSO scanner the resolution improves from 1.9-mm to 1.6-mm with the inter-crystal technique. The Compton scatter rejection technique shows higher gains in spatial resolution but at the cost of reduction in scanner sensitivity. The inter-crystal positioning technique represents a modest acquisition software modification for an improvement in spatial resolution, but at a cost of potentially longer data correction and reconstruction times. The Compton scatter rejection technique, while also requiring a modest acquisition software change with no increased data correction and reconstruction times, will be useful in applications where the scanner sensitivity is very high and larger improvements in spatial resolution are desirable. PMID:19779586

Moving microphone arrays to reduce spatial aliasing in the beamforming technique: theoretical background and numerical investigation.

PubMed

Cigada, Alfredo; Lurati, Massimiliano; Ripamonti, Francesco; Vanali, Marcello

2008-12-01

This paper introduces a measurement technique aimed at reducing or possibly eliminating the spatial aliasing problem in the beamforming technique. Beamforming main disadvantages are a poor spatial resolution, at low frequency, and the spatial aliasing problem, at higher frequency, leading to the identification of false sources. The idea is to move the microphone array during the measurement operation. In this paper, the proposed approach is theoretically and numerically investigated by means of simple sound propagation models, proving its efficiency in reducing the spatial aliasing. A number of different array configurations are numerically investigated together with the most important parameters governing this measurement technique. A set of numerical results concerning the case of a planar rotating array is shown, together with a first experimental validation of the method.

The Variable Grid Method, an Approach for the Simultaneous Visualization and Assessment of Spatial Trends and Uncertainty

NASA Astrophysics Data System (ADS)

Rose, K.; Glosser, D.; Bauer, J. R.; Barkhurst, A.

2015-12-01

The products of spatial analyses that leverage the interpolation of sparse, point data to represent continuous phenomena are often presented without clear explanations of the uncertainty associated with the interpolated values. As a result, there is frequently insufficient information provided to effectively support advanced computational analyses and individual research and policy decisions utilizing these results. This highlights the need for a reliable approach capable of quantitatively producing and communicating spatial data analyses and their inherent uncertainties for a broad range of uses. To address this need, we have developed the Variable Grid Method (VGM), and associated Python tool, which is a flexible approach that can be applied to a variety of analyses and use case scenarios where users need a method to effectively study, evaluate, and analyze spatial trends and patterns while communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations, etc. We will present examples of our research utilizing the VGM to quantify key spatial trends and patterns for subsurface data interpolations and their uncertainties and leverage these results to evaluate storage estimates and potential impacts associated with underground injection for CO2 storage and unconventional resource production and development. The insights provided by these examples identify how the VGM can provide critical information about the relationship between uncertainty and spatial data that is necessary to better support their use in advance computation analyses and informing research, management and policy decisions.

Catalysts at work: From integral to spatially resolved X-ray absorption spectroscopy

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

Grunwaldt, Jan-Dierk; Kimmerle, Bertram; Baiker, Alfons

2009-09-25

Spectroscopic studies on heterogeneous catalysts have mostly been done in an integral mode. However, in many cases spatial variations in catalyst structure can occur, e.g. during impregnation of pre-shaped particles, during reaction in a catalytic reactor, or in microstructured reactors as the present overview shows. Therefore, spatially resolved molecular information on a microscale is required for a comprehensive understanding of theses systems, partly in ex situ studies, partly under stationary reaction conditions and in some cases even under dynamic reaction conditions. Among the different available techniques, X-ray absorption spectroscopy (XAS) is a well-suited tool for this purpose as the differentmore » selected examples highlight. Two different techniques, scanning and full-field X-ray microscopy/tomography, are described and compared. At first, the tomographic structure of impregnated alumina pellets is presented using full-field transmission microtomography and compared to the results obtained with a scanning X-ray microbeam technique to analyse the catalyst bed inside a catalytic quartz glass reactor. On the other hand, by using XAS in scanning microtomography, the structure and the distribution of Cu(0), Cu(I), Cu(II) species in a Cu/ZnO catalyst loaded in a quartz capillary microreactor could be reconstructed quantitatively on a virtual section through the reactor. An illustrating example for spatially resolved XAS under reaction conditions is the partial oxidation of methane over noble metal-based catalysts. In order to obtain spectroscopic information on the spatial variation of the oxidation state of the catalyst inside the reactor XAS spectra were recorded by scanning with a micro-focussed beam along the catalyst bed. Alternatively, full-field transmission imaging was used to efficiently determine the distribution of the oxidation state of a catalyst inside a reactor under reaction conditions. The new technical approaches together with quantitative data analysis and an appropriate in situ catalytic experiment allowed drawing important conclusions on the reaction mechanism, and the analytical strategy might be similarly applied in other case studies. The corresponding temperature profiles and the catalytic performance were measured by means of an IR-camera and mass spectrometric analysis. In a more advanced experiment the ignition process of the partial oxidation of methane was followed in a spatiotemporal manner which demonstrates that spatially resolved spectroscopic information can even be obtained in the subsecond scale.« less

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

PubMed Central

Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

Geostatistics: a new tool for describing spatially-varied surface conditions from timber harvested and burned hillslopes

Treesearch

Peter R. Robichaud

1997-01-01

Geostatistics provides a method to describe the spatial continuity of many natural phenomena. Spatial models are based upon the concept of scaling, kriging and conditional simulation. These techniques were used to describe the spatially-varied surface conditions on timber harvest and burned hillslopes. Geostatistical techniques provided estimates of the ground cover (...

3D/4D analyses of damage and fracture behaviours in structural materials via synchrotron X-ray tomography.

PubMed

Toda, Hiroyuki

2014-11-01

X-ray microtomography has been utilized for the in-situ observation of various structural metals under external loading. Recent advances in X-ray microtomography provide remarkable tools to image the interior of materials. In-situ X-ray microtomography provides a unique possibility to access the 3D character of internal microstructure and its time evolution behaviours non-destructively, thereby enabling advanced techniques for measuring local strain distribution. Local strain mapping is readily enabled by processing such high-resolution tomographic images either by the particle tracking technique or the digital image correlation technique [1]. Procedures for tracking microstructural features which have been developed by the authors [2], have been applied to analyse localised deformation and damage evolution in a material [3]. Typically several tens of thousands of microstructural features, such as particles and pores, are tracked in a tomographic specimen (0.2 - 0.3 mm(3) in volume). When a sufficient number of microstructural features is dispersed in 3D space, the Delaunay tessellation algorithm is used to obtain local strain distribution. With these techniques, 3D strain fields can be measured with reasonable accuracy. Even local crack driving forces, such as local variations in the stress intensity factor, crack tip opening displacement and J integral along a crack front line, can be measured from discrete crack tip displacement fields [4]. In the present presentation, complicated crack initiation and growth behaviour and the extensive formation of micro cracks ahead of a crack tip are introduced as examples.A novel experimental method has recently been developed by amalgamating a pencil beam X-Ray diffraction (XRD) technique with the microstructural tracking technique [5]. The technique provides information about individual grain orientations and 1-micron-level grain morphologies in 3D together with high-density local strain mapping. The application of this technique to the deformation behavior of a polycrystalline aluminium alloy will be demonstrated in the presentation [6].The synchrotron-based microtomography has been mainly utilized to light materials due to their good X-ray transmission. In the present talk, the application of the synchrotron-based microtomography to steels will be also introduced. Degradation of contrast and spatial resolution due to forward scattering could be avoided by selecting appropriate experimental conditions in order to obtain superior spatial resolution close to the physical limit even in ferrous materials [7]. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

NASA Technical Reports Server (NTRS)

Browder, J. A. (Principal Investigator); Rosenthal, A.; May, L. N., Jr.; Bauman, R. H.; Gosselink, J. G.

1985-01-01

The purpose of the project is to refine and validate a probabilistic spatial computer model through the analyses of thematic mapper imagery. The model is designed to determine how the interface between marshland and water changes as marshland is converted to water in a disintegrating marsh. Coastal marshland in Louisiana is disintegrating at the rate of approximately 40 sq mi a year, and an evaluation of the potential impact of this loss on the landings of estuarine-dependent fisheries is needed by fisheries managers. Understanding how marshland-water interface changes as coastal marshland is lost is essential to the process of evaluating fisheries effects, because several studies suggest that the production of estuarine-dependent fish and shellfish may be more closely related to the interface between marshland and water than to acreage of marshland. The need to address this practical problem has provided an opportunity to apply some scientifically interesting new techniques to the analyses of satellite imagery. Progress with the development of these techniques is the subject of this report.

Modeling of Aerosol Optical Depth Variability during the 1998 Canadian Forest Fire Smoke Event

NASA Astrophysics Data System (ADS)

Aubé, M.; O`Neill, N. T.; Royer, A.; Lavoué, D.

2003-04-01

Monitoring of aerosol optical depth (AOD) is of particular importance due to the significant role of aerosols in the atmospheric radiative budget. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as based DDV (Dense Dark Vegetation) inversion algorithms which extract AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new methodology that links AOD measurements and particulate matter Transport Model using a data assimilation approach. This modelling package (AODSEM for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian-Eulerian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution is tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important but crude parameter. We applied this methodology to a significant smoke event that occurred over Canada in august 1998. The results show the potential of this approach inasmuch as residuals between AODSEM assimilated analysis and measurements are smaller than typical errors associated to remotely sensed AOD (satellite or ground based). The AODSEM assimilation approach also gives better results than classical interpolation techniques. This improvement is especially evident when the available number of AOD measurements is small.

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

NASA Astrophysics Data System (ADS)

Digman, Michelle

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

3D shape representation with spatial probabilistic distribution of intrinsic shape keypoints

NASA Astrophysics Data System (ADS)

Ghorpade, Vijaya K.; Checchin, Paul; Malaterre, Laurent; Trassoudaine, Laurent

2017-12-01

The accelerated advancement in modeling, digitizing, and visualizing techniques for 3D shapes has led to an increasing amount of 3D models creation and usage, thanks to the 3D sensors which are readily available and easy to utilize. As a result, determining the similarity between 3D shapes has become consequential and is a fundamental task in shape-based recognition, retrieval, clustering, and classification. Several decades of research in Content-Based Information Retrieval (CBIR) has resulted in diverse techniques for 2D and 3D shape or object classification/retrieval and many benchmark data sets. In this article, a novel technique for 3D shape representation and object classification has been proposed based on analyses of spatial, geometric distributions of 3D keypoints. These distributions capture the intrinsic geometric structure of 3D objects. The result of the approach is a probability distribution function (PDF) produced from spatial disposition of 3D keypoints, keypoints which are stable on object surface and invariant to pose changes. Each class/instance of an object can be uniquely represented by a PDF. This shape representation is robust yet with a simple idea, easy to implement but fast enough to compute. Both Euclidean and topological space on object's surface are considered to build the PDFs. Topology-based geodesic distances between keypoints exploit the non-planar surface properties of the object. The performance of the novel shape signature is tested with object classification accuracy. The classification efficacy of the new shape analysis method is evaluated on a new dataset acquired with a Time-of-Flight camera, and also, a comparative evaluation on a standard benchmark dataset with state-of-the-art methods is performed. Experimental results demonstrate superior classification performance of the new approach on RGB-D dataset and depth data.

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

PubMed

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

2018-04-01

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

Substrate-Mediated Laser Ablation under Ambient Conditions for Spatially-Resolved Tissue Proteomics

PubMed Central

Fatou, Benoit; Wisztorski, Maxence; Focsa, Cristian; Salzet, Michel; Ziskind, Michael; Fournier, Isabelle

2015-01-01

Numerous applications of ambient Mass Spectrometry (MS) have been demonstrated over the past decade. They promoted the emergence of various micro-sampling techniques such as Laser Ablation/Droplet Capture (LADC). LADC consists in the ablation of analytes from a surface and their subsequent capture in a solvent droplet which can then be analyzed by MS. LADC is thus generally performed in the UV or IR range, using a wavelength at which analytes or the matrix absorb. In this work, we explore the potential of visible range LADC (532 nm) as a micro-sampling technology for large-scale proteomics analyses. We demonstrate that biomolecule analyses using 532 nm LADC are possible, despite the low absorbance of biomolecules at this wavelength. This is due to the preponderance of an indirect substrate-mediated ablation mechanism at low laser energy which contrasts with the conventional direct ablation driven by sample absorption. Using our custom LADC system and taking advantage of this substrate-mediated ablation mechanism, we were able to perform large-scale proteomic analyses of micro-sampled tissue sections and demonstrated the possible identification of proteins with relevant biological functions. Consequently, the 532 nm LADC technique offers a new tool for biological and clinical applications. PMID:26674367

Micro-CT analyses of apical enlargement and molar root canal complexity.

PubMed

Markvart, M; Darvann, T A; Larsen, P; Dalstra, M; Kreiborg, S; Bjørndal, L

2012-03-01

To compare the effectiveness of two rotary hybrid instrumentation techniques with focus on apical enlargement in molar teeth and to quantify and visualize spatial details of instrumentation efficacy in root canals of different complexity. Maxillary and mandibular molar teeth were scanned using X-ray microcomputed tomography. Root canals were prepared using either a GT/Profile protocol or a RaCe/NiTi protocol. Variables used for evaluation were the following: distance between root canal surfaces before and after preparation (distance after preparation, DAP), percentage of root canal area remaining unprepared and increase in canal volume after preparation. Root canals were classified according to size and complexity, and consequences of unprepared portions of narrow root canals and intraradicular connections/isthmuses were included in the analyses. One- and two-way anova were used in the statistical analyses. No difference was found between the two techniques: DAP(apical-third) (P = 0.590), area unprepared(apical-third) (P = 0.126) and volume increase(apical-third) (P = 0.821). Unprepared root canal area became larger in relation to root canal size and complexity, irrespective of the technique used. Percentage of root canal area remaining unprepared was significantly lower in small root canals and complex systems compared to large root canals. The isthmus area per se contributed with a mean of 17.6%, and with a mean of 25.7%, when a narrow root canal remained unprepared. The addition of isthmuses did not significantly alter the ratio of instrumented to unprepared areas at total root canal level. Distal and palatal root canals had the highest level of unprepared area irrespective of the two instrumentation techniques examined. © 2011 International Endodontic Journal.

A Dialogue on Space and Method in Qualitative Research on Education

ERIC Educational Resources Information Center

Gildersleeve, Ryan Evely; Kuntz, Aaron M.

2011-01-01

In this article, the authors critically examine the use of space in education research and illustrate how spatial analyses of education reframe persistent educational problems in productive, actionable ways. The authors juxtapose critical spatial analyses with traditional temporal analyses. The authors approach the knowledge-construction process…

How does modifying a DEM to reflect known hydrology affect subsequent terrain analysis?

NASA Astrophysics Data System (ADS)

Callow, John Nikolaus; Van Niel, Kimberly P.; Boggs, Guy S.

2007-01-01

SummaryMany digital elevation models (DEMs) have difficulty replicating hydrological patterns in flat landscapes. Efforts to improve DEM performance in replicating known hydrology have included a variety of soft (i.e. algorithm-based approaches) and hard techniques, such as " Stream burning" or "surface reconditioning" (e.g. Agree or ANUDEM). Using a representation of the known stream network, these methods trench or mathematically warp the original DEM to improve how accurately stream position, stream length and catchment boundaries replicate known hydrological conditions. However, these techniques permanently alter the DEM and may affect further analyses (e.g. slope). This paper explores the impact that commonly used hydrological correction methods ( Stream burning, Agree.aml and ANUDEM v4.6.3 and ANUDEM v5.1) have on the overall nature of a DEM, finding that different methods produce non-convergent outcomes for catchment parameters (such as catchment boundaries, stream position and length), and differentially compromise secondary terrain analysis. All hydrological correction methods successfully improved calculation of catchment area, stream position and length as compared to using the DEM without any modification, but they all increased catchment slope. No single method performing best across all categories. Different hydrological correction methods changed elevation and slope in different spatial patterns and magnitudes, compromising the ability to derive catchment parameters and conduct secondary terrain analysis from a single DEM. Modification of a DEM to better reflect known hydrology can be useful, however knowledge of the magnitude and spatial pattern of the changes are required before using a DEM for subsequent analyses.

Spatial Distribution of Trehalose Dihydrate Crystallization in Tablets by X-ray Diffractometry.

PubMed

Thakral, Naveen K; Yamada, Hiroyuki; Stephenson, Gregory A; Suryanarayanan, Raj

2015-10-05

Crystallization of trehalose dihydrate (C12H22O11·2H2O) was induced by storing tablets of amorphous anhydrous trehalose (C12H22O11) at 65% RH (RT). Our goal was to evaluate the advantages and limitations of two approaches of profiling spatial distribution of drug crystallization in tablets. The extent of crystallization, as a function of depth, was determined in tablets stored for different time-periods. The first approach was glancing angle X-ray diffractometry, where the penetration depth of X-rays was modulated by the incident angle. Based on the mass attenuation coefficient of the matrix, the depth of X-ray penetration was calculated as a function of incident angle, which in turn enabled us to "calculate" the extent of crystallization to different depths. In the second approach, the tablets were split into halves and the split surfaces were analyzed directly. Starting from the tablet surface and moving toward the midplane, XRD patterns were collected in 36 "regions", in increments of 0.05 mm. The results obtained by the two approaches were, in general, in good agreement. Additionally, the results obtained were validated by determining the "average" crystallization in the entire tablet by using synchrotron radiation in the transmission mode. The glancing angle method could detect crystallization up to ∼650 μm and had a "surface bias". Being a nondestructive technique, this method will permit repeated analyses of the same tablet at different time points, for example, during a stability study. However, split tablet analyses, while a "destructive" technique, provided comprehensive and unbiased depth profiling information.

Analysis strategies for high-resolution UHF-fMRI data.

PubMed

Polimeni, Jonathan R; Renvall, Ville; Zaretskaya, Natalia; Fischl, Bruce

2018-03-01

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential. Copyright © 2017 Elsevier Inc. All rights reserved.

Biogenicity and Syngeneity of Organic Matter in Ancient Sedimentary Rocks: Recent Advances in the Search for Evidence of Past Life

NASA Astrophysics Data System (ADS)

Oehler, Dorothy Z.; Cady, Sherry L.

2014-08-01

The past decade has seen an explosion of new technologies for assessment of biogenicity and syngeneity of carbonaceous material within sedimentary rocks. Advances have been made in techniques for analysis of in situ organic matter as well as for extracted bulk samples of soluble and insoluble (kerogen) organic fractions. The in situ techniques allow analysis of micrometer-to-sub-micrometer-scale organic residues within their host rocks and include Raman and fluorescence spectroscopy/imagery, confocal laser scanning microscopy, and forms of secondary ion/laser-based mass spectrometry, analytical transmission electron microscopy, and X-ray absorption microscopy/spectroscopy. Analyses can be made for chemical, molecular, and isotopic composition coupled with assessment of spatial relationships to surrounding minerals, veins, and fractures. The bulk analyses include improved methods for minimizing contamination and recognizing syngenetic constituents of soluble organic fractions as well as enhanced spectroscopic and pyrolytic techniques for unlocking syngenetic molecular signatures in kerogen. Together, these technologies provide vital tools for the study of some of the oldest and problematic carbonaceous residues and for advancing our understanding of the earliest stages of biological evolution on Earth and the search for evidence of life beyond Earth. We discuss each of these new technologies, emphasizing their advantages and disadvantages, applications, and likely future directions.

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Possibilities of LA-ICP-MS technique for the spatial elemental analysis of the recent fish scales: Line scan vs. depth profiling

NASA Astrophysics Data System (ADS)

Holá, Markéta; Kalvoda, Jiří; Nováková, Hana; Škoda, Radek; Kanický, Viktor

2011-01-01

LA-ICP-MS and solution based ICP-MS in combination with electron microprobe are presented as a method for the determination of the elemental spatial distribution in fish scales which represent an example of a heterogeneous layered bone structure. Two different LA-ICP-MS techniques were tested on recent common carp ( Cyprinus carpio) scales: A line scan through the whole fish scale perpendicular to the growth rings. The ablation crater of 55 μm width and 50 μm depth allowed analysis of the elemental distribution in the external layer. Suitable ablation conditions providing a deeper ablation crater gave average values from the external HAP layer and the collagen basal plate. Depth profiling using spot analysis was tested in fish scales for the first time. Spot analysis allows information to be obtained about the depth profile of the elements at the selected position on the sample. The combination of all mentioned laser ablation techniques provides complete information about the elemental distribution in the fish scale samples. The results were compared with the solution based ICP-MS and EMP analyses. The fact that the results of depth profiling are in a good agreement both with EMP and PIXE results and, with the assumed ways of incorporation of the studied elements in the HAP structure, suggests a very good potential for this method.

Geographic profiling applied to testing models of bumble-bee foraging.

PubMed

Raine, Nigel E; Rossmo, D Kim; Le Comber, Steven C

2009-03-06

Geographic profiling (GP) was originally developed as a statistical tool to help police forces prioritize lists of suspects in investigations of serial crimes. GP uses the location of related crime sites to make inferences about where the offender is most likely to live, and has been extremely successful in criminology. Here, we show how GP is applicable to experimental studies of animal foraging, using the bumble-bee Bombus terrestris. GP techniques enable us to simplify complex patterns of spatial data down to a small number of parameters (2-3) for rigorous hypothesis testing. Combining computer model simulations and experimental observation of foraging bumble-bees, we demonstrate that GP can be used to discriminate between foraging patterns resulting from (i) different hypothetical foraging algorithms and (ii) different food item (flower) densities. We also demonstrate that combining experimental and simulated data can be used to elucidate animal foraging strategies: specifically that the foraging patterns of real bumble-bees can be reliably discriminated from three out of nine hypothetical foraging algorithms. We suggest that experimental systems, like foraging bees, could be used to test and refine GP model predictions, and that GP offers a useful technique to analyse spatial animal behaviour data in both the laboratory and field.

Nanoscale Chemical Imaging of Zeolites Using Atom Probe Tomography.

PubMed

Weckhuysen, Bert Marc; Schmidt, Joel; Peng, Linqing; Poplawsky, Jonathan

2018-05-02

Understanding structure-composition-property relationships in zeolite-based materials is critical to engineering improved solid catalysts. However, this can be difficult to realize as even single zeolite crystals can exhibit heterogeneities spanning several orders of magnitude, with consequences for e.g. reactivity, diffusion as well as stability. Great progress has been made in characterizing these porous solids using tomographic techniques, though each method has an ultimate spatial resolution limitation. Atom Probe Tomography (APT) is the only technique so far capable of producing 3-D compositional reconstructions with sub-nm-scale resolution, and has only recently been applied to zeolite-based catalysts. Herein, we discuss the use of APT to study zeolites, including the critical aspects of sample preparation, data collection, assignment of mass spectral peaks including the predominant CO peak, the limitations of spatial resolution for the recovery of crystallographic information, and proper data analysis. All sections are illustrated with examples from recent literature, as well as previously unpublished data and analyses to demonstrate practical strategies to overcome potential pitfalls in applying APT to zeolites, thereby highlighting new insights gained from the APT method. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Innovating Big Data Computing Geoprocessing for Analysis of Engineered-Natural Systems

NASA Astrophysics Data System (ADS)

Rose, K.; Baker, V.; Bauer, J. R.; Vasylkivska, V.

2016-12-01

Big data computing and analytical techniques offer opportunities to improve predictions about subsurface systems while quantifying and characterizing associated uncertainties from these analyses. Spatial analysis, big data and otherwise, of subsurface natural and engineered systems are based on variable resolution, discontinuous, and often point-driven data to represent continuous phenomena. We will present examples from two spatio-temporal methods that have been adapted for use with big datasets and big data geo-processing capabilities. The first approach uses regional earthquake data to evaluate spatio-temporal trends associated with natural and induced seismicity. The second algorithm, the Variable Grid Method (VGM), is a flexible approach that presents spatial trends and patterns, such as those resulting from interpolation methods, while simultaneously visualizing and quantifying uncertainty in the underlying spatial datasets. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analyses to efficiently consume and utilize large geospatial data in these custom analytical algorithms through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom `Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations.

Exploring biological, chemical and geomorphological patterns in fluvial ecosystems with Structural Equation Modelling

NASA Astrophysics Data System (ADS)

Bizzi, S.; Surridge, B.; Lerner, D. N.:

2009-04-01

River ecosystems represent complex networks of interacting biological, chemical and geomorphological processes. These processes generate spatial and temporal patterns in biological, chemical and geomorphological variables, and a growing number of these variables are now being used to characterise the status of rivers. However, integrated analyses of these biological-chemical-geomorphological networks have rarely been undertaken, and as a result our knowledge of the underlying processes and how they generate the resulting patterns remains weak. The apparent complexity of the networks involved, and the lack of coherent datasets, represent two key challenges to such analyses. In this paper we describe the application of a novel technique, Structural Equation Modelling (SEM), to the investigation of biological, chemical and geomorphological data collected from rivers across England and Wales. The SEM approach is a multivariate statistical technique enabling simultaneous examination of direct and indirect relationships across a network of variables. Further, SEM allows a-priori conceptual or theoretical models to be tested against available data. This is a significant departure from the solely exploratory analyses which characterise other multivariate techniques. We took biological, chemical and river habitat survey data collected by the Environment Agency for 400 sites in rivers spread across England and Wales, and created a single, coherent dataset suitable for SEM analyses. Biological data cover benthic macroinvertebrates, chemical data relate to a range of standard parameters (e.g. BOD, dissolved oxygen and phosphate concentration), and geomorphological data cover factors such as river typology, substrate material and degree of physical modification. We developed a number of a-priori conceptual models, reflecting current research questions or existing knowledge, and tested the ability of these conceptual models to explain the variance and covariance within the dataset. The conceptual models we developed were able to explain correctly the variance and covariance shown by the datasets, proving to be a relevant representation of the processes involved. The models explained 65% of the variance in indices describing benthic macroinvertebrate communities. Dissolved oxygen was of primary importance, but geomorphological factors, including river habitat type and degree of habitat degradation, also had significant explanatory power. The addition of spatial variables, such as latitude or longitude, did not provide additional explanatory power. This suggests that the variables already included in the models effectively represented the eco-regions across which our data were distributed. The models produced new insights into the relative importance of chemical and geomorphological factors for river macroinvertebrate communities. The SEM technique proved a powerful tool for exploring complex biological-chemical-geomorphological networks, for example able to deal with the co-correlations that are common in rivers due to multiple feedback mechanisms.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana.

PubMed

Kumi-Kyereme, Akwasi; Amo-Adjei, Joshua

2013-06-17

This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable.

Identifying residential neighbourhood types from settlement points in a machine learning approach.

PubMed

Jochem, Warren C; Bird, Tomas J; Tatem, Andrew J

2018-05-01

Remote sensing techniques are now commonly applied to map and monitor urban land uses to measure growth and to assist with development and planning. Recent work in this area has highlighted the use of textures and other spatial features that can be measured in very high spatial resolution imagery. Far less attention has been given to using geospatial vector data (i.e. points, lines, polygons) to map land uses. This paper presents an approach to distinguish residential settlement types (regular vs. irregular) using an existing database of settlement points locating structures. Nine data features describing the density, distance, angles, and spacing of the settlement points are calculated at multiple spatial scales. These data are analysed alone and with five common remote sensing measures on elevation, slope, vegetation, and nighttime lights in a supervised machine learning approach to classify land use areas. The method was tested in seven provinces of Afghanistan (Balkh, Helmand, Herat, Kabul, Kandahar, Kunduz, Nangarhar). Overall accuracy ranged from 78% in Kandahar to 90% in Nangarhar. This research demonstrates the potential to accurately map land uses from even the simplest representation of structures.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana

PubMed Central

2013-01-01

Background This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. Methods The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. Results By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. Conclusions The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable. PMID:23768255

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Driving magnetic turbulence using flux ropes in a moderate guide field linear system

NASA Astrophysics Data System (ADS)

Brookhart, Matthew I.; Stemo, Aaron; Waleffe, Roger; Forest, Cary B.

2017-12-01

We present a series of experiments on novel, line-tied plasma geometries as a study of the generation of chaos and turbulence in line-tied systems. Plasma production and the injection scale for magnetic energy is provided by spatially discrete plasma guns that inject both plasma and current. The guns represent a technique for controlling the injection scale of magnetic energy. A two-dimensional (2-D) array of magnetic probes provides spatially resolved time histories of the magnetic fluctuations at a single cross-section of the experimental cylinder, allowing simultaneous spatial measurements of chaotic and turbulent behaviour. The first experiment shows chaotic fluctuations and self-organization in a hollow-current line-tied screw pinch. These dynamics is modulated primarily by the applied magnetic field and weakly by the plasma current and safety factor. The second experiment analyses the interactions of multiple line-tied flux ropes. The flux ropes all exhibit chaotic behaviour, and under certain conditions develop an inverse cascade to larger scales and a turbulent inertial range with magnetic energy ( ) related to perpendicular wave number ( \\bot $ ) as \\bot -2.5\\pm 0.5$ .

Geographic analysis of road accident severity index in Nigeria.

PubMed

Iyanda, Ayodeji E

2018-05-28

Before 2030, deaths from road traffic accidents (RTAs) will surpass cerebrovascular disease, tuberculosis, and HIV/AIDS. Yet, there is little knowledge on the geographic distribution of RTA severity in Nigeria. Accident Severity Index is the proportion of deaths that result from a road accident. This study analysed the geographic pattern of RTA severity based on the data retrieved from Federal Road Safety Corps (FRSC). The study predicted a two-year data from a historic road accident data using exponential smoothing technique. To determine spatial autocorrelation, global and local indicators of spatial association were implemented in a geographic information system. Results show significant clusters of high RTA severity among states in the northeast and the northwest of Nigeria. Hence, the findings are discussed from two perspectives: Road traffic law compliance and poor emergency response. Conclusion, the severity of RTA is high in the northern states of Nigeria, hence, RTA remains a public health concern.

Geostatistics and GIS: tools for characterizing environmental contamination.

PubMed

Henshaw, Shannon L; Curriero, Frank C; Shields, Timothy M; Glass, Gregory E; Strickland, Paul T; Breysse, Patrick N

2004-08-01

Geostatistics is a set of statistical techniques used in the analysis of georeferenced data that can be applied to environmental contamination and remediation studies. In this study, the 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) contamination at a Superfund site in western Maryland is evaluated. Concern about the site and its future clean up has triggered interest within the community because residential development surrounds the area. Spatial statistical methods, of which geostatistics is a subset, are becoming increasingly popular, in part due to the availability of geographic information system (GIS) software in a variety of application packages. In this article, the joint use of ArcGIS software and the R statistical computing environment are demonstrated as an approach for comprehensive geostatistical analyses. The spatial regression method, kriging, is used to provide predictions of DDE levels at unsampled locations both within the site and the surrounding areas where residential development is ongoing.

Building the 3D Geological Model of Wall Rock of Salt Caverns Based on Integration Method of Multi-source data

NASA Astrophysics Data System (ADS)

Yongzhi, WANG; hui, WANG; Lixia, LIAO; Dongsen, LI

2017-02-01

In order to analyse the geological characteristics of salt rock and stability of salt caverns, rough three-dimensional (3D) models of salt rock stratum and the 3D models of salt caverns on study areas are built by 3D GIS spatial modeling technique. During implementing, multi-source data, such as basic geographic data, DEM, geological plane map, geological section map, engineering geological data, and sonar data are used. In this study, the 3D spatial analyzing and calculation methods, such as 3D GIS intersection detection method in three-dimensional space, Boolean operations between three-dimensional space entities, three-dimensional space grid discretization, are used to build 3D models on wall rock of salt caverns. Our methods can provide effective calculation models for numerical simulation and analysis of the creep characteristics of wall rock in salt caverns.

Verification of spatial and temporal pressure distributions in segmented solid rocket motors

NASA Technical Reports Server (NTRS)

Salita, Mark

1989-01-01

A wide variety of analytical tools are in use today to predict the history and spatial distributions of pressure in the combustion chambers of solid rocket motors (SRMs). Experimental and analytical methods are presented here that allow the verification of many of these predictions. These methods are applied to the redesigned space shuttle booster (RSRM). Girth strain-gage data is compared to the predictions of various one-dimensional quasisteady analyses in order to verify the axial drop in motor static pressure during ignition transients as well as quasisteady motor operation. The results of previous modeling of radial flows in the bore, slots, and around grain overhangs are supported by approximate analytical and empirical techniques presented here. The predictions of circumferential flows induced by inhibitor asymmetries, nozzle vectoring, and propellant slump are compared to each other and to subscale cold air and water tunnel measurements to ascertain their validity.

Bibliography of spatial interferometry in optical astronomy

NASA Technical Reports Server (NTRS)

Gezari, Daniel Y.; Roddier, Francois; Roddier, Claude

1990-01-01

The Bibliography of Spatial Interferometry in Optical Astronomy is a guide to the published literature in applications of spatial interferometry techniques to astronomical observations, theory and instrumentation at visible and infrared wavelengths. The key words spatial and optical define the scope of this discipline, distinguishing it from spatial interferometry at radio wavelengths, interferometry in the frequency domain applied to spectroscopy, or more general electro-optics theoretical and laboratory research. The main bibliography is a listing of all technical articles published in the international scientific literature and presented at the major international meetings and workshops attended by the spatial interferometry community. Section B summarizes publications dealing with the basic theoretical concepts and algorithms proposed and applied to optical spatial interferometry and imaging through a turbulent atmosphere. The section on experimental techniques is divided into twelve categories, representing the most clearly identified major areas of experimental research work. Section D, Observations, identifies publications dealing specifically with observations of astronomical sources, in which optical spatial interferometry techniques have been applied.

Implementing GIS in real estate price prediction and mass valuation: the case study of Nicosia District

NASA Astrophysics Data System (ADS)

Yiorkas, Charalambos; Dimopoulos, Thomas

2017-09-01

When the European Commission, International Monetary Fund and European Central Bank arrived in Cyprus to assist for a sustainable solution on the crisis on the banking sector, one of the first things they ordered was a New General Valuation (a mass appraisal that would revalue all properties in Cyprus as on 1st of January 2013), that it would be used for taxation purposes. The above indicates the importance of property mass appraising tools. This task was successfully conducted by the Department of Lands and Surveys. Authors aim to move a step further and implement the use of GIS and GWR techniques to improve the results of the New General Valuation. On a sample of comparative evidences for flats in Nicosia District, GIS was used to measure the impact of spatial attributes on real estate prices and to construct a prediction model in terms of spatially estimating apartment values. In addition to the structural property characteristics, some spatial attributes (landmarks) were also analysed to assess their contribution on the prices of the apartments, including the Central Business District (CBD), schools and universities, as well as the major city roads and the restricted zone that divides the country into two parts; the occupied by Turkish area and the Greek area. The values of the spatial attributes, or locational characteristics, were determined by employing GIS, considering an established model of multicriteria analysis. The price prediction model was analysed using the OLS method and calibrated based on the GWR method. The results of the statistic process indicate an accuracy of 81.34%, showing better performance than the mass valuation system applied by the Department of Land and Surveys in Cyprus with accuracy of 66.76%. This approach suggests that GIS systems are fundamentally important in mass valuation procedures in order to identify the spatial pattern of the attributes, provided that the database is comprised by a sufficient number of comparable information and it is continuously updated.

Volcanic Eruption Classification on Io and Earth from Low Spatial Resolution Remote-Sensing Data

NASA Astrophysics Data System (ADS)

Davies, A. G.; Keszthelyi, L. P.

2005-08-01

Earth and Io exhibit high-temperature (silicate) active volcanism. While there are important differences in the eruptions on Earth and Io, in low-spatial-resolution data (corresponding to the bulk of available and foreseeable data of Io), similar styles of effusive and explosive volcanism yield similar thermal flux densities [1-3]. If, from observed thermal emission as a function of wavelength and change in thermal emission with time, the eruption style of an ionian volcano can be constrained, estimates of volumetric fluxes can be made and compared with terrestrial volcanoes using techniques derived for analysing terrestrial remotely-sensed data. We find that ionian volcanoes fundamentally differ from their terrestrial counterparts only in areal extent, with Io volcanoes covering larger areas, with higher volumetric fluxes. Even with the low-spatial resolution data available it is possible to sometimes constrain and classify eruption style both on Io and Earth from the integrated thermal emission spectrum, and how this changes temporally. Plotting 2 and 5 μm fluxes reveals the evolution of individual eruptions of different styles, as well as the relative intensity of eruptions, allowing comparison to be made from individual eruptions on both planets. For some Ionian volcanoes, low-resolution analyses are confirmed from observations obtained at high spatial resolution Of great importance, possibly more so than spatial resolution, is temporal resolution, as this has proven diagnostic in determining style of eruption at a number of volcanoes (e.g., Prometheus, Pele, Loki Patera, Pillan 1997) [1-3]. Active lava lakes, fire-fountains and insulated flows are identified using this methodology, and this allows comparison of individual eruptions on both planets. References: [1] Davies et al. (2001) JGR, 106, 33079-33,103. [2] Keszthelyi et al. (2001) LPSC XXXII Abstract 1523. [3] Davies (2003) JGR, 108, 10.1029/2001JE001509. This work was carried out at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA.

Electron Microscopy and Analytical X-ray Characterization of Compositional and Nanoscale Structural Changes in Fossil Bone

NASA Astrophysics Data System (ADS)

Boatman, Elizabeth Marie

The nanoscale structure of compact bone contains several features that are direct indicators of bulk tissue mechanical properties. Fossil bone tissues represent unique opportunities to understand the compact bone structure/property relationships from a deep time perspective, offering a possible array of new insights into bone diseases, biomimicry of composite materials, and basic knowledge of bioapatite composition and nanoscale bone structure. To date, most work with fossil bone has employed microscale techniques and has counter-indicated the survival of bioapatite and other nanoscale structural features. The obvious disconnect between the use of microscale techniques and the discernment of nanoscale structure has prompted this work. The goal of this study was to characterize the nanoscale constituents of fossil compact bone by applying a suite of diffraction, microscopy, and spectrometry techniques, representing the highest levels of spatial and energy resolution available today, and capable of complementary structural and compositional characterization from the micro- to the nanoscale. Fossil dinosaur and crocodile long bone specimens, as well as modern ratite and crocodile femurs, were acquired from the UC Museum of Paleontology. Preserved physiological features of significance were documented with scanning electron microscopy back-scattered imaging. Electron microprobe wavelength-dispersive X-ray spectroscopy (WDS) revealed fossil bone compositions enriched in fluorine with a complementary loss of oxygen. X-ray diffraction analyses demonstrated that all specimens were composed of apatite. Transmission electron microscopy (TEM) imaging revealed preserved nanocrystallinity in the fossil bones and electron diffraction studies further identified these nanocrystallites as apatite. Tomographic analyses of nanoscale elements imaged by TEM and small angle X-ray scattering were performed, with the results of each analysis further indicating that nanoscale structure is highly conserved in these four fossil specimens. Finally, the results of this study indicate that bioapatite can be preserved in even the most ancient vertebrate specimens, further supporting the idea that fossilization is a preservational process. This work also underlines the importance of using appropriately selected characterization and analytical techniques for the study of fossil bone, especially from the perspective of spatial resolution and the scale of the bone structural features in question.

The SELGIFS data challenge: generating synthetic observations of CALIFA galaxies from hydrodynamical simulations

NASA Astrophysics Data System (ADS)

Guidi, G.; Casado, J.; Ascasibar, Y.; García-Benito, R.; Galbany, L.; Sánchez-Blázquez, P.; Sánchez, S. F.; Rosales-Ortega, F. F.; Scannapieco, C.

2018-06-01

In this work we present a set of synthetic observations that mimic the properties of the Integral Field Spectroscopy (IFS) survey CALIFA, generated using radiative transfer techniques applied to hydrodynamical simulations of galaxies in a cosmological context. The simulated spatially-resolved spectra include stellar and nebular emission, kinematic broadening of the lines, and dust extinction and scattering. The results of the radiative transfer simulations have been post-processed to reproduce the main properties of the CALIFA V500 and V1200 observational setups. The data has been further formatted to mimic the CALIFA survey in terms of field of view size, spectral range and sampling. We have included the effect of the spatial and spectral Point Spread Functions affecting CALIFA observations, and added detector noise after characterizing it on a sample of 367 galaxies. The simulated datacubes are suited to be analysed by the same algorithms used on real IFS data. In order to provide a benchmark to compare the results obtained applying IFS observational techniques to our synthetic datacubes, and test the calibration and accuracy of the analysis tools, we have computed the spatially-resolved properties of the simulations. Hence, we provide maps derived directly from the hydrodynamical snapshots or the noiseless spectra, in a way that is consistent with the values recovered by the observational analysis algorithms. Both the synthetic observations and the product datacubes are public and can be found in the collaboration website http://astro.ft.uam.es/selgifs/data_challenge/.

Vander Lugt correlation of DNA sequence data

NASA Astrophysics Data System (ADS)

Christens-Barry, William A.; Hawk, James F.; Martin, James C.

1990-12-01

DNA, the molecule containing the genetic code of an organism, is a linear chain of subunits. It is the sequence of subunits, of which there are four kinds, that constitutes the unique blueprint of an individual. This sequence is the focus of a large number of analyses performed by an army of geneticists, biologists, and computer scientists. Most of these analyses entail searches for specific subsequences within the larger set of sequence data. Thus, most analyses are essentially pattern recognition or correlation tasks. Yet, there are special features to such analysis that influence the strategy and methods of an optical pattern recognition approach. While the serial processing employed in digital electronic computers remains the main engine of sequence analyses, there is no fundamental reason that more efficient parallel methods cannot be used. We describe an approach using optical pattern recognition (OPR) techniques based on matched spatial filtering. This allows parallel comparison of large blocks of sequence data. In this study we have simulated a Vander Lugt1 architecture implementing our approach. Searches for specific target sequence strings within a block of DNA sequence from the Co/El plasmid2 are performed.

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PubMed Central

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F.; Beale, Colin M.

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation. PMID:25915899

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa.

PubMed

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F; Beale, Colin M

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation.

Mean field analysis of a spatial stochastic model of a gene regulatory network.

PubMed

Sturrock, M; Murray, P J; Matzavinos, A; Chaplain, M A J

2015-10-01

A gene regulatory network may be defined as a collection of DNA segments which interact with each other indirectly through their RNA and protein products. Such a network is said to contain a negative feedback loop if its products inhibit gene transcription, and a positive feedback loop if a gene product promotes its own production. Negative feedback loops can create oscillations in mRNA and protein levels while positive feedback loops are primarily responsible for signal amplification. It is often the case in real biological systems that both negative and positive feedback loops operate in parameter regimes that result in low copy numbers of gene products. In this paper we investigate the spatio-temporal dynamics of a single feedback loop in a eukaryotic cell. We first develop a simplified spatial stochastic model of a canonical feedback system (either positive or negative). Using a Gillespie's algorithm, we compute sample trajectories and analyse their corresponding statistics. We then derive a system of equations that describe the spatio-temporal evolution of the stochastic means. Subsequently, we examine the spatially homogeneous case and compare the results of numerical simulations with the spatially explicit case. Finally, using a combination of steady-state analysis and data clustering techniques, we explore model behaviour across a subregion of the parameter space that is difficult to access experimentally and compare the parameter landscape of our spatio-temporal and spatially-homogeneous models.

Paper-based analytical devices for environmental analysis.

PubMed

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

2016-03-21

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

Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

NASA Astrophysics Data System (ADS)

Mitchell, K. E.

2006-12-01

The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global precipitation analyses by other institutions. Other global precipitation analyses produced by other methodologies are also used by EMC in certain applications, such as CPC's well-known satellite-IR based technique known as "GPI", and satellite-microwave based estimates from NESDIS or NASA. Finally, the presentation will cover the three assimilation methods used by EMC to assimilate precipitation data, including 1) 3D-VAR variational assimilation in NCEP's Global Data Assimilation System (GDAS), 2) direct insertion of precipitation-inferred vertical latent heating profiles in NCEP's N. American Data Assimilation System (NDAS) and its N. American Regional Reanalysis (NARR) counterpart, and 3) direct use of observed precipitation to drive the Noah land model component of NCEP's Global and N. American Land Data Assimilation Systems (GLDAS and NLDAS). In the applications of precipitation analyses in data assimilation at NCEP, the analyses are temporally disaggregated to hourly or less using time-weights calculated from A) either radar-based estimates or an analysis of hourly gauge-observations for the CONUS-domain daily precipitation analyses, or B) global model forecasts of 6-hourly precipitation (followed by linear interpolation to hourly or less) for the global CMAP precipitation analysis.

Monitoring Building Deformation with InSAR: Experiments and Validation

PubMed Central

Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

2016-01-01

Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403

VIRTIS on Venus Express: retrieval of real surface emissivity on global scales

NASA Astrophysics Data System (ADS)

Arnold, Gabriele E.; Kappel, David; Haus, Rainer; Telléz Pedroza, Laura; Piccioni, Giuseppe; Drossart, Pierre

2015-09-01

The extraction of surface emissivity data provides the data base for surface composition analyses and enables to evaluate Venus' geology. The Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS) aboard ESA's Venus Express mission measured, inter alia, the nightside thermal emission of Venus in the near infrared atmospheric windows between 1.0 and 1.2 μm. These data can be used to determine information about surface properties on global scales. This requires a sophisticated approach to understand and consider the effects and interferences of different atmospheric and surface parameters influencing the retrieved values. In the present work, results of a new technique for retrieval of the 1.0 - 1.2 μm - surface emissivity are summarized. It includes a Multi-Window Retrieval Technique, a Multi-Spectrum Retrieval technique (MSR), and a detailed reliability analysis. The MWT bases on a detailed radiative transfer model making simultaneous use of information from different atmospheric windows of an individual spectrum. MSR regularizes the retrieval by incorporating available a priori mean values, standard deviations as well as spatial-temporal correlations of parameters to be retrieved. The capability of this method is shown for a selected surface target area. Implications for geologic investigations are discussed. Based on these results, the work draws conclusions for future Venus surface composition analyses on global scales using spectral remote sensing techniques. In that context, requirements for observational scenarios and instrumental performances are investigated, and recommendations are derived to optimize spectral measurements for Venus' surface studies.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Integrating hydrologic and geophysical data to constrain coastal surficial aquifer processes at multiple spatial and temporal scales

USGS Publications Warehouse

Schultz, Gregory M.; Ruppel, Carolyn; Fulton, Patrick; Hyndman, David W.; Day-Lewis, Frederick D.; Singha, Kamini

2007-01-01

Since 1997, repeated, coincident geophysical surveys and extensive hydrologic studies in shallow monitoring wells have been used to study static and dynamic processes associated with surface water-groundwater interaction at a range of spatial scales at the estuarine and ocean boundaries of an undeveloped, permeable barrier island in the Georgia part of the U.S. South Atlantic Bight. Because geophysical and hydrologic data measure different parameters, at different resolution and precision, and over vastly different spatial scales, reconciling the coincident data or even combining complementary inversion, hydrogeochemcial analyses and well-based groundwater monitoring, and, in some cases, limited vegetation mapping to demonstrate the utility of an integrative, multidisciplinary approach for elucidating groundwater processes at spatial scales (tens to thousands of meters) that are often difficult to capture with traditional hydrologic approaches. The case studies highlight regional aquifer characteristics, varying degrees of lateral saltwater intrusion at estuarine boundaries, complex subsurface salinity gradients at the ocean boundary, and imaging of submarsh groundwater discharge and possible free convection in the pore waters of a clastic marsh. This study also documents the use of geophysical techniques for detecting temporal changes in groundwater salinity regimes under natural (not forced) gradients at intratidal to interannual (1998-200 Southeastern U.S.A. drought) time scales.

Collaborative development of land use change scenarios for analysing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

Malek, Žiga; Glade, Thomas

2015-04-01

Simulating future land use changes remains a difficult task, due to uncontrollable and uncertain driving forces of change. Scenario development emerged as a tool to address these limitations. Scenarios offer the exploration of possible futures and environmental consequences, and enable the analysis of possible decisions. Therefore, there is increasing interest of both decision makers and researchers to apply scenarios when studying future land use changes and their consequences. The uncertainties related to generating land use change scenarios are among others defined by the accuracy of data, identification and quantification of driving forces, and the relation between expected future changes and the corresponding spatial pattern. To address the issue of data and intangible driving forces, several studies have applied collaborative, participatory techniques when developing future scenarios. The involvement of stakeholders can lead to incorporating a broader spectrum of professional values and experience. Moreover, stakeholders can help to provide missing data, improve detail, uncover mistakes, and offer alternatives. Thus, collaborative scenarios can be considered as more reliable and relevant. Collaborative scenario development has been applied to study a variety of issues in environmental sciences on different spatial and temporal scales. Still, these participatory approaches are rarely spatially explicit, making them difficult to apply when analysing changes to hydro-meteorological risk on a local scale. Spatial explicitness is needed to identify potentially critical areas of land use change, leading to locations where the risk might increase. In order to allocate collaboratively developed scenarios of land change, we combined participatory modeling with geosimulation in a multi-step scenario generation framework. We propose a framework able to develop scenarios that are plausible, can overcome data inaccessibility, address intangible and external driving forces of land change, and is transferable to other case study areas with different land use change processes and consequences. The framework starts with the involvement of stakeholders where driving forces of land use change are being studied by performing interviews and group discussions. In order to bridge the gap between qualitative methods and conventional geospatial techniques, we applied cognitive mapping and the Drivers-Pressures-State-Impact and Response framework (DPSIR) to develop a conceptual land use change model. This was later transformed into a spatially explicit land use change model based on remote sensing data, GIS and cellular automata spatial allocation. The methodology was developed and applied in a study area in the eastern Italian Alps, where the uncertainties regarding future urban expansion are high. Later, we transferred it to a study area in the Romanian Carpathians, where the identified prevailing process of land use change is deforestation. Both areas are subject to hydro-meteorological risk, posing a need for the analysis of the possible future spatial pattern and locations of land use change. The resulting scenarios enabled us, to point at identifying hot-spots of land use change, serving as a possible input for a risk assessment.

Contour advection with surgery: A technique for investigating finescale structure in tracer transport

NASA Technical Reports Server (NTRS)

Waugh, Darryn W.; Plumb, R. Alan

1994-01-01

We present a trajectory technique, contour advection with surgery (CAS), for tracing the evolution of material contours in a specified (including observed) evolving flow. CAS uses the algorithms developed by Dritschel for contour dynamics/surgery to trace the evolution of specified contours. The contours are represented by a series of particles, which are advected by a specified, gridded, wind distribution. The resolution of the contours is preserved by continually adjusting the number of particles, and finescale features are produced that are not present in the input data (and cannot easily be generated using standard trajectory techniques). The reliability, and dependence on the spatial and temporal resolution of the wind field, of the CAS procedure is examined by comparisons with high-resolution numerical data (from contour dynamics calculations and from a general circulation model), and with routine stratospheric analyses. These comparisons show that the large-scale motions dominate the deformation field and that CAS can accurately reproduce small scales from low-resolution wind fields. The CAS technique therefore enables examination of atmospheric tracer transport at previously unattainable resolution.

Geostatistical Investigations of Displacements on the Basis of Data from the Geodetic Monitoring of a Hydrotechnical Object

NASA Astrophysics Data System (ADS)

Namysłowska-Wilczyńska, Barbara; Wynalek, Janusz

2017-12-01

Geostatistical methods make the analysis of measurement data possible. This article presents the problems directed towards the use of geostatistics in spatial analysis of displacements based on geodetic monitoring. Using methods of applied (spatial) statistics, the research deals with interesting and current issues connected to space-time analysis, modeling displacements and deformations, as applied to any large-area objects on which geodetic monitoring is conducted (e.g., water dams, urban areas in the vicinity of deep excavations, areas at a macro-regional scale subject to anthropogenic influences caused by mining, etc.). These problems are very crucial, especially for safety assessment of important hydrotechnical constructions, as well as for modeling and estimating mining damage. Based on the geodetic monitoring data, a substantial basic empirical material was created, comprising many years of research results concerning displacements of controlled points situated on the crown and foreland of an exemplary earth dam, and used to assess the behaviour and safety of the object during its whole operating period. A research method at a macro-regional scale was applied to investigate some phenomena connected with the operation of the analysed big hydrotechnical construction. Applying a semivariogram function enabled the spatial variability analysis of displacements. Isotropic empirical semivariograms were calculated and then, theoretical parameters of analytical functions were determined, which approximated the courses of the mentioned empirical variability measure. Using ordinary (block) kriging at the grid nodes of an elementary spatial grid covering the analysed object, the values of the Z* estimated means of displacements were calculated together with the accompanying assessment of uncertainty estimation - a standard deviation of estimation σk. Raster maps of the distribution of estimated averages Z* and raster maps of deviations of estimation σk (in perspective) were obtained for selected years (1995 and 2007), taking the ground height 136 m a.s.l. into calculation. To calculate raster maps of Z* interpolated values, methods of quick interpolation were also used, such as the technique of the inverse distance squares, a linear model of kriging, a spline kriging, which made the recognition of the general background of displacements possible, without the accuracy assessment of Z* value estimation, i.e., the value of σk. These maps are also related to 1995 and 2007 and the elevation. As a result of applying these techniques, clear boundaries of subsiding areas, upthrusting and also horizontal displacements on the examined hydrotechnical object were marked out, which can be interpreted as areas of local deformations of the object, important for the safety of the construction. The effect of geostatistical research conducted, including the structural analysis, semivariograms modeling, estimating the displacements of the hydrotechnical object, are rich cartographic characteristic (semivariograms, raster maps, block diagrams), which present the spatial visualization of the conducted various analyses of the monitored displacements. The prepared geostatistical model (3D) of displacement variability (analysed within the area of the dam, during its operating period and including its height) will be useful not only in the correct assessment of displacements and deformations, but it will also make it possible to forecast these phenomena, which is crucial when the operating safety of such constructions is taken into account.

Multi-scale dynamical behavior of spatially distributed systems: a deterministic point of view

NASA Astrophysics Data System (ADS)

Mangiarotti, S.; Le Jean, F.; Drapeau, L.; Huc, M.

2015-12-01

Physical and biophysical systems are spatially distributed systems. Their behavior can be observed or modelled spatially at various resolutions. In this work, a deterministic point of view is adopted to analyze multi-scale behavior taking a set of ordinary differential equation (ODE) as elementary part of the system.To perform analyses, scenes of study are thus generated based on ensembles of identical elementary ODE systems. Without any loss of generality, their dynamics is chosen chaotic in order to ensure sensitivity to initial conditions, that is, one fundamental property of atmosphere under instable conditions [1]. The Rössler system [2] is used for this purpose for both its topological and algebraic simplicity [3,4].Two cases are thus considered: the chaotic oscillators composing the scene of study are taken either independent, or in phase synchronization. Scale behaviors are analyzed considering the scene of study as aggregations (basically obtained by spatially averaging the signal) or as associations (obtained by concatenating the time series). The global modeling technique is used to perform the numerical analyses [5].One important result of this work is that, under phase synchronization, a scene of aggregated dynamics can be approximated by the elementary system composing the scene, but modifying its parameterization [6]. This is shown based on numerical analyses. It is then demonstrated analytically and generalized to a larger class of ODE systems. Preliminary applications to cereal crops observed from satellite are also presented.[1] Lorenz, Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141 (1963).[2] Rössler, An equation for continuous chaos, Phys. Lett. A, 57, 397-398 (1976).[3] Gouesbet & Letellier, Global vector-field reconstruction by using a multivariate polynomial L2 approximation on nets, Phys. Rev. E 49, 4955-4972 (1994).[4] Letellier, Roulin & Rössler, Inequivalent topologies of chaos in simple equations, Chaos, Solitons & Fractals, 28, 337-360 (2006).[5] Mangiarotti, Coudret, Drapeau, & Jarlan, Polynomial search and global modeling, Phys. Rev. E 86(4), 046205 (2012).[6] Mangiarotti, Modélisation globale et Caractérisation Topologique de dynamiques environnementales. Habilitation à Diriger des Recherches, Univ. Toulouse 3 (2014).

Ecological economics of soil erosion: a review of the current state of knowledge.

PubMed

Adhikari, Bhim; Nadella, Karthik

2011-02-01

The economics of land degradation has received relatively little attention until recent years. Although a number of studies have undertaken valuation of ecosystem services ranging from the global to the micro level, and quite a few studies have attempted to quantify the costs of soil erosion, studies that address the full costs of land degradation are still scarce. In this review, we attempt to analyze different land resource modeling and valuation techniques applied in earlier research and the type of data used in these analyses, and to assess their utility for different forms of land resource and management appraisal. We also report on the strengths and weaknesses of different valuation techniques used in studies on the economics of soil erosion, and the relevance of these valuation techniques. We make a case for the need for more appropriate models that can make the analysis more robust in estimating the economic costs of land degradation while recognizing the spatial heterogeneity in biophysical and economic conditions. © 2011 New York Academy of Sciences.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Optimization of spatial frequency domain imaging technique for estimating optical properties of food and biological materials

USDA-ARS?s Scientific Manuscript database

Spatial frequency domain imaging technique has recently been developed for determination of the optical properties of food and biological materials. However, accurate estimation of the optical property parameters by the technique is challenging due to measurement errors associated with signal acquis...

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

Evolution and enabling capabilities of spatially resolved techniques for the characterization of heterogeneously catalyzed reactions

DOE PAGES

Morgan, Kevin; Touitou, Jamal; Choi, Jae -Soon; ...

2016-01-15

The development and optimization of catalysts and catalytic processes requires knowledge of reaction kinetics and mechanisms. In traditional catalyst kinetic characterization, the gas composition is known at the inlet, and the exit flow is measured to determine changes in concentration. As such, the progression of the chemistry within the catalyst is not known. Technological advances in electromagnetic and physical probes have made visualizing the evolution of the chemistry within catalyst samples a reality, as part of a methodology commonly known as spatial resolution. Herein, we discuss and evaluate the development of spatially resolved techniques, including the evolutions and achievements ofmore » this growing area of catalytic research. The impact of such techniques is discussed in terms of the invasiveness of physical probes on catalytic systems, as well as how experimentally obtained spatial profiles can be used in conjunction with kinetic modeling. Moreover, some aims and aspirations for further evolution of spatially resolved techniques are considered.« less

Nondestructive and intuitive determination of circadian chlorophyll rhythms in soybean leaves using multispectral imaging

PubMed Central

Pan, Wen-Juan; Wang, Xia; Deng, Yong-Ren; Li, Jia-Hang; Chen, Wei; Chiang, John Y.; Yang, Jian-Bo; Zheng, Lei

2015-01-01

The circadian clock, synchronized by daily cyclic environmental cues, regulates diverse aspects of plant growth and development and increases plant fitness. Even though much is known regarding the molecular mechanism of circadian clock, it remains challenging to quantify the temporal variation of major photosynthesis products as well as their metabolic output in higher plants in a real-time, nondestructive and intuitive manner. In order to reveal the spatial-temporal scenarios of photosynthesis and yield formation regulated by circadian clock, multispectral imaging technique has been employed for nondestructive determination of circadian chlorophyll rhythms in soybean leaves. By utilizing partial least square regression analysis, the determination coefficients R2, 0.9483 for chlorophyll a and 0.8906 for chlorophyll b, were reached, respectively. The predicted chlorophyll contents extracted from multispectral data showed an approximately 24-h rhythm which could be entrained by external light conditions, consistent with the chlorophyll contents measured by chemical analyses. Visualization of chlorophyll map in each pixel offers an effective way to analyse spatial-temporal distribution of chlorophyll. Our results revealed the potentiality of multispectral imaging as a feasible nondestructive universal assay for examining clock function and robustness, as well as monitoring chlorophyll a and b and other biochemical components in plants. PMID:26059057

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI.

PubMed

Zhao, Huawei; Crozier, Stuart; Liu, Feng

2002-12-01

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model. Copyright 2002 Wiley-Liss, Inc.

Nondestructive and intuitive determination of circadian chlorophyll rhythms in soybean leaves using multispectral imaging

NASA Astrophysics Data System (ADS)

Pan, Wen-Juan; Wang, Xia; Deng, Yong-Ren; Li, Jia-Hang; Chen, Wei; Chiang, John Y.; Yang, Jian-Bo; Zheng, Lei

2015-06-01

The circadian clock, synchronized by daily cyclic environmental cues, regulates diverse aspects of plant growth and development and increases plant fitness. Even though much is known regarding the molecular mechanism of circadian clock, it remains challenging to quantify the temporal variation of major photosynthesis products as well as their metabolic output in higher plants in a real-time, nondestructive and intuitive manner. In order to reveal the spatial-temporal scenarios of photosynthesis and yield formation regulated by circadian clock, multispectral imaging technique has been employed for nondestructive determination of circadian chlorophyll rhythms in soybean leaves. By utilizing partial least square regression analysis, the determination coefficients R2, 0.9483 for chlorophyll a and 0.8906 for chlorophyll b, were reached, respectively. The predicted chlorophyll contents extracted from multispectral data showed an approximately 24-h rhythm which could be entrained by external light conditions, consistent with the chlorophyll contents measured by chemical analyses. Visualization of chlorophyll map in each pixel offers an effective way to analyse spatial-temporal distribution of chlorophyll. Our results revealed the potentiality of multispectral imaging as a feasible nondestructive universal assay for examining clock function and robustness, as well as monitoring chlorophyll a and b and other biochemical components in plants.

Inferring animal social networks and leadership: applications for passive monitoring arrays.

PubMed

Jacoby, David M P; Papastamatiou, Yannis P; Freeman, Robin

2016-11-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. © 2016 The Authors.

Inferring animal social networks and leadership: applications for passive monitoring arrays

PubMed Central

Papastamatiou, Yannis P.; Freeman, Robin

2016-01-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. PMID:27881803

Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland.

PubMed

Zhang, Chaosheng

2006-08-01

Galway is a small but rapidly growing tourism city in western Ireland. To evaluate its environmental quality, a total of 166 surface soil samples (0-10 cm depth) were collected from parks and grasslands at the density of 1 sample per 0.25 km2 at the end of 2004. All samples were analysed using ICP-AES for the near-total concentrations of 26 chemical elements. Multivariate statistics and GIS techniques were applied to classify the elements and to identify elements influenced by human activities. Cluster analysis (CA) and principal component analysis (PCA) classified the elements into two groups: the first group predominantly derived from natural sources, the second being influenced by human activities. GIS mapping is a powerful tool in identifying the possible sources of pollutants. Relatively high concentrations of Cu, Pb and Zn were found in the city centre, old residential areas, and along major traffic routes, showing significant effects of traffic pollution. The element As is enriched in soils of the old built-up areas, which can be attributed to coal and peat combustion for home heating. Such significant spatial patterns of pollutants displayed by urban soils may imply potential health threat to residents of the contaminated areas of the city.

Biogenicity and Syngeneity of Organic Matter in Ancient Sedimentary Rocks: Recent Advances in the Search for Evidence of Past Life

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

Oehler, Dorothy Z.; Cady, Sherry L.

2014-12-01

he past decade has seen an explosion of new technologies for assessment of biogenicity and syngeneity of carbonaceous material within sedimentary rocks. Advances have been made in techniques for analysis of in situ organic matter as well as for extracted bulk samples of soluble and insoluble (kerogen) organic fractions. The in situ techniques allow analysis of micrometer-to-sub-micrometer-scale organic residues within their host rocks and include Raman and fluorescence spectroscopy/imagery, confocal laser scanning microscopy, and forms of secondary ion/laser-based mass spectrometry, analytical transmission electron microscopy, and X-ray absorption microscopy/spectroscopy. Analyses can be made for chemical, molecular, and isotopic composition coupled withmore » assessment of spatial relationships to surrounding minerals, veins, and fractures. The bulk analyses include improved methods for minimizing contamination and recognizing syngenetic constituents of soluble organic fractions as well as enhanced spectroscopic and pyrolytic techniques for unlocking syngenetic molecular signatures in kerogen. Together, these technologies provide vital tools for the study of some of the oldest and problematic carbonaceous residues and for advancing our understanding of the earliest stages of biological evolution on Earth and the search for evidence of life beyond Earth. We discuss each of these new technologies, emphasizing their advantages and disadvantages, applications, and likely future directions.« less

Long-term ground deformation patterns of Bucharest using multi-temporal InSAR and multivariate dynamic analyses: a possible transpressional system?

PubMed Central

Armaş, Iuliana; Mendes, Diana A.; Popa, Răzvan-Gabriel; Gheorghe, Mihaela; Popovici, Diana

2017-01-01

The aim of this exploratory research is to capture spatial evolution patterns in the Bucharest metropolitan area using sets of single polarised synthetic aperture radar (SAR) satellite data and multi-temporal radar interferometry. Three sets of SAR data acquired during the years 1992–2010 from ERS-1/-2 and ENVISAT, and 2011–2014 from TerraSAR-X satellites were used in conjunction with the Small Baseline Subset (SBAS) and persistent scatterers (PS) high-resolution multi-temporal interferometry (InSAR) techniques to provide maps of line-of-sight displacements. The satellite-based remote sensing results were combined with results derived from classical methodologies (i.e., diachronic cartography) and field research to study possible trends in developments over former clay pits, landfill excavation sites, and industrial parks. The ground displacement trend patterns were analysed using several linear and nonlinear models, and techniques. Trends based on the estimated ground displacement are characterised by long-term memory, indicated by low noise Hurst exponents, which in the long-term form interesting attractors. We hypothesize these attractors to be tectonic stress fields generated by transpressional movements. PMID:28252103

Long-term ground deformation patterns of Bucharest using multi-temporal InSAR and multivariate dynamic analyses: a possible transpressional system?

PubMed

Armaş, Iuliana; Mendes, Diana A; Popa, Răzvan-Gabriel; Gheorghe, Mihaela; Popovici, Diana

2017-03-02

The aim of this exploratory research is to capture spatial evolution patterns in the Bucharest metropolitan area using sets of single polarised synthetic aperture radar (SAR) satellite data and multi-temporal radar interferometry. Three sets of SAR data acquired during the years 1992-2010 from ERS-1/-2 and ENVISAT, and 2011-2014 from TerraSAR-X satellites were used in conjunction with the Small Baseline Subset (SBAS) and persistent scatterers (PS) high-resolution multi-temporal interferometry (InSAR) techniques to provide maps of line-of-sight displacements. The satellite-based remote sensing results were combined with results derived from classical methodologies (i.e., diachronic cartography) and field research to study possible trends in developments over former clay pits, landfill excavation sites, and industrial parks. The ground displacement trend patterns were analysed using several linear and nonlinear models, and techniques. Trends based on the estimated ground displacement are characterised by long-term memory, indicated by low noise Hurst exponents, which in the long-term form interesting attractors. We hypothesize these attractors to be tectonic stress fields generated by transpressional movements.

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

GIS-supported epidemiological analysis on canine Angiostrongylus vasorum and Crenosoma vulpis infections in Germany.

PubMed

Maksimov, Pavlo; Hermosilla, Carlos; Taubert, Anja; Staubach, Christoph; Sauter-Louis, Carola; Conraths, Franz J; Vrhovec, Majda Globokar; Pantchev, Nikola

2017-02-28

Angiostrongylus vasorum infections are the cause of severe cardiopulmonary diseases in dogs. In the past, canine angiostrongylosis has largely been neglected in Europe, although some recent studies indicated an expansion of historically known endemic areas, a phenomenon that might also apply to Crenosoma vulpis. The aim of the present study was to analyse temporal and spatial trends of canine A. vasorum and C. vulpis infections and to perform GIS-supported risk factor analysis to evaluate the role of landscape, age and seasonality in the life-cycle of these nematodes. A total of 12,682 faecal samples from German dogs (collected in 2003-2015) with clinical suspicion for lungworm infection were examined for the presence of A. vasorum and C. vulpis larvae by the Baermann funnel technique and respective epidemiological data (location and age of the sampled dogs, date of sampling) were subjected to GIS-supported risk factor analysis. Overall, A. vasorum and C. vulpis larvae were detected in 288 (2.3%) and 285 (2.2%) faecal samples, respectively. In general, both lungworm infections were found to be widely spread in Germany. GIS-supported analyses demonstrate spatial differences in the occurrence of canine A. vasorum and C. vulpis infections in Germany. also, risk factor analyses revealed an overlap but also diverging risk and protective factors for A. vasorum and C. vulpis infections. The current data also indicate a significant increase of A. vasorum and C. vulpis prevalences from 2003 to 2015 and from 2008 until 2015, respectively, and a potential spread of A. vasorum endemic areas to the northeastern part of Germany. The results of the present study show an insight into the epidemiological situation of lungworm infections (A. vasorum and C. vulpis) of the past 13 years in Germany. The data clearly demonstrate an increase of diagnosed A. vasorum prevalence in the tested dog population between 2003 and 2015 as well as spatial differences in the occurrence of diagnosed A. vasorum and C. vulpis infections of dogs in Germany. Risk factor analyses suggest possible differences in the biology of these parasites, presumably at the intermediate host level.

Impacts of Climate Change On The Occurrence of Extreme Events: The Mice Project

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Mice Team

It is widely accepted that climate change due to global warming will have substan- tial impacts on the natural environment, and on human activities. Furthermore, it is increasingly recognized that changes in the severity and frequency of extreme events, such as windstorm and flood, are likely to be more important than changes in the average climate. The EU-funded project MICE (Modelling the Impacts of Climate Extremes) commenced in January 2002. It seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warm- ing, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives are: a) to evaluate, by comparison with gridded and station observations, the ability of climate models to successfully reproduce the occurrence of extremes at the required spatial and temporal scales. b) to analyse model output with respect to future changes in the occurrence of extremes. Statistical analyses will determine changes in (i) the return periods of ex- tremes, (ii) the joint probability of extremes (combinations of damaging events such as windstorm followed by heavy rain), (iii) the sequential behaviour of extremes (whether events are well-separated or clustered) and (iv) the spatial patterns of extreme event occurrence across Europe. The range of uncertainty in model predictions will be ex- plored by analysing changes in model experiments with different spatial resolutions and forcing scenarios. c) to determine the impacts of the predicted changes in extremes occurrence on selected activity sectors: agriculture (Mediterranean drought), commer- cial forestry and natural forest ecosystems (windstorm and flood in northern Europe, fire in the Mediterranean), energy use (temperature extremes), tourism (heat stress and Mediterranean beach holidays, changes in the snow pack and winter sports ) and civil protection/insurance (windstorm and flood). Impacts will be evaluated through a combination of techniques ranging from quantitative analyses through to expert judge- ment. Throughout the project, a continuing dialogue with stakeholders and end-users will be maintained.

SIMS analyses of minor and trace element distributions in fracture calcite from Yucca Mountain, Nevada, USA

NASA Astrophysics Data System (ADS)

Denniston, Rhawn F.; Shearer, Charles K.; Layne, Graham D.; Vaniman, David T.

1997-05-01

Fracture-lining calcite samples from Yucca Mountain, Nevada, obtained as part of the extensive vertical sampling in studies of this site as a potential high-level waste repository, have been characterized according to microbeam-scale (25-30 μm) trace and minor element chemistry, and cathodoluminescent zonation patterns. As bulk chemical analyses are limited in spatial resolution and are subject to contamination by intergrown phases, a technique for analysis by secondary ion mass spectrometry (SIMS) of minor (Mn, Fe, Sr) and trace (REE) elements in calcite was developed and applied to eighteen calcite samples from four boreholes and one trench. SIMS analyses of REE in calcite and dolomite have been shown to be quantitative to abundances < 1 × chondrite. Although the low secondary ion yields associated with carbonates forced higher counting times than is necessary in most silicates, Mn, Fe, Sr, and REE analyses were obtained with sub-ppm detection limits and 2-15% analytical precision. Bulk chemical signatures noted by Vaniman (1994) allowed correlation of minor and trace element signatures in Yucca Mountain calcite with location of calcite precipitation (saturated vs. unsaturated zone). For example, upper unsaturated zone calcite exhibits pronounced negative Ce and Eu anomalies not observed in calcite collected below in the deep unsaturated zone. These chemical distinctions served as fingerprints which were applied to growth zones in order to examine temporal changes in calcite crystallization histories; analyses of such fine-scale zonal variations are unattainable using bulk analytical techniques. In addition, LREE (particularly Ce) scavenging of calcite-precipitating solutions by manganese oxide phases is discussed as the mechanism for Ce-depletion in unsaturated zone calcite.

Synchrony, Weather, and Cycles in Southern Pine Beetle (Coleoptera: Curculionidae).

PubMed

Reeve, John D

2018-02-08

Spatial synchrony and cycles are common features of forest insect pests, but are often studied as separate phenomenon. Using time series of timber damage caused by Dendroctonus frontalis Zimmermann (Coleoptera: Curculionidae) (southern pine beetle) in 10 states within the southern United States, this study examines synchrony in D. frontalis abundance, the synchronizing effects of temperature extremes, and the evidence for shared cycles among state populations. Cross-correlation and cluster analyses are used to quantify synchrony across a range of geographic distances and to identify groups of states with synchronous dynamics. Similar techniques are used to quantify spatial synchrony in temperature extremes and to examine their relationship to D. frontalis fluctuations. Cross-wavelet analysis is then used to examine pairs of time series for shared cycles. These analyses suggest there is substantial synchrony among states in D. frontalis fluctuations, and there are regional groups of states with similar dynamics. Synchrony in D. frontalis fluctuations also appears related to spatial synchrony in summer and winter temperature extremes. The cross-wavelet results suggest that D. frontalis dynamics may differ among regions and are not stationary. Significant oscillations were present in some states over certain time intervals, suggesting an endogenous feedback mechanism. Management of D. frontalis outbreaks could potentially benefit from a multistate regional approach because populations are synchronous on this level. Extreme summer temperatures are likely to become the most important synchronizing agent due to climate change. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

a Spatial Analysis on Gis-Hedonic Pricing Model on the Influence of Public Open Space and House Price in Klang Valley, Malaysia

NASA Astrophysics Data System (ADS)

Zainora, A. M.; Norzailawati, M. N.; Tuminah, P.

2016-06-01

Presently, it is noticeable that there is a significant influence of public open space about house price, especially in many developed nations. Literature suggests the relationship between the two aspects give impact on the housing market, however not many studies undertaken in Malaysia. Thus, this research was initiated to analyse the relationship of open space and house price via the techniques of GIS-Hedonic Pricing Model. In this regards, the GIS tool indicates the pattern of the relationship between open space and house price spatially. Meanwhile, Hedonic Pricing Model demonstrates the index of the selected criteria in determining the housing price. This research is a perceptual study of 200 respondents who were the house owners of double-storey terrace houses in four townships, namely Bandar Baru Bangi, Taman Melawati, Subang Jaya and Shah Alam, in Klang Valley. The key research question is whether the relationship between open space and house price exists and the nature of its pattern and intensity. The findings indicate that there is a positive correlation between open space and house price. Correlation analysis reveals that a weak relationship (rs < 0.1) established between the variable of open space and house price (rs = 0.91, N = 200, p = 0.2). Consequently, the rate of house price change is rather small. In overall, this research has achieved its research aims and thus, offers the value added in applying the GIS-Hedonic pricing model in analysing the influence of open space to the house price in the form of spatially and textually.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

MOSAIC - A space-multiplexing technique for optical processing of large images

NASA Technical Reports Server (NTRS)

Athale, Ravindra A.; Astor, Michael E.; Yu, Jeffrey

1993-01-01

A technique for Fourier processing of images larger than the space-bandwidth products of conventional or smart spatial light modulators and two-dimensional detector arrays is described. The technique involves a spatial combination of subimages displayed on individual spatial light modulators to form a phase-coherent image, which is subsequently processed with Fourier optical techniques. Because of the technique's similarity with the mosaic technique used in art, the processor used is termed an optical MOSAIC processor. The phase accuracy requirements of this system were studied by computer simulation. It was found that phase errors of less than lambda/8 did not degrade the performance of the system and that the system was relatively insensitive to amplitude nonuniformities. Several schemes for implementing the subimage combination are described. Initial experimental results demonstrating the validity of the mosaic concept are also presented.

A large capacity time division multiplexed (TDM) laser beam combining technique enabled by nanosecond speed KTN deflector

NASA Astrophysics Data System (ADS)

Yin, Stuart (Shizhuo); Chao, Ju-Hung; Zhu, Wenbin; Chen, Chang-Jiang; Campbell, Adrian; Henry, Michael; Dubinskiy, Mark; Hoffman, Robert C.

2017-08-01

In this paper, we present a novel large capacity (a 1000+ channel) time division multiplexing (TDM) laser beam combining technique by harnessing a state-of-the-art nanosecond speed potassium tantalate niobate (KTN) electro-optic (EO) beam deflector as the time division multiplexer. The major advantages of TDM approach are: (1) large multiplexing capability (over 1000 channels), (2) high spatial beam quality (the combined beam has the same spatial profile as the individual beam), (3) high spectral beam quality (the combined beam has the same spectral width as the individual beam, and (4) insensitive to the phase fluctuation of individual laser because of the nature of the incoherent beam combining. The quantitative analyses show that it is possible to achieve over one hundred kW average power, single aperture, single transverse mode solid state and/or fiber laser by pursuing this innovative beam combining method, which represents a major technical advance in the field of high energy lasers. Such kind of 100+ kW average power diffraction limited beam quality lasers can play an important role in a variety of applications such as laser directed energy weapons (DEW) and large-capacity high-speed laser manufacturing, including cutting, welding, and printing.

Using Space Syntax to Assess Safety in Public Areas - Case Study of Tarbiat Pedestrian Area, Tabriz-Iran

NASA Astrophysics Data System (ADS)

Cihangir Çamur, Kübra; Roshani, Mehdi; Pirouzi, Sania

2017-10-01

In studying the urban complex issues, simulation and modelling of public space use considerably helps in determining and measuring factors such as urban safety. Depth map software for determining parameters of the spatial layout techniques; and Statistical Package for Social Sciences (SPSS) software for analysing and evaluating the views of the pedestrians on public safety were used in this study. Connectivity, integration, and depth of the area in the Tarbiat city blocks were measured using the Space Syntax Method, and these parameters are presented as graphical and mathematical data. The combination of the results obtained from the questionnaire and statistical analysis with the results of spatial arrangement technique represents the appropriate and inappropriate spaces for pedestrians. This method provides a useful and effective instrument for decision makers, planners, urban designers and programmers in order to evaluate public spaces in the city. Prior to physical modification of urban public spaces, space syntax simulates the pedestrian safety to be used as an analytical tool by the city management. Finally, regarding the modelled parameters and identification of different characteristics of the case, this study represents the strategies and policies in order to increase the safety of the pedestrians of Tarbiat in Tabriz.

International Watershed Technology: Improving Water Quality and Quantity at the Local, Basin, and Regional Scales

USGS Publications Warehouse

Tollner, Ernest W.; Douglas-Mankin, Kyle R.

2017-01-01

This article introduces the five papers in the “International Watershed Technology” collection. These papers were selected from 60 technical presentations at the fifth biennial ASABE 21st Century Watershed Technology Conference and Workshop: Improving the Quality of Water Resources at Local, Basin, and Regional Scales, held in Quito, Ecuador, on 3-9 December 2016. The conference focused on solving spatial and temporal water quality and quantity problems and addressed topics such as watershed management in developing countries, aquatic ecology and ecohydrology, ecosystem services, climate change mitigation strategies, flood forecasting, remote sensing, and water resource policy and management. While diverse, the presentation topics reflected the continuing evolution of the “data mining” and “big data” themes of past conferences related to geospatial data applications, with increasing emphasis on practical solutions. The papers selected for this collection represent applications of spatial data analyses toward practical ends with a theme of “tools and techniques for sustainability.” The papers address a range of topics, including the matching of crops with water availability, and assessing the environmental impacts of agricultural production. The papers identify some of the latest tools and techniques for improving sustainability in watershed resource management that are relevant to both developing and developed countries.

A technique to calibrate spatial light modulator for varying phase response over its spatial regions

NASA Astrophysics Data System (ADS)

Gupta, Deepak K.; Tata, B. V. R.; Ravindran, T. R.

2018-05-01

Holographic Optical Tweezers (HOTs) employ the technique of beam shaping and holography in an optical manipulation system to create a multitude of focal spots for simultaneous trapping and manipulation of sub-microscopic particles. The beam shaping is accomplished by the use of a phase only liquid crystal spatial light modulator (SLM). The efficiency and the uniformity in the generated traps greatly depend on the phase response behavior of SLMs. In addition the SLMs are found to show different phase response over its different spatial regions, due to non-flat structure of SLMs. Also the phase responses are found to vary over different spatial regions due to non-uniform illumination (Gaussian profile of incident laser). There are various techniques to calibrate for the varying phase response by characterizing the phase modulation at various sub-sections. We present a simple and fast technique to calibrate the SLM suffering with spatially varying phase response. We divide the SLM into many sub-sections and optimize the brightness and gamma of each sub-section for maximum diffraction efficiency. This correction is incorporated in the Weighted Gerchberg Saxton (WGS) algorithm for generation of holograms.

A spatial analysis of social and economic determinants of tuberculosis in Brazil.

PubMed

Harling, Guy; Castro, Marcia C

2014-01-01

We investigated the spatial distribution, and social and economic correlates, of tuberculosis in Brazil between 2002 and 2009 using municipality-level age/sex-standardized tuberculosis notification data. Rates were very strongly spatially autocorrelated, being notably high in urban areas on the eastern seaboard and in the west of the country. Non-spatial ecological regression analyses found higher rates associated with urbanicity, population density, poor economic conditions, household crowding, non-white population and worse health and healthcare indicators. These associations remained in spatial conditional autoregressive models, although the effect of poverty appeared partially confounded by urbanicity, race and spatial autocorrelation, and partially mediated by household crowding. Our analysis highlights both the multiple relationships between socioeconomic factors and tuberculosis in Brazil, and the importance of accounting for spatial factors in analysing socioeconomic determinants of tuberculosis. © 2013 Published by Elsevier Ltd.

Using software agents to preserve individual health data confidentiality in micro-scale geographical analyses.

PubMed

Kamel Boulos, Maged N; Cai, Qiang; Padget, Julian A; Rushton, Gerard

2006-04-01

Confidentiality constraints often preclude the release of disaggregate data about individuals, which limits the types and accuracy of the results of geographical health analyses that could be done. Access to individually geocoded (disaggregate) data often involves lengthy and cumbersome procedures through review boards and committees for approval (and sometimes is not possible). Moreover, current data confidentiality-preserving solutions compatible with fine-level spatial analyses either lack flexibility or yield less than optimal results (because of confidentiality-preserving changes they introduce to disaggregate data), or both. In this paper, we present a simulation case study to illustrate how some analyses cannot be (or will suffer if) done on aggregate data. We then quickly review some existing data confidentiality-preserving techniques, and move on to explore a solution based on software agents with the potential of providing flexible, controlled (software-only) access to unmodified confidential disaggregate data and returning only results that do not expose any person-identifiable details. The solution is thus appropriate for micro-scale geographical analyses where no person-identifiable details are required in the final results (i.e., only aggregate results are needed). Our proposed software agent technique also enables post-coordinated analyses to be designed and carried out on the confidential database(s), as needed, compared to a more conventional solution based on the Web Services model that would only support a rigid, pre-coordinated (pre-determined) and rather limited set of analyses. The paper also provides an exploratory discussion of mobility, security, and trust issues associated with software agents, as well as possible directions/solutions to address these issues, including the use of virtual organizations. Successful partnerships between stakeholder organizations, proper collaboration agreements, clear policies, and unambiguous interpretations of laws and regulations are also much needed to support and ensure the success of any technological solution.

Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

NASA Astrophysics Data System (ADS)

Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

2016-10-01

Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

Spatial distribution of Munida intermedia and M. sarsi (crustacea: Anomura) on the Galician continental shelf (NW Spain): Application of geostatistical analysis

NASA Astrophysics Data System (ADS)

Freire, J.; González-Gurriarán, E.; Olaso, I.

1992-12-01

Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.

Spatial distribution of grape root borer (Lepidoptera: Sesiidae) infestations in Virginia vineyards and implications for sampling.

PubMed

Rijal, J P; Brewster, C C; Bergh, J C

2014-06-01

Grape root borer, Vitacea polistiformis (Harris) (Lepidoptera: Sesiidae) is a potentially destructive pest of grape vines, Vitis spp. in the eastern United States. After feeding on grape roots for ≍2 yr in Virginia, larvae pupate beneath the soil surface around the vine base. Adults emerge during July and August, leaving empty pupal exuviae on or protruding from the soil. Weekly collections of pupal exuviae from an ≍1-m-diameter weed-free zone around the base of a grid of sample vines in Virginia vineyards were conducted in July and August, 2008-2012, and their distribution was characterized using both nonspatial (dispersion) and spatial techniques. Taylor's power law showed a significant aggregation of pupal exuviae, based on data from 19 vineyard blocks. Combined use of geostatistical and Spatial Analysis by Distance IndicEs methods indicated evidence of an aggregated pupal exuviae distribution pattern in seven of the nine blocks used for those analyses. Grape root borer pupal exuviae exhibited spatial dependency within a mean distance of 8.8 m, based on the range values of best-fitted variograms. Interpolated and clustering index-based infestation distribution maps were developed to show the spatial pattern of the insect within the vineyard blocks. The temporal distribution of pupal exuviae showed that the majority of moths emerged during the 3-wk period spanning the third week of July and the first week of August. The spatial distribution of grape root borer pupal exuviae was used in combination with temporal moth emergence patterns to develop a quantitative and efficient sampling scheme to assess infestations.

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Rainfall: State of the Science

NASA Astrophysics Data System (ADS)

Testik, Firat Y.; Gebremichael, Mekonnen

Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Use of Synchrotron X-ray Fluorescence to Measure Trace Metal Distribution in the Brain

NASA Astrophysics Data System (ADS)

Linkous, D.; Flinn, J. M.; Lanzirotti, A.; Frederickson, C.; Jones, B. F.; Bertsch, P. M.

2002-12-01

X26A, National Synchrotron Light Source, was used to quantitatively evaluate the spatial distribution of trace metals, such as Zn and Cu, in brain tissue. X-ray microprobe techniques offer distinct advantages over other analytical methods by allowing analyses to be done in-situ with little or no chemical pretreatment and low detection limits (about 1 ppm). In the context of neuroscience, SXRF can provide non-destructive measurements of specific metal concentrations and distribution within nerve (brain) tissue. Neuronal tissue from organisms having undergone different normal or experimental conditions may be compared, with analytical capacities not limited by binding states of the metal (i.e., vesicular or enzymatic), as is the case with staining techniques.. Whole regions of tissue may be scanned for detectable trace metals at spatial resolutions of 10um or less using focused monochromatic x-ray beams. Here special attention has been given to zinc because it is the most common trace metal in the brain, and levels have been increasing in the environment. In this investigation, zinc concentrations present within the hilus of a rat hippocampus, and to a lesser extent in the cortex, have been shown to increase following long-term ingestion of zinc-enhanced drinking water that was associated with deficits in spatial memory. Concomitantly, copper concentrations in the internal capsule were comparatively lower. Other first order transition metals, Cr, V, Mn, and Co were not detected. In contrast, elevated levels of Zn, Cu, and Fe have been seen in amyloid plaques associated with Alzheimer's disease.

High-Order Space-Time Methods for Conservation Laws

NASA Technical Reports Server (NTRS)

Huynh, H. T.

2013-01-01

Current high-order methods such as discontinuous Galerkin and/or flux reconstruction can provide effective discretization for the spatial derivatives. Together with a time discretization, such methods result in either too small a time step size in the case of an explicit scheme or a very large system in the case of an implicit one. To tackle these problems, two new high-order space-time schemes for conservation laws are introduced: the first is explicit and the second, implicit. The explicit method here, also called the moment scheme, achieves a Courant-Friedrichs-Lewy (CFL) condition of 1 for the case of one-spatial dimension regardless of the degree of the polynomial approximation. (For standard explicit methods, if the spatial approximation is of degree p, then the time step sizes are typically proportional to 1/p(exp 2)). Fourier analyses for the one and two-dimensional cases are carried out. The property of super accuracy (or super convergence) is discussed. The implicit method is a simplified but optimal version of the discontinuous Galerkin scheme applied to time. It reduces to a collocation implicit Runge-Kutta (RK) method for ordinary differential equations (ODE) called Radau IIA. The explicit and implicit schemes are closely related since they employ the same intermediate time levels, and the former can serve as a key building block in an iterative procedure for the latter. A limiting technique for the piecewise linear scheme is also discussed. The technique can suppress oscillations near a discontinuity while preserving accuracy near extrema. Preliminary numerical results are shown

Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach.

PubMed

Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H

2017-04-20

Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression analyses, and assessment of associations between HCV clustering and the built environment are needed to expand upon our combined spatial epidemiological and statistical methods.

A comparison between EDA-EnVar and ETKF-EnVar data assimilation techniques using radar observations at convective scales through a case study of Hurricane Ike (2008)

NASA Astrophysics Data System (ADS)

Shen, Feifei; Xu, Dongmei; Xue, Ming; Min, Jinzhong

2017-07-01

This study examines the impacts of assimilating radar radial velocity (Vr) data for the simulation of hurricane Ike (2008) with two different ensemble generation techniques in the framework of the hybrid ensemble-variational (EnVar) data assimilation system of Weather Research and Forecasting model. For the generation of ensemble perturbations we apply two techniques, the ensemble transform Kalman filter (ETKF) and the ensemble of data assimilation (EDA). For the ETKF-EnVar, the forecast ensemble perturbations are updated by the ETKF, while for the EDA-EnVar, the hybrid is employed to update each ensemble member with perturbed observations. The ensemble mean is analyzed by the hybrid method with flow-dependent ensemble covariance for both EnVar. The sensitivity of analyses and forecasts to the two applied ensemble generation techniques is investigated in our current study. It is found that the EnVar system is rather stable with different ensemble update techniques in terms of its skill on improving the analyses and forecasts. The EDA-EnVar-based ensemble perturbations are likely to include slightly less organized spatial structures than those in ETKF-EnVar, and the perturbations of the latter are constructed more dynamically. Detailed diagnostics reveal that both of the EnVar schemes not only produce positive temperature increments around the hurricane center but also systematically adjust the hurricane location with the hurricane-specific error covariance. On average, the analysis and forecast from the ETKF-EnVar have slightly smaller errors than that from the EDA-EnVar in terms of track, intensity, and precipitation forecast. Moreover, ETKF-EnVar yields better forecasts when verified against conventional observations.

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

NASA Astrophysics Data System (ADS)

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

2005-10-01

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

Non-destructive trace element microanalysis of as-received cometary nucleus samples using synchrotron x ray fluorescence

NASA Technical Reports Server (NTRS)

Sutton, S. R.

1989-01-01

The Synchrotron X ray Fluorescence (SXRF) microprobe at the National Synchrotron Light Source (NSLS), Brookhaven National Laboratory, will be an excellent instrument for non-destructive trace element analyses of cometary nucleus samples. Trace element analyses of as-received cometary nucleus material will also be possible with this technique. Bulk analysis of relatively volatile elements will be important in establishing comet formation conditions. However, as demonstrated for meteorites, microanalyses of individual phases in their petrographic context are crucial in defining the histories of particular components in unequilibrated specimens. Perhaps most informative in comparing cometary material with meteorites will be the halogens and trace metals. In-situ, high spatial resolution microanalyses will be essential in establishing host phases for these elements and identifying terrestrial (collection/processing) overprints. The present SXRF microprobe is a simple, yet powerful, instrument in which specimens are excited with filtered, continuum synchrotron radiation from a bending magnet on a 2.5 GeV electron storage ring. A refrigerated cell will be constructed to permit analyses at low temperatures. The cell will consist essentially of an air tight housing with a cold stage. Kapton windows will be used to allow the incident synchrotron beam to enter the cell and fluorescent x rays to exit it. The cell will be either under vacuum or continuous purge by ultrapure helium during analyses. Several other improvements of the NSLS microprobe will be made prior to the cometary nucleus sample return mission that will greatly enhance the sensitivity of the technique.

Multi-Scale and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Applying spatial analysis techniques to assess the suitability of multipurpose uses of spring water in the Jiaosi Hot Spring Region, Taiwan.

PubMed

Jang, Cheng-Shin; Huang, Han-Chen

2017-07-01

The Jiaosi Hot Spring Region is one of the most famous tourism destinations in Taiwan. The spring water is processed for various uses, including irrigation, aquaculture, swimming, bathing, foot spas, and recreational tourism. Moreover, the multipurpose uses of spring water can be dictated by the temperature of the water. To evaluate the suitability of spring water for these various uses, this study spatially characterized the spring water temperatures of the Jiaosi Hot Spring Region by integrating ordinary kriging (OK), sequential Gaussian simulation (SGS), and Geographic information system (GIS). First, variogram analyses were used to determine the spatial variability of spring water temperatures. Next, OK and SGS were adopted to model the spatial uncertainty and distributions of the spring water temperatures. Finally, the land use (i.e., agriculture, dwelling, public land, and recreation) was determined using GIS and combined with the estimated distributions of the spring water temperatures. A suitable development strategy for the multipurpose uses of spring water is proposed according to the integration of the land use and spring water temperatures. The study results indicate that the integration of OK, SGS, and GIS is capable of characterizing spring water temperatures and the suitability of multipurpose uses of spring water. SGS realizations are more robust than OK estimates for characterizing spring water temperatures compared to observed data. Furthermore, current land use is almost ideal in the Jiaosi Hot Spring Region according to the estimated spatial pattern of spring water temperatures.

High-contrast differentiation resolution 3D imaging of rodent brain by X-ray computed microtomography

NASA Astrophysics Data System (ADS)

Zikmund, T.; Novotná, M.; Kavková, M.; Tesařová, M.; Kaucká, M.; Szarowská, B.; Adameyko, I.; Hrubá, E.; Buchtová, M.; Dražanová, E.; Starčuk, Z.; Kaiser, J.

2018-02-01

The biomedically focused brain research is largely performed on laboratory mice considering a high homology between the human and mouse genomes. A brain has an intricate and highly complex geometrical structure that is hard to display and analyse using only 2D methods. Applying some fast and efficient methods of brain visualization in 3D will be crucial for the neurobiology in the future. A post-mortem analysis of experimental animals' brains usually involves techniques such as magnetic resonance and computed tomography. These techniques are employed to visualize abnormalities in the brains' morphology or reparation processes. The X-ray computed microtomography (micro CT) plays an important role in the 3D imaging of internal structures of a large variety of soft and hard tissues. This non-destructive technique is applied in biological studies because the lab-based CT devices enable to obtain a several-micrometer resolution. However, this technique is always used along with some visualization methods, which are based on the tissue staining and thus differentiate soft tissues in biological samples. Here, a modified chemical contrasting protocol of tissues for a micro CT usage is introduced as the best tool for ex vivo 3D imaging of a post-mortem mouse brain. This way, the micro CT provides a high spatial resolution of the brain microscopic anatomy together with a high tissue differentiation contrast enabling to identify more anatomical details in the brain. As the micro CT allows a consequent reconstruction of the brain structures into a coherent 3D model, some small morphological changes can be given into context of their mutual spatial relationships.

Population genomic analysis suggests strong influence of river network on spatial distribution of genetic variation in invasive saltcedar across the southwestern United States

USGS Publications Warehouse

Lee, Soo-Rang; Jo, Yeong-Seok; Park, Chan-Ho; Friedman, Jonathan M.; Olson, Matthew S.

2018-01-01

Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in an invasive riparian shrub, saltcedar (Tamarix L.) by analysing 1,997 genomewide SNP markers for 259 individuals from 25 populations collected throughout the southwestern United States. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers and founder effects during range expansion.

A morphometric analysis of vegetation patterns in dryland ecosystems

PubMed Central

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

2017-01-01

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

A morphometric analysis of vegetation patterns in dryland ecosystems.

PubMed

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

2017-02-01

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

The analysis of a cardiological network in a regulated setting: a spatial interaction approach.

PubMed

Lippi Bruni, Matteo; Nobilio, Lucia; Ugolini, Cristina

2008-02-01

We analyse referral patterns for patients undergoing percutaneous transluminal coronary angioplasty (PTCA) in the Emilia Romagna region of Italy, a procedure for which the assumption of a negative association between volume and adverse outcomes is used to justify its territorial concentration. Nevertheless, recent clinical evidence shows PTCA superiority for immediate treatment of acute myocardial infarction, which advises an increase in the number of points of delivery. Our paper aims to develop analytical tools designed to provide support to policy makers when they are asked to evaluate the spatial distribution of catheterisation laboratories that perform PTCA. Information is drawn from the regional administrative hospital discharge data (SDO) for the year 2002. We first use entropy indexes to investigate the spatial accessibility of the cardiological network. Secondly, by means of a gravity model estimated using Bayesian techniques we identify the determinants of patient flows in terms of demand and supply factors. Our results suggest that information on destinations is processed hierarchically and that agglomeration-like forces are dominant. Furthermore, although self-sufficiency of provision at the provincial level has been achieved to a large extent, there is still scope to improve the organisational efficiency of the network.

A morphometric analysis of vegetation patterns in dryland ecosystems

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Patterns of genetic diversity in the polymorphic ground snake (Sonora semiannulata).

PubMed

Cox, Christian L; Chippindale, Paul T

2014-08-01

We evaluated the genetic diversity of a snake species with color polymorphism to understand the evolutionary processes that drive genetic structure across a large geographic region. Specifically, we analyzed genetic structure of the highly polymorphic ground snake, Sonora semiannulata, (1) among populations, (2) among color morphs (3) at regional and local spatial scales, using an amplified fragment length polymorphism dataset and multiple population genetic analyses, including FST-based and clustering analytical techniques. Based upon these methods, we found that there was moderate to low genetic structure among populations. However, this diversity was not associated with geographic locality at either spatial scale. Similarly, we found no evidence for genetic divergence among color morphs at either spatial scale. These results suggest that despite dramatic color polymorphism, this phenotypic diversity is not a major driver of genetic diversity within or among populations of ground snakes. We suggest that there are two mechanisms that could explain existing genetic diversity in ground snakes: recent range expansion from a genetically diverse founder population and current or recent gene flow among populations. Our findings have further implications for the types of color polymorphism that may generate genetic diversity in snakes.

Discrimination of fluoride and phosphate contamination in central Florida for analyses of environmental effects

NASA Technical Reports Server (NTRS)

Coker, A. E.; Marshall, R.; Thomson, F.

1972-01-01

A study was made of the spatial registration of fluoride and phosphate pollution parameters in central Florida by utilizing remote sensing techniques. Multispectral remote sensing data were collected over the area and processed to produce multispectral recognition maps. These processed data were used to map land areas and waters containing concentrations of fluoride and phosphate. Maps showing distribution of affected and unaffected vegetation were produced. In addition, the multispectral data were processed by single band radiometric slicing to produce radiometric maps used to delineate areas of high ultraviolet radiance, which indicates high fluoride concentrations. The multispectral parameter maps and radiometric maps in combination showed distinctive patterns, which are correlated with areas known to be affected by fluoride and phosphate contamination. These remote sensing techniques have the potential for regional use to assess the environmental impact of fluoride and phosphate wastes in central Florida.

Probing the solar corona with very long baseline interferometry.

PubMed

Soja, B; Heinkelmann, R; Schuh, H

2014-06-20

Understanding and monitoring the solar corona and solar wind is important for many applications like telecommunications or geomagnetic studies. Coronal electron density models have been derived by various techniques over the last 45 years, principally by analysing the effect of the corona on spacecraft tracking. Here we show that recent observational data from very long baseline interferometry (VLBI), a radio technique crucial for astrophysics and geodesy, could be used to develop electron density models of the Sun's corona. The VLBI results agree well with previous models from spacecraft measurements. They also show that the simple spherical electron density model is violated by regional density variations and that on average the electron density in active regions is about three times that of low-density regions. Unlike spacecraft tracking, a VLBI campaign would be possible on a regular basis and would provide highly resolved spatial-temporal samplings over a complete solar cycle.

Correlation analysis of fracture arrangement in space

NASA Astrophysics Data System (ADS)

Marrett, Randall; Gale, Julia F. W.; Gómez, Leonel A.; Laubach, Stephen E.

2018-03-01

We present new techniques that overcome limitations of standard approaches to documenting spatial arrangement. The new techniques directly quantify spatial arrangement by normalizing to expected values for randomly arranged fractures. The techniques differ in terms of computational intensity, robustness of results, ability to detect anti-correlation, and use of fracture size data. Variation of spatial arrangement across a broad range of length scales facilitates distinguishing clustered and periodic arrangements-opposite forms of organization-from random arrangements. Moreover, self-organized arrangements can be distinguished from arrangements due to extrinsic organization. Traditional techniques for analysis of fracture spacing are hamstrung because they account neither for the sequence of fracture spacings nor for possible coordination between fracture size and position, attributes accounted for by our methods. All of the new techniques reveal fractal clustering in a test case of veins, or cement-filled opening-mode fractures, in Pennsylvanian Marble Falls Limestone. The observed arrangement is readily distinguishable from random and periodic arrangements. Comparison of results that account for fracture size with results that ignore fracture size demonstrates that spatial arrangement is dominated by the sequence of fracture spacings, rather than coordination of fracture size with position. Fracture size and position are not completely independent in this example, however, because large fractures are more clustered than small fractures. Both spatial and size organization of veins here probably emerged from fracture interaction during growth. The new approaches described here, along with freely available software to implement the techniques, can be applied with effect to a wide range of structures, or indeed many other phenomena such as drilling response, where spatial heterogeneity is an issue.

Effects of titanium surface topography on bone integration: a systematic review.

PubMed

Wennerberg, Ann; Albrektsson, Tomas

2009-09-01

To analyse possible effects of titanium surface topography on bone integration. Our analyses were centred on a PubMed search that identified 1184 publications of assumed relevance; of those, 1064 had to be disregarded because they did not accurately present in vivo data on bone response to surface topography. The remaining 120 papers were read and analysed, after removal of an additional 20 papers that mainly dealt with CaP-coated and Zr implants; 100 papers remained and formed the basis for this paper. The bone response to differently configurated surfaces was mainly evaluated by histomorphometry (bone-to-implant contact), removal torque and pushout/pullout tests. A huge number of the experimental investigations have demonstrated that the bone response was influenced by the implant surface topography; smooth (S(a)<0.5 microm) and minimally rough (S(a) 0.5-1 mum) surfaces showed less strong bone responses than rougher surfaces. Moderately rough (S(a)>1-2 microm) surfaces showed stronger bone responses than rough (S(a)>2 microm) in some studies. One limitation was that it was difficult to compare many studies because of the varying quality of surface evaluations; a surface termed 'rough' in one study was not uncommonly referred to as 'smooth' in another; many investigators falsely assumed that surface preparation per se identified the roughness of the implant; and many other studies used only qualitative techniques such as SEM. Furthermore, filtering techniques differed or only height parameters (S(a), R(a)) were reported. * Surface topography influences bone response at the micrometre level. * Some indications exist that surface topography influences bone response at the nanometre level. * The majority of published papers present an inadequate surface characterization. * Measurement and evaluation techniques need to be standardized. * Not only height descriptive parameters but also spatial and hybrid ones should be used.

GIS based procedure of cumulative environmental impact assessment.

PubMed

Balakrishna Reddy, M; Blah, Baiantimon

2009-07-01

Scale and spatial limits of impact assessment study in a GIS platform are two very important factors that could have a bearing on the genuineness and quality of impact assessment. While effect of scale has been documented and well understood, no significant study has been carried out on spatial considerations in an impact assessment study employing GIS technique. A novel technique of impact assessment demonstrable through GIS approach termed hereby as 'spatial data integrated GIS impact assessment method (SGIAM)' is narrated in this paper. The technique makes a fundamental presumption that the importance of environmental impacts is dependent, among other things, on spatial distribution of the effects of the proposed action and of the affected receptors in a study area. For each environmental component considered (e.g., air quality), impact indices are calculated through aggregation of impact indicators which are measures of the severity of the impact. The presence and spread of environmental descriptors are suitably quantified through modeling techniques and depicted. The environmental impact index is calculated from data exported from ArcINFO, thus giving significant importance to spatial data in the impact assessment exercise.

Up, Down, and All Around: Scale-Dependent Spatial Variation in Rocky-Shore Communities of Fildes Peninsula, King George Island, Antarctica

PubMed Central

Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván

2014-01-01

Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

PubMed Central

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-01-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications. PMID:26525841

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope.

PubMed

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-03

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Assessment of illumination conditions in a single-pixel imaging configuration

NASA Astrophysics Data System (ADS)

Garoi, Florin; Udrea, Cristian; Damian, Cristian; Logofǎtu, Petre C.; Colţuc, Daniela

2016-12-01

Single-pixel imaging based on multiplexing is a promising technique, especially in applications where 2D detectors or raster scanning imaging are not readily applicable. With this method, Hadamard masks are projected on a spatial light modulator to encode an incident scene and a signal is recorded at the photodiode detector for each of these masks. Ultimately, the image is reconstructed on the computer by applying the inverse transform matrix. Thus, various algorithms were optimized and several spatial light modulators already characterized for such a task. This work analyses the imaging quality of such a single-pixel arrangement, when various illumination conditions are used. More precisely, the main comparison is made between coherent and incoherent ("white light") illumination and between two multiplexing methods, namely Hadamard and Scanning. The quality of the images is assessed by calculating their SNR, using two relations. The results show better images are obtained with "white light" illumination for the first method and coherent one for the second.

Escherichia coli Biofilms Have an Organized and Complex Extracellular Matrix Structure

PubMed Central

Hung, Chia; Zhou, Yizhou; Pinkner, Jerome S.; Dodson, Karen W.; Crowley, Jan R.; Heuser, John; Chapman, Matthew R.; Hadjifrangiskou, Maria; Henderson, Jeffrey P.; Hultgren, Scott J.

2013-01-01

ABSTRACT Bacterial biofilms are ubiquitous in nature, and their resilience is derived in part from a complex extracellular matrix that can be tailored to meet environmental demands. Although common developmental stages leading to biofilm formation have been described, how the extracellular components are organized to allow three-dimensional biofilm development is not well understood. Here we show that uropathogenic Escherichia coli (UPEC) strains produce a biofilm with a highly ordered and complex extracellular matrix (ECM). We used electron microscopy (EM) techniques to image floating biofilms (pellicles) formed by UPEC. EM revealed intricately constructed substructures within the ECM that encase individual, spatially segregated bacteria with a distinctive morphology. Mutational and biochemical analyses of these biofilms confirmed curli as a major matrix component and revealed important roles for cellulose, flagella, and type 1 pili in pellicle integrity and ECM infrastructure. Collectively, the findings of this study elucidated that UPEC pellicles have a highly organized ultrastructure that varies spatially across the multicellular community. PMID:24023384

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

NASA Astrophysics Data System (ADS)

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Channel correlation of free space optical communication systems with receiver diversity in non-Kolmogorov atmospheric turbulence

NASA Astrophysics Data System (ADS)

Ma, Jing; Fu, Yulong; Tan, Liying; Yu, Siyuan; Xie, Xiaolong

2018-05-01

Spatial diversity as an effective technique to mitigate the turbulence fading has been widely utilized in free space optical (FSO) communication systems. The received signals, however, will suffer from channel correlation due to insufficient spacing between component antennas. In this paper, the new expressions of the channel correlation coefficient and specifically its components (the large- and small-scale channel correlation coefficients) for a plane wave with aperture effects are derived for horizontal link in moderate-to-strong turbulence, using a non-Kolmogorov spectrum that has a generalized power law in the range of 3-4 instead of the fixed classical Kolmogorov power law of 11/3. And then the influence of power law variations on the channel correlation coefficient and its components are analysed. The numerical results indicated that various value of the power law lead to varying effects on the channel correlation coefficient and its components. This work will help with the further investigation on the fading correlation in spatial diversity systems.

Long Term trends in Meridional ISO Activity as seen in CMIP5 Simulations

NASA Astrophysics Data System (ADS)

Srivastava, G.; Chakraborty, A.; Nanjundaiah, R. S.

2016-12-01

Active and break phases of Indian Summer Monsoon (ISM) are manifested as subseasonal increase and decrease of convection. Major part of this intra-seasonal variability comes from low-frequency oscillations. Previous studies showed that northward propagating convective cloud bands are associated with these low-frequency intra-seasonal oscillations. Therefore, a thorough understanding of their spatial extent, location and intensity will be useful to understand and model the ISM. In this study, we have used Continous Wavelet Transform (CWT) technique to estimate the spatial extent (scale), center and intensity of these poleward propagating oscillatory systems. Using observation datasets, we show that scale, centre and intensity of these nothward propagating modes show different characteristics during floods and droughts of ISM. We have analysed different scenarios of CMIP5 and find that the change in mean ISM is related to changes in scale, center and intensity of northward propagations. We further show using AGCM simulations that SST over different regions of the world can modulate ISO over the Indian region.

Raman hyperspectral imaging as an effective and highly informative tool to study the diagenetic alteration of fossil bones.

PubMed

Dal Sasso, Gregorio; Angelini, Ivana; Maritan, Lara; Artioli, Gilberto

2018-03-01

Retrieving the pristine chemical or isotopic composition of archaeological bones is of great interest for many studies aiming to reconstruct the past life of ancient populations (i.e. diet, mobility, palaeoenvironment, age). However, from the death of the individual onwards, bones undergo several taphonomic and diagenetic processes that cause the alteration of their microstructure and composition. A detailed study on bone diagenesis has the double purpose to assess the preservation state of archaeological bones and to understand the alteration pathways, thus providing evidence that may contribute to evaluate the reliability of the retrieved information. On these bases, this research aims to explore the effectiveness of Raman hyperspectral imaging to detect types, extent and spatial distribution of diagenetic alteration at the micro-scale level. An early-Holocene bone sample from the Al Khiday cemetery (Khartoum, Sudan) was here analysed. Parameters related to the collagen content, bioapatite crystallinity and structural carbonate content, and to the occurrence of secondary mineral phases were calculated from Raman spectra. The acquired data provided spatially-resolved information on both the preservation state of bone constituents and the diagenetic processes occurring during burial. Given the minimal sample preparation, the easy and fast data acquisition and the improvement of system configurations, micro-Raman spectroscopy can be extensively applied as a screening method on a large set of samples in order to characterise the preservation state of archaeological bones. This technique can be effectively applied to identify suitable and well preserved portions of the analysed sample on which perform further analyses. Copyright © 2017 Elsevier B.V. All rights reserved.

D Nearest Neighbour Search Using a Clustered Hierarchical Tree Structure

NASA Astrophysics Data System (ADS)

Suhaibah, A.; Uznir, U.; Anton, F.; Mioc, D.; Rahman, A. A.

2016-06-01

Locating and analysing the location of new stores or outlets is one of the common issues facing retailers and franchisers. This is due to assure that new opening stores are at their strategic location to attract the highest possible number of customers. Spatial information is used to manage, maintain and analyse these store locations. However, since the business of franchising and chain stores in urban areas runs within high rise multi-level buildings, a three-dimensional (3D) method is prominently required in order to locate and identify the surrounding information such as at which level of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN) analysis. It uses a point location and identifies the surrounding neighbours. However, with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results are presented in this paper. Another advantage of this structure is that it also offers a minimal overlap and coverage among nodes which can reduce repetitive data entry.

Acquisition of dental skills in preclinical technique courses: influence of spatial and manual abilities.

PubMed

Schwibbe, Anja; Kothe, Christian; Hampe, Wolfgang; Konradt, Udo

2016-10-01

Sixty years of research have not added up to a concordant evaluation of the influence of spatial and manual abilities on dental skill acquisition. We used Ackerman's theory of ability determinants of skill acquisition to explain the influence of spatial visualization and manual dexterity on the task performance of dental students in two consecutive preclinical technique courses. We measured spatial and manual abilities of applicants to Hamburg Dental School by means of a multiple choice test on Technical Aptitude and a wire-bending test, respectively. Preclinical dental technique tasks were categorized as consistent-simple and inconsistent-complex based on their contents. For analysis, we used robust regression to circumvent typical limitations in dental studies like small sample size and non-normal residual distributions. We found that manual, but not spatial ability exhibited a moderate influence on the performance in consistent-simple tasks during dental skill acquisition in preclinical dentistry. Both abilities revealed a moderate relation with the performance in inconsistent-complex tasks. These findings support the hypotheses which we had postulated on the basis of Ackerman's work. Therefore, spatial as well as manual ability are required for the acquisition of dental skills in preclinical technique courses. These results support the view that both abilities should be addressed in dental admission procedures in addition to cognitive measures.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Combining multiple approaches and optimized data resolution for an improved understanding of stream temperature dynamics of a forested headwater basin in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Belica, L.; Mitasova, H.; Caldwell, P.; McCarter, J. B.; Nelson, S. A. C.

2017-12-01

Thermal regimes of forested headwater streams continue to be an area of active research as climatic, hydrologic, and land cover changes can influence water temperature, a key aspect of aquatic ecosystems. Widespread monitoring of stream temperatures have provided an important data source, yielding insights on the temporal and spatial patterns and the underlying processes that influence stream temperature. However, small forested streams remain challenging to model due to the high spatial and temporal variability of stream temperatures and the climatic and hydrologic conditions that drive them. Technological advances and increased computational power continue to provide new tools and measurement methods and have allowed spatially explicit analyses of dynamic natural systems at greater temporal resolutions than previously possible. With the goal of understanding how current stream temperature patterns and processes may respond to changing landcover and hydroclimatoligical conditions, we combined high-resolution, spatially explicit geospatial modeling with deterministic heat flux modeling approaches using data sources that ranged from traditional hydrological and climatological measurements to emerging remote sensing techniques. Initial analyses of stream temperature monitoring data revealed that high temporal resolution (5 minutes) and measurement resolutions (<0.1°C) were needed to adequately describe diel stream temperature patterns and capture the differences between paired 1st order and 4th order forest streams draining north and south facing slopes. This finding along with geospatial models of subcanopy solar radiation and channel morphology were used to develop hypotheses and guide field data collection for further heat flux modeling. By integrating multiple approaches and optimizing data resolution for the processes being investigated, small, but ecologically significant differences in stream thermal regimes were revealed. In this case, multi-approach research contributed to the identification of the dominant mechanisms driving stream temperature in the study area and advanced our understanding of the current thermal fluxes and how they may change as environmental conditions change in the future.

The U.S. Geological Survey's TRIGA® reactor

USGS Publications Warehouse

DeBey, Timothy M.; Roy, Brycen R.; Brady, Sally R.

2012-01-01

The U.S. Geological Survey (USGS) operates a low-enriched uranium-fueled, pool-type reactor located at the Federal Center in Denver, Colorado. The mission of the Geological Survey TRIGA® Reactor (GSTR) is to support USGS science by providing information on geologic, plant, and animal specimens to advance methods and techniques unique to nuclear reactors. The reactor facility is supported by programs across the USGS and is organizationally under the Associate Director for Energy and Minerals, and Environmental Health. The GSTR is the only facility in the United States capable of performing automated delayed neutron analyses for detecting fissile and fissionable isotopes. Samples from around the world are submitted to the USGS for analysis using the reactor facility. Qualitative and quantitative elemental analyses, spatial elemental analyses, and geochronology are performed. Few research reactor facilities in the United States are equipped to handle the large number of samples processed at the GSTR. Historically, more than 450,000 sample irradiations have been performed at the USGS facility. Providing impartial scientific information to resource managers, planners, and other interested parties throughout the world is an integral part of the research effort of the USGS.

Pulsed-neutron imaging by a high-speed camera and center-of-gravity processing

NASA Astrophysics Data System (ADS)

Mochiki, K.; Uragaki, T.; Koide, J.; Kushima, Y.; Kawarabayashi, J.; Taketani, A.; Otake, Y.; Matsumoto, Y.; Su, Y.; Hiroi, K.; Shinohara, T.; Kai, T.

2018-01-01

Pulsed-neutron imaging is attractive technique in the research fields of energy-resolved neutron radiography and RANS (RIKEN) and RADEN (J-PARC/JAEA) are small and large accelerator-driven pulsed-neutron facilities for its imaging, respectively. To overcome the insuficient spatial resolution of the conunting type imaging detectors like μ NID, nGEM and pixelated detectors, camera detectors combined with a neutron color image intensifier were investigated. At RANS center-of-gravity technique was applied to spots image obtained by a CCD camera and the technique was confirmed to be effective for improving spatial resolution. At RADEN a high-frame-rate CMOS camera was used and super resolution technique was applied and it was recognized that the spatial resolution was futhermore improved.

Major influencing factors of indoor radon concentrations in Switzerland.

PubMed

Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios, Martha; Baechler, Sébastien

2014-03-01

In Switzerland, nationwide large-scale radon surveys have been conducted since the early 1980s to establish the distribution of indoor radon concentrations (IRC). The aim of this work was to study the factors influencing IRC in Switzerland using univariate analyses that take into account biases caused by spatial irregularities of sampling. About 212,000 IRC measurements carried out in more than 136,000 dwellings were available for this study. A probability map to assess risk of exceeding an IRC of 300 Bq/m(3) was produced using basic geostatistical techniques. Univariate analyses of IRC for different variables, namely the type of radon detector, various building characteristics such as foundation type, year of construction and building type, as well as the altitude, the average outdoor temperature during measurement and the lithology, were performed comparing 95% confidence intervals among classes of each variable. Furthermore, a map showing the spatial aggregation of the number of measurements was generated for each class of variable in order to assess biases due to spatially irregular sampling. IRC measurements carried out with electret detectors were 35% higher than measurements performed with track detectors. Regarding building characteristics, the IRC of apartments are significantly lower than individual houses. Furthermore, buildings with concrete foundations have the lowest IRC. A significant decrease in IRC was found in buildings constructed after 1900 and again after 1970. Moreover, IRC decreases at higher outdoor temperatures. There is also a tendency to have higher IRC with altitude. Regarding lithology, carbonate rock in the Jura Mountains produces significantly higher IRC, almost by a factor of 2, than carbonate rock in the Alps. Sedimentary rock and sediment produce the lowest IRC while carbonate rock from the Jura Mountains and igneous rock produce the highest IRC. Potential biases due to spatially unbalanced sampling of measurements were identified for several influencing factors. Significant associations were found between IRC and all variables under study. However, we showed that the spatial distribution of samples strongly affected the relevance of those associations. Therefore, future methods to estimate local radon hazards should take the multidimensionality of the process of IRC into account. Copyright © 2013 Elsevier Ltd. All rights reserved.

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

Advanced Corrections for InSAR Using GPS and Numerical Weather Models

NASA Astrophysics Data System (ADS)

Cossu, F.; Foster, J. H.; Amelung, F.; Varugu, B. K.; Businger, S.; Cherubini, T.

2017-12-01

We present results from an investigation into the application of numerical weather models for generating tropospheric correction fields for Interferometric Synthetic Aperture Radar (InSAR). We apply the technique to data acquired from a UAVSAR campaign as well as from the CosmoSkyMed satellites. The complex spatial and temporal changes in the atmospheric propagation delay of the radar signal remain the single biggest factor limiting InSAR's potential for hazard monitoring and mitigation. A new generation of InSAR systems is being built and launched, and optimizing the science and hazard applications of these systems requires advanced methodologies to mitigate tropospheric noise. We use the Weather Research and Forecasting (WRF) model to generate a 900 m spatial resolution atmospheric models covering the Big Island of Hawaii and an even higher, 300 m resolution grid over the Mauna Loa and Kilauea volcanoes. By comparing a range of approaches, from the simplest, using reanalyses based on typically available meteorological observations, through to the "kitchen-sink" approach of assimilating all relevant data sets into our custom analyses, we examine the impact of the additional data sets on the atmospheric models and their effectiveness in correcting InSAR data. We focus particularly on the assimilation of information from the more than 60 GPS sites in the island. We ingest zenith tropospheric delay estimates from these sites directly into the WRF analyses, and also perform double-difference tomography using the phase residuals from the GPS processing to robustly incorporate heterogeneous information from the GPS data into the atmospheric models. We assess our performance through comparisons of our atmospheric models with external observations not ingested into the model, and through the effectiveness of the derived phase screens in reducing InSAR variance. Comparison of the InSAR data, our atmospheric analyses, and assessments of the active local and mesoscale meteorological processes allows us to assess under what conditions the technique works most effectively. This work will produce best-practice recommendations for the use of weather models for InSAR correction, and inform efforts to design a global strategy for the NISAR mission, for both low-latency and definitive atmospheric correction products.

DEFINITION OF MULTIVARIATE GEOCHEMICAL ASSOCIATIONS WITH POLYMETALLIC MINERAL OCCURRENCES USING A SPATIALLY DEPENDENT CLUSTERING TECHNIQUE AND RASTERIZED STREAM SEDIMENT DATA - AN ALASKAN EXAMPLE.

USGS Publications Warehouse

Jenson, Susan K.; Trautwein, C.M.

1984-01-01

The application of an unsupervised, spatially dependent clustering technique (AMOEBA) to interpolated raster arrays of stream sediment data has been found to provide useful multivariate geochemical associations for modeling regional polymetallic resource potential. The technique is based on three assumptions regarding the compositional and spatial relationships of stream sediment data and their regional significance. These assumptions are: (1) compositionally separable classes exist and can be statistically distinguished; (2) the classification of multivariate data should minimize the pair probability of misclustering to establish useful compositional associations; and (3) a compositionally defined class represented by three or more contiguous cells within an array is a more important descriptor of a terrane than a class represented by spatial outliers.

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

PubMed

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

2018-05-22

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

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

2005-01-01

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Multi-Scale Modeling to Improve Single-Molecule, Single-Cell Experiments

NASA Astrophysics Data System (ADS)

Munsky, Brian; Shepherd, Douglas

2014-03-01

Single-cell, single-molecule experiments are producing an unprecedented amount of data to capture the dynamics of biological systems. When integrated with computational models, observations of spatial, temporal and stochastic fluctuations can yield powerful quantitative insight. We concentrate on experiments that localize and count individual molecules of mRNA. These high precision experiments have large imaging and computational processing costs, and we explore how improved computational analyses can dramatically reduce overall data requirements. In particular, we show how analyses of spatial, temporal and stochastic fluctuations can significantly enhance parameter estimation results for small, noisy data sets. We also show how full probability distribution analyses can constrain parameters with far less data than bulk analyses or statistical moment closures. Finally, we discuss how a systematic modeling progression from simple to more complex analyses can reduce total computational costs by orders of magnitude. We illustrate our approach using single-molecule, spatial mRNA measurements of Interleukin 1-alpha mRNA induction in human THP1 cells following stimulation. Our approach could improve the effectiveness of single-molecule gene regulation analyses for many other process.

Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

NASA Astrophysics Data System (ADS)

Köhler, P.; Huth, A.

2010-08-01

The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb) with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60%) between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques such as LIDAR and radar interferometry have the potential to quantify the carbon contained in the vegetation, although this calculation contains due to the heterogeneity of the forest landscape structural uncertainties which restrict future applications to spatial averages of about one hectare in size. The uncertainties in AGB for a given canopy height are here 20-40% (95% confidence level) corresponding to a standard deviation of less than ± 10%. This uncertainty on the 1 ha-scale is much smaller than in the analysis of 0.04 ha-scale data. At this small scale (0.04 ha) AGB can only be calculated out of canopy height with an uncertainty which is at least of the magnitude of the signal itself due to the natural spatial heterogeneity of these forests.

Physics Mining of Multi-Source Data Sets

NASA Technical Reports Server (NTRS)

Helly, John; Karimabadi, Homa; Sipes, Tamara

2012-01-01

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images

NASA Technical Reports Server (NTRS)

Memon, Nasir D.; Galatsanos, Nikolas

1995-01-01

In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.

Implications of different digital elevation models and preprocessing techniques to delineate debris flow inundation hazard zones in El Salvador

NASA Astrophysics Data System (ADS)

Anderson, E. R.; Griffin, R.; Irwin, D.

2013-12-01

Heavy rains and steep, volcanic slopes in El Salvador cause numerous landslides every year, posing a persistent threat to the population, economy and environment. Although potential debris inundation hazard zones have been delineated using digital elevation models (DEMs), some disparities exist between the simulated zones and actual affected areas. Moreover, these hazard zones have only been identified for volcanic lahars and not the shallow landslides that occur nearly every year. This is despite the availability of tools to delineate a variety of landslide types (e.g., the USGS-developed LAHARZ software). Limitations in DEM spatial resolution, age of the data, and hydrological preprocessing techniques can contribute to inaccurate hazard zone definitions. This study investigates the impacts of using different elevation models and pit filling techniques in the final debris hazard zone delineations, in an effort to determine which combination of methods most closely agrees with observed landslide events. In particular, a national DEM digitized from topographic sheets from the 1970s and 1980s provide an elevation product at a 10 meter resolution. Both natural and anthropogenic modifications of the terrain limit the accuracy of current landslide hazard assessments derived from this source. Global products from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM) offer more recent data but at the cost of spatial resolution. New data derived from the NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) in 2013 provides the opportunity to update hazard zones at a higher spatial resolution (approximately 6 meters). Hydrological filling of sinks or pits for current hazard zone simulation has previously been achieved through ArcInfo spatial analyst. Such hydrological processing typically only fills pits and can lead to drastic modifications of original elevation values. Optimized pit filling techniques use both cut and fill operations to minimize modifications of the original DEM. Satellite image interpretation and field surveying provide the baseline upon which to test the accuracy of each model simulation. By outlining areas that could potentially be inundated by debris flows, these efforts can be used to more accurately identify the places and assets immediately exposed to landslide hazards. We contextualize the results of the previous and ongoing efforts into how they may be incorporated into decision support systems. We also discuss if and how these analyses would have provided additional knowledge in the past, and identify specific recommendations as to how they could contribute to a more robust decision support system in the future.

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

NASA Astrophysics Data System (ADS)

Conen, N.; Hastedt, H.; Kahmen, O.; Luhmann, T.

2018-05-01

In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud. To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results. However, the filter may influence the camera's orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002) using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (Δc ≤ 4 μm) with the polarising filter in use. Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.

Analytical Analyses of Spatial and Temporal Characteristics of Infiltrated Water for Managed Aquifer Recharge

NASA Astrophysics Data System (ADS)

Zlotnik, V. A.; Ledder, G.; Kacimov, A. R.

2014-12-01

Disposal of excessive runoff or treated sewage into wadis and ephemeral streams is a common practice and an important hydrological problem in many Middle Eastern countries. While chemical and biological properties of the injected treated wastewater may be different from those of the receiving aquifer, the density contrast between the two fluids can be small. Therefore, studies of the fluid interface for variable density fluids or water intrusion are not directly relevant in many Managed Aquifer Recharge (MAR) problems. Other factors, such as the transient nature of injection and lack of detailed aquifer information must be considered. The disposed water reaching the water table through the vadose zone creates groundwater mounds, deforms the original water table, and develops finite-size convex-concave lenses of treated water over receiving water. After cessation of infiltration, these mounds flatten, water levels become horizontal, and infiltrated water becomes fully embedded in the receiving aquifer. The shape of the treated water body is controlled by the aquifer parameters, the magnitude of ambient flow, and the duration, rate, and cyclicity of infiltration. In case of limited aquifer data, advective transport modeling offers the most appropriate tools for predicting plume shapes over time, but surprisingly little work has been done on this important 3D flow problem. We investigate the lateral and vertical spreading of infiltrated water combining techniques of spatial velocity analyses by Zlotnik and Ledder (1992, 1993) with particle tracking. This approach allows for evaluating the geometry of the plume and the protection zone, the flow development phases, and other temporal and spatial effects and results can be used in conditions of limited data availability and quality. (Funding was provided by the USAID, DAI Subcontract 1001624-12S-19745)

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

PubMed

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

2018-04-30

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

Quantitative Characterisation and Analysis of Siliciclastic Fluvial Depositional Systems Using 3D Digital Outcrop Models

NASA Astrophysics Data System (ADS)

Burnham, Brian Scott

Outcrop analogue studies of fluvial sedimentary systems are often undertaken to identify spatial and temporal characteristics (e.g. stacking patterns, lateral continuity, lithofacies proportions). However, the lateral extent typically exceeds that of the exposure, and/or the true width and thickness are not apparent. Accurate characterisation of fluvial sand bodies is integral for accurate identification and subsequent modelling of aquifer and hydrocarbon reservoir architecture. The studies presented in this thesis utilise techniques that integrate lidar, highresolution photography and differential geospatial measurements, to create accurate three-dimensional (3D) digital outcrop models (DOMs) of continuous 3D and laterally extensive 2D outcrop exposures. The sedimentary architecture of outcrops in the medial portion of a large Distributive Fluvial System (DFS) (Huesca fluvial fan) in the Ebro Basin, north-east Spain, and in the fluvio-deltaic succession of the Breathitt Group in the eastern Appalachian Basin, USA, are evaluated using traditional sedimentological and digital outcrop analytical techniques. The major sand bodies in the study areas are quantitatively analysed to accurately characterise spatial and temporal changes in sand body architecture, from two different outcrop exposure types and scales. Several stochastic reservoir simulations were created to approximate fluvial sand body lithological component and connectivity within the medial portion of the Huesca DFS. Results demonstrate a workflow and current methodology adaptation of digital outcrop techniques required for each study to approximate true geobody widths, thickness and characterise architectural patterns (internal and external) of major fluvial sand bodies interpreted as products of DFSs in the Huesca fluvial fan, and both palaeovalleys and progradational DFSs in the Pikeville and Hyden Formations in the Breathitt Group. The results suggest key geostatistical metrics, which are translatable across any fluvial system that can be used to analyse 3D digital outcrop data, and identify spatial attributes of sand bodies to identify their genetic origin and lithological component within fluvial reservoir systems, and the rock record. 3D quantitative analysis of major sand bodies have allowed more accurate width vs. thickness relationships within the La Serreta area, showing a vertical increase in width and channel-fill facies, and demonstrates a 22% increase of in-channel facies from previous interpretations. Additionally, identification of deposits that are products of a nodal avulsion event have been characterised and are interpreted to be the cause for the increase in width and channel-fill facies. Furthermore, analysis of the Pikeville and Hyden Fms contain sand bodies of stacked distributaries and palaeovalleys, as previously interpreted, and demonstrates that a 3D spatial approach to determine basin-wide architectural trends is integral to identifying the genetic origin, and preservation potential of sand bodies of both palaeovalleys and distributive fluvial systems. The resultant geostatistics assimilated in the thesis demonstrates the efficacy of integrated lidar studies of outcrop analogues, and provide empirical relationships which can be applied to subsurface analogues for reservoir model development and the distribution of both DFS and palaeovalley depositional systems in the rock record.

A spatially constrained ecological classification: rationale, methodology and implementation

Treesearch

Franz Mora; Louis Iverson; Louis Iverson

2002-01-01

The theory, methodology and implementation for an ecological and spatially constrained classification are presented. Ecological and spatial relationships among several landscape variables are analyzed in order to define a new approach for a landscape classification. Using ecological and geostatistical analyses, several ecological and spatial weights are derived to...

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Bhardwaj, Kaushal; Patra, Swarnajyoti

2018-04-01

Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

Multi-Criteria GIS Analyses with the Use of Uavs for the Needs of Spatial Planning

NASA Astrophysics Data System (ADS)

Zawieska, D.; Markiewicz, J.; Turek, A.; Bakuła, K.; Kowalczyk, M.; Kurczyński, Z.; Ostrowski, W.; Podlasiak, P.

2016-06-01

Utilization of Unmanned Aerial Systems (UAVs) in agriculture, forestry, or other environmental contexts has recently become common. However, in the case of spatial planning, the role of UAVs still seems to be underestimated. At present, sections of municipal development use UAVs mainly for promotional purposes (films, folders, brochures, etc.). The use of UAVs for spatial management provides results, first of all, in the form of savings in human resources and time; however, more frequently, it is also connected with financial savings (given the decreasing cost of UAVs and photogrammetric software). The performed research presented here relates to the possibilities of using UAVs to update planning documents, and, in particular, to update the study of conditions and directions of spatial management and preparation of local plans for physical management. Based on acquired photographs with a resolution of 3 cm, a cloud of points is generated, as well as 3D models and the true orthophotomap. These data allow multi-criteria spatial analyses. Additionally, directions of development and changes in physical management are analysed for the given area.

Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.

2016-12-01

Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.

Legal Implications of Nuclear Propulsion for Space Objects

NASA Astrophysics Data System (ADS)

Pop, V.

2002-01-01

This paper is intended to examine nuclear propulsion concepts such as "Project Orion", "Project Daedalus", NERVA, VASIMIR, from the legal point of view. The UN Principles Relevant to the Use of Nuclear Power Sources in Outer Space apply to nuclear power sources in outer space devoted to the generation of electric power on board space objects for non-propulsive purposes, and do not regulate the use of nuclear energy as a means of propulsion. However, nuclear propulsion by means of detonating atomic bombs (ORION) is, in principle, banned under the 1963 Treaty Banning Nuclear Weapon Tests in the Atmosphere, in Outer Space, and Under Water. The legality of use of nuclear propulsion will be analysed from different approaches - historical (i.e. the lawfulness of these projects at the time of their proposal, at the present time, and in the future - in the light of the mutability and evolution of international law), spatial (i.e. the legal regime governing peaceful nuclear explosions in different spatial zones - Earth atmosphere, Earth orbit, Solar System, and interstellar space), and technical (i.e, the legal regime applicable to different nuclear propulsion techniques, and to the various negative effects - e.g. damage to other space systems as an effect of the electromagnetic pulse, etc). The paper will analyse the positive law, and will also come with suggestions "de lege ferenda".

Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework

USGS Publications Warehouse

Godt, J.W.; Baum, R.L.; Savage, W.Z.; Salciarini, D.; Schulz, W.H.; Harp, E.L.

2008-01-01

Application of transient deterministic shallow landslide models over broad regions for hazard and susceptibility assessments requires information on rainfall, topography and the distribution and properties of hillside materials. We survey techniques for generating the spatial and temporal input data for such models and present an example using a transient deterministic model that combines an analytic solution to assess the pore-pressure response to rainfall infiltration with an infinite-slope stability calculation. Pore-pressures and factors of safety are computed on a cell-by-cell basis and can be displayed or manipulated in a grid-based GIS. Input data are high-resolution (1.8??m) topographic information derived from LiDAR data and simple descriptions of initial pore-pressure distribution and boundary conditions for a study area north of Seattle, Washington. Rainfall information is taken from a previously defined empirical rainfall intensity-duration threshold and material strength and hydraulic properties were measured both in the field and laboratory. Results are tested by comparison with a shallow landslide inventory. Comparison of results with those from static infinite-slope stability analyses assuming fixed water-table heights shows that the spatial prediction of shallow landslide susceptibility is improved using the transient analyses; moreover, results can be depicted in terms of the rainfall intensity and duration known to trigger shallow landslides in the study area.

Seasonal and biogeographical patterns of gastrointestinal parasites in large carnivores: wolves in a coastal archipelago.

PubMed

Bryan, Heather M; Darimont, Chris T; Hill, Janet E; Paquet, Paul C; Thompson, R C Andrew; Wagner, Brent; Smits, Judit E G

2012-05-01

Parasites are increasingly recognized for their profound influences on individual, population and ecosystem health. We provide the first report of gastrointestinal parasites in gray wolves from the central and north coasts of British Columbia, Canada. Across 60 000 km(2), wolf feces were collected from 34 packs in 2005-2008. At a smaller spatial scale (3300 km(2)), 8 packs were sampled in spring and autumn. Parasite eggs, larvae, and cysts were identified using standard flotation techniques and morphology. A subset of samples was analysed by PCR and sequencing to identify tapeworm eggs (n=9) and Giardia cysts (n=14). We detected ≥14 parasite taxa in 1558 fecal samples. Sarcocystis sporocysts occurred most frequently in feces (43·7%), followed by taeniid eggs (23·9%), Diphyllobothrium eggs (9·1%), Giardia cysts (6·8%), Toxocara canis eggs (2·1%), and Cryptosporidium oocysts (1·7%). Other parasites occurred in ≤1% of feces. Genetic analyses revealed Echinococcus canadensis strains G8 and G10, Taenia ovis krabbei, Diphyllobothrium nehonkaiense, and Giardia duodenalis assemblages A and B. Parasite prevalence differed between seasons and island/mainland sites. Patterns in parasite prevalence reflect seasonal and spatial resource use by wolves and wolf-salmon associations. These data provide a unique, extensive and solid baseline for monitoring parasite community structure in relation to environmental change.

Ecogeographic Genetic Epidemiology

PubMed Central

Sloan, Chantel D.; Duell, Eric J.; Shi, Xun; Irwin, Rebecca; Andrew, Angeline S.; Williams, Scott M.; Moore, Jason H.

2009-01-01

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial “clusters” of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic Information Systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence. PMID:19025788

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Fractals and Spatial Methods for Mining Remote Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina; Emerson, Charles; Quattrochi, Dale

2003-01-01

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Deriving spatial patterns from a novel database of volcanic rock geochemistry in the Virunga Volcanic Province, East African Rift

NASA Astrophysics Data System (ADS)

Poppe, Sam; Barette, Florian; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2016-04-01

The Virunga Volcanic Province (VVP) is situated within the western branch of the East-African Rift. The geochemistry and petrology of its' volcanic products has been studied extensively in a fragmented manner. They represent a unique collection of silica-undersaturated, ultra-alkaline and ultra-potassic compositions, displaying marked geochemical variations over the area occupied by the VVP. We present a novel spatially-explicit database of existing whole-rock geochemical analyses of the VVP volcanics, compiled from international publications, (post-)colonial scientific reports and PhD theses. In the database, a total of 703 geochemical analyses of whole-rock samples collected from the 1950s until recently have been characterised with a geographical location, eruption source location, analytical results and uncertainty estimates for each of these categories. Comparative box plots and Kruskal-Wallis H tests on subsets of analyses with contrasting ages or analytical methods suggest that the overall database accuracy is consistent. We demonstrate how statistical techniques such as Principal Component Analysis (PCA) and subsequent cluster analysis allow the identification of clusters of samples with similar major-element compositions. The spatial patterns represented by the contrasting clusters show that both the historically active volcanoes represent compositional clusters which can be identified based on their contrasted silica and alkali contents. Furthermore, two sample clusters are interpreted to represent the most primitive, deep magma source within the VVP, different from the shallow magma reservoirs that feed the eight dominant large volcanoes. The samples from these two clusters systematically originate from locations which 1. are distal compared to the eight large volcanoes and 2. mostly coincide with the surface expressions of rift faults or NE-SW-oriented inherited Precambrian structures which were reactivated during rifting. The lava from the Mugogo eruption of 1957 belongs to these primitive clusters and is the only known to have erupted outside the current rift valley in historical times. We thus infer there is a distributed hazard of vent opening susceptibility additional to the susceptibility associated with the main Virunga edifices. This study suggests that the statistical analysis of such geochemical database may help to understand complex volcanic plumbing systems and the spatial distribution of volcanic hazards in active and poorly known volcanic areas such as the Virunga Volcanic Province.

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

Treesearch

Mark Spencer; Kevin O' Hara

2006-01-01

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

Algorithm for Identifying Erroneous Rain-Gauge Readings

NASA Technical Reports Server (NTRS)

Rickman, Doug

2005-01-01

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

In vivo correlation mapping microscopy

NASA Astrophysics Data System (ADS)

McGrath, James; Alexandrov, Sergey; Owens, Peter; Subhash, Hrebesh; Leahy, Martin

2016-04-01

To facilitate regular assessment of the microcirculation in vivo, noninvasive imaging techniques such as nailfold capillaroscopy are required in clinics. Recently, a correlation mapping technique has been applied to optical coherence tomography (OCT), which extends the capabilities of OCT to microcirculation morphology imaging. This technique, known as correlation mapping optical coherence tomography, has been shown to extract parameters, such as capillary density and vessel diameter, and key clinical markers associated with early changes in microvascular diseases. However, OCT has limited spatial resolution in both the transverse and depth directions. Here, we extend this correlation mapping technique to other microscopy modalities, including confocal microscopy, and take advantage of the higher spatial resolution offered by these modalities. The technique is achieved as a processing step on microscopy images and does not require any modification to the microscope hardware. Results are presented which show that this correlation mapping microscopy technique can extend the capabilities of conventional microscopy to enable mapping of vascular networks in vivo with high spatial resolution in both the transverse and depth directions.

Optical spatial heterodyne interferometric Fourier transform technique (OSHIFT) and a resulting interferometer

NASA Astrophysics Data System (ADS)

Georges, James A., III

2007-09-01

This article reports on the novel patent pending Optical Spatial Heterodyne Interferometric Fourier Transform Technique (the OSHIFT technique), the resulting interferometer also referred to as OSHIFT, and its preliminary results. OSHIFT was borne out of the following requirements: wavefront sensitivity on the order of 1/100 waves, high-frequency wavefront spatial sampling, snapshot 100Hz operation, and the ability to deal with discontinuous wavefronts. The first two capabilities lend themselves to the use of traditional interferometric techniques; however, the last two prove difficult for standard techniques, e.g., phase shifting interferometry tends to take a time sequence of images and most interferometers require estimation of a center fringe across wavefront discontinuities. OSHIFT overcomes these challenges by employing a spatial heterodyning concept in the Fourier (image) plane of the optic-under-test. This concept, the mathematical theory, an autocorrelation view of operation, and the design with results of OSHIFT will be discussed. Also discussed will be future concepts such as a sensor that could interrogate an entire imaging system as well as a methodology to create innovative imaging systems that encode wavefront information onto the image. Certain techniques and systems described in this paper are the subject of a patent application currently pending in the United States Patent Office.

Spatial and seasonal dynamics of brook trout populations inhabiting a central Appalachian watershed

USGS Publications Warehouse

Petty, J.T.; Lamothe, P.J.; Mazik, P.M.

2005-01-01

We quantified the watershed-scale spatial population dynamics of brook trout Salvelinus fontinalis in the Second Fork, a third-order tributary of Shavers Fork in eastern West Virginia. We used visual surveys, electrofishing, and mark-recapture techniques to quantify brook trout spawning intensity, population density, size structure, and demographic rates (apparent survival and immigration) throughout the watershed. Our analyses produced the following results. Spawning by brook trout was concentrated in streams with small basin areas (i.e., segments draining less than 3 km2), relatively high alkalinity (>10 mg CaCO3/L), and high amounts of instream cover. The spatial distribution of juvenile and small-adult brook trout within the watershed was relatively stable and was significantly correlated with spawning intensity. However, no such relationship was observed for large adults, which exhibited highly variable distribution patterns related to seasonally important habitat features, including instream cover, stream depth and width, and riparian canopy cover. Brook trout survival and immigration rates varied seasonally, spatially, and among size-classes. Differential survival and immigration tended to concentrate juveniles and small adults in small, alkaline streams, whereas dispersal tended to redistribute large adults at the watershed scale. Our results suggest that spatial and temporal variations in spawning, survival, and movement interact to determine the distribution, abundance, and size structure of brook trout populations at a watershed scale. These results underscore the importance of small tributaries for the persistence of brook trout in this watershed and the need to consider watershed-scale processes when designing management plans for Appalachian brook trout populations. ?? Copyright by the American Fisheries Society 2005.

Remote Monitoring of Groundwater Overdraft Using GRACE and InSAR

NASA Astrophysics Data System (ADS)

Scher, C.; Saah, D.

2017-12-01

Gravity Recovery and Climate Experiment (GRACE) data paired with radar-derived analyses of volumetric changes in aquifer storage capacity present a viable technique for remote monitoring of aquifer depletion. Interferometric Synthetic Aperture Radar (InSAR) analyses of ground level subsidence can account for a significant portion of mass loss observed in GRACE data and provide information on point-sources of overdraft. This study summed one water-year of GRACE monthly mass change grids and delineated regions with negative water storage anomalies for further InSAR analyses. Magnitude of water-storage anomalies observed by GRACE were compared to InSAR-derived minimum volumetric changes in aquifer storage capacity as a result of measurable compaction at the surface. Four major aquifers were selected within regions where GRACE observed a net decrease in water storage (Central Valley, California; Mekong Delta, Vietnam; West Bank, occupied Palestinian Territory; and the Indus Basin, South Asia). Interferogram imagery of the extent and magnitude of subsidence within study regions provided estimates for net minimum volume of groundwater extracted between image acquisitions. These volumetric estimates were compared to GRACE mass change grids to resolve a percent contribution of mass change observed by GRACE likely due to groundwater overdraft. Interferograms revealed characteristic cones of depression within regions of net mass loss observed by GRACE, suggesting point-source locations of groundwater overdraft and demonstrating forensic potential for the use of InSAR and GRACE data in remote monitoring of aquifer depletion. Paired GRACE and InSAR analyses offer a technique to increase the spatial and temporal resolution of remote applications for monitoring groundwater overdraft in addition to providing a novel parameter - measurable vertical deformation at the surface - to global groundwater models.

Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier and Spatial Domain Techniques

DTIC Science & Technology

2012-09-01

Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain techniques Peter N. Crabtree, Collin Seanor...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain...demonstrate performance of a hybrid algorithm . These results are from analysis of a set of images of an ISO 12233 [12] resolution chart captured in the

Optimization techniques for integrating spatial data

USGS Publications Warehouse

Herzfeld, U.C.; Merriam, D.F.

1995-01-01

Two optimization techniques ta predict a spatial variable from any number of related spatial variables are presented. The applicability of the two different methods for petroleum-resource assessment is tested in a mature oil province of the Midcontinent (USA). The information on petroleum productivity, usually not directly accessible, is related indirectly to geological, geophysical, petrographical, and other observable data. This paper presents two approaches based on construction of a multivariate spatial model from the available data to determine a relationship for prediction. In the first approach, the variables are combined into a spatial model by an algebraic map-comparison/integration technique. Optimal weights for the map comparison function are determined by the Nelder-Mead downhill simplex algorithm in multidimensions. Geologic knowledge is necessary to provide a first guess of weights to start the automatization, because the solution is not unique. In the second approach, active set optimization for linear prediction of the target under positivity constraints is applied. Here, the procedure seems to select one variable from each data type (structure, isopachous, and petrophysical) eliminating data redundancy. Automating the determination of optimum combinations of different variables by applying optimization techniques is a valuable extension of the algebraic map-comparison/integration approach to analyzing spatial data. Because of the capability of handling multivariate data sets and partial retention of geographical information, the approaches can be useful in mineral-resource exploration. ?? 1995 International Association for Mathematical Geology.

Implications of cellular models of dopamine neurons for disease

PubMed Central

Evans, Rebekah C.; Oster, Andrew M.; Pissadaki, Eleftheria K.; Drion, Guillaume; Kuznetsov, Alexey S.; Gutkin, Boris S.

2016-01-01

This review addresses the present state of single-cell models of the firing pattern of midbrain dopamine neurons and the insights that can be gained from these models into the underlying mechanisms for diseases such as Parkinson's, addiction, and schizophrenia. We will explain the analytical technique of separation of time scales and show how it can produce insights into mechanisms using simplified single-compartment models. We also use morphologically realistic multicompartmental models to address spatially heterogeneous aspects of neural signaling and neural metabolism. Separation of time scale analyses are applied to pacemaking, bursting, and depolarization block in dopamine neurons. Differences in subpopulations with respect to metabolic load are addressed using multicompartmental models. PMID:27582295

Using image mapping towards biomedical and biological data sharing

PubMed Central

2013-01-01

Image-based data integration in eHealth and life sciences is typically concerned with the method used for anatomical space mapping, needed to retrieve, compare and analyse large volumes of biomedical data. In mapping one image onto another image, a mechanism is used to match and find the corresponding spatial regions which have the same meaning between the source and the matching image. Image-based data integration is useful for integrating data of various information structures. Here we discuss a broad range of issues related to data integration of various information structures, review exemplary work on image representation and mapping, and discuss the challenges that these techniques may bring. PMID:24059352

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Discrimination of Closely-Spaced Geosynchronous Satellites - Phase Curve Analysis & New Small Business Innovative Research (SBIR) Efforts

NASA Astrophysics Data System (ADS)

Levan, P.

2010-09-01

Geosynchronous objects appear as unresolved blurs even when observed with the largest ground-based telescopes. Due to the lack of any spatial detail, two or more objects appearing at similar brightness levels within the spectral bandpass they are observed are difficult to distinguish. Observing a changing pattern of such objects from one time epoch to another showcases the deficiencies in associating individual objects before and after the configuration change. This paper explores solutions to this deficiency in the form of spectral (under small business innovative research) and phase curve analyses. The extension of the technique to phase curves proves to be a powerful new capability.

Clouds and the Earth's Radiant Energy System (CERES) algorithm theoretical basis document. volume 2; Geolocation, calibration, and ERBE-like analyses (subsystems 1-3)

NASA Technical Reports Server (NTRS)

Wielicki, B. A. (Principal Investigator); Barkstrom, B. R. (Principal Investigator); Charlock, T. P.; Baum, B. A.; Green, R. N.; Minnis, P.; Smith, G. L.; Coakley, J. A.; Randall, D. R.; Lee, R. B., III

1995-01-01

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 2 details the techniques used to geolocate and calibrate the CERES scanning radiometer measurements of shortwave and longwave radiance to invert the radiances to top-of-the-atmosphere (TOA) and surface fluxes following the Earth Radiation Budget Experiment (ERBE) approach, and to average the fluxes over various time and spatial scales to produce an ERBE-like product. Spacecraft ephemeris and sensor telemetry are used with calibration coefficients to produce a chronologically ordered data product called bidirectional scan (BDS) radiances. A spatially organized instrument Earth scan product is developed for the cloud-processing subsystem. The ERBE-like inversion subsystem converts BDS radiances to unfiltered instantaneous TOA and surface fluxes. The TOA fluxes are determined by using established ERBE techniques. Hourly TOA fluxes are computed from the instantaneous values by using ERBE methods. Hourly surface fluxes are estimated from TOA fluxes by using simple parameterizations based on recent research. The averaging process produces daily, monthly-hourly, and monthly means of TOA and surface fluxes at various scales. This product provides a continuation of the ERBE record.

Assessment of synthetic image fidelity

NASA Astrophysics Data System (ADS)

Mitchell, Kevin D.; Moorhead, Ian R.; Gilmore, Marilyn A.; Watson, Graham H.; Thomson, Mitch; Yates, T.; Troscianko, Tomasz; Tolhurst, David J.

2000-07-01

Computer generated imagery is increasingly used for a wide variety of purposes ranging from computer games to flight simulators to camouflage and sensor assessment. The fidelity required for this imagery is dependent on the anticipated use - for example when used for camouflage design it must be physically correct spectrally and spatially. The rendering techniques used will also depend upon the waveband being simulated, spatial resolution of the sensor and the required frame rate. Rendering of natural outdoor scenes is particularly demanding, because of the statistical variation in materials and illumination, atmospheric effects and the complex geometric structures of objects such as trees. The accuracy of the simulated imagery has tended to be assessed subjectively in the past. First and second order statistics do not capture many of the essential characteristics of natural scenes. Direct pixel comparison would impose an unachievable demand on the synthetic imagery. For many applications, such as camouflage design, it is important that nay metrics used will work in both visible and infrared wavebands. We are investigating a variety of different methods of comparing real and synthetic imagery and comparing synthetic imagery rendered to different levels of fidelity. These techniques will include neural networks (ICA), higher order statistics and models of human contrast perception. This paper will present an overview of the analyses we have carried out and some initial results along with some preliminary conclusions regarding the fidelity of synthetic imagery.

Spatially explicit spectral analysis of point clouds and geospatial data

USGS Publications Warehouse

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.

A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

NASA Astrophysics Data System (ADS)

Mayer, J. M.; Stead, D.

2017-04-01

With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

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

NASA Astrophysics Data System (ADS)

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

2014-02-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Color selectivity of the spatial congruency effect: evidence from the focused attention paradigm.

PubMed

Makovac, Elena; Gerbino, Walter

2014-01-01

The multisensory response enhancement (MRE), occurring when the response to a visual target integrated with a spatially congruent sound is stronger than the response to the visual target alone, is believed to be mediated by the superior colliculus (SC) (Stein & Meredith, 1993). Here, we used a focused attention paradigm to show that the spatial congruency effect occurs with red (SC-effective) but not blue (SC-ineffective) visual stimuli, when presented with spatially congruent sounds. To isolate the chromatic component of SC-ineffective targets and to demonstrate the selectivity of the spatial congruency effect we used the random luminance modulation technique (Experiment 1) and the tritanopic technique (Experiment 2). Our results indicate that the spatial congruency effect does not require the distribution of attention over different sensory modalities and provide correlational evidence that the SC mediates the effect.

Detecting Spatial Patterns in Biological Array Experiments

PubMed Central

ROOT, DAVID E.; KELLEY, BRIAN P.; STOCKWELL, BRENT R.

2005-01-01

Chemical genetic screening and DNA and protein microarrays are among a number of increasingly important and widely used biological research tools that involve large numbers of parallel experiments arranged in a spatial array. It is often difficult to ensure that uniform experimental conditions are present throughout the entire array, and as a result, one often observes systematic spatially correlated errors, especially when array experiments are performed using robots. Here, the authors apply techniques based on the discrete Fourier transform to identify and quantify spatially correlated errors superimposed on a spatially random background. They demonstrate that these techniques are effective in identifying common spatially systematic errors in high-throughput 384-well microplate assay data. In addition, the authors employ a statistical test to allow for automatic detection of such errors. Software tools for using this approach are provided. PMID:14567791

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

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

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Spatial regression test for ensuring temperature data quality in southern Spain

NASA Astrophysics Data System (ADS)

Estévez, J.; Gavilán, P.; García-Marín, A. P.

2018-01-01

Quality assurance of meteorological data is crucial for ensuring the reliability of applications and models that use such data as input variables, especially in the field of environmental sciences. Spatial validation of meteorological data is based on the application of quality control procedures using data from neighbouring stations to assess the validity of data from a candidate station (the station of interest). These kinds of tests, which are referred to in the literature as spatial consistency tests, take data from neighbouring stations in order to estimate the corresponding measurement at the candidate station. These estimations can be made by weighting values according to the distance between the stations or to the coefficient of correlation, among other methods. The test applied in this study relies on statistical decision-making and uses a weighting based on the standard error of the estimate. This paper summarizes the results of the application of this test to maximum, minimum and mean temperature data from the Agroclimatic Information Network of Andalusia (southern Spain). This quality control procedure includes a decision based on a factor f, the fraction of potential outliers for each station across the region. Using GIS techniques, the geographic distribution of the errors detected has been also analysed. Finally, the performance of the test was assessed by evaluating its effectiveness in detecting known errors.

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

The nature of giant clumps in distant galaxies probed by the anatomy of the cosmic snake

NASA Astrophysics Data System (ADS)

Cava, Antonio; Schaerer, Daniel; Richard, Johan; Pérez-González, Pablo G.; Dessauges-Zavadsky, Miroslava; Mayer, Lucio; Tamburello, Valentina

2018-01-01

Giant stellar clumps are ubiquitous in high-redshift galaxies1,2. They are thought to play an important role in the build-up of galactic bulges3 and as diagnostics of star formation feedback in galactic discs4. Hubble Space Telescope (HST) blank field imaging surveys have estimated that these clumps have masses of up to 109.5 M⊙ and linear sizes of ≳1 kpc5,6. Recently, gravitational lensing has also been used to get higher spatial resolution7-9. However, both recent lensed observations10,11 and models12,13 suggest that the clumps' properties may be overestimated by the limited resolution of standard imaging techniques. A definitive proof of this observational bias is nevertheless still missing. Here we investigate directly the effect of resolution on clump properties by analysing multiple gravitationally lensed images of the same galaxy at different spatial resolutions, down to 30 pc. We show that the typical mass and size of giant clumps, generally observed at 1 kpc resolution in high-redshift galaxies, are systematically overestimated. The high spatial resolution data, only enabled by strong gravitational lensing using currently available facilities, support smaller scales of clump formation by fragmentation of the galactic gas disk via gravitational instabilities.

Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

USGS Publications Warehouse

Lemeshewsky, George P.; Schowengerdt, Robert A.

2000-01-01

Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Spatial Visualization--A Gateway to Computer-Based Technology.

ERIC Educational Resources Information Center

Norman, Kent L.

1994-01-01

A model is proposed for the influence of individual differences on performance when computer-based technology is introduced. The primary cognitive factor driving differences in performance is spatial visualization ability. Four techniques for mitigating the negative impact of low spatial visualization are discussed: spatial metaphors, graphical…

Classified one-step high-radix signed-digit arithmetic units

NASA Astrophysics Data System (ADS)

Cherri, Abdallah K.

1998-08-01

High-radix number systems enable higher information storage density, less complexity, fewer system components, and fewer cascaded gates and operations. A simple one-step fully parallel high-radix signed-digit arithmetic is proposed for parallel optical computing based on new joint spatial encodings. This reduces hardware requirements and improves throughput by reducing the space-bandwidth produce needed. The high-radix signed-digit arithmetic operations are based on classifying the neighboring input digit pairs into various groups to reduce the computation rules. A new joint spatial encoding technique is developed to present both the operands and the computation rules. This technique increases the spatial bandwidth product of the spatial light modulators of the system. An optical implementation of the proposed high-radix signed-digit arithmetic operations is also presented. It is shown that our one-step trinary signed-digit and quaternary signed-digit arithmetic units are much simpler and better than all previously reported high-radix signed-digit techniques.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Does Face Inversion Change Spatial Frequency Tuning?

ERIC Educational Resources Information Center

Willenbockel, Verena; Fiset, Daniel; Chauvin, Alan; Blais, Caroline; Arguin, Martin; Tanaka, James W.; Bub, Daniel N.; Gosselin, Frederic

2010-01-01

The authors examined spatial frequency (SF) tuning of upright and inverted face identification using an SF variant of the Bubbles technique (F. Gosselin & P. G. Schyns, 2001). In Experiment 1, they validated the SF Bubbles technique in a plaid detection task. In Experiments 2a-c, the SFs used for identifying upright and inverted inner facial…

Spatial interferometry in optical astronomy

NASA Technical Reports Server (NTRS)

Gezari, Daniel Y.; Roddier, Francois; Roddier, Claude

1990-01-01

A bibliographic guide is presented to publications of spatial interferometry techniques applied to optical astronomy. Listings appear in alphabetical order, by first author, as well as in specific subject categories listed in chronological order, including imaging theory and speckle interferometry, experimental techniques, and observational results of astronomical studies of stars, the Sun, and the solar system.

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Lineage range estimation method reveals fine-scale endemism linked to Pleistocene stability in Australian rainforest herpetofauna.

PubMed

Rosauer, Dan F; Catullo, Renee A; VanDerWal, Jeremy; Moussalli, Adnan; Moritz, Craig

2015-01-01

Areas of suitable habitat for species and communities have arisen, shifted, and disappeared with Pleistocene climate cycles, and through this shifting landscape, current biodiversity has found paths to the present. Evolutionary refugia, areas of relative habitat stability in this shifting landscape, support persistence of lineages through time, and are thus crucial to the accumulation and maintenance of biodiversity. Areas of endemism are indicative of refugial areas where diversity has persisted, and endemism of intraspecific lineages in particular is strongly associated with late-Pleistocene habitat stability. However, it remains a challenge to consistently estimate the geographic ranges of intraspecific lineages and thus infer phylogeographic endemism, because spatial sampling for genetic analyses is typically sparse relative to species records. We present a novel technique to model the geographic distribution of intraspecific lineages, which is informed by the ecological niche of a species and known locations of its constituent lineages. Our approach allows for the effects of isolation by unsuitable habitat, and captures uncertainty in the extent of lineage ranges. Applying this method to the arc of rainforest areas spanning 3500 km in eastern Australia, we estimated lineage endemism for 53 species of rainforest dependent herpetofauna with available phylogeographic data. We related endemism to the stability of rainforest habitat over the past 120,000 years and identified distinct concentrations of lineage endemism that can be considered putative refugia. These areas of lineage endemism are strongly related to historical stability of rainforest habitat, after controlling for the effects of current environment. In fact, a dynamic stability model that allows movement to track suitable habitat over time was the most important factor in explaining current patterns of endemism. The techniques presented here provide an objective, practical method for estimating geographic ranges below the species level, and including them in spatial analyses of biodiversity.

Lineage Range Estimation Method Reveals Fine-Scale Endemism Linked to Pleistocene Stability in Australian Rainforest Herpetofauna

PubMed Central

Rosauer, Dan F.; Catullo, Renee A.; VanDerWal, Jeremy; Moussalli, Adnan; Moritz, Craig

2015-01-01

Areas of suitable habitat for species and communities have arisen, shifted, and disappeared with Pleistocene climate cycles, and through this shifting landscape, current biodiversity has found paths to the present. Evolutionary refugia, areas of relative habitat stability in this shifting landscape, support persistence of lineages through time, and are thus crucial to the accumulation and maintenance of biodiversity. Areas of endemism are indicative of refugial areas where diversity has persisted, and endemism of intraspecific lineages in particular is strongly associated with late-Pleistocene habitat stability. However, it remains a challenge to consistently estimate the geographic ranges of intraspecific lineages and thus infer phylogeographic endemism, because spatial sampling for genetic analyses is typically sparse relative to species records. We present a novel technique to model the geographic distribution of intraspecific lineages, which is informed by the ecological niche of a species and known locations of its constituent lineages. Our approach allows for the effects of isolation by unsuitable habitat, and captures uncertainty in the extent of lineage ranges. Applying this method to the arc of rainforest areas spanning 3500 km in eastern Australia, we estimated lineage endemism for 53 species of rainforest dependent herpetofauna with available phylogeographic data. We related endemism to the stability of rainforest habitat over the past 120,000 years and identified distinct concentrations of lineage endemism that can be considered putative refugia. These areas of lineage endemism are strongly related to historical stability of rainforest habitat, after controlling for the effects of current environment. In fact, a dynamic stability model that allows movement to track suitable habitat over time was the most important factor in explaining current patterns of endemism. The techniques presented here provide an objective, practical method for estimating geographic ranges below the species level, and including them in spatial analyses of biodiversity. PMID:26020936

New developments in spatial interpolation methods of Sea-Level Anomalies in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Troupin, Charles; Barth, Alexander; Beckers, Jean-Marie; Pascual, Ananda

2014-05-01

The gridding of along-track Sea-Level Anomalies (SLA) measured by a constellation of satellites has numerous applications in oceanography, such as model validation, data assimilation or eddy tracking. Optimal Interpolation (OI) is often the preferred method for this task, as it leads to the lowest expected error and provides an error field associated to the analysed field. However, the numerical cost of the method may limit its utilization in situations where the number of data points is significant. Furthermore, the separation of non-adjacent regions with OI requires adaptation of the code, leading to a further increase of the numerical cost. To solve these issues, the Data-Interpolating Variational Analysis (DIVA), a technique designed to produce gridded from sparse in situ measurements, is applied on SLA data in the Mediterranean Sea. DIVA and OI have been shown to be equivalent (provided some assumptions on the covariances are made). The main difference lies in the covariance function, which is not explicitly formulated in DIVA. The particular spatial and temporal distributions of measurements required adaptation in the Software tool (data format, parameter determinations, ...). These adaptation are presented in the poster. The daily analysed and error fields obtained with this technique are compared with available products such as the gridded field from the Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO) data server. The comparison reveals an overall good agreement between the products. The time evolution of the mean error field evidences the need of a large number of simultaneous altimetry satellites: in period during which 4 satellites are available, the mean error is on the order of 17.5%, while when only 2 satellites are available, the error exceeds 25%. Finally, we propose the use sea currents to improve the results of the interpolation, especially in the coastal area. These currents can be constructed from the bathymetry or extracted from a HF radar located in the Balearic Sea.

Upside-Down Brilliance: The Visual-Spatial Learner.

ERIC Educational Resources Information Center

Silverman, Linda Kreger

This book describes the unique characteristics of visual-spatial learners and teaching techniques designed for this population. Following a quiz to identify visual-spatial learners, chapters address: (1) how visual-spatial learners think and the plight of being non-sequential; (2) the power of the right hemisphere, eye movement patterns, and…

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Techniques for noise removal and registration of TIMS data

USGS Publications Warehouse

Hummer-Miller, S.

1990-01-01

Extracting subtle differences from highly correlated thermal infrared aircraft data is possible with appropriate noise filters, constructed and applied in the spatial frequency domain. This paper discusses a heuristic approach to designing noise filters for removing high- and low-spatial frequency striping and banding. Techniques for registering thermal infrared aircraft data to a topographic base using Thematic Mapper data are presented. The noise removal and registration techniques are applied to TIMS thermal infrared aircraft data. -Author

Modelling dendritic ecological networks in space: anintegrated network perspective

USGS Publications Warehouse

Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

2013-01-01

the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

High-spatial-resolution mapping of precipitable water vapour using SAR interferograms, GPS observations and ERA-Interim reanalysis

NASA Astrophysics Data System (ADS)

Tang, Wei; Liao, Mingsheng; Zhang, Lu; Li, Wei; Yu, Weimin

2016-09-01

A high spatial and temporal resolution of the precipitable water vapour (PWV) in the atmosphere is a key requirement for the short-scale weather forecasting and climate research. The aim of this work is to derive temporally differenced maps of the spatial distribution of PWV by analysing the tropospheric delay "noise" in interferometric synthetic aperture radar (InSAR). Time series maps of differential PWV were obtained by processing a set of ENVISAT ASAR (Advanced Synthetic Aperture Radar) images covering the area of southern California, USA from 6 October 2007 to 29 November 2008. To get a more accurate PWV, the component of hydrostatic delay was calculated and subtracted by using ERA-Interim reanalysis products. In addition, the ERA-Interim was used to compute the conversion factors required to convert the zenith wet delay to water vapour. The InSAR-derived differential PWV maps were calibrated by means of the GPS PWV measurements over the study area. We validated our results against the measurements of PWV derived from the Medium Resolution Imaging Spectrometer (MERIS) which was located together with the ASAR sensor on board the ENVISAT satellite. Our comparative results show strong spatial correlations between the two data sets. The difference maps have Gaussian distributions with mean values close to zero and standard deviations below 2 mm. The advantage of the InSAR technique is that it provides water vapour distribution with a spatial resolution as fine as 20 m and an accuracy of ˜ 2 mm. Such high-spatial-resolution maps of PWV could lead to much greater accuracy in meteorological understanding and quantitative precipitation forecasts. With the launch of Sentinel-1A and Sentinel-1B satellites, every few days (6 days) new SAR images can be acquired with a wide swath up to 250 km, enabling a unique operational service for InSAR-based water vapour maps with unprecedented spatial and temporal resolution.

Longitudinal patterns and response lengths of algae in riverine ecosystems: A model analysis emphasising benthic-pelagic interactions.

PubMed

Jäger, Christoph G; Borchardt, Dietrich

2018-04-07

In riverine ecosystems primary production is principally possible in two habitats: in the benthic layer by sessile algae and in the surface water by planktonic algae being transported downstream. The relevance of these two habitats generally changes along the rivers' continuum. However, analyses of the interaction of algae in these two habitats and their controlling factors in riverine ecosystems are, so far, very rare. We use a simplified advection-diffusion model system combined with ecological process kinetics to analyse the interaction of benthic and planktonic algae and nutrients along idealised streams and rivers at regional to large scales. Because many of the underlying processes affecting algal dynamics are influenced by depth, we focus particularly on the impact of river depth on this interaction. At constant environmental conditions all state variables approach stable spatial equilibria along the river, independent of the boundary conditions at the upstream end. Because our model is very robust against changes of turbulent diffusion and stream velocity, these spatial equilibria can be analysed by a simplified ordinary differential equation (ode) version of our model. This model variant reveals that at shallower river depths, phytoplankton can exist only when it is subsidised by detaching benthic algae, and in turn, at deeper river depths, benthic algae can exist only in low biomasses which are subsidised by sinking planktonic algae. We generalise the spatial dynamics of the model system using different conditions at the upstream end of the model, which mimic various natural or anthropogenic factors (pristine source, dam, inflow of a waste water treatment plant, and dilution from e.g. a tributary) and analyse how these scenarios influence different aspects of the longitudinal spatial dynamics of the full spatial model: the relation of spatial equilibrium to spatial maximum, the distance to the spatial maximum, and the response length. Generally, our results imply that shallow systems recover within significantly shorter distances from spatially distinct disturbances when compared to deep systems, independent of the type of disturbance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales.

PubMed

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.

High-resolution bottom-loss estimation using the ambient-noise vertical coherence function.

PubMed

Muzi, Lanfranco; Siderius, Martin; Quijano, Jorge E; Dosso, Stan E

2015-01-01

The seabed reflection loss (shortly "bottom loss") is an important quantity for predicting transmission loss in the ocean. A recent passive technique for estimating the bottom loss as a function of frequency and grazing angle exploits marine ambient noise (originating at the surface from breaking waves, wind, and rain) as an acoustic source. Conventional beamforming of the noise field at a vertical line array of hydrophones is a fundamental step in this technique, and the beamformer resolution in grazing angle affects the quality of the estimated bottom loss. Implementation of this technique with short arrays can be hindered by their inherently poor angular resolution. This paper presents a derivation of the bottom reflection coefficient from the ambient-noise spatial coherence function, and a technique based on this derivation for obtaining higher angular resolution bottom-loss estimates. The technique, which exploits the (approximate) spatial stationarity of the ambient-noise spatial coherence function, is demonstrated on both simulated and experimental data.

"Relative CIR": an image enhancement and visualization technique

USGS Publications Warehouse

Fleming, Michael D.

1993-01-01

Many techniques exist to spectrally and spatially enhance digital multispectral scanner data. One technique enhances an image while keeping the colors as they would appear in a color-infrared (CIR) image. This "relative CIR" technique generates an image that is both spectrally and spatially enhanced, while displaying a maximum range of colors. The technique enables an interpreter to visualize either spectral or land cover classes by their relative CIR characteristics. A relative CIR image is generated by developed spectral statistics for each class in the classifications and then, using a nonparametric approach for spectral enhancement, the means of the classes for each band are ranked. A 3 by 3 pixel smoothing filter is applied to the classification for spatial enhancement and the classes are mapped to the representative rank for each band. Practical applications of the technique include displaying an image classification product as a CIR image that was not derived directly from a spectral image, visualizing how a land cover classification would look as a CIR image, and displaying a spectral classification or intermediate product that will be used to label spectral classes.

Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

NASA Astrophysics Data System (ADS)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

2018-02-01

This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

How do frugivores track resources? Insights from spatial analyses of bird foraging in a tropical forest

USGS Publications Warehouse

Saracco, J.F.; Collazo, J.A.; Groom, Martha J.

2004-01-01

Frugivores often track ripe fruit abundance closely across local areas despite the ephemeral and typically patchy distributions of this resource. We use spatial auto- and cross-correlation analyses to quantify spatial patterns of fruit abundance and avian frugivory across a 4-month period within a forested 4.05-ha study grid in Puerto Rico. Analyses focused on two tanager species, Spindalis portoricensis and Nesospingus speculiferus, and their principal food plants. Three broad questions are addressed: (1) at what spatial scales is fruit abundance and frugivory patchy; (2) at what spatial scales do frugivores respond to fruit abundance; and (3) to what extent do spatial patterns of frugivory overlap between bird species? Fruit patch size, species composition, and heterogeneity was variable among months, despite fruit patch locations remaining relatively consistent between months. Positive correlations between frugivory and fruit abundance suggested tanagers successfully tracked fruit abundance. Frugivory was, however, more localized than fruit abundance. Scales of spatial overlap in frugivory and monthly variation in the foraging locations of the two tanager species suggested that interspecific facilitation may have been important in determining bird foraging locations. In particular, S. portoricensis, a specialist frugivore, may have relied on the loud calls of the gregarious generalist, N. speculiferus, to find new foraging areas. Such a mechanism could help explain the formation of mixed species feeding flocks and highlights the potential importance of facilitation between species that share resources. ?? Springer-Verlag 2004.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

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

PubMed

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

2018-05-07

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

Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

PubMed Central

Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

2018-01-01

Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

Exploring spatial evolution of economic clusters: A case study of Beijing

NASA Astrophysics Data System (ADS)

Yang, Zhenshan; Sliuzas, Richard; Cai, Jianming; Ottens, Henk F. L.

2012-10-01

An identification of economic clusters and analysing their changing spatial patterns is important for understanding urban economic space dynamics. Previous studies, however, suffer from limitations as a consequence of using fixed geographically areas and not combining functional and spatial dynamics. The paper presents an approach, based on local spatial statistics and the case of Beijing to understand the spatial clustering of industries that are functionally interconnected by common or complementary patterns of demand or supply relations. Using register data of business establishments, it identifies economic clusters and analyses their pattern based on postcodes at different time slices during the period 1983-2002. The study shows how the advanced services occupy the urban centre and key sub centres. The Information and Communication Technology (ICT) cluster is mainly concentrated in the north part of the city and circles the urban centre, and the main manufacturing clusters are evolved in the key sub centers. This type of outcomes improves understanding of urban-economic dynamics, which can support spatial and economic planning.

Big Data Geo-Analytical Tool Development for Spatial Analysis Uncertainty Visualization and Quantification Needs

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J. R.; Baker, D. V.

2015-12-01

As big data computing capabilities are increasingly paired with spatial analytical tools and approaches, there is a need to ensure uncertainty associated with the datasets used in these analyses is adequately incorporated and portrayed in results. Often the products of spatial analyses, big data and otherwise, are developed using discontinuous, sparse, and often point-driven data to represent continuous phenomena. Results from these analyses are generally presented without clear explanations of the uncertainty associated with the interpolated values. The Variable Grid Method (VGM) offers users with a flexible approach designed for application to a variety of analyses where users there is a need to study, evaluate, and analyze spatial trends and patterns while maintaining connection to and communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analysis through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom 'Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations. The presentation includes examples of the approach being applied to a range of subsurface, geospatial studies (e.g. induced seismicity risk).

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Measurement of replication structures at the nanometer scale using super-resolution light microscopy

PubMed Central

Baddeley, D.; Chagin, V. O.; Schermelleh, L.; Martin, S.; Pombo, A.; Carlton, P. M.; Gahl, A.; Domaing, P.; Birk, U.; Leonhardt, H.; Cremer, C.; Cardoso, M. C.

2010-01-01

DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses. PMID:19864256

Parallel and Scalable Clustering and Classification for Big Data in Geosciences

NASA Astrophysics Data System (ADS)

Riedel, M.

2015-12-01

Machine learning, data mining, and statistical computing are common techniques to perform analysis in earth sciences. This contribution will focus on two concrete and widely used data analytics methods suitable to analyse 'big data' in the context of geoscience use cases: clustering and classification. From the broad class of available clustering methods we focus on the density-based spatial clustering of appliactions with noise (DBSCAN) algorithm that enables the identification of outliers or interesting anomalies. A new open source parallel and scalable DBSCAN implementation will be discussed in the light of a scientific use case that detects water mixing events in the Koljoefjords. The second technique we cover is classification, with a focus set on the support vector machines algorithm (SVMs), as one of the best out-of-the-box classification algorithm. A parallel and scalable SVM implementation will be discussed in the light of a scientific use case in the field of remote sensing with 52 different classes of land cover types.

Secondary ion mass spectrometry: The application in the analysis of atmospheric particulate matter

DOE PAGES

Huang, Di; Hua, Xin; Xiu, Guang-Li; ...

2017-07-24

Currently, considerable attention has been paid to atmospheric particulate matter (PM) investigation due to its importance in human health and global climate change. Surface characterization, single particle analysis and depth profiling of PM is important for a better understanding of its formation processes and predicting its impact on the environment and human being. Secondary ion mass spectrometry (SIMS) is a surface technique with high surface sensitivity, high spatial resolution chemical imaging and unique depth profiling capabilities. Recent research shows that SIMS has great potential in analyzing both surface and bulk chemical information of PM. In this review, we give amore » brief introduction of SIMS working principle and survey recent applications of SIMS in PM characterization. In particular, analyses from different types of PM sources by various SIMS techniques were discussed concerning their advantages and limitations. Finally, we propose, the future development and needs of SIMS in atmospheric aerosol measurement with a perspective in broader environmental sciences.« less

Monthly Strontium/Calcium oscillations in symbiotic coral aragonite: Biological effects limiting the precision of the paleotemperature proxy

USGS Publications Warehouse

Meibom, A.; Stage, M.; Wooden, J.; Constantz, B.R.; Dunbar, R.B.; Owen, A.; Grumet, N.; Bacon, C.R.; Chamberlain, C.P.

2003-01-01

In thermodynamic equilibrium with sea water the Sr/Ca ratio of aragonite varies predictably with temperature and the Sr/Ca ratio in coral have thus become a frequently used proxy for past Sea Surface Temperature (SST). However, biological effects can offset the Sr/Ca ratio from its equilibrium value. We report high spatial resolution ion microprobe analyses of well defined skeletal elements in the reef-building coral Porites lutea that reveal distinct monthly oscillations in the Sr/Ca ratio, with an amplitude in excess of ten percent. The extreme Sr/Ca variations, which we propose result from metabolic changes synchronous with the lunar cycle, introduce variability in Sr/Ca measurements based on conventional sampling techniques well beyond the analytical precision. These variations can limit the accuracy of Sr/Ca paleothermometry by conventional sampling techniques to about 2??C. Our results may help explain the notorious difficulties involved in obtaining an accurate and consistent calibration of the Sr/Ca vs. SST relationship.

Secondary ion mass spectrometry: The application in the analysis of atmospheric particulate matter

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

Huang, Di; Hua, Xin; Xiu, Guang-Li

Currently, considerable attention has been paid to atmospheric particulate matter (PM) investigation due to its importance in human health and global climate change. Surface characterization, single particle analysis and depth profiling of PM is important for a better understanding of its formation processes and predicting its impact on the environment and human being. Secondary ion mass spectrometry (SIMS) is a surface technique with high surface sensitivity, high spatial resolution chemical imaging and unique depth profiling capabilities. Recent research shows that SIMS has great potential in analyzing both surface and bulk chemical information of PM. In this review, we give amore » brief introduction of SIMS working principle and survey recent applications of SIMS in PM characterization. In particular, analyses from different types of PM sources by various SIMS techniques were discussed concerning their advantages and limitations. Finally, we propose, the future development and needs of SIMS in atmospheric aerosol measurement with a perspective in broader environmental sciences.« less

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

PubMed

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

2013-07-15

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

4D ground penetrating radar measurements as non-invasive means for hydrological process investigation

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Allroggen, Niklas

2017-04-01

The missing vision into the subsurface appears to be a major limiting factor for our hydrological process understanding and theory development. Today, hydrology-related sciences have collected tremendous evidence for soils acting as drainage network and retention stores simultaneously in structured and self-organising domains. However, our present observation technology relies mainly on point-scale sensors, which integrate over a volume of unknown structures and is blind for their distribution. Although heterogeneity is acknowledged at all scales, it is rarely seen as inherent system property. At small scales (soil moisture probe) and at large scales (neutron probe) our measurements leave quite some ambiguity. Consequently, spatially and temporally continuous measurement of soil water states is essential for advancing our understanding and development of subsurface process theories. We present results from several irrigation experiments accompanied by 2D and 3D time-lapse GPR for the development of a novel technique to visualise and quantify water dynamics in the subsurface. Through the comparison of TDR, tracer and gravimetric measurement of soil moisture it becomes apparent that all sensor-based techniques are capable to record temporal dynamics, but are challenged to precisely quantify the measurements and to extrapolate them in space. At the same time excavative methods are very limited in temporal and spatial resolution. The application of non-invasive 4D GPR measurements complements the existing techniques and reveals structural and temporal dynamics simultaneously. By consequently increasing the density of the GPR data recordings in time and space, we find means to process the data also in the time-dimension. This opens ways to quantitatively analyse soil water dynamics in complex settings.

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

U-Pb SHRIMP dating of uraniferous opals

USGS Publications Warehouse

Nemchin, A.A.; Neymark, L.A.; Simons, S.L.

2006-01-01

U-Pb and U-series analyses of four U-rich opal samples using sensitive high-resolution ion microprobe (SHRIMP) demonstrate the potential of this technique for the dating of opals with ages ranging from several tens of thousand years to millions of years. The major advantages of the technique, compared to the conventional thermal ionisation mass spectrometry (TIMS), are the high spatial resolution (???20 ??m), the ability to analyse in situ all isotopes required to determine both U-Pb and U-series ages, and a relatively short analysis time which allows obtaining a growth rate of opal as a result of a single SHRIMP session. There are two major limitations to this method, determined by both current level of development of ion probes and understanding of ion sputtering processes. First, sufficient secondary ion beam intensities can only be obtained for opal samples with U concentrations in excess of ???20 ??g/g. However, this restriction still permits dating of a large variety of opals. Second, U-Pb ratios in all analyses drifted with time and were only weakly correlated with changes in other ratios (such as U/UO). This drift, which is difficult to correct for, remains the main factor currently limiting the precision and accuracy of the U-Pb SHRIMP opal ages. Nevertheless, an assumption of similar behaviour of standard and unknown opals under similar analytical conditions allowed successful determination of ages with precisions of ???10% for the samples investigated in this study. SHRIMP-based U-series and U-Pb ages are consistent with TIMS dating results of the same materials and known geological timeframes. ?? 2005 Elsevier B.V. All rights reserved.

Comparison between two non-contact techniques for art digitalization

NASA Astrophysics Data System (ADS)

Bianconi, F.; Catalucci, S.; Filippucci, M.; Marsili, R.; Moretti, M.; Rossi, G.; Speranzini, E.

2017-08-01

Many measurements techniques have been proposed for the “digitalization of objects”: structured light 3D scanner, laser scanner, high resolution camera, depth cam, thermal-cam, … Since the adoption of the European Agenda for Culture in 2007, heritage has been a priority for the Council’s work plans for culture, and cooperation at European level has advanced through the Open Method of Coordination. Political interest at EU level has steadily grown cultural and heritage stakeholders recently highlighted in the Declaration on a New Narrative for Europe: “Europe as a political body needs to recognize the value of Cultural Heritage”. Photomodelling is an innovative and extremely economical technique related to the conservation of Cultural Heritage, which leads to the creation of three-dimensional models starting from simple photographs. The aim of the research is to understand the full potential offered by this new technique and dedicated software, analysing the reliability of each instrument, with particular attention to freeware ones. An analytical comparison between photomodelling and structured light 3D scanner guarantees a first measure of the reliability of instruments, tested in the survey of several Umbrian heritage artefacts. The comparison between tests and reference models is explained using different algorithms and criteria, spatial, volumetric and superficial.

An Information-Based Machine Learning Approach to Elasticity Imaging

PubMed Central

Hoerig, Cameron; Ghaboussi, Jamshid; Insana, Michael. F.

2016-01-01

An information-based technique is described for applications in mechanical-property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for this purpose. The Autoprogressive method is a computational technique that combines knowledge of object shape and a sparse distribution of force and displacement measurements with finite-element analyses and artificial neural networks to estimate a complete set of stress and strain vectors. Elasticity imaging parameters are then computed from estimated stresses and strains. We introduce the technique using ultrasonic pulse-echo measurements in simple gelatin imaging phantoms having linear-elastic properties so that conventional finite-element modeling can be used to validate results. The Autoprogressive algorithm does not require any assumptions about the material properties and can, in principle, be used to image media with arbitrary properties. We show that by selecting a few well-chosen force-displacement measurements that are appropriately applied during training and establish convergence, we can estimate all nontrivial stress and strain vectors throughout an object and accurately estimate an elastic modulus at high spatial resolution. This new method of modeling the mechanical properties of tissue-like materials introduces a unique method of solving the inverse problem and is the first technique for imaging stress without assuming the underlying constitutive model. PMID:27858175

Regression and Geostatistical Techniques: Considerations and Observations from Experiences in NE-FIA

Treesearch

Rachel Riemann; Andrew Lister

2005-01-01

Maps of forest variables improve our understanding of the forest resource by allowing us to view and analyze it spatially. The USDA Forest Service's Northeastern Forest Inventory and Analysis unit (NE-FIA) has used geostatistical techniques, particularly stochastic simulation, to produce maps and spatial data sets of FIA variables. That work underscores the...

Spatial interpolation of forest conditions using co-conditional geostatistical simulation

Treesearch

H. Todd Mowrer

2000-01-01

In recent work the author used the geostatistical Monte Carlo technique of sequential Gaussian simulation (s.G.s.) to investigate uncertainty in a GIS analysis of potential old-growth forest areas. The current study compares this earlier technique to that of co-conditional simulation, wherein the spatial cross-correlations between variables are included. As in the...

Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures

PubMed Central

Zavodszky, Maria I.

2017-01-01

Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information). PMID:29190747

Spatial patterns in vegetation fires in the Indian region.

PubMed

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

2008-12-01

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

Neural Correlates of Temporal-Order Judgments versus Those of Spatial-Location: Deactivation of Hippocampus May Facilitate Spatial Performance

ERIC Educational Resources Information Center

Rekkas, P. V.; Westerveld, M.; Skudlarski, P.; Zumer, J.; Pugh, K.; Spencer, D. D.; Constable, R. T.

2005-01-01

The retrieval of temporal-order versus spatial-location information was investigated using fMRI. The primary finding in the hippocampus proper, seen in region of interest analyses, was an increase in BOLD signal intensity for temporal retrieval, and a decrease in signal intensity for spatial retrieval, relative to baseline. The negative BOLD…

Examining leisure event opportunities of Isle Royale National Park: bridging the gap between social process and spatial form

Treesearch

Chad D. Pierskalla; Dorothy H. Anderson; David W. Lime

2000-01-01

To manage various recreation opportunities, managers and planners must consider the spatial and temporal scale of social process when identifying opportunities on base maps. However, analyses of social process and spatial form are often treated as two distinct approaches--sociological and geographical approaches. A sociologist might control for spatial form by adopting...

Metacognition Difficulty of Students with Visual-Spatial Intelligence during Solving Open-Ended Problem

NASA Astrophysics Data System (ADS)

Rimbatmojo, S.; Kusmayadi, T. A.; Riyadi, R.

2017-09-01

This study aims to find out students metacognition difficulty during solving open-ended problem in mathematics. It focuses on analysing the metacognition difficulty of students with visual-spatial intelligence in solving open-ended problem. A qualitative research with case study strategy is used in this study. Data in the form of visual-spatial intelligence test result and recorded interview during solving open-ended problems were analysed qualitatively. The results show that: (1) students with high visual-spatial intelligence have no difficulty on each metacognition aspects, (2) students with medium visual-spatial intelligence have difficulty on knowledge aspect on strategy and cognitive tasks, (3) students with low visual-spatial intelligence have difficulty on three metacognition aspects, namely knowledge on strategy, cognitive tasks and self-knowledge. Even though, several researches about metacognition process and metacognition literature recommended the steps to know the characteristics. It is still important to discuss that the difficulties of metacognitive is happened because of several factors, one of which on the characteristics of student’ visual-spatial intelligence. Therefore, it is really important for mathematics educators to consider and pay more attention toward students’ visual-spatial intelligence and metacognition difficulty in designing better mathematics learning.

From fields to objects: A review of geographic boundary analysis

NASA Astrophysics Data System (ADS)

Jacquez, G. M.; Maruca, S.; Fortin, M.-J.

Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique for defining objects - geographic boundaries - on spatial fields, and for evaluating the statistical significance of characteristics of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes (variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic boundary analysis is clearly a valuable addition to the spatial statistical toolbox. This paper presents the philosophy of, and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques, with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the implementation of these methods within geographic boundary analysis software: GEM.

Using Deep Learning for Tropical Cyclone Intensity Estimation

NASA Astrophysics Data System (ADS)

Miller, J.; Maskey, M.; Berendes, T.

2017-12-01

Satellite-based techniques are the primary approach to estimating tropical cyclone (TC) intensity. Tropical cyclone warning centers worldwide still apply variants of the Dvorak technique for such estimations that include visual inspection of the satellite images. The National Hurricane Center (NHC) estimates about 10-20% uncertainty in its post analyses when only satellite-based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to TC intensity. With the ever-increasing quality and quantity of satellite observations of TCs, deep learning techniques designed to excel at pattern recognition have become more relevant in this area of study. In our current study, we aim to provide a fully objective approach to TC intensity estimation by utilizing deep learning in the form of a convolutional neural network trained to predict TC intensity (maximum sustained wind speed) using IR satellite imagery. Large amounts of training data are needed to train a convolutional neural network, so we use GOES IR images from historical tropical storms from the Atlantic and Pacific basins spanning years 2000 to 2015. Images are labeled using a special subset of the HURDAT2 dataset restricted to time periods with airborne reconnaissance data available in order to improve the quality of the HURDAT2 data. Results and the advantages of this technique are to be discussed.

Investigating Gravity Waves in Polar Mesospheric Clouds Using Tomographic Reconstructions of AIM Satellite Imagery

NASA Astrophysics Data System (ADS)

Hart, V. P.; Taylor, M. J.; Doyle, T. E.; Zhao, Y.; Pautet, P.-D.; Carruth, B. L.; Rusch, D. W.; Russell, J. M.

2018-01-01

This research presents the first application of tomographic techniques for investigating gravity wave structures in polar mesospheric clouds (PMCs) imaged by the Cloud Imaging and Particle Size instrument on the NASA AIM satellite. Albedo data comprising consecutive PMC scenes were used to tomographically reconstruct a 3-D layer using the Partially Constrained Algebraic Reconstruction Technique algorithm and a previously developed "fanning" technique. For this pilot study, a large region (760 × 148 km) of the PMC layer (altitude 83 km) was sampled with a 2 km horizontal resolution, and an intensity weighted centroid technique was developed to create novel 2-D surface maps, characterizing the individual gravity waves as well as their altitude variability. Spectral analysis of seven selected wave events observed during the Northern Hemisphere 2007 PMC season exhibited dominant horizontal wavelengths of 60-90 km, consistent with previous studies. These tomographic analyses have enabled a broad range of new investigations. For example, a clear spatial anticorrelation was observed between the PMC albedo and wave-induced altitude changes, with higher-albedo structures aligning well with wave troughs, while low-intensity regions aligned with wave crests. This result appears to be consistent with current theories of PMC development in the mesopause region. This new tomographic imaging technique also provides valuable wave amplitude information enabling further mesospheric gravity wave investigations, including quantitative analysis of their hemispheric and interannual characteristics and variations.

Sumatran tiger survival threatened by deforestation despite increasing densities in parks.

PubMed

Luskin, Matthew Scott; Albert, Wido Rizki; Tobler, Mathias W

2017-12-05

The continuing development of improved capture-recapture (CR) modeling techniques used to study apex predators has also limited robust temporal and cross-site analyses due to different methods employed. We develop an approach to standardize older non-spatial CR and newer spatial CR density estimates and examine trends for critically endangered Sumatran tigers (Panthera tigris sumatrae) using a meta-regression of 17 existing densities and new estimates from our own fieldwork. We find that tiger densities were 47% higher in primary versus degraded forests and, unexpectedly, increased 4.9% per yr from 1996 to 2014, likely indicating a recovery from earlier poaching. However, while tiger numbers may have temporarily risen, the total potential island-wide population declined by 16.6% from 2000 to 2012 due to forest loss and degradation and subpopulations are significantly more fragmented. Thus, despite increasing densities in smaller parks, we conclude that there are only two robust populations left with >30 breeding females, indicating Sumatran tigers still face a high risk of extinction unless deforestation can be controlled.

Multi-focused geospatial analysis using probes.

PubMed

Butkiewicz, Thomas; Dou, Wenwen; Wartell, Zachary; Ribarsky, William; Chang, Remco

2008-01-01

Traditional geospatial information visualizations often present views that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in for local inspection, spatial awareness and comparison between regions become limited. In our model, coordinated visualizations are integrated within individual probe interfaces, which depict the local data in user-defined regions-of-interest. Our probe concept can be incorporated into a variety of geospatial visualizations to empower users with the ability to observe, coordinate, and compare data across multiple local regions. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. We illustrate the effectiveness of our technique over traditional interfaces by incorporating it within three existing geospatial visualization systems: an agent-based social simulation, a census data exploration tool, and an 3D GIS environment for analyzing urban change over time. In each case, the probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users.

Regional gray matter correlates of vocational interests

PubMed Central

2012-01-01

Background Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. Findings First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic (“blue-collar”) interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Conclusions Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations. PMID:22591829

Regional gray matter correlates of vocational interests.

PubMed

Schroeder, David H; Haier, Richard J; Tang, Cheuk Ying

2012-05-16

Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic ("blue-collar") interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations.

BaTMAn: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2016-12-01

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

Pseudo color ghost coding imaging with pseudo thermal light

NASA Astrophysics Data System (ADS)

Duan, De-yang; Xia, Yun-jie

2018-04-01

We present a new pseudo color imaging scheme named pseudo color ghost coding imaging based on ghost imaging but with multiwavelength source modulated by a spatial light modulator. Compared with conventional pseudo color imaging where there is no nondegenerate wavelength spatial correlations resulting in extra monochromatic images, the degenerate wavelength and nondegenerate wavelength spatial correlations between the idle beam and signal beam can be obtained simultaneously. This scheme can obtain more colorful image with higher quality than that in conventional pseudo color coding techniques. More importantly, a significant advantage of the scheme compared to the conventional pseudo color coding imaging techniques is the image with different colors can be obtained without changing the light source and spatial filter.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

Quantification of Spatial Heterogeneity in Old Growth Forst of Korean Pine

Treesearch

Wang Zhengquan; Wang Qingcheng; Zhang Yandong

1997-01-01

Spatial hetergeneity is a very important issue in studying functions and processes of ecological systems at various scales. Semivariogram analysis is an effective technique to summarize spatial data, and quantification of sptail heterogeneity. In this paper, we propose some principles to use semivariograms to characterize and compare spatial heterogeneity of...

MERINOVA: Meteorological risks as drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Oger, Robert; Marlier, Catherine; Van De Vijver, Hans; Vandermeulen, Valerie; Van Huylenbroeck, Guido; Zamani, Sepideh; Curnel, Yannick; Mettepenningen, Evi

2013-04-01

The BELSPO funded project 'MERINOVA' deals with risks associated with extreme weather phenomena and with risks of biological origin such as pests and diseases. The major objectives of the proposed project are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: (i) Hazard: Assessing the likely frequency and magnitude of extreme meteorological events by means of probability density functions; (ii) Impact: Analysing the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems in Belgium using process-based modelling techniques commensurate with the regional scale; (iii) Vulnerability: Identifying the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (iv) Risk Management: Uncovering innovative risk management and adaptation options using actor-network theory and fuzzy cognitive mapping techniques; and, (v) Communication: Communicating to research, policy and practitioner communities using web-based techniques. The different tasks of the MERINOVA project require expertise in several scientific disciplines: meteorology, statistics, spatial database management, agronomy, bio-physical impact modelling, socio-economic modelling, actor-network theory, fuzzy cognitive mapping techniques. These expertises are shared by the four scientific partners who each lead one work package. The MERINOVA project will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts will enlarge the basis for vulnerability mapping, risk management and adaptation options. A strong expert and end-user network will be established to help disseminating and exploiting project results to meet user needs.

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images.

PubMed

Ahmadi, Farshid Farnood; Ebadi, Hamid

2009-01-01

3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented.

Electric field stimulation setup for photoemission electron microscopes.

PubMed

Buzzi, M; Vaz, C A F; Raabe, J; Nolting, F

2015-08-01

Manipulating magnetisation by the application of an electric field in magnetoelectric multiferroics represents a timely issue due to the potential applications in low power electronics and the novel physics involved. Thanks to its element sensitivity and high spatial resolution, X-ray photoemission electron microscopy is a uniquely suited technique for the investigation of magnetoelectric coupling in multiferroic materials. In this work, we present a setup that allows for the application of in situ electric and magnetic fields while the sample is analysed in the microscope. As an example of the performances of the setup, we present measurements on Ni/Pb(Mg(0.66)Nb(0.33))O3-PbTiO3 and La(0.7)Sr(0.3)MnO3/PMN-PT artificial multiferroic nanostructures.

Identification of individual biofilm-forming bacterial cells using Raman tweezers

NASA Astrophysics Data System (ADS)

Samek, Ota; Bernatová, Silvie; Ježek, Jan; Šiler, Martin; Šerý, Mojmir; Krzyžánek, Vladislav; Hrubanová, Kamila; Zemánek, Pavel; Holá, Veronika; Růžička, Filip

2015-05-01

A method for in vitro identification of individual bacterial cells is presented. The method is based on a combination of optical tweezers for spatial trapping of individual bacterial cells and Raman microspectroscopy for acquisition of spectral "Raman fingerprints" obtained from the trapped cell. Here, Raman spectra were taken from the biofilm-forming cells without the influence of an extracellular matrix and were compared with biofilm-negative cells. Results of principal component analyses of Raman spectra enabled us to distinguish between the two strains of Staphylococcus epidermidis. Thus, we propose that Raman tweezers can become the technique of choice for a clearer understanding of the processes involved in bacterial biofilms which constitute a highly privileged way of life for bacteria, protected from the external environment.

Identification of individual biofilm-forming bacterial cells using Raman tweezers.

PubMed

Samek, Ota; Bernatová, Silvie; Ježek, Jan; Šiler, Martin; Šerý, Mojmir; Krzyžánek, Vladislav; Hrubanová, Kamila; Zemánek, Pavel; Holá, Veronika; Růžička, Filip

2015-05-01

A method for in vitro identification of individual bacterial cells is presented. The method is based on a combination of optical tweezers for spatial trapping of individual bacterial cells and Raman microspectroscopy for acquisition of spectral “Raman fingerprints” obtained from the trapped cell. Here, Raman spectra were taken from the biofilm-forming cells without the influence of an extracellular matrix and were compared with biofilm-negative cells. Results of principal component analyses of Raman spectra enabled us to distinguish between the two strains of Staphylococcus epidermidis. Thus, we propose that Raman tweezers can become the technique of choice for a clearer understanding of the processes involved in bacterial biofilms which constitute a highly privileged way of life for bacteria, protected from the external environment.

Application of Raytracing Through the High Resolution Numerical Weather Model HIRLAM for the Analysis of European VLBI

NASA Technical Reports Server (NTRS)

Garcia-Espada, Susana; Haas, Rudiger; Colomer, Francisco

2010-01-01

An important limitation for the precision in the results obtained by space geodetic techniques like VLBI and GPS are tropospheric delays caused by the neutral atmosphere, see e.g. [1]. In recent years numerical weather models (NWM) have been applied to improve mapping functions which are used for tropospheric delay modeling in VLBI and GPS data analyses. In this manuscript we use raytracing to calculate slant delays and apply these to the analysis of Europe VLBI data. The raytracing is performed through the limited area numerical weather prediction (NWP) model HIRLAM. The advantages of this model are high spatial (0.2 deg. x 0.2 deg.) and high temporal resolution (in prediction mode three hours).

Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos.

PubMed

Zhao, Ziqing W; White, Melanie D; Bissiere, Stephanie; Levi, Valeria; Plachta, Nicolas

2016-12-23

Probing dynamic processes occurring within the cell nucleus at the quantitative level has long been a challenge in mammalian biology. Advances in bio-imaging techniques over the past decade have enabled us to directly visualize nuclear processes in situ with unprecedented spatial and temporal resolution and single-molecule sensitivity. Here, using transcription as our primary focus, we survey recent imaging studies that specifically emphasize the quantitative understanding of nuclear dynamics in both time and space. These analyses not only inform on previously hidden physical parameters and mechanistic details, but also reveal a hierarchical organizational landscape for coordinating a wide range of transcriptional processes shared by mammalian systems of varying complexity, from single cells to whole embryos.

The effect of length and starting year on trend analyses of temperatures in Spanish mainland (1951-2010). Seasonal analyses: Spring (III)

NASA Astrophysics Data System (ADS)

Salinas Solé, Celia; Peña Angulo, Dhais; Gonzalez Hidalgo, Jose Carlos; Brunetti, Michele

2017-04-01

In this poster we applied the moving window approach (see Poster I of this collection) to analyze trends of spring and its corresponding months (March, April, May) temperature mean values of maximum (Tmax) and minimum (Tmin) in Spanish mainland to detect the effects of length period and starting year. Monthly series belong to Monthly Temperature dataset of Spanish mainland (MOTEDAS). Database contains in its grid format of 5236 pixels of monthly series (10x10 km). The threshold used in spatial analyses considers 20% of land under significant trend (p<0.05). The most striking results are as follow: • Seasonal Tmax shows that global trend was positive and significant until the mid 80's with higher values than 75% from between 1954-2010 to 1979-2010, being reduced after to the north region. So, from 1985-2010 no significant trend have been detected. Monthly analyses show differences. March trend is not significant (<20% of area) since 1974-2010, while significant trend in April and May varies between 1961-2010/1979-2010 and 1965-2010/1980-2010 respectively, clearly located in northern midland and Mediterranean coastland. • Spring Tmin trend analyses is significantly (>20%) during all temporal windows, notwithstanding NW do not show global significant trend, and in the most recent temporal windows only affect significantly SE. Monthly analyses also differ. Not significant trend is detected in March from 1979-2010, and from 1985-2010 in May, being April the month in any temporal windows with more than 20% of land affected by significant trend. • Spatial differences are detected between windows (South-North in March, East-West in April-May. We can conclude Tmax trend varies accordingly temporal windows dramatically in spring and no significance has been detected in the recent decades. Northern areas and Mediterranean coastland seems to be the most affected. Monthy Tmax trend spatial analyses confirm the heterogeneity of diurnal temperatures; different spatial gradients in windows have been detected between months. Seasonal Tmin show a more global temporal pattern. Spatial gradients of significance between months have been detected, in some sense contraries to the observed in Tmax.

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

PubMed

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

2014-08-01

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

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

PubMed

Heino, Jani; Melo, Adriano S; Bini, Luis Mauricio; Altermatt, Florian; Al-Shami, Salman A; Angeler, David G; Bonada, Núria; Brand, Cecilia; Callisto, Marcos; Cottenie, Karl; Dangles, Olivier; Dudgeon, David; Encalada, Andrea; Göthe, Emma; Grönroos, Mira; Hamada, Neusa; Jacobsen, Dean; Landeiro, Victor L; Ligeiro, Raphael; Martins, Renato T; Miserendino, María Laura; Md Rawi, Che Salmah; Rodrigues, Marciel E; Roque, Fabio de Oliveira; Sandin, Leonard; Schmera, Denes; Sgarbi, Luciano F; Simaika, John P; Siqueira, Tadeu; Thompson, Ross M; Townsend, Colin R

2015-03-01

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.

Imaging of Scleral Collagen Deformation Using Combined Confocal Raman Microspectroscopy and Polarized Light Microscopy Techniques.

PubMed

Chakraborty, Nilay; Wang, Mian; Solocinski, Jason; Kim, Wonsuk; Argento, Alan

2016-01-01

This work presents an optospectroscopic characterization technique for soft tissue microstructure using site-matched confocal Raman microspectroscopy and polarized light microscopy. Using the technique, the microstructure of soft tissue samples is directly observed by polarized light microscopy during loading while spatially correlated spectroscopic information is extracted from the same plane, verifying the orientation and arrangement of the collagen fibers. Results show the response and orientation of the collagen fiber arrangement in its native state as well as during tensile and compressive loadings in a porcine sclera model. An example is also given showing how the data can be used with a finite element program to estimate the strain in individual collagen fibers. The measurements demonstrate features that indicate microstructural reorganization and damage of the sclera's collagen fiber arrangement under loading. The site-matched confocal Raman microspectroscopic characterization of the tissue provides a qualitative measure to relate the change in fibrillar arrangement with possible chemical damage to the collagen microstructure. Tests and analyses presented here can potentially be used to determine the stress-strain behavior, and fiber reorganization of the collagen microstructure in soft tissue during viscoelastic response.

Analysis of Multi-Antenna GNSS Receiver Performance under Jamming Attacks.

PubMed

Vagle, Niranjana; Broumandan, Ali; Lachapelle, Gérard

2016-11-17

Although antenna array-based Global Navigation Satellite System (GNSS) receivers can be used to mitigate both narrowband and wideband electronic interference sources, measurement distortions induced by array processing methods are not suitable for high precision applications. The measurement distortions have an adverse effect on the carrier phase ambiguity resolution, affecting the navigation solution. Depending on the array attitude information availability and calibration parameters, different spatial processing methods can be implemented although they distort carrier phase measurements in some cases. This paper provides a detailed investigation of the effect of different array processing techniques on array-based GNSS receiver measurements and navigation performance. The main novelty of the paper is to provide a thorough analysis of array-based GNSS receivers employing different beamforming techniques from tracking to navigation solution. Two beamforming techniques, namely Power Minimization (PM) and Minimum Power Distortionless Response (MPDR), are being investigated. In the tracking domain, the carrier Doppler, Phase Lock Indicator (PLI), and Carrier-to-Noise Ratio (C/N₀) are analyzed. Pseudorange and carrier phase measurement distortions and carrier phase position performance are also evaluated. Performance analyses results from simulated GNSS signals and field tests are provided.

Beamforming array techniques for acoustic emission monitoring of large concrete structures

NASA Astrophysics Data System (ADS)

McLaskey, Gregory C.; Glaser, Steven D.; Grosse, Christian U.

2010-06-01

This paper introduces a novel method of acoustic emission (AE) analysis which is particularly suited for field applications on large plate-like reinforced concrete structures, such as walls and bridge decks. Similar to phased-array signal processing techniques developed for other non-destructive evaluation methods, this technique adapts beamforming tools developed for passive sonar and seismological applications for use in AE source localization and signal discrimination analyses. Instead of relying on the relatively weak P-wave, this method uses the energy-rich Rayleigh wave and requires only a small array of 4-8 sensors. Tests on an in-service reinforced concrete structure demonstrate that the azimuth of an artificial AE source can be determined via this method for sources located up to 3.8 m from the sensor array, even when the P-wave is undetectable. The beamforming array geometry also allows additional signal processing tools to be implemented, such as the VESPA process (VElocity SPectral Analysis), whereby the arrivals of different wave phases are identified by their apparent velocity of propagation. Beamforming AE can reduce sampling rate and time synchronization requirements between spatially distant sensors which in turn facilitates the use of wireless sensor networks for this application.

Downscaling Global Land Cover Projections from an Integrated Assessment Model for Use in Regional Analyses: Results and Evaluation for the US from 2005 to 2095

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

West, Tristram O.; Le Page, Yannick LB; Huang, Maoyi

2014-06-05

Projections of land cover change generated from Integrated Assessment Models (IAM) and other economic-based models can be applied for analyses of environmental impacts at subregional and landscape scales. For those IAM and economic models that project land use at the sub-continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30m) and at the global extent with relatively coarse spatial resolution (0.5 degree).

Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds

USGS Publications Warehouse

O'Connell, Allan F.; Gardner, Beth; Oppel, Steffen; Meirinho, Ana; Ramírez, Iván; Miller, Peter I.; Louzao, Maite

2012-01-01

Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (Puffinus mauretanicus) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.

Neogene Uplift and Magmatism of Anatolia: New Insights from Drainage Analysis and Basalt Geochemistry

NASA Astrophysics Data System (ADS)

McNab, F.; Ball, P.; Hoggard, M.; White, N.

2017-12-01

The origin of Anatolia's high elevation and low relief plateaux has been the subject of much recent debate. Marine sedimentary rocks distributed across Central and Eastern Anatolia require significant regional uplift in Neogene times. This uplift cannot be explained by the present-day pattern of crustal deformation which, particularly across Central and Western Anatolia, is dominanted by strike-slip and extensional faulting. Positive long wavelength free-air gravity anomalies combined with slow upper mantle seismic wave speeds suggest that the sub-lithospheric mantle provides substantial topographic support. A range of geodynamic processes have been invoked, including complex slab fragmentation and lithospheric delamination. The temporal and spatial evolution of the Anatolian landscape should be recorded by drainage networks. Indeed, major catchments contain prominent knickzones with heights of hundreds of meters and length scales of several hundred kilometers. The stream power formulation for fluvial erosion permits these knickzones to be interpreted in terms of uplift history along a river's length. Here, we jointly invert an inventory of 1,844 river profiles to determine a spatial and temporal uplift rate history. When calibrated against independent observations of uplift rate, the resultant history provides significant new constraints for the evolution of Anatolian topography. In our model, the bulk of this topography appears to grow in Neogene times. Uplift initiates in Eastern Anatolia and propagates westward at uplift rates of up to 0.5 mm/yr. Coeval with this phase of uplift, abundant basaltic magmatism has occurred throughout Anatolia. We have compiled an extensive database of published geochemical analyses. Using this database, we analyse spatial and temporal patterns of basaltic compositions to discriminate between different modes of melt generation. Two independent techniques for estimating asthenospheric potential temperatures from the compositions of high-Mg basalts have been used. Elevated temperatures of c. 1380 ºC occur beneath Eastern Anatolia with a notable decrease towards the west. Overall, our results imply that the spatial and temporal evolution Anatolian topography is controlled by temperature variations within the asthenospheric mantle.

Synchrotron x-ray imaging of acoustic cavitation bubbles induced by acoustic excitation

NASA Astrophysics Data System (ADS)

Jung, Sung Yong; Park, Han Wook; Park, Sung Ho; Lee, Sang Joon

2017-04-01

The cavitation induced by acoustic excitation has been widely applied in various biomedical applications because cavitation bubbles can enhance the exchanges of mass and energy. In order to minimize the hazardous effects of the induced cavitation, it is essential to understand the spatial distribution of cavitation bubbles. The spatial distribution of cavitation bubbles visualized by the synchrotron x-ray imaging technique is compared to that obtained with a conventional x-ray tube. Cavitation bubbles with high density in the region close to the tip of the probe are visualized using the synchrotron x-ray imaging technique, however, the spatial distribution of cavitation bubbles in the whole ultrasound field is not detected. In this study, the effects of the ultrasound power of acoustic excitation and working medium on the shape and density of the induced cavitation bubbles are examined. As a result, the synchrotron x-ray imaging technique is useful for visualizing spatial distributions of cavitation bubbles, and it could be used for optimizing the operation conditions of acoustic cavitation.

Extracellular oxygen concentration mapping with a confocal multiphoton laser scanning microscope and TCSPC card

NASA Astrophysics Data System (ADS)

Hosny, Neveen A.; Lee, David A.; Knight, Martin M.

2010-02-01

Extracellular oxygen concentrations influence cell metabolism and tissue function. Fluorescence Lifetime Imaging Microscopy (FLIM) offers a non-invasive method for quantifying local oxygen concentrations. However, existing methods show limited spatial resolution and/or require custom made systems. This study describes a new optimised approach for quantitative extracellular oxygen detection, providing an off-the-shelf system with high spatial resolution and an improved lifetime determination over previous techniques, while avoiding systematic photon pile-up. Fluorescence lifetime detection of an oxygen sensitive fluorescent dye, tris(2,2'-bipyridyl)ruthenium(II) chloride hexahydrate [Ru(bipy)3]2+, was measured using a Becker&Hickl time-correlated single photon counting (TCSPC) card with excitation provided by a multi-photon laser. This technique was able to identify a subpopulation of isolated chondrocyte cells, seeded in three-dimensional agarose gel, displaying a significant spatial oxygen gradient. Thus this technique provides a powerful tool for quantifying spatial oxygen gradients within three-dimensional cellular models.

Assessing the spatial representability of charcoal and PAH-based paleofire records with integrated GIS, modelling, and empirical approaches

NASA Astrophysics Data System (ADS)

Vachula, R. S.; Huang, Y.; Russell, J. M.

2017-12-01

Lake sediment-based fire reconstructions offer paleoenvironmental context in which to assess modern fires and predict future burning. However, despite the ubiquity, many uncertainties remain regarding the taphonomy of paleofire proxies and the spatial scales for which they record variations in fire history. Here we present down-core proxy analyses of polycyclic aromatic hydrocarbons (PAHs) and three size-fractions of charcoal (63-150, >150 and >250 μm) from Swamp Lake, California, an annually laminated lacustrine archive. Using a statewide historical GIS dataset of area burned, we assess the spatial scales for which these proxies are reliable recorders of fire history. We find that the coherence of observed and proxy-recorded fire history inherently depends upon spatial scale. Contrary to conventional thinking that charcoal mainly records local fires, our results indicate that macroscopic charcoal (>150 μm) may record spatially broader (<25 km) changes in fire history, and as such, the coarsest charcoal particles (>250 μm) may be a more conservative proxy for local burning. We find that sub-macroscopic charcoal particles (63-150 μm) reliably record regional (up to 150 km) changes in fire history. These results indicate that charcoal-based fire reconstructions may represent spatially broader fire history than previously thought, which has major implications for our understanding of spatiotemporal paleofire variations. Our analyses of PAHs show that dispersal mobility is heterogeneous between compounds, but that PAH fluxes are reliable proxies of fire history within 25-50 km, which suggests PAHs may be a better spatially constrained paleofire proxy than sedimentary charcoal. Further, using a linear discriminant analysis model informed by modern emissions analyses, we show that PAH assemblages preserved in lake sediments can differentiate vegetation type burned, and are thus promising paleoecological biomarkers warranting further research and implementation. In sum, our analyses offer new insight into the spatial dimensions of paleofire proxies and constitute a methodology that can be applied to other locations and proxies to better inform site-specific reconstructions.

Development of portable defocusing micro-scale spatially offset Raman spectroscopy.

PubMed

Realini, Marco; Botteon, Alessandra; Conti, Claudia; Colombo, Chiara; Matousek, Pavel

2016-05-10

We present, for the first time, portable defocusing micro-Spatially Offset Raman Spectroscopy (micro-SORS). Micro-SORS is a concept permitting the analysis of thin, highly turbid stratified layers beyond the reach of conventional Raman microscopy. The technique is applicable to the analysis of painted layers in cultural heritage (panels, canvases and mural paintings, painted statues and decorated objects in general) as well as in many other areas including polymer, biological and biomedical applications, catalytic and forensics sciences where highly turbid stratified layers are present and where invasive analysis is undesirable or impossible. So far the technique has been demonstrated only on benchtop Raman microscopes precluding the non-invasive analysis of larger samples and samples in situ. The new set-up is characterised conceptually on a range of artificially assembled two-layer systems demonstrating its benefits and performance across several application areas. These included stratified polymer sample, pharmaceutical tablet and layered paint samples. The same samples were also analysed by a high performance (non-portable) benchtop Raman microscope to provide benchmarking against our earlier research. The realisation of the vision of delivering portability to micro-SORS has a transformative potential spanning across multiple disciplines as it fully unlocks, for the first time, the non-invasive and non-destructive aspects of micro-SORS enabling it to be applied also to large and non-portable samples in situ without recourse to removing samples, or their fragments, for laboratory analysis on benchtop Raman microscopes.

Assessment of geometry in 2D immune systems using high accuracy laser-based bioprinting techniques (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lauzurica, Sara; Márquez, Andrés.; Molpeceres, Carlos; Notario, Laura; Gómez-Fontela, Miguel; Lauzurica, Pilar

2017-02-01

The immune system is a very complex system that comprises a network of genetic and signaling pathways subtending a network of interacting cells. The location of the cells in a network, along with the gene products they interact with, rules the behavior of the immune system. Therefore, there is a great interest in understanding properly the role of a cell in such networks to increase our knowledge of the immune system response. In order to acquire a better understanding of these processes, cell printing with high spatial resolution emerges as one of the promising approaches to organize cells in two and three-dimensional patterns to enable the study the geometry influence in these interactions. In particular, laser assisted bio-printing techniques using sub-nanosecond laser sources have better characteristics for application in this field, mainly due to its higher spatial resolution, cell viability percentage and process automation. This work presents laser assisted bio-printing of antigen-presenting cells (APCs) in two-dimensional geometries, placing cellular components on a matrix previously generated on demand, permitting to test the molecular interactions between APCs and lymphocytes; as well as the generation of two-dimensional structures designed ad hoc in order to study the mechanisms of mobilization of immune system cells. The use of laser assisted bio-printing, along with APCs and lymphocytes emulate the structure of different niches of the immune system so that we can analyse functional requirement of these interaction.

Decay assessment through thermographic analysis in architectural and archaeological heritage

NASA Astrophysics Data System (ADS)

Gomez-Heras, Miguel; Martinez-Perez, Laura; Fort, Rafael; Alvarez de Buergo, Monica

2010-05-01

Any exposed stone-built structure is subject to thermal variations due to daily, seasonal and secular environmental temperature changes. Surface temperature is a function of air temperature (due to convective heat transfer) and of infrared radiation received through insolation. While convective heat transfer homogenizes surface temperature, stone response to insolation is much more complex and the temporal and spatial temperature differences across structures are enhanced. Surface temperature in stone-built structures will be affected by orientation, sunlight inclination and the complex patterns of light and shadows generated by the often intricate morphology of historical artefacts and structures. Surface temperature will also be affected by different material properties, such as albedo, thermal conductivity, transparency and absorbance to infrared radiation of minerals and rocks. Moisture and the occurrence of salts will also be a factor affecting surface temperatures. Surface temperatures may as well be affected by physical disruptions of rocks due to differences in thermal inertia generated by cracks and other discontinuities. Thermography is a non-invasive, non-destructive technique that measures temperature variations on the surface of a material. With this technique, surface temperature rates of change and their spatial variations can be analysed. This analysis may be used not only to evaluate the incidence of thermal decay as a factor that generates or enhances stone decay, but also to detect and evaluate other factors that affect the state of conservation of architectural and archaeological heritage, as for example moisture, salts or mechanical disruptions.

Semi-automted analysis of high-resolution aerial images to quantify docks in Upper Midwest glacial lakes

USGS Publications Warehouse

Beck, Marcus W.; Vondracek, Bruce C.; Hatch, Lorin K.; Vinje, Jason

2013-01-01

Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on ) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.

Three-dimensional spectral-spatial EPR imaging of free radicals in the heart: a technique for imaging tissue metabolism and oxygenation.

PubMed Central

Kuppusamy, P; Chzhan, M; Vij, K; Shteynbuk, M; Lefer, D J; Giannella, E; Zweier, J L

1994-01-01

It has been hypothesized that free radical metabolism and oxygenation in living organs and tissues such as the heart may vary over the spatially defined tissue structure. In an effort to study these spatially defined differences, we have developed electron paramagnetic resonance imaging instrumentation enabling the performance of three-dimensional spectral-spatial images of free radicals infused into the heart and large vessels. Using this instrumentation, high-quality three-dimensional spectral-spatial images of isolated perfused rat hearts and rabbit aortas are obtained. In the isolated aorta, it is shown that spatially and spectrally accurate images of the vessel lumen and wall could be obtained in this living vascular tissue. In the isolated rat heart, imaging experiments were performed to determine the kinetics of radical clearance at different spatial locations within the heart during myocardial ischemia. The kinetic data show the existence of regional and transmural differences in myocardial free radical clearance. It is further demonstrated that EPR imaging can be used to noninvasively measure spatially localized oxygen concentrations in the heart. Thus, the technique of spectral-spatial EPR imaging is shown to be a powerful tool in providing spatial information regarding the free radical distribution, metabolism, and tissue oxygenation in living biological organs and tissues. Images PMID:8159757

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method

NASA Astrophysics Data System (ADS)

Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.

2017-02-01

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

Image coding of SAR imagery

NASA Technical Reports Server (NTRS)

Chang, C. Y.; Kwok, R.; Curlander, J. C.

1987-01-01

Five coding techniques in the spatial and transform domains have been evaluated for SAR image compression: linear three-point predictor (LTPP), block truncation coding (BTC), microadaptive picture sequencing (MAPS), adaptive discrete cosine transform (ADCT), and adaptive Hadamard transform (AHT). These techniques have been tested with Seasat data. Both LTPP and BTC spatial domain coding techniques provide very good performance at rates of 1-2 bits/pixel. The two transform techniques, ADCT and AHT, demonstrate the capability to compress the SAR imagery to less than 0.5 bits/pixel without visible artifacts. Tradeoffs such as the rate distortion performance, the computational complexity, the algorithm flexibility, and the controllability of compression ratios are also discussed.

Holographic grating relaxation technique for soft matter science

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

Lesnichii, Vasilii, E-mail: vasilii.lesnichii@physchem.uni-freiburg.de; ITMO University, Kronverksky prospekt 49, Saint-Petersburg 197101; Kiessling, Andy

2016-06-17

The holographic grating relaxation technique also known as forced Rayleigh scattering consists basically in writing a holographic grating in the specimen of interest and monitoring its diffraction efficiency as a function of time, from which valuable information on mass or heat transfer and photoinduced transformations can be extracted. In a more detailed view, the shape of the relaxation curve and the relaxation rate as a function of the grating period were found to be affected by the architecture of diffusing species (molecular probes) that constitute the grating, as well as that of the environment they diffuse in, thus making itmore » possible to access and study spatial heterogeneity of materials and different modes of e.g., polymer motion. Minimum displacements and spatial domains approachable by the technique are in nanometer range, well below spatial periods of holographic gratings. In the present paper, several cases of holographic relaxation in heterogeneous media and complex motions are exemplified. Nano- to micro-structures or inhomogeneities comparable in spatial scale with holographic gratings manifest themselves in relaxation experiments via non-exponential decay (stepwise or stretched), spatial-period-dependent apparent diffusion coefficient, or unusual dependence of diffusion coefficient on molecular volume of diffusing probes.« less

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

PubMed

Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

Assessing potential spatial accessibility of health services in rural China: a case study of Donghai county

PubMed Central

2013-01-01

Introduction There is a great health services disparity between urban and rural areas in China. The percentage of people who are unable to access health services due to long travel times increases. This paper takes Donghai County as the study unit to analyse areas with physician shortages and characteristics of the potential spatial accessibility of health services. We analyse how the unequal health services resources distribution and the New Cooperative Medical Scheme affect the potential spatial accessibility of health services in Donghai County. We also give some advice on how to alleviate the unequal spatial accessibility of health services in areas that are more remote and isolated. Methods The shortest traffic times of from hospitals to villages are calculated with an O-D matrix of GIS extension model. This paper applies an enhanced two-step floating catchment area (E2SFCA) method to study the spatial accessibility of health services and to determine areas with physician shortages in Donghai County. The sensitivity of the E2SFCA for assessing variation in the spatial accessibility of health services is checked using different impedance coefficient valuesa. Geostatistical Analyst model and spatial analyst method is used to analyse the spatial pattern and the edge effect of potential spatial accessibility of health services. Results The results show that 69% of villages have access to lower potential spatial accessibility of health services than the average for Donghai County, and 79% of the village scores are lower than the average for Jiangsu Province. The potential spatial accessibility of health services diminishes greatly from the centre of the county to outlying areas. Using a smaller impedance coefficient leads to greater disparity among the villages. The spatial accessibility of health services is greater along highway in the county. Conclusions Most of villages are in underserved health services areas. An unequal distribution of health service resources and the reimbursement policies of the New Cooperative Medical Scheme have led to an edge effect regarding spatial accessibility of health services in Donghai County, whereby people living on the edge of the county have less access to health services. Comprehensive measures should be considered to alleviate the unequal spatial accessibility of health services in areas that are more remote and isolated. PMID:23688278

Uncertainties on the definition of critical rainfall patterns for debris-flows triggering. Results from the Rebaixader monitoring site (Central Pyrenees)

NASA Astrophysics Data System (ADS)

Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc

2015-04-01

Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the catchment may be considered useful or not to describe the rainfall depending on the type of rainfall. For widespread rainfalls, further rain gauges can give a reliable measurement, because the spatial correlation decreases slowly with the distance between the rain gauge and the debris-flow initiation area. Contrarily, local storm cells show higher space-time variability and, therefore, representative rainfall measurements are obtained only by the closest rain gauges. In conclusion, the definition of rainfall thresholds is a delicate task. When the rainfall records are coming from gauges that are outside the catchment under consideration, the data should be carefully analysed and crosschecked with radar data (especially for small convective cells).

The star formation history of the Hubble sequence: spatially resolved colour distributions of intermediate-redshift galaxies in the Hubble Deep Field

NASA Astrophysics Data System (ADS)

Abraham, R. G.; Ellis, R. S.; Fabian, A. C.; Tanvir, N. R.; Glazebrook, K.

1999-03-01

We analyse the spatially resolved colours of distant galaxies of known redshift in the Hubble Deep Field, using a new technique based on matching resolved four-band colour data to the predictions of evolutionary synthesis models. Given some simplifying assumptions, we demonstrate how our technique is capable of probing the evolutionary history of high-redshift systems, noting the specific advantage of observing galaxies at an epoch closer to the time of their formation. We quantify the relative age, dispersion in age, on-going star formation rate and star formation history of distinct components. We explicitly test for the presence of dust and quantify its effect on our conclusions. To demonstrate the potential of the method, we study the spirals and ellipticals in the near-complete sample of 32 I_814<21.9 mag galaxies with z~0.5 studied by Bouwens, Broadhurst & Silk. The dispersion of the internal colours of a sample of 0.4

The spatial patterns of directional phenotypic selection.

PubMed

Siepielski, Adam M; Gotanda, Kiyoko M; Morrissey, Michael B; Diamond, Sarah E; DiBattista, Joseph D; Carlson, Stephanie M

2013-11-01

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.

Probing spatial locality in ionic liquids with the grand canonical adaptive resolution molecular dynamics technique

NASA Astrophysics Data System (ADS)

Shadrack Jabes, B.; Krekeler, C.; Klein, R.; Delle Site, L.

2018-05-01

We employ the Grand Canonical Adaptive Resolution Simulation (GC-AdResS) molecular dynamics technique to test the spatial locality of the 1-ethyl 3-methyl imidazolium chloride liquid. In GC-AdResS, atomistic details are kept only in an open sub-region of the system while the environment is treated at coarse-grained level; thus, if spatial quantities calculated in such a sub-region agree with the equivalent quantities calculated in a full atomistic simulation, then the atomistic degrees of freedom outside the sub-region play a negligible role. The size of the sub-region fixes the degree of spatial locality of a certain quantity. We show that even for sub-regions whose radius corresponds to the size of a few molecules, spatial properties are reasonably reproduced thus suggesting a higher degree of spatial locality, a hypothesis put forward also by other researchers and that seems to play an important role for the characterization of fundamental properties of a large class of ionic liquids.

Spatial Ability Learning through Educational Robotics

ERIC Educational Resources Information Center

Julià, Carme; Antolí, Juan Òscar

2016-01-01

Several authors insist on the importance of students' acquisition of spatial abilities and visualization in order to have academic success in areas such as science, technology or engineering. This paper proposes to discuss and analyse the use of educational robotics to develop spatial abilities in 12 year old students. First of all, a course to…

Using experimental design and spatial analyses to improve the precision of NDVI estimates in upland cotton field trials

USDA-ARS?s Scientific Manuscript database

Controlling for spatial variability is important in high-throughput phenotyping studies that enable large numbers of genotypes to be evaluated across time and space. In the current study, we compared the efficacy of different experimental designs and spatial models in the analysis of canopy spectral...

Characterizing forest fragments in boreal, temperate, and tropical ecosystems

Treesearch

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

2008-01-01

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

Assessing the role of spatial correlations during collective cell spreading

PubMed Central

Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.

2014-01-01

Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987

Controlled supercontinua via spatial beam shaping

NASA Astrophysics Data System (ADS)

Zhdanova, Alexandra A.; Shen, Yujie; Thompson, Jonathan V.; Scully, Marlan O.; Yakovlev, Vladislav V.; Sokolov, Alexei V.

2018-06-01

Recently, optimization techniques have had a significant impact in a variety of fields, leading to a higher signal-to-noise and more streamlined techniques. We consider the possibility for using programmable phase-only spatial optimization of the pump beam to influence the supercontinuum generation process. Preliminary results show that significant broadening and rough control of the supercontinuum spectrum in the visible region are possible without loss of input energy. This serves as a proof-of-concept demonstration that spatial effects can controllably influence the supercontinuum spectrum, leading to possibilities for utilizing supercontinuum power more efficiently and achieving excellent spectral control.

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

2012-01-01

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

High spatial resolution restoration of IRAS images

NASA Technical Reports Server (NTRS)

Grasdalen, Gary L.; Inguva, R.; Dyck, H. Melvin; Canterna, R.; Hackwell, John A.

1990-01-01

A general technique to improve the spatial resolution of the IRAS AO data was developed at The Aerospace Corporation using the Maximum Entropy algorithm of Skilling and Gull. The technique has been applied to a variety of fields and several individual AO MACROS. With this general technique, resolutions of 15 arcsec were achieved in 12 and 25 micron images and 30 arcsec in 60 and 100 micron images. Results on galactic plane fields show that both photometric and positional accuracy achieved in the general IRAS survey are also achieved in the reconstructed images.

Characteristic-eddy decomposition of turbulence in a channel

NASA Technical Reports Server (NTRS)

Moin, Parviz; Moser, Robert D.

1989-01-01

Lumley's proper orthogonal decomposition technique is applied to the turbulent flow in a channel. Coherent structures are extracted by decomposing the velocity field into characteristic eddies with random coefficients. A generalization of the shot-noise expansion is used to determine the characteristic eddies in homogeneous spatial directions. Three different techniques are used to determine the phases of the Fourier coefficients in the expansion: (1) one based on the bispectrum, (2) a spatial compactness requirement, and (3) a functional continuity argument. Similar results are found from each of these techniques.

Tempo-spatial analysis of Fennoscandian intraplate seismicity

NASA Astrophysics Data System (ADS)

Roberts, Roland; Lund, Björn

2017-04-01

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

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia.

PubMed

Tadesse, Sebsibe; Enqueselassie, Fikre; Hagos, Seifu

2018-01-01

Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016. A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran's I, Getis-Ord [Formula: see text] and Kulldorff's scan statistics. Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period. This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme.

PubMed

Espinosa, Manuel O; Polop, Francisco; Rotela, Camilo H; Abril, Marcelo; Scavuzzo, Carlos M

2016-11-21

The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

LWIR hyperspectral change detection for target acquisition and situation awareness in urban areas

NASA Astrophysics Data System (ADS)

Dekker, Rob J.; Schwering, Piet B. W.; Benoist, Koen W.; Pignatti, Stefano; Santini, Federico; Friman, Ola

2013-05-01

This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.

Detection of trace nitric oxide concentrations using 1-D laser-induced fluorescence imaging

NASA Astrophysics Data System (ADS)

Yoo, J.; Lee, T.; Jeffries, J. B.; Hanson, R. K.

2008-06-01

Spectrally resolved laser-induced fluorescence (LIF) with one-dimensional spatial imaging was investigated as a technique for detection of trace concentrations of nitric oxide (NO) in high-pressure flames. Experiments were performed in the burnt gases of premixed methane/argon/oxygen flames with seeded NO (15 to 50 ppm), pressures of 10 to 60 bar, and an equivalence ratio of 0.9. LIF signals were dispersed with a spectrometer and recorded on a 2-D intensified CCD array yielding both spectral resolution and 1-D spatial resolution. This method allows isolation of NO-LIF from interference signals due to alternative species (mainly hot O2 and CO2) while providing spatial resolution along the line of the excitation laser. A fast data analysis strategy was developed to enable pulse-by-pulse NO concentration measurements from these images. Statistical analyses as a function of laser energy of these single-shot data were used to determine the detection limits for NO concentration as well as the measurement precision. Extrapolating these results to pulse energies of ˜ 16 mJ/pulse yielded a predicted detection limit of ˜ 10 ppm for pressures up to 60 bar. Quantitative 1-D LIF measurements were performed in CH4/air flames to validate capability for detection of nascent NO in flames at 10-60 bar.

Visuo-spatial ability in colonoscopy simulator training.

PubMed

Luursema, Jan-Maarten; Buzink, Sonja N; Verwey, Willem B; Jakimowicz, J J

2010-12-01

Visuo-spatial ability is associated with a quality of performance in a variety of surgical and medical skills. However, visuo-spatial ability is typically assessed using Visualization tests only, which led to an incomplete understanding of the involvement of visuo-spatial ability in these skills. To remedy this situation, the current study investigated the role of a broad range of visuo-spatial factors in colonoscopy simulator training. Fifteen medical trainees (no clinical experience in colonoscopy) participated in two psycho-metric test sessions to assess four visuo-spatial ability factors. Next, participants trained flexible endoscope manipulation, and navigation to the cecum on the GI Mentor II simulator, for four sessions within 1 week. Visualization, and to a lesser degree Spatial relations were the only visuo-spatial ability factors to correlate with colonoscopy simulator performance. Visualization additionally covaried with learning rate for time on task on both simulator tasks. High Visualization ability indicated faster exercise completion. Similar to other endoscopic procedures, performance in colonoscopy is positively associated with Visualization, a visuo-spatial ability factor characterized by the ability to mentally manipulate complex visuo-spatial stimuli. The complexity of the visuo-spatial mental transformations required to successfully perform colonoscopy is likely responsible for the challenging nature of this technique, and should inform training- and assessment design. Long term training studies, as well as studies investigating the nature of visuo-spatial complexity in this domain are needed to better understand the role of visuo-spatial ability in colonoscopy, and other endoscopic techniques.

DEVELOPMENT OF AN AGAR LIFT-DNA/DNA HYBRIDIZATION TECHNIQUE FOR USE IN VISUALIZATION OF THE SPATIAL DISTRIBUTION OF EUBACTERIA ON SOIL SURFACES. (R825415)

EPA Science Inventory

Abstract

While microbial growth is well-understood in pure culture systems, less is known about growth in intact soil systems. The objective of this work was to develop a technique to allow visualization of the two-dimensional spatial distribution of bacterial growth o...

Dynamic nuclear polarization and optimal control spatial-selective 13C MRI and MRS

NASA Astrophysics Data System (ADS)

Vinding, Mads S.; Laustsen, Christoffer; Maximov, Ivan I.; Søgaard, Lise Vejby; Ardenkjær-Larsen, Jan H.; Nielsen, Niels Chr.

2013-02-01

Aimed at 13C metabolic magnetic resonance imaging (MRI) and spectroscopy (MRS) applications, we demonstrate that dynamic nuclear polarization (DNP) may be combined with optimal control 2D spatial selection to simultaneously obtain high sensitivity and well-defined spatial restriction. This is achieved through the development of spatial-selective single-shot spiral-readout MRI and MRS experiments combined with dynamic nuclear polarization hyperpolarized [1-13C]pyruvate on a 4.7 T pre-clinical MR scanner. The method stands out from related techniques by facilitating anatomic shaped region-of-interest (ROI) single metabolite signals available for higher image resolution or single-peak spectra. The 2D spatial-selective rf pulses were designed using a novel Krotov-based optimal control approach capable of iteratively fast providing successful pulse sequences in the absence of qualified initial guesses. The technique may be important for early detection of abnormal metabolism, monitoring disease progression, and drug research.

Adaptive proxy map server for efficient vector spatial data rendering

NASA Astrophysics Data System (ADS)

Sayar, Ahmet

2013-01-01

The rapid transmission of vector map data over the Internet is becoming a bottleneck of spatial data delivery and visualization in web-based environment because of increasing data amount and limited network bandwidth. In order to improve both the transmission and rendering performances of vector spatial data over the Internet, we propose a proxy map server enabling parallel vector data fetching as well as caching to improve the performance of web-based map servers in a dynamic environment. Proxy map server is placed seamlessly anywhere between the client and the final services, intercepting users' requests. It employs an efficient parallelization technique based on spatial proximity and data density in case distributed replica exists for the same spatial data. The effectiveness of the proposed technique is proved at the end of the article by the application of creating map images enriched with earthquake seismic data records.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review

PubMed Central

Lamb, Karen E.; Thornton, Lukar E.; Cerin, Ester; Ball, Kylie

2015-01-01

Background Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Methods Searches were conducted for articles published from 2000–2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Results Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. Conclusions With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results. PMID:29546115

Could the outcome of the 2016 US elections have been predicted from past voting patterns?

NASA Astrophysics Data System (ADS)

Schmitz, Peter M. U.; Holloway, Jennifer P.; Dudeni-Tlhone, Nontembeko; Ntlangu, Mbulelo B.; Koen, Renee

2018-05-01

In South Africa, a team of analysts has for some years been using statistical techniques to predict election outcomes during election nights in South Africa. The prediction method involves using statistical clusters based on past voting patterns to predict final election outcomes, using a small number of released vote counts. With the US presidential elections in November 2016 hitting the global media headlines during the time period directly after successful predictions were done for the South African elections, the team decided to investigate adapting their meth-od to forecast the final outcome in the US elections. In particular, it was felt that the time zone differences between states would affect the time at which results are released and thereby provide a window of opportunity for doing election night prediction using only the early results from the eastern side of the US. Testing the method on the US presidential elections would have two advantages: it would determine whether the core methodology could be generalised, and whether it would work to include a stronger spatial element in the modelling, since the early results released would be spatially biased due to time zone differences. This paper presents a high-level view of the overall methodology and how it was adapted to predict the results of the US presidential elections. A discussion on the clustering of spatial units within the US is also provided and the spatial distribution of results together with the Electoral College prediction results from both a `test-run' and the final 2016 presidential elections are given and analysed.

Constraining geostatistical models with hydrological data to improve prediction realism

NASA Astrophysics Data System (ADS)

Demyanov, V.; Rojas, T.; Christie, M.; Arnold, D.

2012-04-01

Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model parameters to the data may lead to geostatistical realisations with unrealistic spatial patterns, which would still honour the data. Such model would result in poor predictions, even though although fit the available data well. Conditioning the model to a wider range of relevant data provide a remedy that avoid producing unrealistic features in spatial models. For instance, there are vast amounts of information about the geometries of river channels that can be used in describing fluvial environment. Relations between the geometrical channel characteristics (width, depth, wave length, amplitude, etc.) are complex and non-parametric and are exhibit a great deal of uncertainty, which is important to propagate rigorously into the predictive model. These relations can be described within a Bayesian approach as multi-dimensional prior probability distributions. We propose a way to constrain multi-point statistics models with intelligent priors obtained from analysing a vast collection of contemporary river patterns based on previously published works. We applied machine learning techniques, namely neural networks and support vector machines, to extract multivariate non-parametric relations between geometrical characteristics of fluvial channels from the available data. An example demonstrates how ensuring geological realism helps to deliver more reliable prediction of a subsurface oil reservoir in a fluvial depositional environment.

Habitat suitability mapping of Anopheles darlingi in the surroundings of the Manso hydropower plant reservoir, Mato Grosso, Central Brazil

PubMed Central

Zeilhofer, Peter; Santos, Emerson Soares dos; Ribeiro, Ana LM; Miyazaki, Rosina D; Santos, Marina Atanaka dos

2007-01-01

Background Hydropower plants provide more than 78 % of Brazil's electricity generation, but the country's reservoirs are potential new habitats for main vectors of malaria. In a case study in the surroundings of the Manso hydropower plant in Mato Grosso state, Central Brazil, habitat suitability of Anopheles darlingi was studied. Habitat profile was characterized by collecting environmental data. Remote sensing and GIS techniques were applied to extract additional spatial layers of land use, distance maps, and relief characteristics for spatial model building. Results Logistic regression analysis and ROC curves indicate significant relationships between the environment and presence of An. darlingi. Probabilities of presence strongly vary as a function of land cover and distance from the lake shoreline. Vector presence was associated with spatial proximity to reservoir and semi-deciduous forests followed by Cerrado woodland. Vector absence was associated with open vegetation formations such as grasslands and agricultural areas. We suppose that non-significant differences of vector incidences between rainy and dry seasons are associated with the availability of anthropogenic breeding habitat of the reservoir throughout the year. Conclusion Satellite image classification and multitemporal shoreline simulations through DEM-based GIS-analyses consist in a valuable tool for spatial modeling of A. darlingi habitats in the studied hydropower reservoir area. Vector presence is significantly increased in forested areas near reservoirs in bays protected from wind and wave action. Construction of new reservoirs under the tropical, sub-humid climatic conditions should therefore be accompanied by entomologic studies to predict the risk of malaria epidemics. PMID:17343728

Habitat suitability mapping of Anopheles darlingi in the surroundings of the Manso hydropower plant reservoir, Mato Grosso, Central Brazil.

PubMed

Zeilhofer, Peter; dos Santos, Emerson Soares; Ribeiro, Ana L M; Miyazaki, Rosina D; dos Santos, Marina Atanaka

2007-03-07

Hydropower plants provide more than 78 % of Brazil's electricity generation, but the country's reservoirs are potential new habitats for main vectors of malaria. In a case study in the surroundings of the Manso hydropower plant in Mato Grosso state, Central Brazil, habitat suitability of Anopheles darlingi was studied. Habitat profile was characterized by collecting environmental data. Remote sensing and GIS techniques were applied to extract additional spatial layers of land use, distance maps, and relief characteristics for spatial model building. Logistic regression analysis and ROC curves indicate significant relationships between the environment and presence of An. darlingi. Probabilities of presence strongly vary as a function of land cover and distance from the lake shoreline. Vector presence was associated with spatial proximity to reservoir and semi-deciduous forests followed by Cerrado woodland. Vector absence was associated with open vegetation formations such as grasslands and agricultural areas. We suppose that non-significant differences of vector incidences between rainy and dry seasons are associated with the availability of anthropogenic breeding habitat of the reservoir throughout the year. Satellite image classification and multitemporal shoreline simulations through DEM-based GIS-analyses consist in a valuable tool for spatial modeling of A. darlingi habitats in the studied hydropower reservoir area. Vector presence is significantly increased in forested areas near reservoirs in bays protected from wind and wave action. Construction of new reservoirs under the tropical, sub-humid climatic conditions should therefore be accompanied by entomologic studies to predict the risk of malaria epidemics.

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

PubMed Central

Wallace, Bryan P.; DiMatteo, Andrew D.; Hurley, Brendan J.; Finkbeiner, Elena M.; Bolten, Alan B.; Chaloupka, Milani Y.; Hutchinson, Brian J.; Abreu-Grobois, F. Alberto; Amorocho, Diego; Bjorndal, Karen A.; Bourjea, Jerome; Bowen, Brian W.; Dueñas, Raquel Briseño; Casale, Paolo; Choudhury, B. C.; Costa, Alice; Dutton, Peter H.; Fallabrino, Alejandro; Girard, Alexandre; Girondot, Marc; Godfrey, Matthew H.; Hamann, Mark; López-Mendilaharsu, Milagros; Marcovaldi, Maria Angela; Mortimer, Jeanne A.; Musick, John A.; Nel, Ronel; Pilcher, Nicolas J.; Seminoff, Jeffrey A.; Troëng, Sebastian; Witherington, Blair; Mast, Roderic B.

2010-01-01

Background Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques — including site-based monitoring, genetic analyses, mark-recapture studies and telemetry — can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework — including maps and supporting metadata — will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis. PMID:21253007

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox.

PubMed

Basto, Mafalda P; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox

PubMed Central

Basto, Mafalda P.; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W.; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation. PMID:26727497

Soot and Radiation Measurements in Microgravity Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Ku, Jerry C.

1996-01-01

The subject of soot formation and radiation heat transfer in microgravity jet diffusion flames is important not only for the understanding of fundamental transport processes involved but also for providing findings relevant to spacecraft fire safety and soot emissions and radiant heat loads of combustors used in air-breathing propulsion systems. Our objectives are to measure and model soot volume fraction, temperature, and radiative heat fluxes in microgravity jet diffusion flames. For this four-year project, we have successfully completed three tasks, which have resulted in new research methodologies and original results. First is the implementation of a thermophoretic soot sampling technique for measuring particle size and aggregate morphology in drop-tower and other reduced gravity experiments. In those laminar flames studied, we found that microgravity soot aggregates typically consist of more primary particles and primary particles are larger in size than those under normal gravity. Comparisons based on data obtained from limited samples show that the soot aggregate's fractal dimension varies within +/- 20% of its typical value of 1.75, with no clear trends between normal and reduced gravity conditions. Second is the development and implementation of a new imaging absorption technique. By properly expanding and spatially-filtering the laser beam to image the flame absorption on a CCD camera and applying numerical smoothing procedures, this technique is capable of measuring instantaneous full-field soot volume fractions. Results from this technique have shown the significant differences in local soot volume fraction, smoking point, and flame shape between normal and reduced gravity flames. We observed that some laminar flames become open-tipped and smoking under microgravity. The third task we completed is the development of a computer program which integrates and couples flame structure, soot formation, and flame radiation analyses together. We found good agreements between model predictions and experimental data for laminar and turbulent flames under both normal and reduced gravity. We have also tested in the laboratory the techniques of rapid-insertion fine-wire thermocouples and emission pyrometry for temperature measurements. These techniques as well as laser Doppler velocimetry and spectral radiative intensity measurement have been proposed to provide valuable data and improve the modeling analyses.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

Source-space ICA for MEG source imaging.

PubMed

Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging.

PubMed

Khairalseed, Mawia; Xiong, Fangyuan; Kim, Jung-Whan; Mattrey, Robert F; Parker, Kevin J; Hoyt, Kenneth

2018-01-01

H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Effects of cyclic flexure on endothelial permeability and apoptosis in arterial segments perfused ex vivo.

PubMed

Van Epps, J Scott; Chew, Douglas W; Vorp, David A

2009-10-01

Certain arteries (e.g., coronary, femoral, etc.) are exposed to cyclic flexure due to their tethering to surrounding tissue beds. It is believed that such stimuli result in a spatially variable biomechanical stress distribution, which has been implicated as a key modulator of remodeling associated with atherosclerotic lesion localization. In this study we utilized a combined ex vivo experimental/computational methodology to address the hypothesis that local variations in shear and mural stress associated with cyclic flexure influence the distribution of early markers of atherogenesis. Bilateral porcine femoral arteries were surgically harvested and perfused ex vivo under pulsatile arterial conditions. One of the paired vessels was exposed to cyclic flexure (0-0.7 cm(-1)) at 1 Hz for 12 h. During the last hour, the perfusate was supplemented with Evan's blue dye-labeled albumin. A custom tissue processing protocol was used to determine the spatial distribution of endothelial permeability, apoptosis, and proliferation. Finite element and computational fluid dynamics techniques were used to determine the mural and shear stress distributions, respectively, for each perfused segment. Biological data obtained experimentally and mechanical stress data estimated computationally were combined in an experiment-specific manner using multiple linear regression analyses. Arterial segments exposed to cyclic flexure had significant increases in intimal and medial apoptosis (3.42+/-1.02 fold, p=0.029) with concomitant increases in permeability (1.14+/-0.04 fold, p=0.026). Regression analyses revealed specific mural stress measures including circumferential stress at systole, and longitudinal pulse stress were quantitatively correlated with the distribution of permeability and apoptosis. The results demonstrated that local variation in mechanical stress in arterial segments subjected to cyclic flexure indeed influence the extent and spatial distribution of the early atherogenic markers. In addition, the importance of including mural stresses in the investigation of vascular mechanopathobiology was highlighted. Specific example results were used to describe a potential mechanism by which systemic risk factors can lead to a heterogeneous disease.

Mortality and long-term exposure to ambient air pollution: ongoing analyses based on the American Cancer Society cohort.

PubMed

Krewski, Daniel; Burnett, Richard; Jerrett, Michael; Pope, C Arden; Rainham, Daniel; Calle, Eugenia; Thurston, George; Thun, Michael

This article provides an overview of previous analysis and reanalysis of the American Cancer Society (ACS) cohort, along with an indication of current ongoing analyses of the cohort with additional follow-up information through to 2000. Results of the first analysis conducted by Pope et al. (1995) showed that higher average sulfate levels were associated with increased mortality, particularly from cardiopulmonary disease. A reanalysis of the ACS cohort, undertaken by Krewski et al. (2000), found the original risk estimates for fine-particle and sulfate air pollution to be highly robust against alternative statistical techniques and spatial modeling approaches. A detailed investigation of covariate effects found a significant modifying effect of education with risk of mortality associated with fine particles declining with increasing educational attainment. Pope et al. (2002) subsequently reported results of a subsequent study using an additional 10 yr of follow-up of the ACS cohort. This updated analysis included gaseous copollutant and new fine-particle measurements, more comprehensive information on occupational exposures, dietary variables, and the most recent developments in statistical modeling integrating random effects and nonparametric spatial smoothing into the Cox proportional hazards model. Robust associations between ambient fine particulate air pollution and elevated risks of cardiopulmonary and lung cancer mortality were clearly evident, providing the strongest evidence to date that long-term exposure to fine particles is an important health risk. Current ongoing analysis using the extended follow-up information will explore the role of ecologic, economic, and, demographic covariates in the particulate air pollution and mortality association. This analysis will also provide insight into the role of spatial autocorrelation at multiple geographic scales, and whether critical instances in time of exposure to fine particles influence the risk of mortality from cardiopulmonary and lung cancer. Information on the influence of covariates at multiple scales and of critical exposure time windows can assist policymakers in establishing timelines for regulatory interventions that maximize population health benefits.

Recurrent patterning in the daily foraging routes of hamadryas baboons (Papio hamadryas): spatial memory in large-scale versus small-scale space.

PubMed

Schreier, Amy L; Grove, Matt

2014-05-01

The benefits of spatial memory for foraging animals can be assessed on two distinct spatial scales: small-scale space (travel within patches) and large-scale space (travel between patches). While the patches themselves may be distributed at low density, within patches resources are likely densely distributed. We propose, therefore, that spatial memory for recalling the particular locations of previously visited feeding sites will be more advantageous during between-patch movement, where it may reduce the distances traveled by animals that possess this ability compared to those that must rely on random search. We address this hypothesis by employing descriptive statistics and spectral analyses to characterize the daily foraging routes of a band of wild hamadryas baboons in Filoha, Ethiopia. The baboons slept on two main cliffs--the Filoha cliff and the Wasaro cliff--and daily travel began and ended on a cliff; thus four daily travel routes exist: Filoha-Filoha, Filoha-Wasaro, Wasaro-Wasaro, Wasaro-Filoha. We use newly developed partial sum methods and distribution-fitting analyses to distinguish periods of area-restricted search from more extensive movements. The results indicate a single peak in travel activity in the Filoha-Filoha and Wasaro-Filoha routes, three peaks of travel activity in the Filoha-Wasaro routes, and two peaks in the Wasaro-Wasaro routes; and are consistent with on-the-ground observations of foraging and ranging behavior of the baboons. In each of the four daily travel routes the "tipping points" identified by the partial sum analyses indicate transitions between travel in small- versus large-scale space. The correspondence between the quantitative analyses and the field observations suggest great utility for using these types of analyses to examine primate travel patterns and especially in distinguishing between movement in small versus large-scale space. Only the distribution-fitting analyses are inconsistent with the field observations, which may be due to the scale at which these analyses were conducted. © 2013 Wiley Periodicals, Inc.

The Review of Nuclear Microscopy Techniques: An Approach for Nondestructive Trace Elemental Analysis and Mapping of Biological Materials.

PubMed

Mulware, Stephen Juma

2015-01-01

The properties of many biological materials often depend on the spatial distribution and concentration of the trace elements present in a matrix. Scientists have over the years tried various techniques including classical physical and chemical analyzing techniques each with relative level of accuracy. However, with the development of spatially sensitive submicron beams, the nuclear microprobe techniques using focused proton beams for the elemental analysis of biological materials have yielded significant success. In this paper, the basic principles of the commonly used microprobe techniques of STIM, RBS, and PIXE for trace elemental analysis are discussed. The details for sample preparation, the detection, and data collection and analysis are discussed. Finally, an application of the techniques to analysis of corn roots for elemental distribution and concentration is presented.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

Spatial cross-correlation of undisturbed, natural shortleaf pine stands in northern Georgia

Treesearch

Robin M. Reich; Raymond L. Czaplewski; William A. Bechtold

1994-01-01

In this study a cross-correlation statistic is used to analyse the spatial relationship among stand characteristics of natural, undisturbed shortleaf pine stands sampled during 1961-72 and 1972-82 in northern Georgia. Stand characteristics included stand age, site index, tree density, hardwood competition, and mortality. In each time period, the spatial cross-...

A spatial-dynamic value transfer model of economic losses from a biological invasion

Treesearch

Thomas P. Holmes; Andrew M. Liebhold; Kent F. Kovacs; Betsy Von Holle

2010-01-01

Rigorous assessments of the economic impacts of introduced species at broad spatial scales are required to provide credible information to policy makers. We propose that economic models of aggregate damages induced by biological invasions need to link microeconomic analyses of site-specific economic damages with spatial-dynamic models of value change associated with...

New data sources and derived products for the SRER digital spatial database

Treesearch

Craig Wissler; Deborah Angell

2003-01-01

The Santa Rita Experimental Range (SRER) digital database was developed to automate and preserve ecological data and increase their accessibility. The digital data holdings include a spatial database that is used to integrate ecological data in a known reference system and to support spatial analyses. Recently, the Advanced Resource Technology (ART) facility has added...

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

Sadowski, F. G.; Malila, W. A.; Sarno, J. E.; Nalepka, R. F.

1977-01-01

Inappropriate spatial resolution and corresponding data processing techniques may be major causes for non-optimal forest classification results frequently achieved from multispectral scanner (MSS) data. Procedures and results of empirical investigations are studied to determine the influence of MSS spatial resolution on the classification of forest features into levels of detail or hierarchies of information that might be appropriate for nationwide forest surveys and detailed in-place inventories. Two somewhat different, but related studies are presented. The first consisted of establishing classification accuracies for several hierarchies of features as spatial resolution was progressively coarsened from (2 meters) squared to (64 meters) squared. The second investigated the capabilities for specialized processing techniques to improve upon the results of conventional processing procedures for both coarse and fine resolution data.

SEM-EDX analysis in the source apportionment of particulate matter on Hypogymnia physodes lichen transplants around the Cu smelter and former mining town of Karabash, South Urals, Russia.

PubMed

Williamson, B J; Mikhailova, I; Purvis, O W; Udachin, V

2004-04-25

Scanning electron microscopy with energy-dispersive X-ray analysis (SEM-EDX) of particulate matter on lichen transplant thalli (Hypogymnia physodes) was assessed as a complementary technique to wet chemical analysis for source apportionment of airborne contaminants. Transplants (2 month exposure) stationed in the Cu smelter and former mining town of Karabash were compared with those from a control site 30 km south. Particulate matter in Karabash samples (715 analyses) showed higher levels of S, Pb, Cu, Sn and Zn compared with the control (598 analyses). Complex element associations among the particles confounded detailed mineralogical identifications, and therefore a simplified particle classification scheme was devised for source apportionment. Karabash samples contained high levels of particles classified as mining-related (MRP), and these were also identified in control samples, indicating wide spatial dispersion from the smelter and highlighting the sensitivity of the method. It was noted that MRP <2.5-microm diameter were poorly represented on lichen surfaces suggesting this may limit the usefulness of Hypogymnia transplants as proxies when assessing human health impacts from airborne particulates. Analyses of the lichen thallus surface (away from surface particulates) revealed high levels of Cu, Zn, Fe and Pb associated with organics in the Karabash samples compared with the control, with a proportionate loss of K, interpreted as being due to a stress-related increase in cell membrane permeability. This type of analysis may provide a novel SEM-EDX-based method for assessing lichen vitality. The techniques developed are presented and further implications of the study are discussed.

Image analysis of skin color heterogeneity focusing on skin chromophores and the age-related changes in facial skin.

PubMed

Kikuchi, Kumiko; Masuda, Yuji; Yamashita, Toyonobu; Kawai, Eriko; Hirao, Tetsuji

2015-05-01

Heterogeneity with respect to skin color tone is one of the key factors in visual perception of facial attractiveness and age. However, there have been few studies on quantitative analyses of the color heterogeneity of facial skin. The purpose of this study was to develop image evaluation methods for skin color heterogeneity focusing on skin chromophores and then characterize ethnic differences and age-related changes. A facial imaging system equipped with an illumination unit and a high-resolution digital camera was used to develop image evaluation methods for skin color heterogeneity. First, melanin and/or hemoglobin images were obtained using pigment-specific image-processing techniques, which involved conversion from Commission Internationale de l'Eclairage XYZ color values to melanin and/or hemoglobin indexes as measures of their contents. Second, a spatial frequency analysis with threshold settings was applied to the individual images. Cheek skin images of 194 healthy Asian and Caucasian female subjects were acquired using the imaging system. Applying this methodology, the skin color heterogeneity of Asian and Caucasian faces was characterized. The proposed pigment-specific image-processing techniques allowed visual discrimination of skin redness from skin pigmentation. In the heterogeneity analyses of cheek skin color, age-related changes in melanin were clearly detected in Asian and Caucasian skin. Furthermore, it was found that the heterogeneity indexes of hemoglobin were significantly higher in Caucasian skin than in Asian skin. We have developed evaluation methods for skin color heterogeneity by image analyses based on the major chromophores, melanin and hemoglobin, with special reference to their size. This methodology focusing on skin color heterogeneity should be useful for better understanding of aging and ethnic differences. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Methods for assessing movement path recursion with application to African buffalo in South Africa

USGS Publications Warehouse

Bar-David, S.; Bar-David, I.; Cross, P.C.; Ryan, S.J.; Knechtel, C.U.; Getz, W.M.

2009-01-01

Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus coffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. ?? 2009 by the Ecological Society of America.

QR code optical encryption using spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Cheremkhin, P. A.; Krasnov, V. V.; Rodin, V. G.; Starikov, R. S.

2017-02-01

Optical encryption is an actively developing field of science. The majority of encryption techniques use coherent illumination and suffer from speckle noise, which severely limits their applicability. The spatially incoherent encryption technique does not have this drawback, but its effectiveness is dependent on the Fourier spectrum properties of the image to be encrypted. The application of a quick response (QR) code in the capacity of a data container solves this problem, and the embedded error correction code also enables errorless decryption. The optical encryption of digital information in the form of QR codes using spatially incoherent illumination was implemented experimentally. The encryption is based on the optical convolution of the image to be encrypted with the kinoform point spread function, which serves as an encryption key. Two liquid crystal spatial light modulators were used in the experimental setup for the QR code and the kinoform imaging, respectively. The quality of the encryption and decryption was analyzed in relation to the QR code size. Decryption was conducted digitally. The successful decryption of encrypted QR codes of up to 129  ×  129 pixels was demonstrated. A comparison with the coherent QR code encryption technique showed that the proposed technique has a signal-to-noise ratio that is at least two times higher.

Copper Decoration of Carbon Nanotubes and High Resolution Electron Microscopy

NASA Astrophysics Data System (ADS)

Probst, Camille

A new process of decorating carbon nanotubes with copper was developed for the fabrication of nanocomposite aluminum-nanotubes. The process consists of three stages: oxidation, activation and electroless copper plating on the nanotubes. The oxidation step was required to create chemical function on the nanotubes, essential for the activation step. Then, catalytic nanoparticles of tin-palladium were deposited on the tubes. Finally, during the electroless copper plating, copper particles with a size between 20 and 60 nm were uniformly deposited on the nanotubes surface. The reproducibility of the process was shown by using another type of carbon nanotube. The fabrication of nanocomposites aluminum-nanotubes was tested by aluminum vacuum infiltration. Although the infiltration of carbon nanotubes did not produce the expected results, an interesting electron microscopy sample was discovered during the process development: the activated carbon nanotubes. Secondly, scanning transmitted electron microscopy (STEM) imaging in SEM was analysed. The images were obtained with a new detector on the field emission scanning electron microscope (Hitachi S-4700). Various parameters were analysed with the use of two different samples: the activated carbon nanotubes (previously obtained) and gold-palladium nanodeposits. Influences of working distance, accelerating voltage or sample used on the spatial resolution of images obtained with SMART (Scanning Microscope Assessment and Resolution Testing) were analysed. An optimum working distance for the best spatial resolution related to the sample analysed was found for the imaging in STEM mode. Finally, relation between probe size and spatial resolution of backscattered electrons (BSE) images was studied. An image synthesis method was developed to generate the BSE images from backscattered electrons coefficients obtained with CASINO software. Spatial resolution of images was determined using SMART. The analysis shown that using a probe size smaller than the size of the observed object (sample features) does not improve the spatial resolution. In addition, the effects of the accelerating voltage, the current intensity and the sample geometry and composition were analysed.

Feasibility of automated dropsize distributions from holographic data using digital image processing techniques. [particle diameter measurement technique

NASA Technical Reports Server (NTRS)

Feinstein, S. P.; Girard, M. A.

1979-01-01

An automated technique for measuring particle diameters and their spatial coordinates from holographic reconstructions is being developed. Preliminary tests on actual cold-flow holograms of impinging jets indicate that a suitable discriminant algorithm consists of a Fourier-Gaussian noise filter and a contour thresholding technique. This process identifies circular as well as noncircular objects. The desired objects (in this case, circular or possibly ellipsoidal) are then selected automatically from the above set and stored with their parametric representations. From this data, dropsize distributions as a function of spatial coordinates can be generated and combustion effects due to hardware and/or physical variables studied.

The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats.

PubMed

De Azevedo, Thiago S; Bourke, Brian Patrick; Piovezan, Rafael; Sallum, Maria Anice M

2018-05-08

We addressed the potential associations among the temporal and spatial distribution of larval habitats of Aedes (Stegomyia) aegypti, the presence of urban heat islands and socioeconomic factors. Data on larval habitats were collected in Santa Bárbara d'Oeste, São Paulo, Brazil, from 2004 to 2006, and spatial and temporal variations were analysed using a wavelet-based approach. We quantified urban heat islands by calculating surface temperatures using the results of wavelet analyses and grey level transformation from Thematic Mapper images (Landsat 5). Ae. aegypti larval habitats were geo-referenced corresponding to the wavelet analyses to test the potential association between geographical distribution of habitats and surface temperature. In an inhomogeneous spatial point process, we estimated the frequency of occurrence of larval habitats in relation to temperature. The São Paulo State Social Vulnerability Index in the municipality of Santa Barbára d'Oeste was used to test the potential association between presence of larval habitats and social vulnerability. We found abundant Ae. aegypti larval habitats in areas of higher surface temperature and social vulnerability and fewer larval habitats in areas with lower surface temperature and social vulnerability.

Spatial quantile regression using INLA with applications to childhood overweight in Malawi.

PubMed

Mtambo, Owen P L; Masangwi, Salule J; Kazembe, Lawrence N M

2015-04-01

Analyses of childhood overweight have mainly used mean regression. However, using quantile regression is more appropriate as it provides flexibility to analyse the determinants of overweight corresponding to quantiles of interest. The main objective of this study was to fit a Bayesian additive quantile regression model with structured spatial effects for childhood overweight in Malawi using the 2010 Malawi DHS data. Inference was fully Bayesian using R-INLA package. The significant determinants of childhood overweight ranged from socio-demographic factors such as type of residence to child and maternal factors such as child age and maternal BMI. We observed significant positive structured spatial effects on childhood overweight in some districts of Malawi. We recommended that the childhood malnutrition policy makers should consider timely interventions based on risk factors as identified in this paper including spatial targets of interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

Carotid arterial wall MRI at 3T using 3D variable-flip-angle turbo spin-echo (TSE) with flow-sensitive dephasing (FSD).

PubMed

Fan, Zhaoyang; Zhang, Zhuoli; Chung, Yiu-Cho; Weale, Peter; Zuehlsdorff, Sven; Carr, James; Li, Debiao

2010-03-01

To evaluate the effectiveness of flow-sensitive dephasing (FSD) magnetization preparation in improving blood signal suppression of three-dimensional (3D) turbo spin-echo (TSE) sequence (SPACE) for isotropic high-spatial-resolution carotid arterial wall imaging at 3T. The FSD-prepared SPACE sequence (FSD-SPACE) was implemented by adding two identical FSD gradient pulses right before and after the first refocusing 180 degrees -pulse of the SPACE sequence in all three orthogonal directions. Nine healthy volunteers were imaged at 3T with SPACE, FSD-SPACE, and multislice T2-weighted 2D TSE coupled with saturation band (SB-TSE). Apparent carotid wall-lumen contrast-to-noise ratio (aCNR(w-l)) and apparent lumen area (aLA) at the locations with residual-blood (rb) signal shown on SPACE images were compared between SPACE and FSD-SPACE. Carotid aCNR(w-l) and lumen (LA) and wall area (WA) measured from FSD-SPACE were compared to those measured from SB-TSE. Plaque-mimicking flow artifacts identified in seven carotids on SPACE images were eliminated on FSD-SPACE images. The FSD preparation resulted in slightly reduced aCNR(w-l) (P = 0.025), but significantly improved aCNR between the wall and rb regions (P < 0.001) and larger aLA (P < 0.001). Compared to SB-TSE, FSD-SPACE offered comparable aCNR(w-l) with much higher spatial resolution, shorter imaging time, and larger artery coverage. The LA and WA measurements from the two techniques were in good agreement based on intraclasss correlation coefficient (0.988 and 0.949, respectively; P < 0.001) and Bland-Altman analyses. FSD-SPACE is a time-efficient 3D imaging technique for carotid arterial wall with superior spatial resolution and blood signal suppression.

3D Tomography of Accretionary Lapilli From The Island of Stromboli (Aeolian Archipelago, Italy): Spatial Arrangement, Internal Structure, Grain Size Distribution and Chemical Characterization

NASA Astrophysics Data System (ADS)

Morgavi, D.; Ielpo, M.; Valentini, L.; Laeger, K.; Paredes, J.; Petrelli, M.; Costa, A.; Perugini, D.

2015-12-01

The Secche di Lazzaro formation (7 Ka) is a phreatomagmatic deposit in the south-western part of the island of Stromboli (Aeolian Archipelago, Italy). The volcanic sequence is constituted by three main sub-units. In two of them abundant accretionary lapilli are present. We performed granulometric analysis to describe the spatial arrangement and the grain-size distribution of the lapilli inside the deposit. Lapilli were characterized by SEM investigations (BSE images). EMPA and LA-ICP-MS analyses of major and trace elements on glasses and minerals were performed. Although BSE images provide accurate morphological information, they do not allow the real 3D microstructure to be accessed. Therefore, non-invasive 3D imaging of the lapilli was performed by X-ray micro-tomography (X-mCT). The results of the X-mCT measurements provided a set of 2D cross-sectional slices stacked along the vertical axis, with a voxel size varying between 2.7 and 4.1 mm, depending on the size of the sample. The X-mCT images represent a mapping of X-ray attenuation, which in turn depends on the density of the phases distributed within the sample. This technique helped us to better constrain the particle and crystal distribution inside the accretionary lapilli. The recognized phases are: glass, clinopyroxene, plagioclase and Ti-Fe minerals. We discover also a high concentration of Na, Cl and SO3 in the ash matrix. This evidence is ubiquitous in all the accretionary lapilli. The work presented here could define a new route for future studies in the field of physical volcanology as X-ray micro-tomography could be a useful, non destructive technique to better characterize the internal structure of accretionary lapilli helping us to describe grain-size distribution of component particles and their spatial distribution within aggregates.

DigiFract: A software and data model implementation for flexible acquisition and processing of fracture data from outcrops

NASA Astrophysics Data System (ADS)

Hardebol, N. J.; Bertotti, G.

2013-04-01

This paper presents the development and use of our new DigiFract software designed for acquiring fracture data from outcrops more efficiently and more completely than done with other methods. Fracture surveys often aim at measuring spatial information (such as spacing) directly in the field. Instead, DigiFract focuses on collecting geometries and attributes and derives spatial information through subsequent analyses. Our primary development goal was to support field acquisition in a systematic digital format and optimized for a varied range of (spatial) analyses. DigiFract is developed using the programming interface of the Quantum Geographic Information System (GIS) with versatile functionality for spatial raster and vector data handling. Among other features, this includes spatial referencing of outcrop photos, and tools for digitizing geometries and assigning attribute information through a graphical user interface. While a GIS typically operates in map-view, DigiFract collects features on a surface of arbitrary orientation in 3D space. This surface is overlain with an outcrop photo and serves as reference frame for digitizing geologic features. Data is managed through a data model and stored in shapefiles or in a spatial database system. Fracture attributes, such as spacing or length, is intrinsic information of the digitized geometry and becomes explicit through follow-up data processing. Orientation statistics, scan-line or scan-window analyses can be performed from the graphical user interface or can be obtained through flexible Python scripts that directly access the fractdatamodel and analysisLib core modules of DigiFract. This workflow has been applied in various studies and enabled a faster collection of larger and more accurate fracture datasets. The studies delivered a better characterization of fractured reservoirs analogues in terms of fracture orientation and intensity distributions. Furthermore, the data organisation and analyses provided more independent constraints on the bed-confined or through-going nature of fractures relative to the stratigraphic layering.

ICA-based artefact and accelerated fMRI acquisition for improved Resting State Network imaging

PubMed Central

Griffanti, Ludovica; Salimi-Khorshidi, Gholamreza; Beckmann, Christian F.; Auerbach, Edward J.; Douaud, Gwenaëlle; Sexton, Claire E.; Zsoldos, Enikő; Ebmeier, Klaus P; Filippini, Nicola; Mackay, Clare E.; Moeller, Steen; Xu, Junqian; Yacoub, Essa; Baselli, Giuseppe; Ugurbil, Kamil; Miller, Karla L.; Smith, Stephen M.

2014-01-01

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB’s ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures were assessed using timeseries (amplitude and spectra), network matrix and spatial map analyses. For timeseries and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses. PMID:24657355

ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging.

PubMed

Griffanti, Ludovica; Salimi-Khorshidi, Gholamreza; Beckmann, Christian F; Auerbach, Edward J; Douaud, Gwenaëlle; Sexton, Claire E; Zsoldos, Enikő; Ebmeier, Klaus P; Filippini, Nicola; Mackay, Clare E; Moeller, Steen; Xu, Junqian; Yacoub, Essa; Baselli, Giuseppe; Ugurbil, Kamil; Miller, Karla L; Smith, Stephen M

2014-07-15

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB's ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures was assessed using time series (amplitude and spectra), network matrix and spatial map analyses. For time series and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Buzzi, M.; Vaz, C. A. F.; Raabe, J.

Manipulating magnetisation by the application of an electric field in magnetoelectric multiferroics represents a timely issue due to the potential applications in low power electronics and the novel physics involved. Thanks to its element sensitivity and high spatial resolution, X-ray photoemission electron microscopy is a uniquely suited technique for the investigation of magnetoelectric coupling in multiferroic materials. In this work, we present a setup that allows for the application of in situ electric and magnetic fields while the sample is analysed in the microscope. As an example of the performances of the setup, we present measurements on Ni/Pb(Mg{sub 0.66}Nb{sub 0.33})O{submore » 3}-PbTiO{sub 3} and La{sub 0.7}Sr{sub 0.3}MnO{sub 3}/PMN-PT artificial multiferroic nanostructures.« less

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

The numerical dynamic for highly nonlinear partial differential equations

NASA Technical Reports Server (NTRS)

Lafon, A.; Yee, H. C.

1992-01-01

Problems associated with the numerical computation of highly nonlinear equations in computational fluid dynamics are set forth and analyzed in terms of the potential ranges of spurious behaviors. A reaction-convection equation with a nonlinear source term is employed to evaluate the effects related to spatial and temporal discretizations. The discretization of the source term is described according to several methods, and the various techniques are shown to have a significant effect on the stability of the spurious solutions. Traditional linearized stability analyses cannot provide the level of confidence required for accurate fluid dynamics computations, and the incorporation of nonlinear analysis is proposed. Nonlinear analysis based on nonlinear dynamical systems complements the conventional linear approach and is valuable in the analysis of hypersonic aerodynamics and combustion phenomena.

Compressive self-interference Fresnel digital holography with faithful reconstruction

NASA Astrophysics Data System (ADS)

Wan, Yuhong; Man, Tianlong; Han, Ying; Zhou, Hongqiang; Wang, Dayong

2017-05-01

We developed compressive self-interference digital holographic approach that allows retrieving three-dimensional information of the spatially incoherent objects from single-shot captured hologram. The Fresnel incoherent correlation holography is combined with parallel phase-shifting technique to instantaneously obtain spatial-multiplexed phase-shifting holograms. The recording scheme is regarded as compressive forward sensing model, thus the compressive-sensing-based reconstruction algorithm is implemented to reconstruct the original object from the under sampled demultiplexed sub-holograms. The concept was verified by simulations and experiments with simulating use of the polarizer array. The proposed technique has great potential to be applied in 3D tracking of spatially incoherent samples.

A technique for evaluating the influence of spatial sampling on the determination of global mean total columnar ozone

NASA Technical Reports Server (NTRS)

Tolson, R. H.

1981-01-01

A technique is described for providing a means of evaluating the influence of spatial sampling on the determination of global mean total columnar ozone. A finite number of coefficients in the expansion are determined, and the truncated part of the expansion is shown to contribute an error to the estimate, which depends strongly on the spatial sampling and is relatively insensitive to data noise. First and second order statistics are derived for each term in a spherical harmonic expansion which represents the ozone field, and the statistics are used to estimate systematic and random errors in the estimates of total ozone.

Analysis of security of optical encryption with spatially incoherent illumination technique

NASA Astrophysics Data System (ADS)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Shifrina, Anna V.

2017-03-01

Applications of optical methods for encryption purposes have been attracting interest of researchers for decades. The first and the most popular is double random phase encoding (DRPE) technique. There are many optical encryption techniques based on DRPE. Main advantage of DRPE based techniques is high security due to transformation of spectrum of image to be encrypted into white spectrum via use of first phase random mask which allows for encrypted images with white spectra. Downsides are necessity of using holographic registration scheme in order to register not only light intensity distribution but also its phase distribution, and speckle noise occurring due to coherent illumination. Elimination of these disadvantages is possible via usage of incoherent illumination instead of coherent one. In this case, phase registration no longer matters, which means that there is no need for holographic setup, and speckle noise is gone. This technique does not have drawbacks inherent to coherent methods, however, as only light intensity distribution is considered, mean value of image to be encrypted is always above zero which leads to intensive zero spatial frequency peak in image spectrum. Consequently, in case of spatially incoherent illumination, image spectrum, as well as encryption key spectrum, cannot be white. This might be used to crack encryption system. If encryption key is very sparse, encrypted image might contain parts or even whole unhidden original image. Therefore, in this paper analysis of security of optical encryption with spatially incoherent illumination depending on encryption key size and density is conducted.

The History of Electromagnetic Induction Techniques in Soil Survey

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2014-05-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.

A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.

PubMed

Moradian, Annie; Porras-Yakushi, Tanya R; Sweredoski, Michael J; Hess, Sonja

2016-01-01

When deciding to perform a quantitative proteomics analysis, selectivity, sensitivity, and reproducibility are important criteria to consider. The use of multiple reaction monitoring (MRM) has emerged as a powerful proteomics technique in that regard since it avoids many of the problems typically observed in discovery-based analyses. A prerequisite for such a targeted approach is that the protein targets are known, either as a result of previous global proteomics experiments or because a specific hypothesis is to be tested. When guidelines that have been established in the pharmaceutical industry many decades ago are taken into account, setting up an MRM assay is relatively straightforward. Typically, proteotypic peptides with favorable mass spectrometric properties are synthesized with a heavy isotope for each protein that is to be monitored. Retention times and calibration curves are determined using triple-quadrupole mass spectrometers. The use of iRT peptide standards is both recommended and fully integrated into the bioinformatics pipeline. Digested biological samples are mixed with the heavy and iRT standards and quantified. Here we present a generic protocol for the development of an MRM assay.

Utilizing Skylab data in on-going resources management programs in the state of Ohio

NASA Technical Reports Server (NTRS)

Baldridge, P. E. (Principal Investigator); Goesling, P. H.; Martin, T. A.; Wukelic, G. E.; Stephan, J. G.; Smail, H. E.; Ebbert, T. F.

1975-01-01

The author has identified the following significant results. The use of Skylab imagery for total area woodland surveys was found to be more accurate and cheaper than conventional surveys using aerial photo-plot techniques. Machine-aided (primarily density slicing) analyses of Skylab 190A and 190B color and infrared color photography demonstrated the feasibility of using such data for differentiating major timber classes including pines, hardwoods, mixed, cut, and brushland providing such analyses are made at scales of 1:24,000 and larger. Manual and machine-assisted image analysis indicated that spectral and spatial capabilities of Skylab EREP photography are adequate to distinguish most parameters of current, coal surface mining concern associated with: (1) active mining, (2) orphan lands, (3) reclaimed lands, and (4) active reclamation. Excellent results were achieved when comparing Skylab and aerial photographic interpretations of detailed surface mining features. Skylab photographs when combined with other data bases (e.g., census, agricultural land productivity, and transportation networks), provide a comprehensive, meaningful, and integrated view of major elements involved in the urbanization/encroachment process.

Distribution and visualisation of chlorhexidine within the skin using ToF-SIMS: a potential platform for the design of more efficacious skin antiseptic formulations.

PubMed

Judd, Amy M; Scurr, David J; Heylings, Jon R; Wan, Ka-Wai; Moss, Gary P

2013-07-01

In order to increase the efficacy of a topically applied antimicrobial compound the permeation profile, localisation and mechanism of action within the skin must first be investigated. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to visualise the distribution of a conventional antimicrobial compound, chlorhexidine digluconate, within porcine skin without the need for laborious preparation, radio-labels or fluorescent tags. High mass resolution and high spatial resolution mass spectra and chemical images were achieved when analysing chlorhexidine digluconate treated cryo-sectioned porcine skin sections by ToF-SIMS. The distribution of chlorhexidine digluconate was mapped throughout the skin sections and our studies indicate that the compound appears to be localised within the stratum corneum. In parallel, tape strips taken from chlorhexidine digluconate treated porcine skin were analysed by ToF-SIMS to support the distribution profile obtained from the skin sections. ToF-SIMS can act as a powerful complementary technique to map the distribution of topically applied compounds within the skin.

A technique for recording polycrystalline structure and orientation during in situ deformation cycles of rock analogues using an automated fabric analyser.

PubMed

Peternell, M; Russell-Head, D S; Wilson, C J L

2011-05-01

Two in situ plane-strain deformation experiments on norcamphor and natural ice using synchronous recording of crystal c-axis orientations have been performed with an automated fabric analyser and a newly developed sample press and deformation stage. Without interrupting the deformation experiment, c-axis orientations are determined for each pixel in a 5 × 5 mm sample area at a spatial resolution of 5 μm/pixel. In the case of norcamphor, changes in microstructures and associated crystallographic information, at a strain rate of ∼2 × 10(-5) s(-1), were recorded for the first time during a complete in situ deformation-cycle experiment that consisted of an annealing, deformation and post-deformation annealing path. In the case of natural ice, slower external strain rates (∼1 × 10(-6) s(-1)) enabled the investigation of small changes in the polycrystal aggregate's crystallography and microstructure for small amounts of strain. The technical setup and first results from the experiments are presented. © 2010 The Authors Journal of Microscopy © 2010 Royal Microscopical Society.

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework. [relations (mathematics)

NASA Technical Reports Server (NTRS)

Peuquet, Donna J.

1987-01-01

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

Spatial and temporal single-cell volume estimation by a fluorescence imaging technique with application to astrocytes in primary culture

NASA Astrophysics Data System (ADS)

Khatibi, Siamak; Allansson, Louise; Gustavsson, Tomas; Blomstrand, Fredrik; Hansson, Elisabeth; Olsson, Torsten

1999-05-01

Cell volume changes are often associated with important physiological and pathological processes in the cell. These changes may be the means by which the cell interacts with its surrounding. Astroglial cells change their volume and shape under several circumstances that affect the central nervous system. Following an incidence of brain damage, such as a stroke or a traumatic brain injury, one of the first events seen is swelling of the astroglial cells. In order to study this and other similar phenomena, it is desirable to develop technical instrumentation and analysis methods capable of detecting and characterizing dynamic cell shape changes in a quantitative and robust way. We have developed a technique to monitor and to quantify the spatial and temporal volume changes in a single cell in primary culture. The technique is based on two- and three-dimensional fluorescence imaging. The temporal information is obtained from a sequence of microscope images, which are analyzed in real time. The spatial data is collected in a sequence of images from the microscope, which is automatically focused up and down through the specimen. The analysis of spatial data is performed off-line and consists of photobleaching compensation, focus restoration, filtering, segmentation and spatial volume estimation.

Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area.

PubMed

Horak, Jakub

2013-01-01

The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.